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• Published: 25 January 2021

Online education in the post-COVID era

• Barbara B. Lockee 1  

Nature Electronics volume  4 ,  pages 5–6 ( 2021 ) Cite this article

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The coronavirus pandemic has forced students and educators across all levels of education to rapidly adapt to online learning. The impact of this — and the developments required to make it work — could permanently change how education is delivered.

The COVID-19 pandemic has forced the world to engage in the ubiquitous use of virtual learning. And while online and distance learning has been used before to maintain continuity in education, such as in the aftermath of earthquakes 1 , the scale of the current crisis is unprecedented. Speculation has now also begun about what the lasting effects of this will be and what education may look like in the post-COVID era. For some, an immediate retreat to the traditions of the physical classroom is required. But for others, the forced shift to online education is a moment of change and a time to reimagine how education could be delivered 2 .

Looking back

Online education has traditionally been viewed as an alternative pathway, one that is particularly well suited to adult learners seeking higher education opportunities. However, the emergence of the COVID-19 pandemic has required educators and students across all levels of education to adapt quickly to virtual courses. (The term ‘emergency remote teaching’ was coined in the early stages of the pandemic to describe the temporary nature of this transition 3 .) In some cases, instruction shifted online, then returned to the physical classroom, and then shifted back online due to further surges in the rate of infection. In other cases, instruction was offered using a combination of remote delivery and face-to-face: that is, students can attend online or in person (referred to as the HyFlex model 4 ). In either case, instructors just had to figure out how to make it work, considering the affordances and constraints of the specific learning environment to create learning experiences that were feasible and effective.

The use of varied delivery modes does, in fact, have a long history in education. Mechanical (and then later electronic) teaching machines have provided individualized learning programmes since the 1950s and the work of B. F. Skinner 5 , who proposed using technology to walk individual learners through carefully designed sequences of instruction with immediate feedback indicating the accuracy of their response. Skinner’s notions formed the first formalized representations of programmed learning, or ‘designed’ learning experiences. Then, in the 1960s, Fred Keller developed a personalized system of instruction 6 , in which students first read assigned course materials on their own, followed by one-on-one assessment sessions with a tutor, gaining permission to move ahead only after demonstrating mastery of the instructional material. Occasional class meetings were held to discuss concepts, answer questions and provide opportunities for social interaction. A personalized system of instruction was designed on the premise that initial engagement with content could be done independently, then discussed and applied in the social context of a classroom.

These predecessors to contemporary online education leveraged key principles of instructional design — the systematic process of applying psychological principles of human learning to the creation of effective instructional solutions — to consider which methods (and their corresponding learning environments) would effectively engage students to attain the targeted learning outcomes. In other words, they considered what choices about the planning and implementation of the learning experience can lead to student success. Such early educational innovations laid the groundwork for contemporary virtual learning, which itself incorporates a variety of instructional approaches and combinations of delivery modes.

Online learning and the pandemic

Fast forward to 2020, and various further educational innovations have occurred to make the universal adoption of remote learning a possibility. One key challenge is access. Here, extensive problems remain, including the lack of Internet connectivity in some locations, especially rural ones, and the competing needs among family members for the use of home technology. However, creative solutions have emerged to provide students and families with the facilities and resources needed to engage in and successfully complete coursework 7 . For example, school buses have been used to provide mobile hotspots, and class packets have been sent by mail and instructional presentations aired on local public broadcasting stations. The year 2020 has also seen increased availability and adoption of electronic resources and activities that can now be integrated into online learning experiences. Synchronous online conferencing systems, such as Zoom and Google Meet, have allowed experts from anywhere in the world to join online classrooms 8 and have allowed presentations to be recorded for individual learners to watch at a time most convenient for them. Furthermore, the importance of hands-on, experiential learning has led to innovations such as virtual field trips and virtual labs 9 . A capacity to serve learners of all ages has thus now been effectively established, and the next generation of online education can move from an enterprise that largely serves adult learners and higher education to one that increasingly serves younger learners, in primary and secondary education and from ages 5 to 18.

The COVID-19 pandemic is also likely to have a lasting effect on lesson design. The constraints of the pandemic provided an opportunity for educators to consider new strategies to teach targeted concepts. Though rethinking of instructional approaches was forced and hurried, the experience has served as a rare chance to reconsider strategies that best facilitate learning within the affordances and constraints of the online context. In particular, greater variance in teaching and learning activities will continue to question the importance of ‘seat time’ as the standard on which educational credits are based 10 — lengthy Zoom sessions are seldom instructionally necessary and are not aligned with the psychological principles of how humans learn. Interaction is important for learning but forced interactions among students for the sake of interaction is neither motivating nor beneficial.

While the blurring of the lines between traditional and distance education has been noted for several decades 11 , the pandemic has quickly advanced the erasure of these boundaries. Less single mode, more multi-mode (and thus more educator choices) is becoming the norm due to enhanced infrastructure and developed skill sets that allow people to move across different delivery systems 12 . The well-established best practices of hybrid or blended teaching and learning 13 have served as a guide for new combinations of instructional delivery that have developed in response to the shift to virtual learning. The use of multiple delivery modes is likely to remain, and will be a feature employed with learners of all ages 14 , 15 . Future iterations of online education will no longer be bound to the traditions of single teaching modes, as educators can support pedagogical approaches from a menu of instructional delivery options, a mix that has been supported by previous generations of online educators 16 .

Also significant are the changes to how learning outcomes are determined in online settings. Many educators have altered the ways in which student achievement is measured, eliminating assignments and changing assessment strategies altogether 17 . Such alterations include determining learning through strategies that leverage the online delivery mode, such as interactive discussions, student-led teaching and the use of games to increase motivation and attention. Specific changes that are likely to continue include flexible or extended deadlines for assignment completion 18 , more student choice regarding measures of learning, and more authentic experiences that involve the meaningful application of newly learned skills and knowledge 19 , for example, team-based projects that involve multiple creative and social media tools in support of collaborative problem solving.

In response to the COVID-19 pandemic, technological and administrative systems for implementing online learning, and the infrastructure that supports its access and delivery, had to adapt quickly. While access remains a significant issue for many, extensive resources have been allocated and processes developed to connect learners with course activities and materials, to facilitate communication between instructors and students, and to manage the administration of online learning. Paths for greater access and opportunities to online education have now been forged, and there is a clear route for the next generation of adopters of online education.

Before the pandemic, the primary purpose of distance and online education was providing access to instruction for those otherwise unable to participate in a traditional, place-based academic programme. As its purpose has shifted to supporting continuity of instruction, its audience, as well as the wider learning ecosystem, has changed. It will be interesting to see which aspects of emergency remote teaching remain in the next generation of education, when the threat of COVID-19 is no longer a factor. But online education will undoubtedly find new audiences. And the flexibility and learning possibilities that have emerged from necessity are likely to shift the expectations of students and educators, diminishing further the line between classroom-based instruction and virtual learning.

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Lockee, B.B. Online education in the post-COVID era. Nat Electron 4 , 5–6 (2021). https://doi.org/10.1038/s41928-020-00534-0

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Education Systems and Technology in 1990, 2020, and Beyond

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• Published: 13 August 2020
• Volume 64 , pages 693–703, ( 2020 )

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• Theodore W. Frick   ORCID: orcid.org/0000-0003-2488-9396 1  

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In Restructuring Education Through Technology, I incorporated systems thinking to identify seven types of relationships in educational systems: teacher-student, student-content, student-context, teacher-content, teacher-context, content-context, and education system-environment relationships (Frick 1991 ). I now revisit these education system relations and discuss potential futures of education. The World Wide Web did not exist when I wrote the original treatise, nor did wireless smartphones and tablets, Google’s search engine, YouTube, Facebook, or Wikipedia. However, one important education system relationship should not change: the affective bonding between teachers and their students.

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Introduction

As we enter the 2020 decade, 30 years have passed since I wrote a small book in 1990 called Restructuring Education Through Technology (Frick 1991 ). It was published about the same time as the World Wide Web first became available to the public, in August, 1991 ( https://en.wikipedia.org/wiki/World_Wide_Web ).

In the present article, I discuss important differences and similarities in education systems and technology in 1990 and 2020. I provide examples of education system affect-relations and system properties, then and now. I conclude with a strong philosophical stance on what is most important in the future.

What Is a System?

Ludwig von Bertalanffy ( 1950a , 1950b , 1972 ) was a biologist who is well-known for his initial development of general system theory (GST). GST was intended as an organizational framework or paradigm applicable to many scientific fields, what von Bertalanffy originally considered a unifying science. Many others built upon von Bertalanffy’s foundational work, including Maccia and Maccia ( 1966 ), Wymore ( 1967 ), Mesarović ( 1972 ), Cornacchio ( 1972 ), Weinberg ( 1975 ), Berlinsky ( 1976 ), Lin ( 1999 ), and Ackoff and Emery ( 2017 ). Thompson ( 2006a , 2006b ) briefly discussed the history of GST through the twentieth century, including the significant contribution of the SIGGS Theory Model (Maccia and Maccia, 1966). Predicate calculus was used to logically define approximately 80 terms. Thompson ( 2019 ) further refined these and other terms in Axiomatic Theories of Intentional Systems (ATIS).

Underlying these efforts is the fundamental goal of logical precision in use of terminology which describes general system , education , and education system . For example, system / negasystem flows were identified such as feedin , feedout , feedback , and feedthrough , and system structural properties were denoted such as size , complexity , strongness , flexibleness , wholeness , and hierarchical order . Further temporal properties included system openness , spillage , filtration , regulation , adaptiveness , compatibleness , and stress .

I present here a fundamental translation and description in natural language to support the main focus here. Think of this introduction to basic systems properties here as a guided tour of a building with many rooms. Readers can go as deep and detailed as they wish by following links to the web to explore further.

Figure 1 depicts an overview of fundamental systems concepts. The Appendix contains an abridged glossary of terms, which I have translated to natural language definitions.

Basic schema for system and negasystem

The first distinction is between a system and its negasystem . A system is defined as “a set of components and a family of affect-relations ” (Thompson 2019 ; https://aptac.sitehost.iu.edu/glossary/atisSystem.pdf ). The negasystem is, literally, the not-system. In natural language, many people refer to system environment , but a distinction is made between toput and negasystem in SIGGS and ATIS. Toput is the system environment , which is part of the negasystem . Toput is what is available for selection by a system . If a system is open , then some of toput may later become system input . That temporal process is feedin . Some toput may not become input , what is termed system spillage . System filtration is a restriction of feedin .

Parallel terms include system fromput and system output . The process of stuff exiting the system is feedout . See Fig.  1 and the Appendix. System feedin and feedout are temporal processes. At time 1, some components are part of system toput, and at time 2 they are part of system input . System feedback is feedout followed at a later time by system feedin .

There are also structural affect-relations , which refer to the configuration of connectedness among component affect-relations , which are relatively stable over some period of time. Temporal affect-relations refer to the changing temporal configurations of event occurrences. In Fig. 1 , system affect-relations are represented by the shape with arrows. In ATIS and SIGGS, mathematical digraphs (directed graphs) are used to characterize affect-relations . In order to keep matters relatively simple here, I will not digress into digraph theory, although it should be noted that it is fundamental to network analysis and complex systems, for example (e.g., see Jensen and Nielsen 2007 ; Brandes and Erlebach 2005 ). Noteworthy also is that components and their affect-relations also occur in the negasystem . Finally, due to space restrictions, more than 80 other important systems properties and their definitions are not discussed here. A broader description is available in Frick ( 2019 ) and on the Educology Website ( 2020) at: https://educology.iu.edu . Further details are provided in the ATIS glossary at https://aptac.sitehost.iu.edu/glossary/ and Thompson ( 2019 ).

What Is an Education System?

An education system is but one kind of system. There are many kinds of systems, including systems of government, military, biology, economy, health care, etc., to name just a few. Some systems are intentional , while others are not (Thompson 2019 ). An education system is an intentional system . Intention refers to willing, i.e., trying to do, seeking a goal. The primary goal of an education system should be to guide student learning (Steiner 1981 , 1988 ).

An education system is defined as an " intentional system that consists of at least one teacher and at least one student in a context ” (Educology, 2020 : https://educology.iu.edu/educationSystem.html ).

Note the differences between Figs.  1 and 2 . Now we are referring to an education system and an education negasystem . Note further the affect-relation shape in the education system, which now indicates relations among teachers , students , content , and contexts . Note also education system toput , which is the education system environment , which includes persons and things available for selection by an education system . Examples of affect-relations in education systems and negasystems are provided in Tables  1 , 2 , 3 , 4 , 5 and 6 below.

Basic schema for an education system and education negasystem

Finally, and most important, an education system is not confined to a place such as a school building with classrooms. This expansion is extremely important, and in fact is one of the main differences between 1990 and 2020 education systems. Some current education systems span the whole planet, and education system feedin and feedout occur through a network of networks referred to as the Internet and Worldwide Web.

An education system requires:

One or more teachers to guide student learning;

One or more students who intend to learn;

Guidance of learning that occurs in a context (i.e., a setting which also includes content for learning) ( https://educology.iu.edu/educationSystem.html )

Note this conception of an education system consists of universals , not limited to time or place ( https://educology.iu.edu/universals.html ). Thus, education systems are not limited to schools or universities as we now know them.

Teachers need not be limited to licensed school teachers or college professors.

Students need not be restricted to young people attending a school or university.

Contexts for teaching and learning need not be classrooms in school buildings or on college campuses.

Content need not be limited to traditional subjects of study in schools or universities such as mathematics, history, language arts, music, chemistry, biology, physics, etc.

These ideas are illustrated in Tables  1 , 2 , 3 , 4 , 5 and 6 , when comparing what was the same in 1990 and 2020, and what is new and different. The list is not exhaustive but is illustrative and parallels largely the organization in Frick ( 1991 ). Note that these are primarily examples of structural affect-relations in education systems and negasystems .

When I first drafted this article in late 2019, novel coronavirus was largely constrained to China. While I finalize the current article in June, 2020, a worldwide pandemic has been declared by the World Health Organization. In the U.S. many K-12 schools and colleges and universities have shut down their physical facilities (school buildings and campuses), and students and teachers were told to stay home during the past several months. Most teachers and professors have been suddenly thrown into a new context to do “emergency remote teaching” as a quick adaptation with little preparation (Hodges et al. 2020 ).

Nonetheless, while the physical facilities have been shut down, most education systems have not. The biggest structural change has been the education system context : students and teachers have remained physically located in their respective homes, and most student-teacher affect-relations have occurred via the Internet—at least for those who have access to the technologies required (e.g., through Zoom, e-mail, and course management systems, but see especially Table 6 , last item in the right hand column). Those unfortunate have-nots have become disconnected from the education systems to which they belonged prior to the coronavirus pandemic (see ATIS property: https://aptac.sitehost.iu.edu/glossary/atisDisconnectedComponentsSet.pdf .)

The other obvious structural change since 1990 in student-context and teacher-context affect-relations is the current prevalence of digital devices and wireless connectivity to the Internet (wi-fi and cellular), as well as in content-context affect-relations (NCES 2018 ). Increasing amounts of content are now digitally encoded and stored in the Cloud (i.e., data centers accessible through the Internet: https://en.wikipedia.org/wiki/Cloud_computing ).

One of the biggest challenges in 2020 is education system filtration (i.e., restriction of feedin ). In 1990, publishers of textbooks, videos, and movies for education served as significant filters . What was available in education system environments (toput) was restricted through highly centralized control within the publishing industry and mass media outlets (see Thompson 2019 , https://aptac.sitehost.iu.edu/glossary/atisCentralness.pdf ).

In 2020, the size of content components (sheer numbers) in the education system environment (toput) is larger than that in 1990 by many orders of magnitude. There are so many more choices in 2020 of what is available in the education system environment when compared with 1990, especially on the Internet (e.g., see Bonk 2009 ; Mitra 2020 ; Waks 2016 ). For example, there were no websites in 1990, one in 1991, and now there are over 1.5 billion in June, 2020 ( https://www.internetlivestats.com/total-number-of-websites/ ). YouTube reports that there are over 2 billion logged-in users each month, who watch over one billion hours of video daily ( https://www.youtube.com/about/press/ ). The website developed at Indiana University on How to Recognize Plagiarism was viewed over 66 million times between 2016 and 2019, with nearly 600,000 students from 222 countries who had passed a certification test ( https://plagiarism.iu.edu/recentChanges.html ). The role of teachers in “selecting the best of culture” is still relevant, and now even more so with so much content available to students worldwide (Frick 1991 , 2019 ).

Control of potential content for education systems has become much more decentralized in general, except in countries such as China where their government has barred access to “inappropriate” content by their citizens and students and teachers in Chinese education systems. The Chinese government has implemented a significant filter , restricting education system feedin (Xu et al. 2011 ).

On the other hand, in the U.S. and other countries which support more system openness , lack of effective filters has become a significant concern for educators, especially in K-12 schools (Bengfort 2019 ). Most of the vast resources on the Internet are unfiltered and uncurated—so there is a quality issue—it can often be difficult to determine what is trustworthy, safe, or accurate. For example, there are “fake news” publications, pornographic websites, and many other unsuitable materials (Kakutani 2018 ). Many K-12 school systems have attempted to filter toput, i.e., restrict Internet access at school by their students and teachers, by limiting which websites or Internet domains they can access (CIPA 2000 ).

Furthermore, students in 2020 can interact with their peers, friends, and others through social media—including Facebook, Instagram, Snapchat, Twitter, etc. Unfortunately, sexual predators and bullies also have access to these apps. Parents of students may try to put filters on their home networks, in order to restrict access to websites they consider to be inappropriate. But clever students can circumvent such attempts, especially when outside their home networks (e.g., see Hoffman 2019 ).

Space prevents further elaboration of important systems concepts in understanding similarities and differences in education systems in 1990 and 2020. However, I hope that the usefulness of universal systems concepts is patent to TechTrends readers.

What if? What Could be?

I now want to address future education systems. Artificial intelligence (AI) and robot teachers could be in future education systems. We already have some examples of AI, such as Alexa and Siri. Just verbally ask a question, and in seconds there is an answer or a list of likely resources.

As mentioned earlier in Table 2 , the Google search engine is likely the best current example of AI. Google bots roam the Web constantly, indexing billions of web pages. The Google Page Rank methodology effectively captures human judgement of what is important and relevant by examining what web page developers include as content and hyperlinks to other websites (e.g., see https://en.wikipedia.org/wiki/PageRank ). Proprietary algorithms subsequently developed at Google have gone far beyond the original page rank method created by Brin and Page ( 1998 ) when doctoral students at Stanford University.

This raises the question that I posed over 20 years ago: “Will these globally interconnected, multimedia computer-television-telephone-stereo-radio systems largely replace teachers? Will these multimedia tutoring systems be intelligent enough to do so?” (Frick 1997 , p. 108). First, there is a distinction between adaptive instruction vs. intelligent tutoring systems . We can already do adaptive instruction with today’s technologies. On the other hand, sentient machines as possible teachers is a futuristic scenario—one that is not within our reach with current technologies.

Adaptive instruction means essentially that what a student encounters next is customized or tailored according to what she or he has done in the past (e.g., Johnson and Sloan 2020 ). Historically, this was referred to as programmed instruction —i.e., structured by an instructional flowchart with decision nodes for branching (Heinich et al. 2002 ). In education systems terms, this is computer-mediated learning software that is designed to guide student learning (i.e., is instructed learning), and which has temporal properties of adaptiveness , feedback and feedthrough in order to increase compatibleness with student learners , and which has structural properties of flexibleness and wholeness . This we can do with present technologies.

Though we might not realize it, this kind of adaptiveness and customization has been going on as we surf the Web through techniques of storing browser cookies and digital fingerprinting (for an overview, see https://www.nytimes.com/2019/07/03/technology/personaltech/fingerprinting-track-devices-what-to-do.html ). If you ever wondered how those running shoes you were shopping for on Amazon.com show up as an advertisement in Rolling Stone Magazine , here is what is going on in the “black box” you are using: When you visit some websites, they plant “tracking devices” on your computer, typically stored as cookies by your web browser (e.g., Chrome, Firefox, Safari, or Edge) and in more recent years by using your digital fingerprint and matching it against those recorded previously by websites.

In addition to cookies, our devices leave digital fingerprints that can uniquely and accurately identify us individually (Eckersley 2010 ). These device fingerprint and cookie data are in turn used by businesses for customizing advertisements tailored to match our unique profiles (Chen 2019 ). These kinds of data can also be used for more clandestine purposes—e.g., as tools for influencing democratic election outcomes, that is, how we vote—by determining which political messages to which we are individually more receptive, what Pariser ( 2011 ) calls a “filter bubble” (e.g., see Baer 2016 ).

In adaptive instruction, as we humans interact with computer software (now called “apps”), these programs can store records of what we have been doing while using the app. These records can in turn be used in conditional logic to govern what is displayed next by the computing device. Highly sophisticated pattern recognition can provide information that drives the conditional logic. This kind of adaptation can be done in computer tutorials, games, simulations, drill and practice, tests, etc. as part of an education system . Over the past five decades, I myself have engineered software programs that are adaptive, and have taught graduate students to do likewise (e.g., Enfield et al. 2012 ; Frick 1989 ; Frick, et al., 2020 ; Welch and Frick, 1993 ).

This kind of adaptation has long been done by human teachers as they become uniquely acquainted with their students and provide instruction that is appropriate for those students’ specific interests and ability to learn. Computer software today can emulate this kind of adaptation up to a point, the primary limitation being the “sensory apparatus” of the computing device (Frick 1997 ). Think of this kind of adaptation as a “smart” e-learning textbook, which is different for each student, depending on what she or he does and has learned thus far.

Next, I discuss so-called intelligent tutoring systems which are currently beyond our reach. Science fiction writers have envisioned some futuristic scenarios.

For example, Arthur C. Clarke ( 1968 ) included HAL as a central character in 2001: A Space Odyssey . The astronauts on the outer space mission conversed in natural language with HAL, played chess games, and queried HAL about ship operations, who was central to running the spaceship. In The Moon is a Harsh Mistress , Robert Heinlein ( 1966 ) described Mycroft Holmes (Mike), which was a sentient supercomputer who conversed with humans in natural language, could program itself, and was smart enough to help rebels living on the moon to overthrow the Lunar Authority, an arm of government controlled from planet earth. Mike and HAL were stationary computers.

In The Robots of Dawn (Azimov 1983 ), Daneel and Giskard were robots who moved around. Central to the plot, they helped a human detective solve a murder case—the death of another robot. Daneel was embodied in humanoid form, nearly indistinguishable from actual humans in form and function, including sex. And while Daneel was incredibly intelligent, Giskard, who was not humanoid, turned out to be even more sentient. This and other science fiction novels by Isaac Azimov were famous for introducing the “three laws of robotics”—prime directives for robots to follow: not harming human beings, following their orders, and self-preservation ( https://en.wikipedia.org/wiki/Laws_of_robotics ). In 3001: The Final Odyssey Clarke ( 1997 ) provided a further futuristic sci-fi scenario. “Braincaps” and “brainboxes” were sophisticated devices that could rapidly download knowledge to a human brain, essentially providing an instant education. Braincaps also allowed a human to have imaginary experiences—a virtual reality that was just as real as dreams, while interacting with others with their own virtual avatars.

In non-fiction, Ray Kurzweil (1999, 2005 ) envisions a future where humans and robots meld, transcending biology . He discusses six epochs of evolution, starting from physics and chemistry and ending with the universe waking up. He predicts that intelligence will evolve far beyond its current embodiment in organic forms, not unlike the underlying premise of Clarke’s first odyssey novel, centered around the mystery of intelligent, powerful monoliths buried on Earth’s moon and orbiting Jupiter.

These are but a few images of humankind’s future. Could future education systems turn out in any of these ways? Will we someday have humanoid robots, braincaps, or literally a universal mind?

Over 20 years ago, I discussed some of the major issues that will need to be addressed (Frick 1997 ), and many of these issues remain unresolved in 2020. More recently, Anderson and Rainie ( 2018 ) surveyed 979 experts on artificial intelligence who expressed their concerns and suggested solutions for our future. Notably, Erik Brynjolfsson, one of the experts surveyed, emphasized that, “… the right question is not ‘What will happen?’ but ‘What will we choose to do?’ We need to work aggressively to make sure technology matches our values.”

I, too, take a similar position. Rather than trying to predict what might be, I next discuss what education should be , taking a philosophical position.

What Should be?

Education is vital to society and our future.

Worthwhile education for everyone is the goal of making intrinsically good and instrumentally good education accessible to everyone everywhere. Every human being has a right to worthwhile education . Why? To:

Enhance the quality of life.

Reduce inequality.

Minimize suffering.

Maximize overall good.

We can do this together. How?

Connect good teachers with students to help them learn worthwhile content .

Provide contexts to support these connections for teaching and learning.

Provide a viable way to sustain worthwhile education for everyone.

( https://educology.iu.edu/worthwhileEducation.html )

The conclusion reached by Greenspan and Benderly ( 1997 ) identifies the essence of the matter for human education:

Computers may be able to perform certain cognitive operations, even more effectively, and certainly faster, than humans. But unless they acquire the ability to experience and react to emotion, silicon chips will be unable to exercise intelligent discrimination…. What separates human intelligence from that of computers, robots, androids, and any other cyber-creatures we can imagine, is the fact that we possess a nervous system capable of—indeed specifically designed for—generating and evaluation of affect…. Unless and until we solve the problem of creating living cellular reactivity and affects, as well as the capacity to abstract patterns of affects, in an artificial form, no machine will think in a truly human way. (pp. 126-127)

Human teachers are essential to education. It is vital that teachers and students form affective bonds. This is the most important relationship in education systems that must be nurtured, no matter how technology might evolve. This is not an empirical claim from science or praxiology. It is a philosophic claim about what should be (Steiner 1981 , 1988 , 2009 ).

The conclusion at the end of Restructuring Education Through Technology is still relevant now and in the future, as it was then:

… the technology cannot select the best of culture for sharing with students.… In short, the technology cannot evaluate the worth of the content that we embody in the medium. That is our essential role as teachers. We must select the best of culture and share it with the next generation. (Frick 1991 , p. 32)

For the more precise predicate calculus definitions, see Thompson ( 2019 , https://aptac.sitehost.iu.edu/glossary/). The symbol, ‘= df ’ means ‘equals by definition’.

Note that an education system should not be assumed to be synonymous with a physical place, such as a particular school system—e.g., a district in a city or county consisting of school buildings containing classrooms. Components and their affect-relations can be in different physical locations —e.g., students could be at their different homes, teachers at their homes, and the content on YouTube (via the Internet); teachers and students could communicate through the Internet (e.g., by texting, Zoom, Facebook, etc.). For further information and examples, see the Educology (2020 ) website: https://educology.iu.edu

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Abridged Glossary

System  =  df “a set of components and a family of affect-relations ” Thompson ( 2019 ). Footnote 1

Affect-Relation  =  df a set of relations either between components or between temporal events, or both.

Structural Affect-Relation  =  df the configuration of connectedness among components.

Temporal Affect-Relation  =  df the changing temporal configuration of events.

Negasystem  =  df not system , i.e., components and affect-relations not in a system .

System Toput  =  df the set of components in the negasystem available for selection by the system (synonym: system environment ).

System Input  =  df the set of negasystem components selected by the system .

System Fromput  =  df the set of system components available for selection by the negasystem .

System Output  =  df the set of system components selected by the negasystem .

System Feedin  =  df the temporal affect-relation for system toput at time 1 and system input at time 2.

System Feedout  =  df the temporal affect-relation for system fromput at time 1 and system output at time 2.

System Filtration  =  df restriction of system feedin .

Education System  =  df an intentional system consisting of at least one teacher and one student in a context . Footnote 2

Context  =  df the setting for teaching and learning that contains content .

Content  =  df signs of objects and objects selected for student learning .

Teaching  =  df the intentional guidance of another person’s learning (synonym: instructing ).

Learning  =  df the increasing of complexity of mental structures .

Student  =  df a person who intends to learn content with a teacher .

Teacher  =  df a person whose intention is to guide another’s learning .

Intention  =  df willing (i.e., trying to do, seeking a goal; synonym: conation ).

Teacher-Student Affect-Relation s =  df structural and temporal affect-relations among students and teachers .

Student-Content Affect-Relation s =  df structural and temporal affect-relations among students and content .

Student-Context Affect-Relation s =  df structural and temporal affect-relations among students and context .

Teacher-Content Affect-Relation s =  df structural and temporal affect-relations among teachers and content .

Teacher-Context Affect-Relation s =  df structural and temporal affect-relations among teachers and context .

Context-Content Affect-Relation s =  df structural and temporal affect-relations between contexts and content .

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Frick, T.W. Education Systems and Technology in 1990, 2020, and Beyond. TechTrends 64 , 693–703 (2020). https://doi.org/10.1007/s11528-020-00527-y

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What Changes to the U.S. Education System Are Needed to Support Long-Term Success for All Americans?

With the pandemic deepening inequities that threaten students’ prospects, the vice president of the Corporation’s National Program provides a vision for transforming our education system from one characterized by uneven and unjust results to one that puts all students on a path to bright futures 

At no point in our nation’s history have we asked so much of our education system as we do today. We ask that our primary and secondary schools prepare all students, regardless of background, for a lifetime of learning. We ask that teachers guide every child toward deeper understanding while simultaneously attending to their social-emotional development. And we ask that our institutions of higher learning serve students with a far broader range of life circumstances than ever before.

We ask these things of education because the future we aspire to requires it. The nature of work and civic participation is evolving at an unprecedented rate. Advances in automation, artificial intelligence, and social media are driving rapid changes in how we interact with each other and what skills hold value. In the world our children will inherit, their ability to adapt, think critically, and work effectively with others will be essential for both their own success and the well-being of society.

At Carnegie Corporation of New York, we focus on supporting people who are in a position to meet this challenge. That includes the full spectrum of educators, administrators, family members, and others who shape young people’s learning experiences as they progress toward and into adulthood. Our mission is to empower all students with the tools, systems, knowledge, and mindsets to prepare them to fully participate in the global economy and in a robust democracy.

All of our work is geared toward transforming student learning. The knowledge, skills, and dispositions required for success today call for a vastly different set of learning experiences than may have sufficed in the past. Students must play a more active role in their own learning, and that learning must encompass more than subject-matter knowledge. Preparing all children for success requires greater attention to inclusiveness in the classroom, differentiation in teaching and learning, and universal high expectations.

This transformation needs to happen in higher education as well. A high school education is no longer enough to ensure financial security. We need more high-quality postsecondary options, better guidance for students as they transition beyond high school, and sufficient supports to enable all students to complete their postsecondary programs. Preparing students for lifelong success requires stronger connections between K–12, higher education, and work.

The need for such transformation has become all the more urgent in the face of COVID-19. As with past economic crises, the downturn resulting from the pandemic is likely to accelerate the erosion of opportunities for low-skilled workers with only a high school education. Investments in innovative learning models and student supports are critical to preventing further inequities in learning outcomes. 

An Urgent Call for Advancing Equity 

The 2020–21 school year may prove to be the most consequential in American history. With unfathomable speed, COVID-19 has forced more change in how schools operate than in the previous half century.

What is most concerning in all of this is the impact on the most underserved and historically marginalized in our society: low-income children and students of color. Even before the current crisis, the future prospects of a young person today looked very different depending on the color of her skin and the zip code in which she grew up, but the pandemic exposed and exacerbated long-standing racial and economic inequities. And the same families who are faring worst in terms of disrupted schooling are bearing the brunt of the economic downturn and disproportionately getting sick, being hospitalized, and dying.

Our mission is to empower all students with the tools, systems, knowledge, and mindsets to prepare them to fully participate in the global economy and in a robust democracy.

Every organization that is committed to educational improvement needs to ask itself what it can do differently to further advance the cause of educational equity during this continuing crisis so that we can make lasting improvements. As we know from past experience, if the goal of equity is not kept front and center, those who are already behind through no fault of their own will benefit the least. If ever there were a time to heed this caution, it is now.

We hope that our nation will approach education with a new sense of purpose and a shared commitment to ensuring that our schools truly work for every child. Whether or not that happens will depend on our resolve and our actions in the coming months. We have the proof points and know-how to transform learning, bolster instruction, and meet the needs of our most disadvantaged students. What has changed is the urgency for doing so at scale.

Our starting place must be a vision of equal opportunity, and from there we must create the conditions that can actually ensure it — irrespective of how different they may look from the ones we now have. We need to reimagine the systems that shape student learning and put the communities whose circumstances we most need to elevate at the center of that process. We need to recognize that we will not improve student outcomes without building the capacity of the adults who work with them, supporting them with high-quality resources and meaningful opportunities for collaboration and professional growth. We need to promote stronger connections between K–12, higher education, and employment so that all students are prepared for lifelong success.

The pandemic has deepened inequities that threaten students’ prospects. But if we seize this moment and learn from it, if we marshal the necessary resources, we have the potential to transform our education system from one characterized by uneven and unjust results to one that puts all students on a path to bright futures.

In a pandemic-induced moment when the American education system has been blown into 25 million homes across the country, where do we go from here?

We Must Learn to Act in New Ways

These are not controversial ideas. In fact, they constitute the general consensus about where American education needs to go. But they also represent a tall order for the people who influence the system. Practically everyone who plays a part in education must learn to act in new ways.

That we have made progress in such areas as high school completion, college-going rates, and the adoption of college- and career-ready standards is a testament to the commitment of those working in the field. But it will take more than commitment to achieve the changes in student learning that our times demand. We can’t expect individuals to figure out what they need to do on their own, nor should we be surprised if they struggle to do so when working in institutional structures designed to produce different outcomes. The transformation we seek calls for much greater coordination and a broader set of allies than would suffice for more incremental changes.

Our starting place must be a vision of equal opportunity, and from there we must create the conditions that can actually ensure it — irrespective of how different they may look from the ones we now have.

Our best hope for achieving equity and the transformation of student learning is to enhance adults’ ability to contribute to that learning. That means building their capacity while supporting their authentic engagement in promoting a high-quality education for every child. It also means ensuring that people operate within systems that are optimized to support their effectiveness and that a growing body of knowledge informs their efforts.

These notions comprise our overarching strategy for promoting the systems change needed to transform student learning experiences on a large scale. We seek to enhance adult capacity and stakeholder engagement in the service of ensuring that all students are prepared to meet the demands of the 21st century. We also support knowledge development and organizational improvement to the extent that investments in these areas enhance adult capacity, stakeholder engagement, and student experiences.

Five Ways We Invest in the Future of Students

These views on how best to promote systems change in education guide our philanthropic work. The strategic areas of change we focus on are major themes throughout our five investment portfolios. Although they are managed separately and support different types of initiatives, each seeks to address its area of focus from multiple angles. A single portfolio may include grants that build adult capacity, enhance stakeholder engagement, and generate new knowledge.

New Designs to Advance Learning

Preparing all students for success requires that we fundamentally reimagine our nation’s schools and classrooms. Our public education system needs to catch up with how the world is evolving and with what we’ve come to understand about how people learn. That means attending to a broader diversity of learning styles and bringing what happens in school into greater alignment with what happens in the worlds of work and civic life. We make investments to increase the number of innovative learning models that support personalized experiences, academic mastery, and positive youth development. We also make investments that build the capacity of districts and intermediaries to improve learning experiences for all students as well as grants to investigate relevant issues of policy and practice.

Pathways to Postsecondary Success

Lifelong success in the United States has never been more dependent on educational attainment than it is today. Completing some education beyond the 12th grade has virtually become a necessity for financial security and meaningful work. But for that possibility to exist for everyone, we need to address the historical barriers that keep many students from pursuing and completing a postsecondary program, and we must strengthen the options available to all students for education after high school. Through our investments, we seek to increase the number of young people able to access and complete a postsecondary program, with a major focus on removing historical barriers for students who are first-generation college-goers, low-income, or from underrepresented groups. We also look to expand the range of high-quality postsecondary options and to strengthen alignment between K–12, higher education, and the world of work.

Leadership and Teaching to Advance Learning

At its core, learning is about the interplay between teachers, students, and content. How teachers and students engage with each other and with their curriculum plays a predominant role in determining what students learn and how well they learn it. That’s not to say that factors outside of school don’t also greatly impact student learning. But the research is clear that among the factors a school might control, nothing outweighs the teaching that students experience. We focus on supporting educators in implementing rigorous college- and career-ready standards in math, science, and English language arts. We make investments to increase the supply of and demand for high-quality curricular materials and professional learning experiences for teachers and administrators.

Public Understanding

As central as they are to the education process, school professionals are hardly the only people with a critical role to play in student learning. Students spend far more time with family and other community members than they do at school. And numerous stakeholders outside of the education system have the potential to strengthen and shape what happens within it. The success of our nation’s schools depends on far more individuals than are employed by them. 

We invest in efforts to engage families and other stakeholders as active partners in supporting equitable access to high-quality student learning. We also support media organizations and policy research groups in building awareness about key issues related to educational equity and improvement.

Integration, Learning, and Innovation

Those of us who work for change in education need a new set of habits to achieve our vision of 21st-century learning. It will take more than a factory-model mindset to transform our education system into one that prepares all learners for an increasingly complex world. We must approach this task with flexibility, empathy for the people involved, and an understanding of how to learn from what’s working and what’s not. We work to reduce the fragmentation, inefficiencies, and missteps that often result when educational improvement strategies are pursued in isolation and without an understanding of the contexts in which they are implemented. Through grants and other activities, we build the capacity of people working in educational organizations to change how they work by emphasizing systems and design thinking, iteration, and knowledge sharing within and across organizations.

Two recent surveys by Carnegie Corporation of New York and Gallup offer insights into how our education system can better help all Americans navigate job and career choices

Join Us in This Ambitious Endeavor

Our approach of supporting multiple stakeholders by pulling multiple levers is informed by our deep understanding of the system we’re trying to move. American education is a massive, diverse, and highly decentralized enterprise. There is no mechanism by which we might affect more than superficial change in many thousands of communities. The type of change that is needed cannot come from compliance alone. It requires that everyone grapple with new ideas.

We know from our history of promoting large-scale improvements in American education that advancements won’t happen overnight or as the result of one kind of initiative. Our vision for 21st-century education will require more than quick wins and isolated successes. Innovation is essential, and a major thrust of our work involves the incubation and dissemination of new models, resources, and exemplars. But we must also learn to move forward with the empathy, flexibility, and systems thinking needed to support people in making the transition. Novel solutions only help if they can be successfully implemented in different contexts.

Only a sustained and concerted effort will shift the center of gravity of a social enterprise that involves millions of adults and many tens of millions of young people. The challenge of philanthropy is to effect widespread social change with limited resources and without formal authority. This takes more than grantmaking. At the Corporation, we convene, communicate, and form coalitions. We provide thought leadership, issue challenges, and launch new initiatives. Through these multifaceted activities, we maximize our ability to forge, share, and put into practice powerful new ideas that build a foundation for more substantial changes in the future.

We encourage everyone who plays a role in education to join us in this work. Our strategy represents more than our priorities as a grantmaker. It conveys our strong beliefs about how to get American education to where it needs to be. The more organizations and individuals we have supporting those who are working to provide students with what they need, the more likely we are to succeed in this ambitious endeavor. 

LaVerne Evans Srinivasan is the vice president of Carnegie Corporation of New York’s National Program and the program director for Education.

TOP: Due to the COVID-19 outbreak, a lower-school substitute teacher works from her home in Arlington, Virginia, on April 1, 2020. Her role in the school changed significantly due to the pandemic. Whereas she previously worked part-time to support teachers when they needed to be absent from the classroom, amid COVID-19 she now helps teachers to build skills with new digital platforms so they can continue to teach in the best way for their students and their families. (Credit: Olivier Douliery/AFP via Getty Images)

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From researching the nation's legacy of poverty in rural areas to creating a user-friendly guide to environmental governance, these Andrew Carnegie Fellows are dissecting problems and offering solutions

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A century of educational inequality in the United States

Michelle jackson.

a Department of Sociology, Stanford University, Stanford, CA, 94305;

Brian Holzman

b Houston Education Research Consortium, Rice University, Houston, TX, 77005

Author contributions: M.J. and B.H. designed research; M.J. and B.H. analyzed data; and M.J. wrote the paper.

Associated Data

The analysis code and auxiliary data required to produce the figures and tables in this paper can be accessed at https://osf.io/jxne5 . Code to produce estimates for each of the individual datasets (see Table 1 ) is also provided. Details on how to access these datasets are provided in SI Appendix (most datasets are available for download upon registration with the data provider, while others are accessible only with a restricted use license from the National Center for Education Statistics).

Significance

There has been widespread concern that the takeoff in income inequality in recent decades has had harmful social consequences. We provide evidence on this concern by assembling all available nationally representative datasets on college enrollment and completion. This approach, which allows us to examine the relationship between income inequality and collegiate inequalities over the full century, reveals that the long-standing worry about income inequality is warranted. Inequalities in college enrollment and completion were low for cohorts born in the late 1950s and 1960s, when income inequality was low, and high for cohorts born in the late 1980s, when income inequality peaked. This grand U-turn means that contemporary birth cohorts are experiencing levels of collegiate inequality not seen for generations.

The “income inequality hypothesis” holds that rising income inequality affects the distribution of a wide range of social and economic outcomes. Although it is often alleged that rising income inequality will increase the advantages of the well-off in the competition for college, some researchers have provided descriptive evidence at odds with the income inequality hypothesis. In this paper, we track long-term trends in family income inequalities in college enrollment and completion (“collegiate inequalities”) using all available nationally representative datasets for cohorts born between 1908 and 1995. We show that the trends in collegiate inequalities moved in lockstep with the trend in income inequality over the past century. There is one exception to this general finding: For cohorts at risk for serving in the Vietnam War, collegiate inequalities were high, while income inequality was low. During this period, inequality in college enrollment and completion was significantly higher for men than for women, suggesting a bona fide “Vietnam War” effect. Aside from this singular confounding event, a century of evidence establishes a strong association between income and collegiate inequality, providing support for the view that rising income inequality is fundamentally changing the distribution of life chances.

It has long been suspected that the takeoff in income inequality has made the good luck of an advantaged birth ever more consequential for accessing opportunities and getting ahead. The “income inequality” hypothesis proposes that intergenerational inequality—with respect to educational attainment, social mobility, and other socioeconomic outcomes—will increase as income inequality grows. Because this hypothesis shot to public attention with Krueger’s ( 1 ) discussion of the Great Gatsby curve, the proposition that high levels of income inequality have generated correspondingly high levels of intergenerational reproduction is now a staple of public and political discourse. Despite the prominence of this argument, the evidence in its favor is less overwhelming than might be assumed ( 2 ), and is largely limited to the empirical result that intergenerational income inheritance has increased in recent decades, at least in some analyses ( 3 , 4 ). Even this result has been contested and is far from widely accepted ( 5 ).

In this paper, we assess the plausibility of the income inequality hypothesis by examining changes over the past century in the income-based gaps in college enrollment and completion. This is a field in which descriptive evidence is key: Designs that would allow for convincing causal inference are in short supply, and where designs are available, the data are not. And yet most of the descriptive evidence in regard to the college level pertains only to recent decades, when both income inequality and collegiate inequalities have increased (refs. 6 – 8 ).

The trends through earlier decades of the century, within which the great U-turn in income inequality occurred, remain largely undocumented. To overcome this evidence deficit, we might be inclined to draw on evidence on other educational outcomes, such as test scores and years of schooling. Reardon’s analysis of family income test score gaps, for example, shows steadily rising gaps between cohorts born in the 1940s and those born in the present day (ref. 9 ; cf. ref. 10 ). But test scores are quite imperfectly correlated with educational attainment, and evidence from studies of inequalities in years of schooling would support different conclusions on trend. Hilger’s ( 11 ) analysis of long-term trends using Census data shows that there was a decline in the effects of parental income on child’s education between the 1940s and 1970s, while Mare ( 12 ) shows an increasing effect of family income on higher-level educational transitions for midcentury cohorts as compared to early-century cohorts. Taking these studies together, it is difficult to reach any firm conclusion about the income inequality hypothesis, as one might infer an increase, a decrease, or stability in collegiate inequalities during the midcentury, depending on which study is considered.

Extending the time series over the whole of the past century allows for a fuller assessment of the income inequality hypothesis, as the long-run historical series on income inequality exhibits a relatively complicated pattern, as opposed to the simple increase in the recent period. In much the same way as the magnitude of changes in income inequality could only be appreciated when considered in the long run, current levels of educational inequality must be evaluated and understood in full historical context ( 13 ). In a comprehensive extension of previous research on collegiate inequalities, we thus use all nationally representative data sources that we were able to locate and access. This strengthens the descriptive evidence that can be brought to bear upon the income inequality hypothesis.

In the following sections, we discuss the available data and the methods of analysis, and present our results on long-term trends in collegiate inequalities. We will focus on inequalities in completion of 4-year college, enrollment in 4-year college, and enrollment in any college (2- or 4-year). We will demonstrate an essential similarity in inequality trends across the range of collegiate outcomes. Although we will show that income inequality is strongly associated with inequalities at the college level, we will also highlight that it is not the only force at work.

College Enrollment and Completion in the Twentieth Century

The twentieth century was the first century in which education systems were widely diffused and, at least in principle, accessible to all social groups. The century witnessed substantial expansion at the college level: The college enrollment rate for 20- to 21-y-olds increased from around 15 % for the mid-1920s birth cohorts to almost 60 % for cohorts born toward the end of the century. * As Fig. 1 shows, rates of enrollment rose rapidly for cohorts born in the early century to midcentury, and flattened out and even declined for the midcentury birth cohorts, before resuming a steady increase for cohorts born in the later decades of the century.

Proportion of birth cohort enrolled in college ages 20 y to 21 y ( 14 ), and proportions completing 2- and 4-year college degrees, Current Population Survey March, Annual Social and Economic Supplement ( 15 ).

We see in Fig. 1 a stark reversal of the gender gap in college enrollment; for birth cohorts from the mid-1950s to mid-1990s, the proportion of women enrolled in college grew by around 30 percentage points, while the corresponding increase for men was just under 20 percentage points ( 16 , 17 ). The reversal occurred immediately after the rapid increase in enrollment rates observed for male birth cohorts at risk for service in the Vietnam War ( 16 ). A literature in economics has demonstrated that men born in the 1940s and 1950s were unusually likely to attend and graduate from college, although there is disagreement with respect to whether the observed increase in men’s college participation rates should be attributed to draft avoidance or to postservice GI Bill enrollments (ref. 18 ; cf. ref. 19 ).

Alongside trends in college enrollment, Fig. 1 presents rates of college completion by type of degree. While rates of completion of 2-year college are rather flat for cohorts born from the 1950s onward, rates of 4-year college completion have increased considerably. As the figure suggests, rates of 4-year college completion are highly correlated with rates of enrollment, but research shows that, over the past half-century, rates of college completion increased less sharply than rates of enrollment, because the college dropout rate increased ( 6 , 20 ).

Materials and Method

Although it is relatively straightforward to examine changes in rates of college enrollment and completion over time, it is rather less straightforward to examine income inequalities in collegiate outcomes across the span of the twentieth century, because data on parental income, college enrollment, and college completion are not routinely collected in government surveys. We must therefore piece together the trends in collegiate inequalities through the analysis of available sources of nationally representative data. We include results from the analysis of both cross-sectional surveys of adults and longitudinal surveys beginning with school-aged children, and, for a number of recent cohorts, we calculate estimates from tax data results in the public domain. Although this approach presents obvious challenges as regards comparability of data sources and measures, for much of the period that we cover, we have multiple estimates of collegiate inequalities for any given period of time. The datasets and their key characteristics are listed in Table 1 ; detailed descriptions of each dataset are included in SI Appendix .

Characteristics of the datasets included in the analysis

Add Health, National Longitudinal Study of Adolescent to Adult Health; ELS, Education Longitudinal Study; HSLS, High School Longitudinal Study.

The datasets cover cohorts born between 1908 and 1995, and it is only at the beginning and the end of the data series that our birth cohorts are represented by no more than one dataset. Although we aim to define cohorts according to year of birth, for some of the datasets we must construct quasi-cohorts based on age or grade, because year of birth was not recorded.

The biggest constraint that we face in analyzing income inequalities in collegiate attainment relates to gender. Data on the earlier birth cohorts come from the Occupational Changes in a Generation (OCG 1973) survey, which was administered in conjunction with the Current Population Survey ( 21 ). This survey was completed by men only, so we lack information on the educational attainment of women in the earliest birth cohorts. By presenting all results separately for men and women, patterns over time can be compared by gender.

The datasets were prepared to provide consistent measures of family income, college enrollment, and college completion. We produce simple binary variables that capture whether an individual completed a 4-year degree, whether an individual enrolled in (without necessarily completing) a 4-year degree program, and whether an individual enrolled in (without necessarily completing) a college program. Unfortunately, the tax data results pertain only to college enrollment per se, so we have fewer available data points for the analyses of 4-year completion and enrollment than for the analyses of enrollment in any college program. All samples are restricted to individuals who enrolled in high school, in order to maximize consistency across samples. In SI Appendix , we also include results for a smaller sample restricted to high school graduates ( SI Appendix , Fig. S6 ).

A more difficult variable to harmonize over time is family income. Although in some datasets family income is measured directly (e.g., annual net family income in dollars), in many of the available datasets family income is measured only as an ordinal variable. For these datasets, we employ the method used by Reardon ( 9 ) to calculate test score gaps from coarsened family income data; the method uses the proportions in each income category to assign an income rank to all of those in a given category, and income rank is then the explanatory variable in the analysis ( SI Appendix , SI Methods ).

We estimate logits predicting college enrollment and completion as a function of family income or income rank. Following Reardon ( 9 ), we fit squared and cubed terms to capture the nonlinear effects of income rank. Using the model, we estimate the enrollment and completion rates of those at the 90th percentile of family income and those at the 10th percentile. We choose the 90 vs. 10 comparison over other ways of defining inequality because it accords with past assessments and with the main source of trend in income inequality ( 9 ). † From these rates, we calculate log-odds ratios capturing, for example, the log-odds of completing a 4-year college degree for the 90 vs. 10 family income comparison.

We would be remiss if we did not note the difficulty in measuring family income reliably, particularly using one-shot measures, which are all that are available in almost all of the datasets that we analyze. Further worries might arise because some of the income measures are retrospective, or because the questions are asked of children, not parents. Although we would not minimize the danger of retrospection or of using children’s reports of family income, evidence suggests that child reports of parental socioeconomic characteristics are not substantially worse than parental reports of those characteristics ( 9 , 22 ). Furthermore, the types of errors that individuals make when reporting income appear to have changed very little over time ( 23 ), which is the key issue when mapping trend. To address concerns about the varying quality of the family income data, we multiply all log-odds ratios by 1 / r , where r is the estimated reliability of the family income measure (see SI Appendix , Table S5 for reliability estimates) ( 9 ).

We recognize that “researcher degrees of freedom” are of particular concern when presenting results from a large number of datasets ( 24 ). We provide additional results based on alternative specifications, in SI Appendix , and make our analysis code publicly available on Open Science Framework, https://osf.io/jxne5 .

The Great U-turn in Collegiate Inequality

We now examine collegiate inequalities for cohorts born between 1908 and 1995. Given data constraints, we are limited to examining inequalities over the whole period for men only, but we present results for women for a more limited range of birth cohorts.

In Fig. 2 we present, for the full male series, the estimated probabilities of completing 4-year college at the 90th and 10th percentiles of family income. ‡ We see in Fig. 2 that the increase in 4-year college degree attainment over the twentieth century was far from equally distributed across income groups. Men from the 90th percentile of family income were at the leading edge of the expansion; the figure shows a rapid increase in college completion rates through the 1940s birth cohorts, then a tailing off through the 1950s cohorts, followed by a further rapid increase for those cohorts born in the 1960s onward. In contrast, expansion at the bottom of the income distribution was more sluggish; 4-year college completion rates at the 10th percentile were less than 10 percentage points higher for cohorts born at the end of the century than for cohorts born at the beginning.

Probabilities of 4-year college completion at the 90th and 10th percentiles of family income, male birth cohorts, 1908–1986.

Fig. 2 shows that absolute differences in completion rates between income groups increased from the beginning to the end of the century. But this important result must be considered alongside changes over the century in the overall completion rate ( 12 ). Although the probability gap was small at the beginning of the century, the odds of college completion were around 7 times higher for the rich than for the poor, because the rich were able to secure a large proportion of the limited number of college slots. In relative terms, the poor born in the early century were more disadvantaged than their counterparts born in the 1960s, when 90 vs. 10 gaps in the probability of college completion were substantially larger. Although both probability gap and odds-ratio measures are informative, we focus from this point forward on odds-ratio measures of educational inequality, which are margin insensitive and thus feature relative—rather than absolute—advantage. But, in SI Appendix , we present probability plots for the three collegiate outcomes ( SI Appendix , Fig. S1 ), and include analyses based on probability gaps in SI Appendix , Table S3 . The key results hold for both types of analysis.

We plot, in Fig. 3 , the 90 vs. 10 log-odds ratios describing inequalities in collegiate outcomes for each of the datasets in our analyses, with trends estimated from generalized additive models (GAM). The GAMs are fitted to the plotted data points, with each point weighted by the inverse of the SE for the estimate. § In the earlier period covered by OCG, we fit the model to the estimates derived from analyses of single birth cohorts, but present point estimates representing groups of birth cohorts to show the consistency across these specifications. Confidence intervals are presented in SI Appendix , Fig. S2 ; figures showing 90 vs. 50 and 50 vs. 10 inequalities are included as SI Appendix , Figs. S3 and S4 .

The 90 vs. 10 log-odds ratios expressing inequality in 4-year completion, 4-year enrollment, and any college enrollment. ( Left ) Male birth cohorts, 1908–1995; ( Right ) female birth cohorts, 1951–1995.

We focus first on describing the trends for men, for whom we have results spanning the whole century. It is clear from Fig. 3 that the over-time trends are similar across the various collegiate outcomes and, further, that there is no simple secular trend for any of the outcomes under consideration. There are three key attributes of the trends that should be emphasized.

First, Fig. 3 shows that, toward the middle of the century, there was a great U-turn in collegiate inequality. Inequalities fell rapidly for cohorts born in the early to mid-1950s, then bottomed out until the mid-1960s, before ultimately rising steeply for cohorts born from the mid-1960s onward. The U-turn appears to be more pronounced for 4-year and “any college” enrollment than for completion of a 4-year degree, but it is present for all of the collegiate outcomes under consideration.

Had we measured collegiate inequalities in but a single dataset, we might be skeptical that our observed trend was on the mark and, in particular, that there was a rapid fall in inequality for the midcentury birth cohorts. But this trend is supported across all of the datasets from the period: OCG and National Longitudinal Study (NLS) Young Men show high inequality in the early 1950s; Panel Study of Income Dynamics (PSID), NLS72, and High School and Beyond (HS&B) pick up the lower inequality of the mid-1950s to the mid-1960s; and the subsequent uptick in inequality is captured in PSID, the school cohort surveys, and the National Longitudinal Studies of Youth (NLSY79&97). Indeed, Fig. 3 demonstrates that there is great consistency across a large number of different data sources. ¶ At the trough, inequality in 4-year college completion was reduced to a log-odds ratio of around 1.5, indicating that, even in this low-inequality period, the odds of those at the 90th income percentile completing a 4-year college degree were almost 4.5 times greater than the equivalent odds for those at the 10th percentile. Inspection of SI Appendix , Fig. S3 suggests that the U-turn observed in Fig. 3 is largely driven by changes in the top half of the income distribution: the U-turn is rather more pronounced for the 90 vs. 50 comparison than for the 50 vs. 10 comparison.

Second, if skepticism about a midcentury fall in collegiate inequality were to be sustained, suspicion would also have to fall upon all currently accepted results on over-time trends, which demonstrate a substantial increase in inequalities in college enrollment and completion between cohorts born in the midcentury and late century. If we were to impose a simple linear smooth on the century-long data series, this would indicate relatively modest increases in collegiate inequalities over the period taken as a whole (see dashed lines, Fig. 3 ). # Again, because the trends are mapped using multiple datasets, we are confident that the pattern of a U-turn in collegiate inequality is supported.

Third, any evidence of a U-turn must bring to mind the pattern of income inequality over the past century. As Piketty and Saez ( 27 ) described, toward the middle of the twentieth century, the share of income going to the top 10% rapidly declined, before rising again over the later decades of the century. The U-turn in collegiate inequality mimics this trend, although it is notable that, insofar as we see similarity in patterns of income inequality and collegiate inequalities, it is income inequality around year of birth that appears to matter most. But, despite the obvious similarities, there is at least one clear divergence in the pattern of collegiate inequality and income inequality: The U-turn in collegiate inequality comes very late. Income inequality begins to fall in the early 1940s, but inequalities in enrollment and completion begin to decline only for cohorts born in the mid-1950s. Men born in the mid-1940s onward were not just born into a period of low inequality, but they spent most of their formative years in a low-inequality society. Despite this, the evidence shows that collegiate inequality increased substantially for the cohorts born in the 1940s and early 1950s; the log-odds ratios describing inequality are increased by around a third over this short period.

Some of the same key features are visible in the results for women, shown in Fig. 3 , Right , although we only have access to data for women born after 1950. We see a basic similarity with the men’s analyses from the mid-1950s birth cohorts onward: Collegiate inequalities are relatively flat for the 1950s to 1960s birth cohorts, and increase for women born in the 1970s and onward. Just as with men, toward the end of the period we see flat and even declining inequalities in enrollment and completion. There are perhaps some subtle differences in the pattern by gender—the upturn in collegiate inequality begins, for example, several years later for women than for men—but we have little evidence here to support a conclusion of substantial difference in inequality for men and women over this period.

There is one notable difference between the men’s and women’s results, relating to the period when trends in male collegiate inequality substantially diverged from trends in income inequality. This exceptional period appears to be exceptional for men, but not for women. Although we cannot track collegiate inequalities for women across the whole midcentury period, the first data points in the female data series (NLS Young Women: 1951–1953 birth cohorts) are lower than the nearby estimates for men (NLS Young Men: 1949–1951 birth cohorts). ** This period of divergence between collegiate inequality and income inequality coincides with the period that we identified above as holding special consequences for men’s educational attainment: Men born in the 1940s and early 1950s were subject to the threat of military service in the Vietnam War.

There are no cohort studies of women that would allow us to compare male and female inequalities in college enrollment and completion throughout this period. We do, however, have access to data on men who fathered children who were at risk for service during the Vietnam War: The NLS Older Men survey can be used to track collegiate inequalities for the children of men who were aged 45 y to 59 y in 1966. The structure of this dataset is somewhat different from the datasets underlying our time series, but we nevertheless find confirmation, in Fig. 4 , that male and female inequalities diverged in the Vietnam years.

The 90 vs.10 log-odds ratios expressing inequality in 4-year college completion, 4-year enrollment, and any college enrollment, men and women born 1935–1943 and 1944–1952, NLS-Older Men data.

In the pre-Vietnam period, male and female collegiate inequalities were of similar magnitude. The log-odds ratio for 4-year enrollment, for example, was 2.3 for men (95% CI: 1.5, 3.1), as compared to 2.4 for women (1.7, 3.2). But, for the birth cohorts at risk for serving in Vietnam, the male log-odds ratio increased slightly, to 2.5 (1.8, 3.2), while inequality fell substantially for women, to 1.4 (0.8, 2.0) (see SI Appendix , Fig. S8 for a figure with CIs). These results provide support for the claim that men’s collegiate inequality was substantially and artificially raised relative to expected levels during this period because of the Vietnam War. Unfortunately, our data are not well-suited to evaluating why male and female collegiate inequality differed in the Vietnam period. But some evidence can be brought to bear on this question by comparing preservice and postservice inequalities in college participation for the men in OCG ( SI Appendix , Fig. S9 ). These data are more consistent with a draft-induced increase in male collegiate inequality than with a GI Bill-induced increase. ††

Bringing the results in Fig. 4 together with what is known about college enrollment and completion patterns during the Vietnam War period, it seems likely that the disproportionate increase in men’s college participation rates observed in Fig. 1 was achieved, at least in part, through a gender-specific change in the effect of family income on college enrollment and completion.

The Association between Income Inequality and Collegiate Inequality.

We now present a formal statistical test of the strength of the association between income inequality and collegiate inequality. We regress the log-odds for collegiate inequalities on income inequality, as measured through the share of wages going to the top 10% ( 27 ). ‡‡ In addition to the income inequality variable, for the full male series (1908–1995), we fit a “Vietnam effect,” with a dummy variable that isolates the cohorts at risk from the draft lotteries (i.e., 1944–1952 birth cohorts). We fit models to the full male series (1908–1995 birth cohorts), a compressed male series (1952–1995 birth cohorts), and the female series (1951–1995 birth cohorts). A full regression table with coefficients and standard errors is included as SI Appendix , Table S4 . §§ In Fig. 5 , we present estimates of the predicted increase in the log-odds ratios for an eight percentage point increase in the share of wages going to the top 10%; this increase is equivalent to the “takeoff” in income inequality that occurred between the midcentury and the 1990s. ¶¶

Predicted increase in collegiate inequality log-odds ratios associated with the top 10%’s share of wages increasing by 0.08 (equivalent to the takeoff in income inequality); 90 vs. 50 (dark gray), 50 vs. 10 (light gray), and 90 vs. 10 (total) comparisons.

The regression coefficients describing the associations between income inequality and 90 vs. 10 collegiate inequalities can be straightforwardly decomposed into two parts: an association between income inequality and the 90 vs. 50 log-odds ratio, and an association between income inequality and the 50 vs. 10 log-odds ratio. In Fig. 5 , the total height of each bar represents the predicted increase in the 90 vs. 10 log-odds ratio for an eight percentage point increase in income inequality, while the dark and light gray bars show the predicted increases in the 90 vs. 50 and 50 vs. 10 log-odds ratios, respectively.

Examining first the results for the 90 vs. 10 comparison, we see confirmation of a relatively strong association between income inequality and collegiate inequality over the full sweep of the twentieth century. For women, for example, the model predicts that an increase in income inequality equivalent to that observed in the takeoff period would increase the 90 vs. 10 log-odds ratio by around 1 for 4-year enrollment and completion, and by around 1.3 for enrollment in any college. Although there is variation in the strength of the association for the different outcome measures, the income inequality effects are large and positive in all of the analyses, indicating substantial support for the income inequality hypothesis.

Given that the takeoff in income inequality was largely characterized by the top of the income distribution moving away from the middle and bottom of the distribution, the income inequality hypothesis would predict larger effect sizes for the 90 vs. 50 comparison than for the 50 vs. 10 comparison. When we decompose the 90 vs. 10 results into 90 vs. 50 and 50 vs. 10 components, we see precisely this result. The income inequality effects for the 90 vs. 50 comparisons in all cases outweigh those for the 50 vs. 10 comparisons, particularly in the analyses of 4-year college enrollment and completion.

But the results also provide grounds for exercising caution when interpreting differences in effect sizes across the models, as the effect sizes in the full and compressed male series are more similar for the “any college” analyses than for the 4-year analyses, where the sample sizes are smaller. Even when analyzing all available datasets and exploiting the full range of variation in income inequality over the century, our statistical power is limited. This is even more clear when we extend the models summarized in Fig. 5 to include additional macro-level regressors that social scientists have previously used to predict inequalities at the college level. These additional variables include the economic returns to schooling, which are assumed to influence individual decisions about whether or not to invest in college education ( 33 ), and the high school graduation rate, which has been shown to influence educational expansion at the college level ( 34 ). As shown in SI Appendix , Table S1 , estimates from these models are more volatile, particularly for women.

The volatility arises because some of our analyses are, like past analyses, limited to more recent cohorts in which the takeoff assumes a monotonically increasing form. This makes it difficult to adjudicate between the large number of monotonically increasing potential causes. An important advantage of our full-century approach is that it reaches back to a time in which these competing causes did not always move together. In Fig. 6 , we present the results of a simulation exercise, in which we run 1,000 regressions for a range of different model specifications on the full and compressed male series, with each regression including a new variable containing random numbers drawn from a normal distribution ( μ = 0; σ = 1). We examine the stability of the income inequality effects with respect to inequality in college enrollment, for which we have the largest number of data points. We add to the basic model in Fig. 5 controls for time, either in the form of 1) a linear effect of year or 2) dummies for decades, and measures of the returns to schooling ( 33 , 35 , 36 ) and the high-school graduation rate ( 34 , 37 ).

Predicted income inequality effects (coefficients × 0.08) from 1,000 regressions of 90 vs. 10 inequality in “any college” enrollment on income inequality and random number variables, for various model specifications, for full and compressed series, men only. Models: 1, Inequality; 2, Inequality+year; 3, Inequality+controls; 4, Inequality+controls+year; and 5, Inequality+controls+decade.

As Fig. 6 shows, the income inequality effects estimated for the full male series are robust to the inclusion of other potential confounding variables. But Fig. 6 also highlights the extent to which a proper evaluation of the income inequality hypothesis requires researchers to exploit all of the available data. Although the bivariate analysis shows a similar effect of the income inequality variable in both the full and compressed series, the effects are a good deal more volatile in the more highly parameterized models in the compressed relative to the full series. *** The substantive implication of this analysis is clear: It is only with the full data series that we obtain relatively precise and reliable estimates of the association between inequality in collegiate outcomes and income inequality.

We have examined descriptive evidence on the association between inequality in collegiate attainment and income inequality over the past century. Although there has been much recent interest in the income inequality hypothesis, it has been difficult to make headway because commonly used datasets pertain only to recent decades, when income inequality was increasing. We have thus proceeded by reaching back to the very beginning of the twentieth century, assembling all of the available datasets, and harmonizing the variables in these datasets.

The results show that collegiate inequalities and income inequality are, in fact, rather strongly associated over the twentieth century. Just as with income inequality, we see evidence of a U-turn in 90 vs. 10 collegiate inequality, and evidence of a substantial takeoff in collegiate inequalities in recent decades. When we examine trends in 90 vs. 50 and 50 vs.10 inequalities, we find that the 90 vs. 50 trends mirror the 90 vs. 10 results. Taken together, our results offer solid descriptive support for the income inequality hypothesis.

Inequalities in collegiate attainment increased hand in hand with the expansion of college education in the United States. Rates of college enrollment and completion were higher at the end of the century than they had been at any time in the preceding hundred years, and yet, for these birth cohorts, we see substantial inequalities, as captured in both percentage point gap and odds ratio measures. In point of fact, the only time during the twentieth century for which we observe a reduction in educational inequality is during the period when expansion at the college level had paused. Although the counterfactual is obviously not observable, these results emphasize the importance of attending to the distribution of college opportunities in addition to overall levels of attainment. These distributional questions will take on even greater significance in the context of the economic and social crisis engendered by coronavirus disease 2019, a crisis that is likely to have enduring effects on both the distribution of income and access to the higher education sector.

Our analyses are not well suited to evaluating the mechanisms generating the association between income inequality and collegiate inequalities. However, given the pattern of collegiate inequality across the century, we suspect that a mechanical effect is likely to be responsible. If money matters, as we know it does, and growing income inequality delivers more money to the top, then, all else being equal, these additional dollars would in themselves produce growing inequality in college enrollment and completion. The mechanical effect is therefore a parsimonious account of the trend that we see here ( 8 ). That the over-time associations are substantially stronger for the 90 vs. 50 comparison as compared to the 50 vs. 10 comparison provides further suggestive evidence in this regard. Nevertheless, there is a period for which we undoubtedly hypothesize an increase in the relational effect of income: the Vietnam War. For the war to lead to increased collegiate inequality, the effect of income on educational attainment would have to increase, particularly given that income inequality was low and stable for these birth cohorts.

Whatever the mechanisms may be, the key descriptive result is that, over the course of the twentieth century, a grand U-turn in collegiate inequality occurred. Cohorts born in the middle of the century witnessed the lowest levels of inequality in college enrollment and completion seen over the past hundred years. Contemporary birth cohorts, in contrast, are experiencing levels of collegiate inequality not seen for generations.

Supplementary Material

Supplementary file, acknowledgments.

We thank David Cox, David Grusky, and Florencia Torche for their detailed comments on earlier versions of this paper, and also Raj Chetty, Maximilian Hell, Robb Willer, the Cornell Mobility Conference, the Stanford Inequality Workshop, the Stanford Sociology Colloquium Series, and University of California, Los Angeles’s California Center for Population Research seminar for useful suggestions. Additionally, we thank Stanford’s Center for Poverty and Inequality, Russell Sage Foundation and Stanford’s United Parcel Service (UPS) Fund for research funding, Stanford’s Institute for Research in the Social Sciences for secure data room access, and the American Institutes for Research for data access. We are grateful to the editor and reviewers for their helpful and productive suggestions.

The authors declare no competing interest.

This article is a PNAS Direct Submission. E.G. is a guest editor invited by the Editorial Board.

Data deposition: Code for data analysis is archived on Open Science Framework ( https://osf.io/jxne5 ).

*Throughout this paper, we use the term “college” as a shorthand for “2- or 4-year college.”

† We also include results based on comparing income quartiles in SI Appendix , Fig. S5 .

‡ The probabilities are estimated from the logit model, and we fit a GAM to establish trend. See SI Appendix , SI Methods for more details.

§ We determine the appropriate number of degrees of freedom for the trend lines by fitting a series of GAMs and comparing model fit (using the Akaike Information Criterion). For the analysis of college enrollment for male birth cohorts, we use the stepwise model builder in R’s gam package to find the best-fitting model ( 25 , 26 ). As we have fewer point estimates in the other analyses, the stepwise approach is less reliable, and we therefore choose smoothing parameters that provide a reasonable (and conservative) summary of the trend.

¶ It is also clear that some datasets are outliers from the trend. It is not surprising to see variation across samples, and we highlight this variation only because it illustrates a potential danger of using but one or two datasets to establish a trend. The estimates for National Education Longitudinal Study (NELS) (1974), for example, are substantially higher than the surrounding estimates based on one-shot income measures, and there is a surprising degree of cross-cohort volatility in the PSID estimates.

# The linear trend is strongest for 4-year completion, and weakest for enrollment in 4-year college. For all collegiate outcomes, the GAM offers a significant improvement in fit over the simple linear model.

**It would be possible to track male and female educational inequality with respect to parental education or socioeconomic index scores (SEI) ( 28 ), but the sample sizes are, unfortunately, too small for a detailed analysis of gender differences in educational attainment by birth cohort. This approach is also unattractive given that parental education, parental income, and SEI were only weakly correlated in this period ( 29 ).

†† Note that, while previous research has suggested that high-socioeconomic status (SES) individuals might have taken advantage of the GI Bill to a greater extent than low-SES individuals ( 30 ), SI Appendix , Fig. S9 provides little evidence that collegiate inequality was substantially affected. See SI Appendix for further discussion of this point.

‡‡ We choose the wages measure because, for the bottom of the income distribution, wages are a more important component of income than the types of income included in the alternative measures (e.g., capital gains). We measure wage inequality in year of birth. Surprisingly, given the prominence of the income inequality hypothesis, there is not yet adequate guidance in the literature as to the age at which income inequality most influences outcomes, although in the “money matters” literature there has been particular emphasis on the prenatal period, the postnatal period, and early childhood as the lifecourse moments when money matters most ( 31 , 32 ).

§§ In the 4-year analyses, we weight the data by the inverse of the standard errors underlying the estimates. In the analysis of any college enrollment, we do not weight the data, as this data series includes the tax data estimates. Given the size of the samples underlying these estimates, weighting would allow the relationship that pertains in the tax data for cohorts born in the 1980s and 1990s to have a disproportionate influence on the estimated century-long relationship between income inequality and inequality in college enrollment.

¶¶ The estimates in Fig. 5 are obtained by multiplying the income inequality coefficients in SI Appendix , Table S4 by 0.08.

***See SI Appendix , Fig. S10 for similar figures for 4-year enrollment and completion.

This article contains supporting information online at https://www.pnas.org/lookup/suppl/doi:10.1073/pnas.1907258117/-/DCSupplemental .

Data Availability.

America’s students are falling behind. Here’s how to reimagine the classroom

Psychologists have the research and expertise schools critically need right now

Vol. 55 No. 3 Print version: page 54

• Schools and Classrooms

It’s a familiar refrain: “America’s students are falling behind.”

Academic progress stalled during the pandemic and has yet to recover. But historic declines in test scores and growing achievement gaps are just part of the problem. Youth mental health issues surged ; behavioral problems increased ; and more teachers left the profession —creating a situation many are calling alarming.

“It should have been obvious to all of us that after a highly disruptive year, kids would come back with issues. But unfortunately, teachers often did not get the resources they needed, such as increased mental health support, to be able to respond to those issues,” said Russell Skiba, PhD, a professor of school psychology at Indiana University Bloomington and an expert in classroom management. One result was a return to more punitive discipline policies in some schools—policies researchers have long known to be ineffective, he added.

But the prospects for U.S. students are not all bleak. Researchers, practitioners, and policymakers are on the scene with creative solutions—more rigorous ways to evaluate student progress, different approaches to teaching and learning, and collaborations that make career training possible from an early age. They are also delivering on-the-ground support, including trauma-informed care and interventions designed to improve school belonging and discipline—using science to get student and educator well-being back on track.

[ Related: Schools in crisis: Here are science-backed ways to improve schools now ]

More progress is needed in guiding educators toward science-backed innovations. “The biggest thing that needs to change is that we need engagement with what the evidence says, in conversation with researchers,” said educational psychologist Francesca Lopez, PhD, a professor of education at Penn State.

To that end, psychologists are touching every part of the school experience, from big ideas about how to reimagine the classroom to targeted interventions that help students and teachers thrive each day. And it is not just about inventing something new. Some are leveraging research insights along with lived expertise to return to doing the basics well.

“What are the strategies that will work to help kids recover and thrive, based upon what we know about kids, education, and the science behind it?” said Randi Weingarten, JD, president of the American Federation of Teachers (AFT).

Skills for today and tomorrow

Among the most exciting changes in education is personalized learning backed by sound science, with the goal of making learning more effective for each student.

In some districts, learning is no longer confined to the walls of an individual school. Denver Public Schools allows middle and high school students to customize their curriculum with a combination of virtual and in-person courses across the entire district. That setup allows more students to access specialized opportunities, including instruction in cybersecurity, nursing, and psychology.

“One school doesn’t have to offer everything to every student. Instead, we can think about the expertise across the district and create more personal learning pathways for kids,” said educational psychologist Nicole Barnes, PhD, who is the senior director for APA’s Center for Psychology in Schools and Education as well as a former elementary school teacher.

A 2015 RAND Corporation study of 62 public schools found that personalized learning approaches improved academic progress. But research also suggests that teachers in schools that already perform well on standardized tests do a better job of implementing personalized learning than those in lower-performing schools ( Lee, D., et al., Education Technology Research and Development , Vol. 69, No. 2, 2021 ). Psychological science is helping educators better parse those findings, Barnes said, by accounting for the way school context interacts with student outcomes.

In a growing number of schools, those personalized pathways also increasingly include career-focused options alongside traditional academic routes. That emphasis is fueled by partnerships with local universities and community organizations: In Washington, DC, Anacostia High School and the University of the District of Columbia joined forces to teach students about environmental science and justice. Students in the program attend conferences, participate in internship programs , and learn essential science, technology, engineering, and math (STEM) skills, including how to collect and analyze data. It can also be woven into the design of an institution: The Alabama School of Cyber Technology and Engineering prepares students for roles in high-demand STEM fields, including with the Department of Defense and military contractors.

AFT is also working with 10 school districts across New York state to strengthen career and technical education (CTE) for careers in the semiconductor industry. Ninety-four percent of students enrolled in CTE programs graduate, compared with just 85% of students at traditional high schools ( “CTE Works!” Fact Sheet, Association for Career and Technical Education, 2022 ). CTE students are also more likely to attend postsecondary school and to have a higher median income 8 years later, so weaving technical skills training into K–12 education should be a priority, Weingarten said.

“With the world of artificial intelligence we’re walking into, we need application, not memorization,” she said. “These are not soft skills—they’re the skills of today and tomorrow.”

Psychologists are among those exploring how to best teach the skills of tomorrow, including critical thinking and information literacy skills. For example: What is real and what is written by Russian bots? How can you trust something you read online? How can you tell when a politician uses manipulation or scare tactics?

“We know from research that this kind of education needs to start early ,” said Susan A. Nolan, PhD, a professor of psychology at Seton Hall University in New Jersey, adding that research suggests belief in conspiracy theories starts around age 14 ( Jolley, D., et al., British Journal of Developmental Psychology , Vol. 39, No. 3, 2021 ).

At Arizona State University, the Center on Reinventing Public Education is exploring how school districts are already using AI and how they can step up their game . Teachers across the nation are experimenting with ways to embrace AI tools , including encouraging its use for outlining papers and challenging students to compare ChatGPT’s outputs with their own ( Zhang, P., & Tur, G., European Journal of Education , online first publication, 2023 ).

While the standard curriculum is still adapting to the advent of ChatGPT, the role of educators is already beginning to shift, Barnes said. Instead of a “sage on the stage” delivering lectures, some schools are shifting teachers into facilitator roles to better support students in developing critical thinking, communication, and relationship-building skills.

Educators are also rethinking how to evaluate students. The nonprofit Mastery Transcript Consortium has developed a new approach to grading: Rather than evaluating students in snapshots when a grading period ends, they learn at their own pace and are rated continually on their progress and mastery of specific skills. That approach is based on research by psychologists and others showing that competency-based learning can boost test scores, improve self-efficacy, and more.

Experts say these shifts are poised to better prepare students for careers of the future, but their implementation varies significantly from one school, district, and state to the next, with most U.S. schools still following a more traditional model. AFT is one example of an organization working to enact broader change through its Real Solutions for Kids and Communities campaign. The multistate effort focuses on providing schools with training and resources to address learning loss, improve student mental health, and provide direct support to help families thrive.

A key tenet of the plan is to increase the number of community schools , which deliver medical, dental, and mental health care to families. A 2023 Department of Education survey of more than 1,300 public schools found that 60% partnered with one or more community organizations to provide noneducational services, up from 45% the year prior ( School Pulse Panel, National Center for Education Statistics, 2023 ).

“If schools can become true centers of community, that is, in our view, the most efficacious and economic way of addressing loneliness and boosting mental health,” Weingarten said.

Enhancing instruction

Psychological research is central to efforts to improve education, starting at the most basic level: pedagogy itself.

Broadly, research on how we learn supports a shift away from direct instruction (the “sage on the stage” model) to experiential, hands-on learning—often called guided play—especially in early education ( Skene, K., et al., Child Development , Vol. 93, No. 4, 2022 ). Active Playful Learning , an evidence-based program developed by psychologists Roberta Golinkoff, PhD, of the University of Delaware, and Kathy Hirsh-Pasek, PhD, of Temple University in Philadelphia, leverages those research insights with the goal of bringing joy back into the classroom for both students and teachers ( Theory Into Practice , Vol. 62, No. 2, 2023 ).

“With guided play, teachers actually collaborate with students to work toward a learning goal they have in mind,” said Golinkoff, who is also a member of the National Academy of Education. “If this happened more, teachers would be happier, and kids would feel more valued as agents of their own learning.”

For example, a first-grade geometry direct instruction lesson might start with a teacher explaining the names and properties of squares, circles, and triangles and finish with a worksheet where students identify and draw each shape. In a guided play lesson, students might visit stations around the classroom where they build structures using specific geometric shapes, receiving feedback from their teacher along the way. Pilot studies in Pennsylvania, New Hampshire, and Michigan show promising results, and Golinkoff and her colleagues received $20 million from the LEGO Foundation to expand tests of the program to schools throughout the country.

Educational psychologists are helping teachers explore how their own beliefs, emotions, and identities may influence their effectiveness in the classroom. Dionne Cross Francis, PhD, a professor of education at the University of North Carolina at Chapel Hill, works with elementary school mathematics teachers to explore how their past experiences and beliefs about math may influence the way they teach ( Frontiers in Psychology , Vol. 11, 2020 ).

“Many bring some degree of negative emotions, dispositions, and even trauma from their own experiences of mathematics in school to the classroom,” said Cross Francis, who is president of APA’s Division 15 (Educational Psychology) . “If that’s not resolved, they can easily pass on those anxieties to their students.”

Cross Francis’s six-step coaching model starts with extensive data collection, including surveys, an hour-long interview, and a video of the subject teaching. Using that data, she delivers individualized coaching, which may include mastery experiences to boost self-efficacy or a critical look at teaching practices that are not working well.

By making teaching more effective, such efforts also help address the growing issue of teacher retention. Large international surveys across both Eastern and Western societies indicate that teachers’ job satisfaction is linked to the quality of instruction they provide ( Harrison, M. G., et al., British Educational Research Journal , Vol. 49, No. 3, 2023 ).

“My approach is directly designed to support teacher retention,” Cross Francis said. “If they feel validated and empowered in their work, that ultimately improves well-being.”

Supporting teachers

Teacher well-being is undoubtedly suffering, with frequent job-related stress about twice as common as it is in the general population, according to a survey by the RAND Corporation ( Restoring Teacher and Principal Well-Being Is an Essential Step for Rebuilding Schools, RAND, 2022 ). More than half of educators polled in a 2022 National Education Association (NEA) survey said they were thinking about leaving the profession ( Poll Results: Stress and Burnout Pose Threat of Educator Shortages, NEA, 2022 [PDF, 344KB] ).

In addition to their teaching responsibilities, many have spent the postpandemic years fielding emotional and behavioral outbursts and other problems they are often ill-equipped to manage ( Baker, C. N., et al., School Psychology Review , Vol. 50, No. 4, 2021 ). They are also facing unprecedented levels of violence on the job. An APA survey of more than 15,000 teachers and school staff across the country found that 54% were threatened at work in the year preceding July 2021 ( Violence Against Educators and School Personnel: Crisis During Covid , APA, 2022 [PDF, 206KB]) .

“Psychologists have a really important role to play in addressing teacher well-being, the violence teachers experience, and the record rates of burnout,” said Stacy Overstreet, PhD, a professor of psychology at Tulane University.

At Tulane, the nationally funded Coalition for Compassionate Schools (CCS) unites government, community, and educational organizations to support 17 schools in New Orleans. In addition to several programs focused on students, CCS dispatches a team to schools after a crisis occurs (for example, the death of a student or the permanent closure of a school in the district) that is specifically focused on supporting educators. The center is also creating a series to educate teachers about secondary traumatic stress, an indirect result of supporting students who have faced trauma, as well as strategies for addressing it.

Basic stress-reduction techniques can make a big difference for both teachers and students. Delaying school start times so that teachers can get more sleep helps improve their daytime functioning ( Wahlstrom, K. L., et al., Journal of School Health , Vol. 93, No. 2, 2023 ). Plenty of research shows that starting school later would benefit students , too, but policymakers and school boards rarely make changes.

Mind-body interventions, which have a growing evidence base, are increasingly used in schools and can benefit students and teachers, said Melissa Bray, PhD, a professor and the director of the school psychology program at the University of Connecticut. Examples include breathing exercises, relaxation and guided imagery, yoga, and nature-based therapies, such as taking a mindful walk outside ( Cozzolino, M., et al., Human Arenas , Vol. 5, 2022 ).

CCS trains educators on trauma-informed approaches to working with students and helps schools develop an action plan to improve behavior and well-being across the board. For example, teachers learn to build safe and supportive classrooms using rituals and routines that create a sense of predictability and trust. A “calm down corner” gives students agency in controlling their emotions, and morning community building circles provide an opportunity to discuss experiences that affect the whole group. CCS also helps teachers develop their own emotion regulation skills and enhance teacher-student relationships using the Search Institute’s Developmental Relationships Framework . Outcomes include improved student engagement and fewer class disruptions, as well as more proactive classroom management efforts by teachers (2015–2022 Impact Report, 2022).

Such programs could be crucial because postpandemic behavioral challenges have led some schools to reinstate discipline policies known to be ineffective—even harmful. The so-called zero-tolerance approach, common in the 1990s, involves mandatory penalties (such as a suspension or arrest) for students caught with drugs or weapons.

“Coercive and punitive approaches are ineffective and especially harmful to Black and brown students,” Skiba said. “We know that they have both short- and long-term negative effects and do nothing to increase the safety of schools.”

Skiba and other psychologists have helped develop, test, and promote research-backed alternatives to zero tolerance, including social-emotional learning, restorative justice practices, and Positive Behavioral Interventions and Supports (PBIS) . PBIS, which is used in more than 25,000 schools across the country, is linked with reductions in out-of-school suspensions and other improvements in school climate.

“We need order in schools, but our attempts to bring order must be grounded in building relationships with children and showing them that we care about their future,” Skiba said.

One relationship-building intervention shows particular promise in an area where many other classroom management approaches have fallen short: reducing racial disparities in discipline. Empathic discipline , developed by Jason Okonofua, PhD, an assistant professor of psychology at the University of California, Berkeley, helps teachers develop a growth mindset toward their students and the capacity for an improved teacher-student relationship, as well as gain perspective about each student’s experience. Studies of empathic discipline show that it can reduce racial disparities in school suspension by up to 50% ( Science Advances , Vol. 8, No. 12, 2022 ; PNAS , Vol. 113, No. 19, 2016 ).

Shifting the overall culture in schools from a fixed to a growth mindset—including via informal messages adults send children, as well as formal learning opportunities such as the ability to revise an assignment for additional credit—could even be a means of reducing educational disparities around the world ( npj Science of Learning , Vol. 8, 2023 ). These “tier 1” supports that teachers can learn and use with all students are where psychologists hold the most power to improve the context of education, said David Yeager, PhD, an associate professor of psychology at the University of Texas at Austin and author of 10 to 25: The Science of Motivating Young People .

“Empowering teachers with concrete, evidence-based advice for busy professionals, whose main job is not to provide psychological help, is a place where our field could make a really big difference,” said Yeager, who is the coprincipal investigator of the National Study of Learning Mindsets and the Texas Mindset Initiative.

Promoting belonging in school

When students feel they are accepted, supported, and valued at school, they do better academically, socially, and behaviorally ( Korpershoek, H., et al., Research Papers in Education , Vol. 35, No. 6, 2020 ). But for students from marginalized groups, a sense of belonging at school could even be lifesaving. In a 2023 study of more than 4,000 Black adolescents, a decrease in school belonging was associated with a 35% increased risk for suicidal thoughts and attempts ( Boyd, D. T., et al., Journal of Racial and Ethnic Health Disparities , 2023 ).

Part of belonging at school is being able to seek support from a trusted source, such as an adult from the same racial or ethnic background. In Seattle, Janine Jones, PhD, a professor of school psychology at the University of Washington, has launched a project that will increase the number of Black male psychologists in the district from 1 to 12.

“Across the country, our school workforce is not as diverse as our population of students,” she said. “Through this project, 20% of the district’s school psychologists will be people who are more representative of who they’re serving.”

Students also benefit when they take classes with others who look like them, especially in advanced placement and STEM courses ( Educational Psychology Review , Vol. 34, No. 4, 2022 ; Bowman, N., et al., AERA Open , online first publication, 2023 ). Sandra Graham, PhD, a professor of human development and psychology at the University of California, Los Angeles, who has led research on that link, said it suggests a major downside of academic tracking, which separates students based on ability level, for young people from underrepresented groups.

“When you see other people like you in your classes, you feel more like you belong, and belonging is related to academic achievement,” Graham said.

Her research shows that increased school diversity can benefit all students. Higher diversity is linked to lower rates of bullying, due in part to shifts in power dynamics, and can improve adolescents’ attitudes toward people from other racial and ethnic groups ( Development and Psychopathology , Vol. 35, No. 5 , 2023 ; Educational Psychologist , Vol. 53, No. 2, 2018 ).

“We have the science behind us to say that we need to promote diversity in schools because it makes school a better place for everybody,” Graham said.

Culturally responsive education practices, including policies that provide adequate sociocultural education for teachers working with bilingual students, are a scientifically sound way to increase school belonging, said Lopez, of Penn State. But educational gag orders and book bans in at least 22 states often paint culturally responsive education as a means of scapegoating students from historically dominant groups ( Educational Censorship, PEN America, 2023 ). Lopez is working with Aspen Institute’s Education and Society Program to create user-friendly policy briefs that summarize research showing the contrary.

“We know that educational gag orders and book bans are making many marginalized students feel like their very identity is threatened, which is why it’s so important to counter the harmful misinformation surrounding them,” she said.

Increasing the school psychology workforce

Big-picture goals for the future should include broader efforts to influence the school context—for example by improving school belonging and mindset culture—rather than a focus on individual student-level interventions, Yeager said. Such programs have received less attention to date, he said, partly because it is difficult to randomize entire schools to test them.

Even if the overall school context gets healthier, there will always be kids who need extra support, and there are still far too few school psychologists to help them. Bray said we know what interventions work, but we often do not have the resources to implement them at scale.

“We need more school psychologists—there’s a dire shortage in the nation. More professionals would allow us to spend more time on interventions and less time on paperwork,” she said. But some hopeful changes, including increased funding from the U.S. Department of Education and more flexible training programs, are starting to boost the ranks of school psychologists.

[ Related: There’s a strong push for more school psychologists ]

Outside the school walls, AFT, APA, and others are committed to challenging social media companies to protect young people. The joint Likes vs. Learning report points to the risks of harm and ways to mitigate them, including limiting feed scrolling for teenagers during the school day or providing a hotline schools can call when bullying happens.

“We did this to show just how easy it is for these companies to change things,” Weingarten said. “There are things they could do—they just choose not to.”

Educational quality in the United States is still largely determined by ZIP code, which will remain the case as long as schools are funded at the local level, Golinkoff said. Changing that model would be a powerful way to reduce disparities, but plenty of other things can happen in the meantime.

“There are big things that have to change around education,” she said. “But we can make education better now. We don’t need to wait for those things to change.”

Information and resources

Learn more about the current state of education, challenges schools are facing, and promising psychological research on education:

Making the case: Compelling data on competency-based teaching and learning Knowledge Works, 2024

Education’s long Covid Lewis, K., & Kuhfeld, M., Center for School and Student Progress, 2023

The alarming state of the American student in 2022 Lake, R., & Pillow, T., The Brookings Institution, 2022

What does the research say about the effectiveness of zero-tolerance school discipline policies? Institute of Education Sciences, 2020

United we learn: Honoring America’s racial and ethnic diversity in education Aspen Institute, 2021

Learning through play: A review of the evidence (PDF, 5.54 MB) Zosh, J. M., et al., The LEGO Foundation, 2017

Continued progress: Promising evidence on personalized learning Pane, J. F., et al., RAND Corporation, 2015

Further reading

Making schools work: Bringing the science of learning to joyful classroom practice Hirsh-Pasek, K., et al., Teachers College Press, 2022

College is not the only answer: 7 policy recommendations to help youth succeed Lammers, J., The 74, 2023

Psychologists highlighting the urgent need to reduce violence against teachers Stringer, H., Monitor on Psychology , September 2022

Boys are facing key challenges in school. Inside the effort to support their success Abrams, Z., Monitor on Psychology , April/May 2023

ChatGPT and the future of education: Learner-centered approaches leading the way Sam, S., Education Reimagined, 2023

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People are hunting for education ‘fads.’ what does that say about schools, by daniel mollenkamp     aug 6, 2024.

Photo By GoodStudio/Shutterstock

It was announced by sweeping statements.

When the New York City Public Schools chancellor, David Banks, caused the largest district in the country to change how it taught students to read last year, it was with a sense of alarm. Statistics showed that many of the city’s students in third through eighth grades couldn’t read proficiently, which Banks blamed on the city embracing a “fundamentally flawed” approach to reading instruction. Per reporting from The New York Times , he told parents: “It’s not your fault. It’s not your child’s fault. It was our fault.” Reforming, Banks said, was “the beginning of a massive turnaround.”

The sentiment wasn’t isolated to New York, with almost all states having passed some legislation in the last few years to correct course on how reading is taught. These changes, called a “decisive victory” in the long-standing “reading wars,” have pitted education research favoring phonics-based instruction against other ways of teaching students to read, including word recognition. In the wake of the shift, a prominent curriculum group dissolved and the educational publisher Heinemann reportedly experienced sagging curriculum sales . Meanwhile, students still struggle to read .

But these recent education scraps in reading have also caused fresh uneasiness, as some observers begin hunting for the next education reform effort to go bust — perhaps in math next time .

There’s an unvoiced assumption behind this — that education is prone to “fads.” So where does this perception come from? And is it accurate?

The Reform Merry-Go-Round

Fad is the wrong word, says Larry Cuban, an emeritus professor at Stanford University who writes a blog about school reforms.

For Cuban, reform movements appear to be caught in a loop, attempting similar changes “ again and again .” But it’s not that schools are constantly being burned by the latest craze. It’s that they’re suffering from deep structural problems, and they seem not to learn from the long history of school reforms.

The lesson? Public schools are particularly vulnerable to pressure, Cuban said on a call with EdSurge. That’s because national problems tend to become school ones, Cuban says. Schools have to walk a “tightrope,” striking a balance that is both stable for students and able to adapt to changes in the broader society, he says.

Pressure on schools to respond to new issues often ends up altering curricula or introducing new courses, because that’s the easiest part of the public education system to change, Cuban argues. But classrooms are isolated from the superintendent’s office, the school board and other “ policy elites ” who push change, he says.

For example, he adds, when it became known that teenage driving was causing road deaths, driving became part of public school curricula. When drugs became a national concern, schools added anti-drug curricula. “When the nation has a cold, schools sneeze,” Cuban says, adding that it’s an old cliche that turns out to be true.

That focus — the classroom, where abstract ideas about school meet real students — is a common sticking point, according to other observers as well.

It's not that specific reform ideas are fads, argues James Stigler, a distinguished professor of psychology at the University of California, Los Angeles. It's that schools seem susceptible to fads because people don't understand what it means to take an idea seriously, he says.

In reality, many ideas out there haven’t been properly tried out, because that would mean focusing largely on how they are put into practice in classrooms, he adds. There are probably a lot of ideas out there that are effective, he says — but nobody knows what they are.

To Ronald Gallimore, a distinguished professor emeritus at the University of California, Los Angeles, these efforts are sincere. Reform advocates believe they are on the cusp of something that will really work this time, he says. But they may not be aware of the history of instruction. It also doesn’t help that the U.S. has a highly decentralized school system, with schools being locally controlled, making it hard to make uniform sweeping changes to how students learn, he adds.

So how would teachers know if a proposed reform is effective?

Can You Prove It?

Evidence is the magic word, says Adrian Simpson, principal of St. Mary's College at Durham University in England and professor of mathematics education.

It’s also the source of part of the problem.

Those questing for evidence-based education approaches tend to rely on randomized controlled trials, a robust form of study widely used in medicine to establish causation, Simpson notes. In education, that can mean field experiments that show a practice worked in a particular context or laboratory experiments in cognitive science, he says.

“But what [these] tell you is very powerful, but very narrow,” Simpson says.

These studies are taken to show that certain approaches work. But, Simpson says, they only really establish that the sum of all the differences in interventions caused learning for some participants. Which specific intervention worked, and whether it would work for other students, is hard to determine, Simpson says.

That also puts pressure on how changes are carried out in the classroom.

Imagine the best teacher. How much time goes into designing his or her lessons, refining them, and adjusting to individual differences? asks Gallimore, the retired professor. That's what makes implementation of any reform effort so difficult, he says: to go from a general idea down into the details of making it work for a specific group of students, often across a range of different learning contexts.

So it’s tricky to translate the lessons of these experiments into learning.

Researchers also understand less about the mechanisms of how people think about, say, fractions than how kidneys function, according to Simpson, of St. Mary's College. So the evidence provided by experiments about specific practices in education is weaker than in other areas like medicine where it tends to be similar from person to person: “You can’t establish laws of the classroom that will apply everywhere,” Simpson says.

Ultimately, there’s no quick fix for the reform cycle, Simpson says. But he thinks teachers could learn from public health medicine, which is striving to make its interventions more attuned to personal peculiarities. Teachers should bring together insights from a number of sources — from research about memory capacity to tips from the teacher next door — to inform how they unlock learning for their students, he suggests. Rather than asking what they can do to make a student better with fractions, a teacher might ask: “What’s causing this child to handle fractions poorly?” That could provide an insight that isn’t solely focused on teacher interventions which could, nonetheless, help the student learn, Simpson says.

To Stigler, of UCLA, it’s hard to know what works in education right now.

Reform movements need to focus more on getting disciplined plans for moving from the idea phase to the implementation phase, he says. Teachers also need the time to make sure ideas have been effectively put in place, he adds.

Without that, Stigler says, nobody knows what’s truly effective.

Daniel Mollenkamp ( @dtmollenkamp ) is a reporter for EdSurge. His email is [email protected].

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Management training programs in healthcare: effectiveness factors, challenges and outcomes

• Lucia Giovanelli 1 ,
• Federico Rotondo 2 &
• Nicoletta Fadda 1  

BMC Health Services Research volume  24 , Article number:  904 ( 2024 ) Cite this article

120 Accesses

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Different professionals working in healthcare organizations (e.g., physicians, veterinarians, pharmacists, biologists, engineers, etc.) must be able to properly manage scarce resources to meet increasingly complex needs and demands. Due to the lack of specific courses in curricular university education, particularly in the field of medicine, management training programs have become an essential element in preparing health professionals to cope with global challenges. This study aims to examine factors influencing the effectiveness of management training programs and their outcomes in healthcare settings, at middle-management level, in general and by different groups of participants: physicians and non-physicians, participants with or without management positions.

A survey was used for gathering information from a purposive sample of professionals in the healthcare field attending management training programs in Italy. Factor analysis, a set of ordinal logistic regressions and an unpaired two-sample t-test were used for data elaboration.

The findings show the importance of diversity of pedagogical approaches and tools and debate, and class homogeneity, as effectiveness factors. Lower competencies held before the training programs and problems of dialogue and discussion during the course are conducive to innovative practice introduction. Interpersonal and career outcomes are greater for those holding management positions.

Conclusions

The study reveals four profiles of participants with different gaps and needs. Training programs should be tailored based on participants’ profiles, in terms of pedagogical approaches and tools, and preserve class homogeneity in terms of professional backgrounds and management levels to facilitate constructive dialogue and solution finding approach.

Peer Review reports

Several healthcare systems worldwide have identified management training as a precondition for developing appropriate strategies to address global challenges such as, on one hand, poor health service outcomes in front of increased health expenditure, particularly for pharmaceuticals, personnel shortages and low productivity, and on the other hand in terms of unbalanced quality and equal access to healthcare across the population [ 1 ]. The sustainability of health systems itself seems to be associated with the presence of leaders, at all levels of health organizations, who are able to correctly manage scarce resources to meet increasingly complex health needs and demands, at the same time motivating health personnel under an increasing amount of stress and steering their behaviors towards the system’s goals, in order to drive the transition towards more decentralized, interorganizational and patient-centered care models [ 2 ].

Recently, professional training as an activity aimed at increasing learning of new capabilities (reskilling) and improving existing ones (upskilling) during the lifetime of individuals (lifelong learning) has been identified by the European Commission as one of the seven flagship programs to be developed in the National Recovery and Resilience Plans (NRRP) to support the achievement of European Union’s goals, such as green and digital transitions, innovation, economic and social inclusion and occupation [ 3 ]. As a consequence, many member states have implemented training programs to face current and future challenges in health, which often represents a core mission in their NRRPs.

The increased importance of developing management training programs is also related to the rigidity and focalization of university degree courses in medicine, which do not provide physicians with the basic tools for fulfilling managerial roles [ 4 ]. Furthermore, taking on these roles does not automatically mean filling existing gaps in management capabilities and skills [ 5 ]. Several studies have demonstrated that, in the health setting, management competencies are influenced by positions and management levels as well as by organization and system’s features [ 6 , 7 ]. Hence, training programs aimed at increasing management competencies cannot be developed without considering these differences.

To date, few studies have focused on investigating management training programs in healthcare [ 8 ]. In particular, much more investigation is required on methods, contents, processes and challenges determining the effectiveness of training programs addressed to health managers by taking into account different environments, positions and management levels [ 1 ]. A gap also exists in the assessment of management training programs’ outcomes [ 9 ]. This study aims to examine factors influencing the effectiveness and outcomes of management training, at the middle-management level, in healthcare. It intends to answer the following research questions: which factors influence the management training process? Which relationships exist between management competencies held before the program, factors of effectiveness, critical issues encountered, and results achieved or prefigured at the end of the program? Are there differences, in terms of factors of effectiveness, challenges and outcomes, between the following groups of management training programs’ participants: physicians and non-physicians, participants with or without management positions?

Management training in healthcare

Currently, there is a wide debate about the added value of management to health organizations [ 10 ] and thus about the importance of spreading management competencies within health organizations to improve their performance. Through a systematic review, Lega et al. [ 11 ] highlighted four approaches to examine the impact of management on healthcare performance, focusing on management practices, managers’ characteristics, engagement of professionals in performance management and organizational features and management styles.

Although findings have not always been univocal, several studies suggest a positive relationship between management competencies and practices and outcomes in healthcare organizations, both from a clinical and financial point of view [ 12 ]. Among others, Vainieri et al. [ 13 ] found, in the Italian setting, a positive association between top management’s competencies and organizational performance, assessed through a multidimensional perspective. This study also reveals the mediating effect of information sharing, in terms of strategy, results and organization structure, in the relationship between managerial competencies and performance.

The key role of management competencies clearly emerges for health executives, who have to turn system policies into a vision, and then articulate it into effective strategies and actions within their organizations to steer and engage professionals [ 14 , 15 , 16 , 17 , 18 , 19 ]. However, health systems are increasingly complex and continually changing across contexts and health service levels. This means the role of health executives is evolving as well and identifying the capacities they need to address current and emerging issues becomes more difficult. For instance, a literature review conducted by Figueroa et al. [ 20 ] sheds light on priorities and challenges for health leadership at three structural levels: macro context (international and national), meso context (organizations) and micro context (individual healthcare managers).

Doctor-managers are requested to carry both clinical tasks and tasks related to budgeting, goal setting and performance evaluation. As a consequence, a growing stream of research has speculated whether managers with a clinical background actually affect healthcare performance outcomes, but studies have produced inconclusive findings. In relation to this topic, Sarto and Veronesi [ 21 ] carried out a literature review showing a generally positive impact of clinical leadership on different types of outcome measures, with only a few studies reporting negative impacts on financial and social performance. Morandi et al. [ 22 ] focused on doctor-managers who have become middle managers and investigated the potential bias in performance appraisal due to the mismatch between self-reported and official performance data. At the individual level, the role played by managerial behavior, training, engagement, and perceived organizational support was analyzed. Among others indications they suggested that training programs should be revised to reduce bias in performance appraisal. Tasi et al. [ 23 ] conducted a cross-sectional analysis of the 115 largest U.S. hospitals, divided into physician-led and non-physician-led, which revealed that physician-led hospital systems have higher quality ratings across all specialities and more inpatient days per hospital bed than non-physician-led hospitals. No differences between the groups were found in total revenue and profit margins. The main implication of their study is that hospital systems may benefit from the presence of physician leadership to improve the quality and efficiency of care delivered to patients as long as education and training are able to adequately prepare them. The main issue, as also observed by others [ 4 , 24 ], is that university education in medicine still includes little focus on aspects such as collaborative management, communication and coordination, and leadership skills. Such a circumstance motivates the call for further training. Regarding the implementation of training programs, Liang et al. [ 1 ] have recently shown how it is hindered, among others, by a lack of sufficient knowledge about needed competencies and existing gaps. Their analysis, which focuses on senior managers from three categories in Chinese hospitals, shows that before commencing the programs senior managers had not acquired adequate management competencies either through formal or informal training. It is worth noticing that significant differences exist between hospital categories and management levels. For this reason, they recommend using a systemic approach to design training programs, which considers different hospital types, management levels and positions. Yarbrough et al. [ 6 ] examined how competence training worked in healthcare organizations and the competencies needed for leaders at different points of their careers at various organizational levels. They carried out a cross-sectional survey of 492 US hospital executives, whose most significant result was that competence training is effective in healthcare organizations.

Walston and Khaliq [ 25 ], from a survey of 2,001 hospital CEOs across the US concluded that the greatest contribution of continuing education is to keep CEOs updated on technological and market changes that impact their current job responsibilities. Conversely, it does not seem to be valued for career or succession planning. About the methods of continuing education, an increasing use of some internet-based tools was found. Walston et al. [ 26 ] identified the factors affecting continuing education, finding, among others, that CEOs from for-profit and larger hospitals tend to take less continuing education, whereas senior managers' commitment to continuing education is influenced by region, gender, the CEO's personal continuing education hours and the focus on change.

Furthermore, the principles that inspire modern healthcare models, such as dehospitalization, horizontal coordination and patient-centeredness, imply the increased importance of middle managers, within single structures but also along clinical pathways and projects, to create and sustain high performances [ 27 , 28 , 29 ].

Whaley and Gillis [ 8 ] investigated the development of training programs aimed at increasing managerial competencies and leadership of middle managers, both from clinical and nonclinical backgrounds, in the US context. By adopting the top managers’ perspective, they found a widespread difficulty in aligning training needs and program contents. A 360° assessment of the competencies of Australian middle-level health service managers from two public hospitals was then conducted by Liang et al. [ 7 ] to identify managerial competence levels and training and development needs. The assessment found competence gaps and confirmed that managerial strengths and weaknesses varied across management groups from different organizations. In general, several studies have shown that leading at various organizational levels, in healthcare, does not necessarily require the same levels and types of competencies.

Liang et al. [ 30 ] explored the core competencies required for middle to senior-level managers in Victorian public hospitals. By adopting mixed methods, they confirmed six core competencies and provided guidance to the development of the competence-based educational approach for training the current and future management workforce. Liang et al. [ 31 ] then focused on the poorly investigated area of community health services, which are one of the main solutions to reducing the increasing demand for hospital care in general, and, in particular, in the reforms of the Australian health system. Their study advanced the understanding of the key competencies required by senior and mid-level managers for effective and efficient community health service delivery. A following cross-sectional study by AbuDagga et al. [ 32 ] highlighted that some community health services, such as home healthcare and hospice agencies, also need specific cultural competence training to be effective, in terms of reducing health disparities.

Using both qualitative and quantitative methods, Liang et al. [ 33 ] developed a management competence framework. Such a framework was then validated on a sample of 117 senior and middle managers working in two public hospitals and five community services in Victoria, Australia [ 34 ]. Fanelli et al. [ 35 ] used mixed methods to identify the following specific managerial competencies, which healthcare professionals perceive as crucial to improve their performance: quality evaluation based on outcomes, enhancement of professional competencies, programming based on process management, project cost assessment, informal communication style and participatory leadership.

Loh [ 5 ], through a qualitative analysis conducted in Australian hospitals, examined the motivation behind the choice of medically trained managers to undertake postgraduate management training. Interesting results stemming from the analysis include the fact that doctors often move into management positions without first undertaking training, but also that clinical experience alone does not lead to required management competencies. It is also interesting to remark that effective postgraduate management training for doctors requires a combination of theory and practice, and that doctors choose to undertake training mostly to gain credibility.

Ravaghi et al. [ 36 ] conducted a literature review to assess the evidence on the effectiveness of different types of training and educational programs delivered to hospital managers. The analysis identifies a set of aspects that are impacted by training programs. Training programs focus on technical, interpersonal and conceptual skills, and positive effects are mainly reported for technical skills. Numerous challenges are involved in designing and delivering training programs, including lack of time, difficulty in employing competencies in the workplace, also due to position instability, continuous changes in the health system environment, and lack of support by policymakers. One of the more common flaws concerns the fact that managers are mainly trained as individuals, but they work in teams. The implications of the study are that increased investments and large-scale planning are required to develop the knowledge and competencies of hospital managers. Another shortage concerns the outcome measurement of training programs, which is a usually neglected issue in the literature [ 9 ]. It also emerges that the training programs performing best are specific, structured and comprehensive.

Kakemam and Liang [ 2 ] conducted a literature review to shed light on the methods used to assess management competencies, and, thus, professional development needs in healthcare. Their analysis confirms that most studies focus on middle and senior managers and demonstrate great variability in methods and processes of assessment. As a consequence, they elaborate a framework to guide the design and implementation of management competence studies in different contexts and countries.

In the end, the literature has long pointed out that developing and strengthening the competencies and skills of health managers represent a core goal for increasing the efficiency and effectiveness of health systems, and management training is crucial for achieving such a goal [ 37 ]. The reasons can be summarized as follows: university education has scarcely been able to provide physicians and, in general, health operators, with adequate, or at least basic, managerial competencies and skills; over time, professionals have been involved in increasingly complex and rapidly changing working environments, requiring increased management responsibilities as well as new competencies and skills; in many settings, for instance in Italy, delays in the enforcement of law requiring the attendance of specific management training courses to take up a leadership position, hindered the acquisition of new competencies and the improvement of existing ones by those already managing health organizations, structures and services.

For the purposes of this study, management competencies refer to the possession and ability to use skills and tools for service organization and service planning, control and evaluation, evidence-informed decision-making and human resource management in the healthcare field.

Management training in the Italian National Health System

The reform of the Italian National Health System (INHS), implemented by Legislative Decree No. 502/1992 and inspired by neo-managerial theories, introduced the role of the general manager and assigned new responsibilities to managers.

However, the inadequate performance achieved in the first years of the application of the reform highlighted the cultural gap that made the normative adoption of managerial approach and tools unproductive on the operational level. Legislation evolved accordingly, and in order to hold management positions, management training became mandatory. Decree-Law No. 583/1996 (converted into Law No. 4/1997) provided that the requirements and criteria for access to the top management level were to be determined. Therefore, Presidential Decree No. 484/1997 determined these requirements and also the requirements and criteria to access the middle-management level of INHS’ healthcare authorities. This regulation also imposed the acquisition of a specific management training certificate, dictated rules concerning the duration, contents, and teaching methods of management training courses issuing this certificate, and indicated the requirements for attendance. Immediately afterwards, Legislative Decree No. 229/1999 amended the discipline of medical management and health professions and promoted continuous training in healthcare. It also regulated management training, which became an essential requirement for the appointments of health directors and directors of complex structures in the healthcare authorities, for the categories of physicians, dentists, veterinarians, pharmacists, biologists, chemists, physicists and psychologists.

The second pillar of the INHS reform was the regionalization of the INHS. Therefore, the Regions had to organize the courses to achieve management training certificates on the basis of specific agreements with the State, which regulated the contents, the methodology, the duration and the procedures for obtaining certification. The State-Regions Conference approved the first interregional agreement on management training in July 2003, whereas the State-Regions Agreement of 16 May 2019 regulated the training courses. The mandatory contents of the management training outlined the skills and behaviors expected from general managers and other top management key players (Health Director, Administrative Director and Social and Health Director), but also for all middle managers.

A survey was used to gather information from a purposive sample of professionals in the healthcare field taking part in management training programs. In particular, a structured questionnaire was submitted to 140 participants enrolled in two management programs organized by an Italian university: a second-level specializing master course and a training program carried out in collaboration with the Region. The programs awarded participants the title needed to be appointed as a director of a ward or administrative unit in a public healthcare organization, and share the same scientific committee, teaching staff, administrative staff and venue. The respondents’ profile is shown in Table  1 .

It is worth pointing out that the teaching staff is characterized by diversity: teachers have different educational and professional backgrounds, are practitioners or academics, and come from different Italian regions.

The questionnaire was submitted and completed in presence and online between November 2022 and February 2023. All participants decided to take part in the analysis spontaneously and gave their consent, being granted total anonymity.

The questionnaire, which was developed for this study and based on the literature, consisted of 64 questions shared in the following five sections: participant profile (10 items), management competencies held by participants before the training program (4 items), effectiveness factors of the training program (23 items), challenges to effectiveness (10 items), and outcomes of the training program (17 items) (an English language version of the questionnaire is attached to this paper as a supplementary file). In particular, the second section aimed to shed light on the participants’ situation regarding management competencies held before the start of the training program and how they were acquired; the third section aimed to collect participants’ opinions regarding how the program was conducted and the factors influencing its effectiveness; the fourth section aimed to collect participants’ opinions regarding the main obstacles encountered during the program; and the fifth section aimed to reveal the main outcomes of the program in terms of knowledge, skills, practices and career.

Except for those of the first section, which collected personal information, all the items of the next four categories – management competencies, effectiveness factors, challenges and outcome — were measured through a 5-point Likert scale. To ensure that the content of the questionnaire was appropriate, clear and relevant, a pre-testing was conducted in October 2022 by asking four academics and four practitioners, both physicians and not, with and without management positions, to fill it out. The aim was to understand whether the questionnaire really addressed the information needs behind the study and was easily and correctly understood by respondents. Therefore, the four individuals involved in the pre-testing were asked to fill it out simultaneously but independently, and at the end of the compilation, a focus group that included them and the three authors was used to collect their opinions and suggestions. After this phase, the following changes were made: in the ‘Participant profile’ section, ‘Veterinary medicine’ was added to the fields accounting for the ‘Educational background’ (item 3); in Sect. 2, it was decided to modify the explanation given to ‘basic management competencies’ and align it to what required by Presidential Decree No. 484/1997; in Sect. 3, item 25 was added to catch a missing aspect that respondents considered important, and brackets were added to the description of items 15, 16 and 29 to clarify the concepts of mixed and homogenous class and pedagogical approaches and tools; in Sect. 4, in the description of item 40, the words ‘find the energy required’ were added to avoid confusion with items 38 and 39, whereas brackets were added to items 41 and 45 to provide more explanation; in Sect. 5, brackets were added to the description of item 51 to increase clarity, and the last item was divided into two (now items 63 and 64) to distinguish the training program’s impact on career at different times.

With reference to the methods, first, a factor analysis based on the principal component method was conducted within each section of the questionnaire (except for the first again), in order to reduce the number of variables and shed light on the factors influencing the management training process. Bartlett's sphericity test and the Kaiser–Meyer–Olkin (KMO) value were performed to assess sampling adequacy, whereas factors were extracted following the Kaiser criterion, i.e., eigenvalues greater than unity, and total variance explained. The rotation method used was the Varimax method with Kaiser normalization, except for the second section (i.e., management competencies held by participants before the training program) that), which did not require rotation since a single factor emerged from the analysis. Bartlett's sphericity test was statistically significant ( p  < 0.001) in all sections, KMO values were all greater than 0.65 (average value 0.765), and the total variances explained were all greater than 65% (average value of approximately 70.89%), which are acceptable values for such analysis.

Second, a set of ordinal logistic regressions were performed to assess the relationships existing between management competencies held before the start of the course, effectiveness factors, challenges, and outcomes of the training program.

The factors that emerged from the factor analysis were used as independent variables, whereas some significant outcome items accounting for different performance aspects were selected as dependent variables: improved management competencies, innovation practices, professional relationships, and career prospects. Ordered logit regressions were used because the dependent variables (outcomes) were measured on ordinal scales. Some control variables for the respondent profiles were included in the regression models: age, gender, educational background, management position, and working in the healthcare field.

With the aim of understanding which explanatory variables could exert an influence, a backward elimination method was used, adopting a threshold level of significance values below 0.20 ( p  < 0.20). Table 4 shows the results of regressions with independent variables obtained following the criterion mentioned above. All four models respected the null hypothesis, which means that the proportional odds assumption behind the ordered logit regressions had not been rejected ( p  > 0.05). Third and last, an unpaired two-sample t-test was used to examine the differences between groups of participants in the management training programs selected based on two criteria: physicians and non-physicians, and participants with or without management positions.

First, descriptive statistics is useful for understanding the aspects participants considered the most and least important by category. This can be done by focusing on the items of the four sections of the questionnaire (except for the first one depicting participant profiles) that were given the highest and lowest scores at the sample level and by different groups of participants (physicians and non-physicians, participants with or without management positions). Table 2 summarizes the mean values and standard deviations by group of these higher and lower scores. Focusing on management competencies, all groups reported having mainly acquired them through professional experience, except for non-physicians who attributed major significance to postgraduate training programs, with a mean value of 3.05 out of 5. All groups agreed on the poor role of university education in providing management competencies, with mean values for the sample and all four groups below 2.5. It is worth noting that this item exhibits the lowest value for physicians (1.67) and the highest for non-physicians (2.37). In addition, physicians are the group attributing the lowest values to postgraduate education and professional experience for acquiring management competencies. In reference to factors of effectiveness, all groups also agree on the necessity of mixing theoretical and practical lessons during the training program with mean values of well above 4.5, whereas exclusive use of self-assessment is generally viewed as the most ineffective practice, except for non-physician, who attribute the lowest value to remote lessons (mean 1.82). Among the challenges, the whole sample and physicians and participants without management positions see the lack of financial support from their organization as the main problem (mean 4.10), while non-physicians and participants with management positions believe this is represented by a lack of time, with mean values, respectively, of 3.75 and 4. All agree that dialogue and discussion during the course have been the least relevant of the problems, with mean values below 1.5. Outcomes show generally high values, as revealed by the fact that the lowest values exhibit mean values around 3.5. It is worth noting that an increased understanding of the healthcare systems has been the main benefit gained from the program, with mean values equal to or higher than 4.50. The lowest positive impact is attributed by all attendees to improved relationships with superiors and top management, with mean values between 3.44 and 3.74, with the exception of participants without management positions who mention improved career prospects.

To shed light on the factors influencing the management training process, the findings of the factor analyses conducted by category are reported. Starting from the management competencies held before the training program, the following single factor was extracted from the four items, named and interpreted as follows:

Basic management competencies, which measures the level of management competencies acquired by participants through higher education, post-graduate training and professional experience.

The effectiveness factors are then grouped into six factors, named and explained as follows:

Diversity and debate, which aggregates five items assessing the importance of diversity in participants’ and teachers’ educational and professional backgrounds and pedagogical approaches and tools, as well as level of participant engagement and discussion during lessons and in carrying out the project work required to complete the program.

Specialization, which includes three items accounting for a robust knowledge of healthcare systems by focusing on teachers’ profiles and lessons’ theoretical approaches.

Lessons in presence, which groups three items explaining that in-presence lessons increase learning outcomes and discussion among participants.

Final self-assessment, made up of three items asserting that learning outcomes should be assessed by participants themselves at the end of the course.

Written intermediate assessment, composed of two items explaining that mid-terms assessment should only be written.

Homogeneous class, which is made up of a single component accounting for participants’ similarity in terms of professional backgrounds and management levels, tasks and responsibilities.

The challenges are aggregated into the following four factors:

Lack of time, which includes three items reporting scarce time and energy for lessons and study.

Problems of dialogue and discussion, which groups three items focusing on difficulties in relating to and debating with other participants and teachers.

Low support from organization, which is made up of two items reporting poor financial support and low value given to the initiative from participants’ own organizations.

Organizational issues, which aggregates two items demonstrating scarce flexibility and collaboration by superiors and colleagues of participants’ own organizations and unfamiliarity to study.

Table 3 shows the component matrix with saturation coefficients and factors obtained for the management competencies held before the training program (unrotated), effectiveness factors (rotated), and challenges (rotated).

A set of ordinal logistic regressions was performed to examine the relationships between management competencies held before the start of the course, effectiveness factors, challenges and outcomes of the training program. The results, shown in Table  4 , are articulated into four models, one for each selected outcome. In relation to model 1, the factors ‘diversity and debate’ ( p  < 0.001), ‘written intermediate assessment’ ( p  < 0.05) and ‘homogeneous class’ ( p  < 0.001) have a significant positive impact on the improvement of management competencies, which is also increased by low values attributed to ‘problems of dialogue and discussion’ ( p  < 0.01). In model 2, the change of professional practices in light of lessons learned during the program, selected as an innovation outcome, is then positively affected by ‘diversity and debate’ ( p  < 0.001), ‘homogeneous class’ ( p  < 0.05) and ‘organizational issues’ ( p  < 0.01), while it was negatively influenced by a high value of ‘basic management competencies’ held before the course ( p  < 0.05). Regarding model 3, ‘Diversity and debate’ ( p  < 0.001) and ‘homogeneous class’ ( p  < 0.01) have a significant positive effect on the improvement of professional relationships as well, whereas the same is negatively affected by ‘lessons in presence’ ( p  < 0.05). Finally, concerning model 4, the outcome career prospects benefit from ‘diversity and debate’ ( p  < 0.05) and ‘homogeneous class’ ( p  < 0.01), since both factors exert a positive effect. ‘Low support from organization’ negatively influences career prospects ( p  < 0.001). Table 4 also shows that the LR test of proportionality of odds across the response categories cannot be rejected (all four p  > 0.05).

Finally, it is worth noting that none of the control variables reflecting the respondent profiles (age, gender, management position, working in the healthcare field, and educational background) was found to be statistically significant. These variables are not reported in Table  4 because regression models were obtained following a backward elimination method, as explained in the method section.

In the end, the t-test reveals significant differences between physicians and non-physicians, as well as between participants with or without management positions. Table 5 shows only figures of t-test statistically significant with regards to competencies held before the attendance of the course, the factors of effectiveness, challenges of the training program, and outcomes achieved. In the first comparison, non-physicians show higher management competencies at the start of the program, with a mean value of 0.31, while physicians suffer from less support from their own organization with a mean value of 0.13 compared to -0.18, the mean value of the non-physicians. Concerning the second comparison, participants with management positions have higher management competencies at the start of the program (0.19 versus -0.13) and suffer more from lack of time, with higher mean values compared to participants without managerial positions, respectively 0.23 and -0.16. For what concerns the factors related to the effectiveness of the training program, participants with management positions exhibit a lower mean value in relation to written mid-term assessments, -0.24 versus 0.17, reported by participants with management positions. Differently, the final self-assessment at the end of the program is higher for participants with management positions, 0.24 compared to -0.17, the mean value of the participants without management positions. This latter category feels more the problem of low support from their organizations, with a mean value of 0.16 compared to -0.23, and is slightly less motivated by possible career improvement, with a mean value of 3.31 compared to 3.73 reported by participants with management positions.

The results stemming from the different analyses are now considered and interpreted in the light of the extant literature. Personal characteristics such as gender and age, differently from what was found by Walston et al. [ 26 ] for executives’ continuing education, and professional characteristics such as seniority and working in public or private sectors, do not seem to affect participation in management training programs.

The findings clearly show the outstanding importance of ‘diversity and debate’ and ‘class homogeneity’ as factors of effectiveness, since they positively impact all outcomes: competencies, innovation, professional relationships and career. These factors capture two key aspects complementing each other: on the one hand, participants and teachers’ different backgrounds provide the class with a wider pool of resources and expertise, whereas the use of pedagogical tools fostering discussion enriches the educational experience and stimulates creativity. On the other hand, due to the high level of professionalism in the setting, sharing common management levels means similar tasks and responsibilities, as well as facing similar problems. Consequently, speaking the same language leads to deeper knowledge and effective technical solutions.

In relation to the improvement of management competencies, it also emerges the critical role of a good class atmosphere, that is, the absence of problems of dialogue and discussion. ‘Diversity and debate’ and ‘class homogeneity’, as explained before, seem to contribute to this, since they enhance freedom of expression and fair confrontation, leading to improved learning outcomes. It is interesting to notice that the problems of dialogue and discussion turned out to be the least relevant challenge across the sample.

Two interesting points come from the factors affecting innovation. First, it seems that lower competencies before the training programs lead to the development of more innovative practices. The reason is that holding fewer basic competencies means a greater scope for action once new capabilities are learned: the spirit of openness is conducive to breaking down routines, and innovative practices hindered by a lack of knowledge and tools can thus be introduced. The reason is that holding fewer basic competencies means greater scope for action once new capabilities are learned: the spirit of openness is conducive to breaking down routines, and innovative practices hindered by a lack of knowledge and tools can thus be introduced. This extends the findings of previous studies since the employment of competencies in the workplace is influenced by the starting competence equipment of professionals [ 36 ], and those showing gaps have more room to recover, also in terms of motivation to change, that is, understanding the importance of meeting current and future challenges [ 26 ]. Second, more innovative practices are introduced by participants perceiving more organizational issues. This may reveal, on the one side, a stronger individual motivation towards professional growth of participants who suffer from lack of flexibility and collaboration from their own superiors and colleagues. In this regard, poor tolerance, flexibility and permissions in their workplace act as a stimulus to innovation, which can be viewed as a way of challenging the status quo. On the other side, in line with the above-mentioned concept, this confirms that unfamiliarity with the study increases the innovative potential of participants. Since this study reveals that physicians are neither adequately educated from a management point of view nor incentivized to attend post-graduation training programs, it points out how important is extending continuing education to all health professional categories [ 25 , 26 ].

The topic of competencies held by different categories needs more attention. The study reveals that physicians and participants without management positions start the program with less basic competencies. At the sample level, higher education is viewed as the most ineffective tool to provide such competencies, whereas professional experience is seen as the best way to gather them. Actually, non-physicians give the highest value to postgraduate education, which suggests they are those more interested or incentivized to take part in continuing education. Although holding managerial positions does not automatically mean having higher competencies [ 5 ], it is evident that such a professional experience contributes to filling existing gaps. Physicians stand out as the category for which university education, postgraduate education and professional experience exert the lowest impact on management competence improvement. Considering the relationship between competence held before the course and innovation, as described above, engaging physicians in training programs, even more if they do not have management responsibilities, has a major impact on health organizations’ development prospects. The findings also point out that effective management training requires a combination of theory and practice for all categories of professionals, not just for physicians, as observed by Loh [ 5 ].

The main outcome, in general and for all participant categories, is an increased understanding of how healthcare systems work, which anticipates increased competencies. This confirms the importance of knowledge on the healthcare environment [ 31 ], and clarifies the order of aspects impacted by training programs as reported by Ravaghi et al. [ 36 ]: first conceptual, then technical, and finally interpersonal. However, interpersonal outcomes are by far greater for those holding management positions, which extends the findings by Liang et al. [ 31 ]. In particular, participants already managing units report the greatest impacts in terms of ability to understand colleagues’ problems, improvement of professional relationships and collaboration with colleagues from other units. Obviously, participants with management positions, more than others, feel the lack of collaborative and communication skills, which represents one of the main flaws of university education in the field of medicine [ 4 ] and is also often neglected in management training [ 36 ]. This also confirms that different management levels show specific competence requirements and education needs [ 6 , 7 ]. 

It is then important to discuss the negative effect of lessons in presence on the improvement of professional relationships. At first glance, it may sound strange, but its real meaning emerges from a comprehensive interpretation of all the findings. First, it does not mean that remote lessons are more effective, as revealed by the fact that they, as a factor of effectiveness, are attributed very low values and, for all categories of participants, lower values than those attributed to lessons in presence and hybrid lessons. Non-physicians, in particular, attribute them the lowest value at all. At most, remote lessons are viewed as convenient rather than effective. The negative influence of lessons in presence can be explained by the fact that a specific category, i.e., those with management positions, rate this aspect much more important than other participants and, as reported above, find much more benefits in terms of improved relationships from management training. Participants with management positions, due to their tasks and responsibilities, suffer more than others from lack of time to be devoted to course participation. For them, as for the category of non-physicians, lack of time represents the main challenge to effectively attending the course. In the literature, such a problem is well considered, and lack of time is also viewed as a challenge to apply the skills learned during the course [ 36 ]. Considering that class discussion and homogeneity contribute to fostering relationships, a comprehensive reading of the findings reveals that due to workload, participants with management positions see particularly convenient and still effective remote lessons. Furthermore, if the class is formed by participants sharing similar professional backgrounds and management levels, debate is not precluded and interpersonal relationships improved as a consequence. From the observation of single items, it can be concluded that participants with management positions and in general those with higher basic management competencies at the start of the program, prefer more flexible and leaner training programs: intermediate assessment through conversation, self-assessment at the end of the course, more concentrated scheduled lessons and greater use of remote lessons.

Differently from what was found by Walston and Khaliq [ 25 ], the findings highlight that participants with management positions value the impact of management training on career prospects positively. These participants are also those more supported by their own organizations. Conversely, the lack of support, especially in terms of inadequate funds devoted to these initiatives, strongly affects physicians and participants without management positions, which clarifies what this challenge is about and who is mainly affected by it [ 36 ]. Low incentives mean having attended fewer training programs in the past, which, together with less management experience, explains why they have developed less competencies. Among the outcomes of the training program, the little attention paid by organizations is also testified by the lowest values attributed by all categories, except for participants without management positions, to the improvement of relationships with superiors and top management.

In general, the study contributes to a better understanding of the outcomes of management training programs in healthcare and their determinants [ 9 ]. In particular, it sheds light on gaps and education needs [ 1 ] by category of health professionals [ 2 ]. The research findings have major implications for practice, which can be drawn after identifying the four profiles of participants revealed by the study. All profiles share common characteristics, such as value given to debate, diversity of pedagogical approaches and tools and class homogeneity, rather than the need for a deeper comprehension of healthcare systems. However, they present characteristics that determine specific issues and education gaps, which are summarized as follows:

Physicians without management positions: low competencies at the start of the program and scarce incentives for attending the course from their own organization;

Physicians with management positions: they partially compensate for competence gaps through professional experience, suffer from lack of time, and are motivated by the chance to improve their career prospects;

Non-physicians without management positions: they partially fill competence gaps through postgraduate education, suffer from lack of time, and have scarce incentives for attending the course from their own organization;

Non-physicians with management positions: they partially bridge competence gaps through postgraduate education and professional experience, are the most affected by a lack of time, and are motivated by the chance to improve their career prospects.

Recommendations are outlined for different levels of action:

For policymakers, it is suggested to strengthen the ability of higher education courses in medicine and related fields to advance the understanding of healthcare systems’ structure and operation, as well as their current and future challenges. Such a new approach in the design curricula should then have as a main goal the provision of adequate management competencies.

For healthcare organizations, it is suggested to incentivize the acquisition of management competencies by all categories of professionals through postgraduate education and training programs. This means supporting them from both financial and organizational point of view, for instance, in terms of more flexible working conditions. Special attention should be paid to physicians who, even without executive roles, manage resources and directly impact the organization's effectiveness and efficiency levels through their day-by-day activity, and are the players holding the greatest innovative potential within the organization. Concerning the executives, especially in the current changing context of healthcare systems, much higher attention should be paid to fostering interpersonal skills, in terms of communication and cooperation.

For those designing training programs, it is suggested to tailor courses on the basis of participants’ profiles, using different pedagogical approaches and tools, for instance, in terms of teacher composition, lesson delivery methods and learning assessment methods, while preserving class homogeneity in terms of professional backgrounds and management levels to facilitate constructive dialogue and solution finding approaches. Designing ad hoc training programs would give the possibility to meet the needs of participants from an organizational point of view as well as, for instance, in terms of program length and lesson concentration.

Limitations

This study has some limitations, which pave the way for future research. First, it is context-specific by country, since it is carried out within the INHS, which mandatorily requires health professionals to attend management training programs to hold certain positions. It is then context-specific by training program, since it focuses on management training programs providing participants with the title to be appointed as a director of a ward or administrative unit in a public healthcare organization. This determines the kind of management competencies included in the study, which are those mandatorily required for such a middle-management category. Therefore, there is a need to extend research and test these findings on different types of management training programs, participants and countries. Second, this study is based on a survey of participants’ perceptions, which causes two kinds of unavoidable issues: although based on the literature and pre-tested, the questionnaire could not be able to measure what it intends to or capture detailed and nuanced insights from respondents, and responses may be affected by biases due to reactive effects. Third, a backward elimination method was adopted to select variables in model building. Providing a balance between simplicity and fit of models, this variable selection technique is not consequences-free. Despite advantages such as starting the process with all variables included, removing the least important early, and leaving the most important in, it also has some disadvantages. The major is that once a variable is deleted from the model, it is not included anymore, although it may become significant later [ 38 ]. For these reasons, it is intended to reinforce research with new data sources, such as teachers’ perspectives and official assessments, and different variable selection strategies. A combination of qualitative and quantitative methods for data elaboration could then be used to deepen the analysis of the relationships between motivations, effectiveness factors and outcomes. Furthermore, since the investigation of competence development, acquisition of new competencies and the transfer of acquired competencies was beyond the purpose of this study, a longitudinal approach will be used to collect data from participants attending future training programs to track changes and identify patterns.

Availability of data and materials

An English-language version of the questionnaire used in this study is attached to this paper as a supplementary file. The raw data collected via the questionnaire are not publicly available due to privacy and other restrictions. However, datasets generated and analyzed during the current study may be available from the corresponding author upon reasonable request.

Abbreviations

Italian National Health System

Kaiser–Meyer–Olkin

National Recovery and Resilience Plan

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Giovanelli, L., Rotondo, F. & Fadda, N. Management training programs in healthcare: effectiveness factors, challenges and outcomes. BMC Health Serv Res 24 , 904 (2024). https://doi.org/10.1186/s12913-024-11229-z

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Director Khari Garvin: Hello, I'm Khari Garvin, the Director of the Office of Head Start. Ensuring Head Start programs are safe places for children that families and communities can trust is one of our top priorities. We know that children need physical and emotional safety in order to develop, learn, heal, and thrive. We have heard and witnessed how challenges in recent years, workforce shortages, staff turnover, mental health needs, and more can affect the safety of children and staff.

We are also witnessing a resounding commitment from Head Start programs to remain steadfast in creating environments and relationships where children can thrive. I'm excited to announce the Building a Culture of Safety series to support this Head Start commitment. From August through November, we'll be providing resources and webinars to share a range of strategies in every program area, and then engaging in discussion with you during special office hours we will make available to support child health and safety across the Head Start ecosystem.

Make sure you are subscribed to our emails to ensure you get the notifications promoting this series. Do you know what we mean by building a culture of safety? Head Start programs are spaces where every child is valued and we know that every single person, Head Start leaders, staff members, and families, plays an important role in safeguarding children.

A culture of safety isn't a one and done training or a checklist. It requires a comprehensive, ongoing, and preventative commitment. There are four core messages about the culture of safety approach. You will learn more about these throughout the series, but I will share them now to anchor us. First, is that Head Start leaders support children’s safety and well - being by creating safe program environments, for example, by mapping and reducing potential risks and hazards or creating wellness spaces for staff.

Now, the second core message about the culture of safety approach is that positive guidance from caregivers supports children's social and emotional development and promotes their engagement in the learning environment. Third, Head Start leaders cultivate an organizational culture that sets an expectation for child safeguarding and that builds trust, accountability, empathy, and equity for staff and families.

Leaders establish how we do things in the program with policies and procedures and by putting supports and systems in place to help everyone uphold those expectations. And by the way, did you know that Head Start and Early Head Start grant recipients that encounter program improvement needs related to health and safety, which cannot be covered by your regular budget, can submit a supplemental one-time funding application anytime throughout the year as needs emerge?

Those things in your program that address health and safety like repairs or upgrades to facilities or playgrounds or maybe adding temporary staff positions to achieve lower ratios in classrooms that need extra support. There is a lot of flexibility for these supplemental funds, although they are limited and available on a one - time basis.

I invite you to reach out to your regional office to learn more about the application process. Finally, everyone who works or volunteers in Head Start programs adheres to the Head Start Standards of Conduct, which are the basic professional expectations for working in a Head Start program. This Building a Culture of Safety series will offer strategies and create space for discussions to put these messages into action and develop a culture of safety in every Head Start program.

You can find out more about this series on the ECLKC website. Thank you for your commitment to making sure Head Start programs are safe. We couldn't do it without you. So long. For Building a Culture of Safety campaign information, visit https://qrco.de/bfEsZn to sign up for Office of Head Start email updates. Visit https://qrco.de/bfEsfn .

Produced by the US Department of Health and Human Services.

Approaches to Preventing and Addressing Child Health and Safety Incidents

Join us Aug. 28, 2024 at 2 p.m. ET , for a special webinar , 4 Steps to Healthy and Safe Learning Environments . It focuses on four strategies that align with OHS core messages on child health and safety.

The next day, Aug. 29 at 2 p.m. ET , bring your child health and safety incident questions to a follow-up live office hour . Experts from the National Center on Health, Behavioral Health, and Safety will be on hand to help you promote positive learning experiences for Head Start children and prevent incidents that can jeopardize their well-being. This event is offered with simultaneous interpretation in Spanish.

Register for Webinar Register for Office Hour

The following resources provide additional background for this event:

• Discipline and the Influence of Our Upbringing
• Keep Children Safe Using Active Supervision

Preventing and Addressing Child Incidents Through an Education Lens

Join us Sept. 20, 2024, from 3–4:30 p.m. ET , for a special webinar , 10 Tips for Creating Supportive Environments That Can Prevent Behaviors that Challenge Us . This Teacher Time episode focuses on useful tips for setting up the physical environment, transitions, schedules, routines, and more.

Following the webinar, stay on to participate in a live office hour session. Experts from the National Center on Early, Childhood, Development, Teaching, and Learning will be on hand to answer your questions about addressing child incidents through an education lens.

Register for Webinar and Office Hour

The following resources provide additional information:

• Visual Supports
• Engaging Interactions and Environments
• Positive Behavior Support

Promoting Child Safety Through Staff and Family Partnerships

Save the date, Thursday, Oct. 10, 3–4:30 p.m. ET , for a webinar and office hour discussion with the National Center on Parent, Family, and Community Engagement! Visit this page and be on the lookout for an email invitation as the date approaches.

Parents and families observe, guide, and participate in the everyday learning of their children at home, school, and in their communities in ways that promote children's safety, health, and development. Join this session to explore partnerships with parents as the lifelong educators and advocates for their children. We're sharing strategies for promoting child safety while exploring restorative practices that build and strengthen community, resolve conflict, facilitate individual and community healing, and prevent harm.

Research to Practice: Preventing Child Incidents Through Effective Systems

Save the date, Thursday, Nov. 14, 3–4:30 p.m. ET , for a webinar and office hour discussion with the National Center on Program Management and Fiscal Operations! Visit this page and be on the lookout for an email invitation as the date approaches.

This event explores how enhanced systems thinking and multi-dimensional perspectives can address a critical issue in Head Start programs: preventing and appropriately responding to child incidents. We're sharing tools, recommendations, and strategies to support Head Start leaders and staff in their ongoing efforts to keep children safe. Join to learn how to apply this information for optimal impact on children and their families.

• Using Motivation-based Interview Techniques
• Gallup's 5 Drivers of Organizational Culture
• Employing Values-based Recruitment in Hiring Practices

Resource Type: Article

National Centers: Office of Head Start

Last Updated: August 14, 2024

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