Key Takeaways

The discussion question (DQ) is a ritual familiar to anyone who has taught or taken an online college course in the last two decades. Maybe first read a chapter or watch a lecture video, and then — dutifully, reluctantly — post a written answer to a DQ thread. The answer has to be substantive and not too short, but not too long. You post something that sounds thoughtful. You must reply to two classmates by a certain day of the week. You receive your participation points. Nobody learns anything particularly profound, and everyone moves on.

That ritual is dying. AI has killed it or will soon. And higher education is only beginning to reckon with what that means to the DQ and virtually everything in the learning management system.

The DQ was already on life support

To be fair, the DQ was never the robust pedagogical tool administrators pretended it was. In theory, asynchronous discussion boards were supposed to replicate the Socratic dialogue of a seminar room — discussions that wrestle with ideas, challenge participants, and build collective understanding. In reality, DQ practice was little more than performative academic writing that students could generate very quickly and very well. Short on insight. Long on filler. Designed to satisfy a rubric, not to think.

Now we have ChatGPT, Claude, Gemini, and a dozen others. And overnight, the time cost of producing a competent, rubric-satisfying discussion post dropped to approximately thirty seconds. It has quickly become the artifice of learning artifacts.

The mistake universities are still making

Here is the uncomfortable truth that many academic VPs and curriculum committees are not yet ready to say out loud: universities have been using discussion boards primarily not to educate students, but to monitor them — AND to monitor faculty.

Discussion posts create artifacts. They demonstrate that a student logged in, engaged with the material, and produced something. They prove — or seemed to prove — that a course was “active.” Administrators could pull engagement reports. Faculty supervisors can create expensive dashboards using glizy business intelligence tools to watch over faculty on the pretense that DQs are the kernel of learning. Accreditors could audit thread counts. The DQ was less a learning tool than a compliance mechanism dressed in the language of pedagogy.

With the arrival of AI, it’s game over for the DQ as we know it

With AI, however, the game is over. When a student can generate a thoughtful, citation-rich, 250-word response to “How does Clayton Christensen’s theory of disruptive innovation apply to the collapse of traditional retail?” in under a minute, the compliance artifact no longer tells you anything about the student. It tells you about their prompting skills, at best.

Doubling down — adding AI detection tools, requiring students to post within specific time windows, demanding webcam-verified responses — is not a solution. It is an arms race that institutions will lose, are already losing, and that corrodes the trust between faculty and students in the process.

How long will it take for enterprising faculty to create automated responses to student answers to feign adequate “engagement” in the online classroom? It’s likely already done.

And a few other things

The death of the discussion question is a symptom, not the disease. The deeper problem is that online higher education has chronically underinvested in the kinds of learning experiences that AI cannot easily replicate: genuine intellectual relationships, productive disagreement, and the friction of being pushed by someone who actually knows you and your thinking.

The problem is greater than DQs. Entire systems of online learning assignments are at risk. The famed 750-word paper--complete with references--can be written by AI in a few minutes. Answers to multiple-choice questions will be readily available even without AI.

We must get beyond the myth of a DQ being the substitute for Socratic dialogue

The rhetoric is there, of course, to keep up the pretense. There are multiple dubious articles claiming that online discussions can somehow mimic “Socratic dialogue” through rich, rapid exchanges.

Online faculty, who are often underpaid adjuncts, were given discussion boards as a substitute for real pedagogical design. Students who were already isolated in asynchronous environments were given thread requirements as a substitute for real community. The DQ wasn’t just a bad assignment — it was a placeholder for something that could never fulfill promises.

A way forward: Real online dialogue

The answer is not to abandon online discussion. It is to redesign it around what AI cannot easily fake: live, authentic, responsive, evolving conversation between specific people about specific ideas.

What this looks like in practice is guided online verbal dialogue — structured, small-group, real-time conversations built around prompts that require students to think while responding to each other, specifically, rather than to an abstract question floating in an empty thread. Not “What do you think about X?” but “Company X attempted to implement the outlined strategy last year — how do you evaluate it and should it be changed?”

This requires students to actually prepare for a discussion and intently listen to what their peers say. It surfaces individual reasoning in ways that are hard to outsource because the conversation is about them — their prior statements, their intellectual growth, their specific disagreements.

Real dialogue is harder to design. It is harder to scale. But it is also what learning actually looks like.

One platform already doing this work seriously is Breakout Learning. Rather than asking students to post to a board, Breakout puts them into live, small-group video discussions — face-to-face, in real time — built around scenario-based content. Students have to articulate ideas verbally, respond to peers on the spot, and reason through follow-up questions in the moment. There is no copy-paste. No prompt engineering. No, quietly running a response through an AI and tweaking the wording.

That model — live dialogue, AI-assisted evaluation, human accountability at the center — is what post-DQ online education may look like. There is plenty of research to do in this area.

The DQ is dead. The question now is whether universities will replace it with something better, or simply with a more sophisticated version of the same hollow compliance theater — this time, with an AI detector bolted on the side.

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Installment two of Affective the Affective is finally here!

Key takeaways

Relevant learning in today’s world requires a substantial amount of “know-who” and “know-how” (affective components) beyond just cognitive knowledge or “know-what”.

Affective skills—such as flexibility, empathy for collaboration, and intellectual humility in critical thinking—serve as “gateways” and catalysts for mastering more cognitive skills, such as information and digital literacy.

The traditional KSA (Knowledge, Skills, Abilities) competency model is suboptimal because it is knowledge-dominant and driven by the convenience of testing, often missing affective elements that are difficult to quantify and test.

The document proposes flipping the script to the ASK (Attention, Skills, Knowledge) model, a learning-centered approach that starts by defining competency in terms of the focus or attention required for successful learning.

Attention is a fundamental gateway to learning; without focused attention, new information is not effectively processed or retained, making attentional capacity a critical prerequisite for knowledge acquisition and skill mastery.

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— Second of a four-part series —

The first installment of this series developed the idea that relevant learning in today’s world involves more than cognitive knowledge—the “know what.” The idea is clear. Modern societies demand more than propositional knowledge, the “know what.” Instead, a substantial amount of “know-who” and “know-how” is needed. That’s where the affective journey should begin.

The real journey begins before the ”know-what” cognitive knowledge

This installment of Affecting the Affective takes a deep dive into the area of competencies, and specifically the learning aspect of affective competencies. What I lay out here is that designing and delivering affective skills learning is different from what we think about a competency.

The affective: Enter the 21st Century Skills

A useful framework for understanding the importance of affective skills is the 21st Century Skills Framework. The concepts were developed shortly after the turn of the century by the Partnership for 21st Century Skills (P21), which included the U.S. Department of Education and tech leaders such as Apple, Oracle, Cisco, and Microsoft. The purpose was to align education with the evolving demands of the digital economy. A key shift embedded in the framework was a move away from ideas rooted exclusively in cognitive knowledge acquisition, such as rote memorization and recall, towards higher-order, multi-skilled competencies. The diagram below shows the positioning of key enabling competencies across the top.

The competencies are divided into three groups as shown below.

The news headlines about 21st-Century skills often focus on fashionable hard skills such as information and digital literacy. The hidden issue is that even literacy skills, which are typically more cognitive in nature, depend on the key affective elements — the gateways — of life/career and learning skills.

Affective skills serve as the gateways to knowledge

For example, useful flexibility requires significant emotional regulation to manage the anxiety of change while remaining in a growth mindset. Critical thinking, often misconstrued as just a bit of cognitive learning, comes only with a healthy dose of intellectual humility and the ability to challenge one’s prior thinking. Collaboration demands empathy and trust to support valuing and acting on diverse perspectives. Without these affective components, the ability to master the literacy skills is severely limited.

The through line, or the red thread, is that the affective components of key skills serve as catalysts for the mastery of cognitive skills. It is here that we can see the divergence from prevailing notions of knowledge-based competencies, often described using the acronym of KSA for knowledge, skills, and abilities.

Why the KSA competency model misses the mark

KSA, an acronym for Knowledge, Skills, and Abilities, is the traditional and widely adopted framework for defining competencies in educational, learning & development (L&D), and human resource contexts. This model typically positions a competency as a measurable outcome, progressing from foundational knowledge (the “know-what”) to skills (often seen as the “know-how”), and culminating in abilities (often combining “know-how” with context, such as “know-who” and “know-why”). It is a suboptimal choice, but it satisfies the convenience of testing.

The real journey of learning begins with the affective components of know-why and know-who

The history of how competencies entered the educational space points to why knowledge is privileged over affective components. David McClelland of Harvard is often credited with coining the phrase “competency” in his 1973 seminal paper “Testing for Competence Rather than Intelligence.”[1] McClelland, however, did not provide a complete model for defining competence or developing learning models around the idea. He published around the idea but did not develop definitional tools and techniques.

The hidden challenge of McClelland’s work was that competencies are difficult to quantify, measure, or assess. That challenge led to competencies being co-opted by assessment and testing. For example, their article “Use of Knowledge, Skill, and Ability Statements in Developing Licensure and Certification Examinations,” [2] Wang, Schnipke, and Witt trace the origins of the KSA trio to professional licensure exams and testing for specific knowledge recall and reasoning rather than interpersonal skills or abilities. This development flipped McClelland’s idea on its proverbial head. Rather than looking for skills, the focus has shifted towards testable knowledge.

The idea of competencies has been co-opted by testing, not learning and education

It is ironic, in light of McClelland’s suggestions for competency evaluation rather than intelligence testing, that the construction of competencies has ended up relying on a knowledge-dominant KSA model. The purpose of a supposed logical progression from knowledge to skills to abilities appears to be largely for the convenience of testing and not grounded in the realities of learning.

It is not surprising that testing or assessment of knowledge has come to dominate competency discussions. Meaningful assessment of skills and abilities, which are more affective in nature, is difficult. For example, OECD’s 2015 Programme for International Student Assessment (PISA) struggled to assess collaboration (one of the 4-Cs). The problems in that experiment confronted the practicalities of assessing conversations, group composition disparities, and a lack of effective technology to capture interpersonal interactions. [3]

Flipping the script from KSA to ASK

Perhaps we should move beyond a testing-driven view of competencies towards a learning-centered approach. A suggestion is to “flip the script” and think of competencies using the acronym ASK rather than KSA. Several issues with the KSA model suggest that an alternative approach is needed.

For starters, the “K” or knowledge element in the KSA model is not as fixed and certain as many learning designers may believe. In an era of hyper-connectivity and ubiquitous web resources, knowledge is more the result of adept access to and use of data and information in context. It is no longer a fixed set of ideas or concepts that define what needs to be learned. Viewing knowledge as a dynamic rather than a fixed characteristic clearly recognizes the role that web resources play in shaping knowledge generation and acquisition. In short, it cannot be the starting point for defining a competency.

The skills or “S” element in KSA also evades an easy definition. A common approach to defining skills is based on skill domains, which require some level of task consistency and practical value for organizations to structure work. [4] The overlap with notions of abilities is obvious and further leads to confusion in the KSA model. A definition of skills by the ILO is “the ability to carry out the tasks and duties of a given job.” [5] The fusing of ability with skills in the ILO definition illustrates a key challenge inherent in the KSA model.

Beyond the confusion inherent in the fusion of skills and abilities, there is another tension in the use of the ability concept. The classic definition of skills is focused on manual tasks. Such an idea could suffice for rather simple repetitive tasks, such as those on a 20th-century assembly line. The idea quickly falls apart with complex tasks in a knowledge economy. For example, the work of a skilled surgeon involves much more than the repetition of a set of tasks with a scalpel.

A proposed use of ASK starts with a competence based on attention

The traditional view of skills, focused on manual dexterity relevant to industrial economies, is inadequate for today’s knowledge-driven economies that require complex relational, technical, and interpersonal abilities. The multifaceted expertise of a surgeon exemplifies this, extending beyond physical manipulation to include deep medical knowledge, diagnostic synthesis, critical decision-making, problem-solving, attention to detail, communication, continuous learning, ethical considerations, and emotional intelligence. A contemporary understanding of skills must encompass this intricate web of abilities, acknowledging the importance of critical thinking, creativity, communication, collaboration, and complex problem-solving in the modern world.

An ability can extend beyond a particular job or task skill set. For example, communication abilities can be valuable in a number of contexts but differ by context. Trying to confine ability to a defined knowledge or skill domain is thus a fool’s errand.

ASK: A learning centered approach to competencies

Moving from the KSA model to ASK is more than a reordering of the letters. The core idea of ASK is that knowledge results from and is determined by the A (attention) and the needed skills. In this formulation, knowledge—the”K”—is determined by capabilities defined by the A and S.

A logical focus of “A” is the concept of attention. The focus recognizes that attention fundamentally defines the ability for learning. [6] A similar concept, tuned perception, has been around for decades in psychology. [7] Both ideas are consistent with emerging neuroscience research, which tells us that we learn where we focus. The use of the capacity for attention first defines and shapes competency as a precursor to knowledge and skills, not the other way around.

Attention is not merely perception; it functions as a gatekeeper for learning. Without focused attention, new information is neither effectively processed nor retained. The brain can be likened to a radio receiver, with attention acting as a tuner – enhanced signal clarity improves comprehension. Research indicates that concentrated focus strengthens neural connections, thereby optimizing the learning process.

Attention, therefore, is not passive presence but an active mechanism that preconditions all learning. Focused attention is a prerequisite for further knowledge acquisition. Proficiency in directing and sustaining attention is critical for learning across disciplines. Given individual variations in attentional capacities, understanding and potentially enhancing these skills is particularly salient in educational and training environments.

Flipping the script from KSA to ASK puts effective learning, not testing, at the forefront of the educational equation.

Defining competencies first in terms of needed focus or attention, then in terms of skills, and only then in terms of knowledge is a more useful approach. As noted by Julia Simms in “Where learning happens,” [8] using attention as the starting point of learning creates a focus on the skills needed for enhancing attention and learning. The current KSA model does not explicitly include attention as an element, despite its importance to learning and performance.

Flipping the script from KSA to ASK puts effective learning, not testing, at the forefront of the educational equation. Transitioning to this model will require redesigning the curriculum to focus first on the mechanics of learning rather than simply transmitting knowledge objects.

Up next: Practical applications of ASK

In the next installment of Affecting the Affective, I will look at a surprising example of how ASK works in a fundamental part of our lives, nutrition. That segment will focus on how a health lifestyle coaching program transformed from in-person education to an online model and improved outcomes by tuning perception and focus.

Installment 4 will focus on how assessment strategies end up degrading rather than improving learning by imposing a fixed mindset on education.

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About the Ex4EDU.Report and EduPartners.news

This report is offered as a free-of-charge contribution by Lone Tree Academics LLC an educational services company dedicated to transformation in higher education. Our services are focused on solutions for the development of institutional and program strategies, crafting engaging LearningScapes™, and developing programs of the scholarship of teaching and learning.

We are also founders of the EduPartners.coop LCA, which supports and sends the newsletter EduPartners.news, which is focused on furthering the use of cooperative and collaborative organizations in higher education.

Notes

[1] McClelland, D. C. (1973). Testing for competence rather than for “intelligence”. The American Psychologist, 28(1), 1-14. https://doi.org/http://dx.doi.org/10.1037/h0034092

[2] Wang, N., Schnipke, D., & Witt, E. A. (2005). Use of knowledge, skill, and ability statements in developing licensure and certification examinations. Educational Measurement: Issues and Practice, 24(1), 15-22. https://doi.org/10.1111/j.1745-3992.2005.00003.x

[3] C. Graesser, A., Foltz, P. W., Rosen, Y., Shaffer, D. W., Forsyth, C., & Germany, M.-L. (2018). Challenges of Assessing Collaborative Problem Solving. In E. Care, P. Griffin, & M. Wilson (Eds.), Assessment and Teaching of 21st Century Skills: Research and Applications (pp. 75–91). Springer International Publishing. https://doi.org/10.1007/978-3-319-65368-6_5

[4] Rodrigues, M., Rernández-Macías, E., & Sostero, M. (2021). A unified conceptual framework of tasks, skills and competences. European Union.

[5] International Labour Organisation [ILO]. (2012). International standard classification of occupations: ISCO-08 (Vol. 1). ILO. p. 11

[6] Keller, A. S., Davidesco, I., & Tanner, K. D. (2020). Attention matters: How orchestrating attention may relate to classroom learning. CBE—Life Sciences Education, 19(3), fe5. https://doi.org/10.1187/cbe.20-05-0106

[7] Carey, B. (2015). How we learn. The surprising truth about when, where, and why it happens. Random House.

[8] Simms, J.A. (2025). Where learning happens : Leveraging working memory and attention in the classroom. Marzano Resources.

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Is the “one-size-fits-all” accreditation model finally cracking? Recent developments suggest that the future of quality assurance is arriving faster than we thought.

When I presented Accreditation Scenarios at the 18th SEAA Conference in India late in 2025, the goal of the discussion was to focus on the critical uncertainties facing global higher education accreditation. The discussions in Bengaluru highlighted a growing tension between traditional institutional accreditation and the rapid evolution of digital learning—a tension that has only intensified in the months since. At the same time, there is a growing divide between traditional higher education and a more active corporate L&D, especially with corporate universities. India is a unique case of a rapidly developing higher education scene with the New Education Policy and a very clear move towards alternative credentials.

We also now see movement in the U.S. Recently, the U.S. Department of Education has awarded $169 million in FIPSE grants, many of which will seek to establish new accreditors in the U.S. Some of the intended new entrants are focused on institutional accreditation, while others are more focused on specialized accreditation. We seem to be at a critical juncture of both accreditation and quality assurance in the U.S.

These areas are exactly the space where a technique called Scenario Planning can be helpful. To understand where this specific development fits into the broader picture, I will focus on four potential futures explored at the SEAA Conference. These scenarios are global and do not focus on any one national system.

Scenarios and The Art of the Long View

To make sense of these shifts, a methodology of Peter Schwartz, author of the seminal text The Art of the Long View, was used. Schwartz was one of the pioneers of scenario planning, not as a prediction tool but as a mechanism for exploring multiple, overlapping possibilities based on critical uncertainties.

The value of this exercise lies in its nuance. As Schwartz suggests, it is rare for any single scenario to come true completely. Instead, the future usually arrives as a complex tapestry, where elements of all four scenarios come true in part. By understanding the extremes, however, we can better navigate the reality that unfolds in the middle.

Normally, no scenario comes true in entireity but all come true in part

The process starts by framing the challenge around “critical uncertainties” affecting the sector. The method defines critical uncertainties as the specific variables that are both highly important to the focal issue and highly unpredictable. Our discussions identified several critical uncertainties worth considering. Those included the following.

• Unit of focus—institutions/programs vs. skills. In essence, will the academic degree maintain a central focus or cede its dominance to skills-based portfolios?

• Locus of control. Will there be a market-based globalization of trade in education services or a national/regional governmental policy-based regulatory approach?

• Societal equity tensions. How will a growing mismatch of economic growth and new jobs vis-à-vis the number of graduates play out?

• Definition of quality. Is higher education quality defined by academic measures and rankings, or by graduate and stakeholder ROI?

Based on the critical uncertainties, four scenarios emerged for discussion. As is typical in these exercises, the scenarios fit distinct patterns. Often, one scenario portrays a continuation of trends already in play. A second one frequently focuses on a breakdown of an existing order while it is still partially intact. A third alternative typically involves a disruptor or disruptive forces with a strong impact. A final common theme focuses on technological disruption.

One cannot say with total confidence that the scenarios are the be-all and end-all points. The goal of the exercise at the SEAA Conference was to inform discussions among higher education institutions about which type of accreditation to seek. The scenarios identified are briefly described below.

Scenario 1: Global Harmonization & Mutual Recognition

In this scenario, the world moves toward tighter integration, an example of the continuation of the existing trends view. This could involve adopting new international standards with unified quality frameworks accepted across nations. For example, inspired by the EU’s Lisbon Recognition Convention, this scenario features automatic recognition of credits and degrees across borders. It could also involve a more minimalist approach of deferring to several ISO standards, such as ISO 21001:2025, ISO 29992:2018, ISO 29993:2017, and ISO 29994:2021.

• The Essence: Seamless global student and workforce mobility, supported by transparent registries of accredited institutions.

• Impact on Accreditors: There will be fewer accreditors, and they will be vertically integrated and global in scope.

Scenario 2: Regional Accreditation Blocs

Alternatively, the world may fragment into regional alliances (e.g., Europe, Asia-Pacific, Americas) that develop region-specific frameworks. Here, standards are context-specific, reflecting local cultures and workforce needs rather than global uniformity. This development can be illustrated by the growth of the European Higher Education Area (EHEA) and of EQAR (European Quality Assurance Register for Higher Education), which covers the 45 nations in the EHEA.

• The Essence: Strengthened regional expertise and institutional development, but cross-regional recognition is restricted and requires bilateral, case-by-case agreements.

• Impact on Accreditors: Regional restrictions increase on access and recognition. Only regional players are allowed to operate. For example, only European-based accreditors in Europe or only India-based accreditors in India.

Scenario 3: The standards marketplace

In this privatization scenario, a competitive “standards marketplace” emerges. Verification becomes industry-driven rather than academic, with private sector organizations vying for market position and share. This could well involve the strong growth of corporate universities and “stacked credentials” delivered by private entities.

• The Essence: Universities are driven to offer multiple “industry accreditation portfolios” to boost their global reputation and attract students, while corporate L&D and corporate universities move into universities’ traditional turf.

• Impact on Accreditors: This scenario would signal a major shift toward industry-centric validation rather than traditional institutional accreditation. Industry standards bodies, rather than traditional accreditors, would create the quality frameworks.

Scenario 4: Technology-Enabled Focus

A potentially disruptive scenario involves replacing episodic reviews with AI and real-time analytics for continuous quality monitoring. Blockchain technology would largely displace traditional learning systems, creating immutable records and reducing verification times from weeks to mere seconds.

• The Essence: Flexible pathways allow diverse learning models—traditional degrees, micro-credentials, bootcamps, and hybrid programs—with adaptive quality standards.

• Impact on Accreditors: Survival depends on the ability to participate in the interoperability of advanced technical systems. An accreditor’s survival will depend on the ability to navigate a fragmented technology landscape with concentrated tech firms poised to displace traditional accreditation quality assurance roles.

The Strategic Takeaways

The scenarios point to a future where the “one-size-fits-all” model of collegial institutional accreditation will be under threat. This could signal a shift from a single, omnibus review that validates every aspect of a university’s complex operations to more focused efforts. Some hints of how this may look for accreditation offerings can be seen in EFMD’s collection of current offerings. This future would tap Scenarios 1 and 3 the most and may signal moves by traditional institutional accreditors into the turf occupied by specialized players, especially business program accreditors.

The concept outlined in my article ISO Alongside, Instead, or Inside? The potential of ISO 21001:2018 to transform and challenge higher education accreditation might warrant consideration. The injection of standards from non-academic standards organizations, such as ISO, could signal a shift towards the use of minimal agreed standards administered by independent bodies, e.g., ISO registrars. The role of traditional accreditors could then shift to one of added value beyond basic quality standards. Such added value could be providing networking and exchange opportunities, but not always standard-setting. Such a scenario would lean most toward Scenario 3 with some elements of Scenario 1.

Lastly, for specialized accreditors—whether in business, engineering, or healthcare—the potential shifts could have dramatic effects. These agencies have operated as a layer on top of a foundational institutional accreditation. They have relied on that base to handle the heavy lifting of governance and financial stability checks. However, as the market fragments and digital transformation evolves, this reliance may become a strategic liability. Either Scenario 3 or 4 could severely disrupt specialized accreditors' current activities.

In conclusion, the future belongs to accreditors who can offer a complete, integrated seal of approval that speaks directly to relevant stakeholders, without relying on a legacy system that may no longer fit the modern world.

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This Substack newsletter is offered as a free-of-charge contribution by Lone Tree Academics LLC and EduPartner.solutions, both educational services companies focused on learning transformation in higher education. Our services are focused on solutions for the development of institutional and program strategies, crafting engaging LearningScapes™, and developing programs of the scholarship of teaching and learning.

We are also founders of the EduPartners.coop LCA, which supports and sends the Substack newsletter EduPartners.news, which is focused on furthering the use of cooperative and collaborative organizations in higher education.

Learning is more than mathematical equations.

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— First of a four-part series —

Decades after identifying the need for interpersonal or “affective” skills in the workplace, higher education still fails to deliver. The focus has remained on cognitive skills and even solely on quantitative subjects.

Well over a decade ago, studies identified a series of studies on 21st-century skills for the modern workplace, including a focus on the 4 Cs of communication, collaboration, critical thinking, and creativity. Essentially, these are key interpersonal or affective skills.

Despite the clear case for affective skills--meaning how we deal with things emotionally, such as feelings, values, appreciation, enthusiasms, motivations, and attitudes--we continue to ignore the clear need. We are often confronted with simplistic notions that teaching and learning STEM subjects will solve all of society’s problems. The recent hype around generative AI such as Chat GPT would have one believe that the only skill needed is data analytics.

Mastering cognitive skills does not guarantee that smart people can work together. In fact, history is littered with brilliant personalities who were unable to reach their full potential because of a lack of the 4 Cs.

The barrier to success as we work in complex organizations and seek to solve complex problems is often that smart people cannot work together effectively. Simply put, it is an issue of the lack of learned affective skills rather than knowledge and mastery of concepts and theories. 

A theme heard at virtually every business or academic conference is around how to deal with constant and evolving change. The key skills of collaboration in problem-solving and change management are largely in an affective domain not some new theory or concept lending itself to cognitive skill building.

Doing better as educators will require that we come to grips with teaching and learning in both the cognitive and affective domains. 

This series will address this area in four installments.

• Clarifying the distinction between cognitive and affective skills and providing an overview of key 21st-century skills in the context of affective intelligence.

• Flipping the script on the idea of competencies from KSA (usually knowledge, skills, and abilities) to ASK (attention, skills, and knowledge).

• Examining the assessment challenges for affective skills using the example of collaborative problem-solving.

• Describing a real-world example of how behavioral change in one of the most difficult affective areas of personal health—nutrition and weight loss—can actually be done at a distance using online and remote technologies.

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Cognitive vs. affective learning

A default assumption when considering learning and education is that knowledge is key. The idea's foundation is that there are data, facts, elements, or concepts out there that need to be learned to be effective as humans. One could perhaps trace this notion to the ideas of enlightenment such as René Descartes's first principle of his philosophy, "I think, therefore I am" (Latin—cogito, ergo sum; or as he put it first in 1637—je pense, donc je suis).

As education thought and theory evolved, notions of different types of knowledge or intelligence emerged. Approaches to measuring levels of knowledge and skill saw refinement as well.  In 1956, Bernard Bloom published a taxonomy of cognitive learning. That was followed in 1965 by an affective taxonomy with David Krathwohl, one of Bloom’s co-authors, as the main author. These two taxonomies were followed by a third, the psychomotor domain, in 1972. The three taxonomies—with the cognitive domain updated in 2001—are foundational to educational program design and outcomes evaluation.

The three taxonomies or domains taken together provide a holistic view.

The distinctions inherent in the domains are important. The cognitive domain comes with a scientific view that there is knowledge “out there,” and it should somehow be captured, assimilated, and mastered. The affective domain is instead rooted in the level of skillfulness of one’s behavior in personal, interpersonal, and group settings. The psychomotor domain looks at the skillfulness of our ability to move and accomplish physical tasks of increasing complexity.

Despite the existence of three distinct learning domains, educational practice is often stuck in the cognitive domain. The myopic focus on programs and skills such as STEM and data analytics illustrates the lack of a broader focus. Curriculum designers are taught to ignore affective skills because they are just too difficult to fit into the model of testing and assessment common in education. 

Enter the 21st-century skills

The multiple turn-of-the-century projects sought to define the knowledge and skills needed in economies driven by rapid technological evolution and interconnectivity. The inventory of skills includes critical thinking, creativity, collaboration, communication, and technological literacy. All of the described skills involve more than just cognitive learning. 

For example, the core skills of critical thinking and problem-solving involve substantial elements of human interaction to leverage collective intelligence. Creativity and innovation are also at their best with effective interpersonal interactions. Collaboration and communication are almost by definition rooted in Krathwohl and Bloom’s affective domain. 

Creativity and critical thinking are also not solo acts. Dialogue and interpersonal relating tremendously enhance both. It is no accident that innovation clusters or centers tend to be in compact geographies. After all, wasn’t that the idea of a university? 

Stuck in the cognitive-only ditch

The time-worn saying of “it’s not what you know but who you know” illustrates a long-held recognition of affective skills. But, if we were to look at the curriculum in any university program, it would be heavily tilted towards a range of cognitive skills and would ignore this idea.

In the business and non-profit management disciplines, where I have taught for decades, quantitative subjects such as finance and accounting reign supreme. Even organizational behavior has been co-opted into an idea of human “resource” management. And, marketing has become a numbers game with customer relationship management (CRM) systems.

In the healthcare disciplines, affective skills are crowded out by all the learning needed for complex medical procedures. But who among us wants a dysfunctional surgical team operating on us?

Even in the liberal arts, learning is often focused on developing “prepositional knowledge” of the discipline's history and seminal theories. The nuances of interpersonal navigation that would seem natural in these disciplines are simply absent.

Flipping the narrative 

So, how can we get out of the cognitive ditch? Should we turn to theories such as problem-based learning or challenge learning? It will take much more than a convenient focus on a problem or challenges.

For a start, concepts such as the 4 Cs should be the foundation or the keystones of learning design. Rather than start with the knowledge to be imparted, the focus should shift to developing affective domain abilities and then adding the needed knowledge on an as-needed basis. 

The next three installments of this series will bring out ideas and concepts in more detail. Stay tuned for more.

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About the Ex4EDU.Report, Student360.Report, and EduPartners.news

This report is offered as a free contribution by EduPartner Solutions, an educational services company focused on transformation in higher education. Our services include solutions for developing institutional and program strategies, crafting engaging LearningScapes™, and developing programs for the scholarship of teaching and learning.

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My first trip to India was in 1989 as a part of an MBA class study tour from IMD in Switzerland. My last trip concluded just a few weeks ago and included speaking at the Association of India Management Schools (AIMS) conference in Coimbatore and at the opening of the year festivities at ASBM University in Bhubaneswar.  I left Delhi just before the start of the G-20 and avoided the disruptions to the normal day-to-day life in a city that any such conference of global leaders creates.

The changes in India from that first visit in 1989 have been nothing short of remarkable. During that first time in India, I vividly recall meeting with the Reserve Bank of India. In the meeting, we were told repeatedly that no economic liberalization agenda was needed or even in the works. At that time, many of the national highways were unpaved and turned into muddy messes with the first rain storm. Mobile phones were the stuff of sci-fi, and even calling home to my wife in Switzerland required scheduling a line two days in advance. The pace of change is noticeably faster in every visit I have made in the past 7 years.

As the most populous country in the world, India will have a significant influence globally on many fronts of higher education. According to the All India Council of Technical Education (AICTE), there are around 8,200 technical higher education institutions and 3,300 offering management education in India and it is growing fast. India’s numbers compare to the roughly 6,000 institutions of all types in the U.S. and 5,000 in the entire 46-country European Higher Education Area. The sheer number of Indian institutions foretells what may be a significant impact on global higher education. But, there are risks to the entire Indian model of growth.

The focus of the first two topics in this edition of Ex4EDU.Report will provide some perspective on what is happening in this dynamic corner of higher education. The final topic will touch on what I see as the pivotal point and risk for future management education in India, which was also the subject of two of my speeches.

The National Education Policy of 2020

India has a public goal to become the world’s third-largest economy, behind the U.S. and China. The goal is widely discussed in business school circles.

Beyond the talking points of “third largest economy,” some elements stand out as examples of how India is getting it right to move forward. In higher education, the National Education Policy (NEP) of 2020 touches on many areas of enabling the growth needed to advance the economy. Of course, one can see new education policies in virtually any country worldwide. But, there are some important aspects of what I see in India’s approach to higher education worthy of discussion here.

Vishwa Guru

The NEP mentions that India should become a “Vishwa Guru” or world or global teacher. There are stated aspirations to allow existing higher education institutions to open branches and allow foreign institutions to open campuses in India. Moving to such a position will require a major transportation of the higher education sector.

The opening for non-Indian players will logically lead to a need for internationally recognized quality systems. Relying on international university rankings—the main marker noted in the NEP—fails to capture the full scope of a quality institution. Defaulting to the top 100 global universities as the source of investment is insufficient. Rankings generally indicate social exclusivity, not excellence, and will be inadequate to grow the number of high-performing institutions at a scale for the world’s most populous country. 

Rankings indicate social exclusivity, not excellence

Turning to international accreditation as an alternative to rankings is only a partial solution. A few internationally relevant accreditation agencies exist in specialized areas such as business. Examples include ACBSP, IACBE, AMBA, EQUIS, and AACSB. The presence of these accrediting agencies in India is limited to a few of the thousands of institutions. Unless these agencies dramatically grow their presence in India, something else will fill the void. The growing group of ISO standards specific to higher education and the ISO certification system may be “the” something else.

ISO standards such as ISO 21001, 29992, 29993, and 29994 focus on quality areas specific to higher education. A soon-to-be-issued ISO standard, ISO/TS 21030:2023 “Educational organizations — Requirements for bodies providing audit and certification of educational organizations' management systems,” enables structures like authorized accreditation agencies. It may foretell one or more ISO certification bodies entering the international accreditation void. ISO/TS 21030 is based largely on an existing standard ISO 17021-1:2015, so the model is a known approach. The process of certifying certification bodies could compete directly with the authorization of accreditation agencies by the University Grants Commission in India, EQAR in Europe, and CHEA in the U.S. Currently, there are two ISO registrars for certifying ISO 21001 in India, so the process may have started.

The ISO standards' position as a truly international and openly available option may lead to a new quality assurance model centered on ISO. I covered several scenarios for how ISO and accreditation may co-exist in my article ISO Alongside, Instead, or Inside and in a prior edition of this report in Beyond the painted mess of education quality.

Academic Bank of Credit (ABC)

Another leading idea in the NEP is the Academic Bank of Credit (ABC). ABC essentially is an academic credit bank account that permits registration of academic credit using a centralized repository model.  The idea allows for greater student mobility across institutions. One interesting feature of ABC is its use of a national digital repository, DigiLocker, for digital documents. Digitization of academic credentials will drive greater consistency across institutions.

There will be a need to reconcile academic credits internationally for the ABC

If the country truly wants to expand its higher education net internationally, India will inevitably face the need to reconcile the ABC norms and standards with international credit recognition. Similar to institutional quality, there will be a need to embrace recognized international standards for academic credential recognition. Current accreditation models do not address this need squarely. Again, ISO could play a role in this. ISO 17024:2012 “Conformity assessment — General requirements for bodies operating certification of persons” could be adapted to fit the higher education standards as has happened with ISO17021-1. This would take action by the ISO technical committee working in the higher education area. The extension is logical, given the committee’s work at the institutional level.

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Faculty research - creating collaborative impact

Many conversations with faculty at the various universities I visited focused on faculty research and scholarship. In this area, we identifed a needed paradigm shift towards teamwork and viewing research as something other than climbing a tenure ladder.

Meaningful research is important in academia to advance knowledge and ensure that what we teach is actually relevant. A challenge discussed in many of the meetings is that research in the real world is not a solo act. Any R&D department in a research-driven company is a team act. That is often not the case in higher education, with faculty promoting themselves as lone ranger research stars.

Yet, nearly all doctorally qualified faculty in social sciences and management disciplines start their research journies with a solo act called a dissertation. They then move on to the tenure treadmill of trying to publish in “ranked” journals in what is often another solo act. The system generates a lot of activity, with little of it creating a meaningful impact on the world. It is akin to navel-gazing. How can we change this?

Research collaboratives are needed to develop ideas and management that matters

One approach we discussed and will test over the coming months is a research collaborative focused on developing ideas and management approaches that matter rather than chasing citation rankings in a publisher’s database. The idea is to follow agile principles of setting a theme and developing ideas and a body of knowledge around it. We intend to support the effort using a worker cooperative structure in EduPartners.coop.

A research collaboration is not a totally new idea, but we hope it can be improved with the assistance of resources from the co-op. Updates on this model will be covered in later editions of the Ex4EDU.Report. If you want to know more about the concept, post a message as a response.

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The 4th Turning and Climate Change — 4, 1, 3

A key aspect of my time in India involved speaking at two sessions at the AIMS conference and the opening convocation of ASBM University. My message centered on three numbers: 4, 1, and 3. It is not a mathematic puzzle but points to key developments that will shape higher education over the next decades.

At nearly every conference with some aspect of future gazing, there is talk about the pace of change. Often there are statistics equating the speed of change with growing terabytes of data, which is not really a meaningful equivalence. The ideas I sought to bring across with the 4, 1, 3 title of my speeches was that we need to look at the level of change (society), where we are at cycles of change (major system transition), and what will be the defining background (dealing with climate change).

The number 4 is meant to reference the concept of The Fourth Turning, a book written by William Strauss and Neil Howe at the turn of the millennium in 1997. The basic idea is that post-enlightenment history has tended to evolve through ~80-year recurring generational cycles or increments. Within each cycle, four generations leave their footprints on the world in strikingly similar patterns in all of the 80-year cycles. 

As noted in the sequel, The Fourth Turning is Here, Neil Howe details how modern society is now turning from period 4 of the cycle, which began after World War II, to something new. The 4th to 1st period transition is typically very tumultuous, filled with crisis, and results in new societal and economic structures. The post-World War II era began with laying the foundations of a rules-based world order based on international organizations, global trade, and a move towards economic integration. We are again at a similar turning point.

The number 1 points to the start of a cycle. The post-WWII international order is rapidly collapsing before our eyes. The first 20 years of the current cycle likely started around 2007, according to Howe. The two dominant generations for this part of the cycle have different names, such as the Millennials or Zoomers. In the Fourth Turning generational concept, these generations are the ones that provide the energy for new structures and rules. 

Today's students in higher education are the generations who will define the new world order.

The number 3 points to what perhaps will be the most impactful and definitional aspect of the next 80 years – climate change. The idea of “3” relates to avoiding a 3-degree Celsius rise in average global temperatures. The post-WWII global model is rapidly driving the world toward a 3-degree Celsius temperature rise. A climate warmed to that level will completely break down and destroy the global systems of commerce and societies built since the 1940s. 

Today's students in higher education are the generations who will define the new world order. Rather than equipping them to optimize organizations for the old order, higher education must adapt to imparting knowledge, teaching skills, and fostering abilities for the future. This should be a wake-up call for us in higher education.

A 3-degree climate risk will define the next generational cycle

The message to students was that their future will be defined by adapting to climate change and trying to avoid the 3-degree future. As aptly described by Peter Ziehan in his book The End of the World Is Just the Beginning: Mapping the Collapse of Globalization, globalization as we know it today will be largely gone within a decade. Climate change may make it happen sooner. The working lives of students now in the classroom will be consumed more by adapting and coping with climate change than by looking for clever ways to play the game of post-WWII globalization.

We only fool ourselves and students if we do not recognize the looming challenges. Teaching students to optimize yesterday’s world tomorrow will be seen as a sad story of failed education. 

We have to do better.  The challenge is significant. It requires rethinking what we teach, how we teach, and where we teach. 

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About the Ex4EDU.Report, Student360.Report, and EduPartners.coop

This report is offered as a free-of-charge contribution by Lone Tree Academics, LLC, an educational services company focused on enabling excellence in higher education. Our services are focused on excellence-based practices for the development of institutional and program strategies, crafting engaging LearningScapes™, and developing programs of the scholarship of teaching and learning.

Another report we offer is the Student360.Report, which focuses on more granular topics of educational design and delivery. It also is offered as a free-of-charge contribution.

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A recurring theme in academic institutions is how to and how often to review the quality of academic offerings. Too often, reviews occur only when there is an external driver, such as licensure, authorization, or accreditation. If there are other periodic reviews, the structure is frequently an ad hoc mixture of curriculum, market trends, and external factors.  In our experience in working with dozens of higher education institutions, program reviews range from trivial broad-brush examinations of curriculum to overly complex market studies.

In working with a number of institutions in several countries, it has become clear that program reviews need a consistent structure and tempo. The following model, which is termed “CLAS,” has been developed in a way to allow actional insights yet avoid the extremes of a trivial surface-level analysis or diving into the details of teaching that are best left to faculty.

Avoiding confusion with education market analysis

An academic offering, be it an entire degree program, a course within a program, or a stand-alone certification course, exists within a competitive context. The analysis of the competitive context is a key part of a program review but will look different depending on the type of program and its competitors.

For example, a degree program in many areas will have not only direct peer competitors but also a growing number of certificate programs that are substitutes. One study that we recently completed in healthcare identified over 100 certificates in healthcare-related topics. There is a similar plethora of offerings in information technology, management, and services occupations. Credential Engine, an aggregator of certificate and credential listings, lists over 967,000 credentials on offer in 2021 in the United States alone.

A labor market and competitor analysis is often helpful for a program review but should not be confused with the core purpose of a program review, which is more around the performance of the academic program at delivering intended outcomes or results. The skills, tools, data, and analysis methods needed for meaningful competitive market analysis are highly specific and best sourced from a specialized provider using specific data analytics skills.

Many of the program reviews we have supported have included a separate market analysis using the real-time labor market and trends datasets from Lightcast, which has an extensive labor market and education institution dataset. The data analytics skills needed to deliver a meaningful market analysis, however, are very different from the needed analysis in reviewing the effectiveness of the curriculum. 

The CLAS Model

The CLAS program review model focuses on four areas: curriculum, learning interactions or Learningscapes™, learning assessment, and the scholarship of teaching and learning. The model is shown in the diagram below. The four areas clarify actionable strategies once the program review is complete.

The essence of program quality can be effectively examined by reviewing the key instructional elements of the CLAS (curriculum, learning interactions, and assessment/evaluation of learning). The CLAS model also includes a review of the scholarship of teaching and learning (SoTL) to gauge how an institution has focused on improving program design and delivery. Research can also be a part of the instructional elements in programs that contain activities such as a thesis, summative project, or dissertation but is distinct from SoTL.

CLAS described

The following discussion with provide a brief description of each of the areas of the CLAS model. Each area will be explored and discussed in future posts in the Student360.Report. Feel free to subscribe to that publication for updated content.

Curriculum

Developing an idea of what should be in a learning encounter can be described as a curriculum. Think of it as the architecture of an academic program or course.  The curriculum serves as a plan for engagement in a teaching and learning process. As with any plan, it will not survive unadapted upon contact with the learning situation. 

Typically, the elements are captured in five categories, as described below.

• Purpose or aims. A program or course description that sets out the essence of the scope and rationale of the learning unit(s).

• Learning objectives. Stylized statements of what will be learned. Objectives are often stated using language relating to knowledge, skills, or abilities that students will acquire.

• Resources. Learning resources often include written materials – books, articles, readings – databases, software, etc.

• Learning activities. An overview of how the learning will be delivered, such as through classroom lectures, assignments, group meetings, etc.

• Assessment or evaluation. A plan for how the outcomes of learning will be determined.

There are many models for curriculum elements using rubrics, checklists, and components. In higher education, there are several well-known models of curriculum development. Those models include Backward Design, Understanding by Design, ADDIE, Community of Inquiry, Universal Design for Learning, etc. To name just two, Quality Matters and the Online Learning Consortium provide guidance for online course content.

The plethora of models illustrates many ways to develop the key elements in a curriculum. Almost any of the models can be used to unify and focus efforts. Ensuring consistency of approach to design is more important than picking the perfect model.

LearningScapes™

The idea behind the term LearningScapes^TM is to describe the totality of how teaching and learning take place. The idea is similar to the servicescapes model first developed by Mary Jo Bitner in the 1990s, beginning with her article Servicescapes: The Impact of Physical Surroundings on Customers and Employees. 

LearningScapes^TM may seem deceptively simple but involves many layers to evolve beyond the servicescapes idea of the physical environment. A learning environment in today’s world includes the interaction of the teacher and student, the learning process, and an ever wider range of technologies available to facilitate learning. I have used this approach to examine the impact of place or space in change management. The presentation is titled Designing Place and Space as Elements of Effective Change and introduces the idea of 3PT for people, process, place, and technology. 

As with curriculum approaches, many models guide the design of LearningScapes^TM. Concepts such as problem-based learning, challenge-based learning, and experiential learning are often used to design learning interactions. A decision to adopt any one of these approaches will drive elements of curriculum design. It is important to ensure that the curriculum aligns with the approach to learning design.

Assessment

With the issuance of ISO 29992:2018, Assessment of outcomes of learning services — Guidance, additional clarity has been brought to the definition of assessment with the following definition:

“assessment
test, examination, observation, or other process, designed to measure an examinee’s knowledge, competence, or performance in a defined area against specific reference points or standards (educational or professional).” (ISO 29992:2018, § 3.1).

The first line of confusion avoidance is to determine the level of focus. Significant differences exist in evaluating the success of a course, an academic program, or an academic department or institution. Effective assessment plays an important but different role at each level.

Once the focus level is determined, different ideas can guide the tools and techniques used. Typically, differences develop at a program level between internal and external and at a course level with direct vs. indirect techniques. Assessment is also seen as formative or summative.

A recent edition of the differences was developed in the Student360.Report in the article The AI imperative - A clear need for systematic assessment. 

SoTL - The Scholarship of Teaching and Learning

Reasearch supportive of an academic program has two primary dimensions. In research-based institutions, a valid and helpful focus is on advancing knowledge in the program's subject matter. Research output is often measured in numbers and types of publications in preferred journals.

A second type of research focuses on developing effective teaching and learning methods. This area was identified as one of four domains of scholarship by Ernest Boyer, who was the president of the Carnegie Foundation for the Advancement of Teaching at the time. In Scholarship Reconsidered: Priorities of the Professoriate – both the 1990 original and the 2015 update – a distinction is made between and among research based on whether it seeks to make an original discovery, apply existing knowledge, integrate existing concepts, or support more effective teaching and learning. 

The Scholarship of Teaching and Learning, or SoTL, is often seen as underserved yet challenging. SoTL is an essential part of whether teaching approaches can improve and, very importantly, address the different needs of new generations of learners, new technologies, and new ways of learning. Perhaps we need no further examples than the turbulent changes and adaptations occurring during the COVID-19 pandemic. Institutions with a strong culture and practice of SoTL pre-pandemic would logically be better positioned to manage the various pivots and challenges.

Centers for teaching and learning often address the need for scholarship in this area. Institutions and programs are well advised to clearly integrate the work of these centers, where available, into instructional design efforts. The International Society for the Scholarship of Teaching and Learning is an umbrella organization providing support and thought leadership for the subject.  Overall, SoTL should be seen as a key process and quality improvement method in education.

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Using the CLAS framework

The CLAS framework provides a set of four containers or areas to ensure a full, complete, and systematic review process for academic programs. Embedded in this program review model are a curriculum review, analysis of the learning approaches used, clarity on the role and outcomes of assessment, and ways to use the information to improve.

The CLAS framework can be applied at an academic program level, to a set of courses, or even to an individual course. The elements will be changed depending on the level of analysis.

The CLAS framework is best not to be confused with the various types of market needs analysis or program success monitoring. Those areas are important companion analyses to a program review but require different data and analytical skills. 

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About the Ex4EDU.Report

This report is offered as a free-of-charge contribution by Lone Tree Academics, LLC, an educational services company focused on enabling excellence in higher education. Our services are focused on excellence-based practices for developing institution and program strategies, curriculum design, and engaging LearningScapes™.

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This is a conversation space in the Substack app that I set up exclusively for my subscribers — kind of like a group chat or live hangout. I’ll post short prompts, thoughts, and updates that come my way, and you can jump into the discussion.

To join our chat, you’ll need to download the Substack app, now available for both iOS and Android. Chats are sent via the app, not email, so turn on push notifications so you don’t miss conversation as it happens.

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1. Download the app by clicking this link or the button below. Substack Chat is now available on both iOS and Android.

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2. Open the app and tap the Chat icon. It looks like two bubbles in the bottom bar, and you’ll see a row for my chat inside.

3. That’s it! Jump into my thread to say hi, and if you have any issues, check out Substack’s FAQ.

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Lean startup evangelist Steve Blank uses the term “innovation theater” to describe why many corporate innovation efforts flop. The theaters have all the decorations of an innovative environment without any real innovation. The myth is that activities such as design thinking courses, innovation workshops, hackathons, and the like, will allow innovation to appear magically. Blank concludes it is just a theater act.

Like it or not, there is a similar process happening with entrepreneurship education. Perhaps the high failure rate of startups, often touted at 75%, should serve as a warning sign that what is done does not work. Further, a study in 2017 analyzed over 3,500 startups across four countries and found that none of the commonly prescribed “essential activities” of incubators, including those nested in universities, were necessary for the successful emergence of new ventures. Walk into any university startup incubator, and one of the prominent parts of the space will be a special place to do “pitches” to venture capital investors. Seems like we have entrepreneurship theater, doesn’t it? So why does this theater persist?

First, entrepreneurship education in higher education is a big business. By the turn of the 21st Century, one study reported in the U.S., there were more than 1,600 colleges and universities offering 2,200 courses in entrepreneurship. By 2013, a Bloomberg article estimated 400,000 students had taken classes in entrepreneurship. Getting a donor to fund an “entrepreneurship” program is a natural sell, even if the program is just theater.

Second, large corporations are disrupting the historic “business education” with internal learning and development or certificate programs. The gravy train of historic university business programs is under threat. Something new and cool beyond the tired disciplines of traditional business education is emerging.

Last, there is a bit of chasing a shiny object. Business programs can often look like the cat chasing a laser pointer on the floor. If you doubt this, do a quick search on “digitalization strategy” among business schools. Sure looks a lot like a rebadging of business process re-engineering of the 1990s!

So, what’s a better approach? To start with, entrepreneurship should be seen more broadly.

A broader view of Entrepreneurship

Always the sage, Steve Blank again provides some ideas here. He defines six types of startups, or essentially six forms of innovation. Those are briefly described below, with some added perspective beyond Steve’s deep roots in the tech sector.

• Lifestyle entrepreneurs. Folks that want to enjoy life and not be tied to working for someone. In my part of the world, Colorado, these folks might be freelance ski instructors or white water rafting guides. They have a passion for what they do, not for an employer.

• Small business entrepreneurs. These hard-working souls start and run local restaurants or dry cleaners, ply skilled trades, or provide personal services. The goal is to feed the family, not conquer the world with some hyper-growth business to be cashed out with VC millions. We find these businesses everywhere, not just in the money-fueled innovation clusters. They are also the true backbone of our economies.

• Scalers. Some business models have the potential, often driven by technology with rapidly declining unit costs, to make it big and even globally. One could even believe that a startup such as Substack (the platform used for this newsletter) fits that description. These firms often enjoy the benefit of venture capital investment. But, they are a distinct minority of innovative organizations.

• Innovation farms. These companies exist to develop a product and service and later sell out to a larger, cash-rich company in need of innovation. The goal is not to build a sustainable company enduring for decades but to find a pathway toward a rich cash-out.

• Large company innovators. Some larger companies do innovate and do so quite well. Economic sectors with large up-front innovation challenges, e.g. chemicals, pharma, advanced manufacturing, etc., are logical places for such innovation. A descriptor often used for such efforts is “intrapreneurship.”

• Social entrepreneurs. For these organizations, the idea is to make an impact, both with the area of focus and how the enterprise is organized. Some of the very interesting developments in this area revolve around the use of cooperative forms of organizing. For example, limited cooperative associations, allowed by Colorado and California, provide an innovative structure to attract investment and allow cooperative ventures to scale beyond the limitations inherent in traditional customer or worker cooperatives.

This breadth of entrepreneurial models clearly spotlights how many entrepreneurship programs at universities are misguided.

The ritualistic and almost religious focus on “pitching” for venture capital focuses only on very few entrepreneurial types. Such misguided focus neglects the clear majority of entrepreneurial organizations. We should do better!

Chasing shiny objects in entrepreneurship theater

An interesting aside about an entrepreneurial journey came from a recent founder session hosted by the IMD Alumni Community for Entrepreneurship. The entrepreneur described the adrenaline rush from the hyped VC process of moving from seed stage to early stage, funding rounds, and the excitement of cap tables and term sheets. All of this is the stuff of very few entrepreneurial companies. Ultimately, this entrepreneur joined the majority of startups by going through the pain of being the last person who had to turn out the lights when leaving.

One could argue that focusing entrepreneurship education on VC-fueled adrenaline rushes is, at best, chasing shiny objects. At its worst, it causes the destruction of value for many aspiring and potentially successful entrepreneurs. Moving beyond this trap requires coming back to what is the core of entrepreneurship. That core should not be confused with funding. It is something far more important and profound.

The “red thread” of entrepreneurship

The “red thread” is often considered the key unifying theme of activities. In the broader entrepreneurial space, such a thread involves combining innovation with collaboration. This can be termed collaborative innovation.

“Collaborative innovation” combines the ability to innovate with capability to involve others.

Innovation without the support of others goes nowhere. Collaborating for the sake of itself is often frustrating and described as being on a sailboat without a rudder. Both are needed.

Innovation is the spark that can light a flame of advancement. Collaboration allows the spark to consistently set things aflame and harness the power of an innovative fire. Both are needed and must work synergistically.

Following the rituals of pitching as the core of entrepreneurship education will not deliver this unique synergy. Entrepreneurship education needs to move beyond just learning to grovel and pitch for scraps from the king’s table. A much more innovative and involved entrepreneurship educational approach is needed.

Changing what and how we teach in entrepreneurship

It should be clear that cap tables and term sheets are not at the core of entrepreneurship. Nor are all the activities of writing business plans, populating business model diagrams, or human resource management.

Collaboration and innovation brought together are the real core or the red thread of success. How can entrepreneurship education programs deliver on this key need?

There are some guiding lights on how to combine collaboration and innovation in entrepreneurship.

The best choice seems to be combining experiential learning with a healthy dose of metacognition (i.e., knowing how we know what we know). Two examples that stand out are the approach taken by the Team Academy, first started in Jyväskylä, Finland, in the early 1990s and since spread to multiple locations across the globe, and Kaospilots, which started in Aarhus, Denmark, over 30 years ago, and since has been replicated in several locations.

Both will be described in depth in future installments of the companion newsletter, Student360.Report. To round out the current discussion, however, a brief mention of how the key elements of each program support collaborative innovation follows.

The approach taken by Team Academy relies heavily on sharing and reflection. Dialogues called “fertilizations” take place twice a week. The sessions support students in creating their own enterprises based on shared experiences and knowledge. Rather than a sage on-the-stage lecture approach to entrepreneurship, students are tasked with self-organizing and reflection as they build their businesses. This one key aspect of Team Academy demonstrates bringing collaboration to the core of learning and building strong metacognition.

Kaospilots demonstrates a highly evolved approach to driving innovation through learning space design for collaboration. The space, called the “HIVE,” was a co-working space before co-working was known to the world. What differentiates the HIVE from most co-working ideas is that the space is designed and used in “frames” built to foster innovation. Innovation is supported by the built environment and the often unplanned interactions in an open innovation space.

The short description of these two guiding lights should lead to reconsidering how most entrepreneurship education occurs. Both programs can serve all types of the six entrepreneurial patterns described above. Their reach and benefit extend far beyond teaching students to pitch for capital when most will never be in that position.

Upcoming editions of the Student360.Report will take a deeper dive into the components of these programs.

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Student360.Report - Affecting the affective online

The next installment of the Student360.Report will look at how a behavioral modification education program offering in-person training for over 40 years successfully went totally online in one of the most challenging areas of change—personal nutrition and health. The approach has allowed substantially lower costs while increasing reach and enrollment for this life-changing program.

Ex4Edu.Report - The destructive myth of job-ready graduates

A future installment of the Ex4Edu.Report will examine how the idea of “job-ready graduates,” often bandied about by business schools and employers, is counterproductive in light of rapidly changing industries and jobs.

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Suddenly ai or artificial intelligence seems to have become a major cause of concern in higher education. A few months ago, discussions emerged in many academic groups about the wonder of an artificial intelligence (ai) tool, ChatGPT, that could even write a student paper. A recent search of New York Times articles netted 10 recent articles on ChatGPT, beginning in December 2022. The Washington Post topped that number with 23 articles over a similar period. Higher education news sources also had coverage. For example, a search of Inside Higher Ed turned up around 15 articles.

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ChatGPT is not the only ai application impacting education. Notion is a collaboration space that many academics and students use to organize work. The application now has ai in alpha with functions for writing or even some coding.

Despite the recent attention and hand-wringing over “the end of education as we know it,” the future may not be so bleak. Will ai totally disrupt education? Probably not. To get past the hype, we need to think holistically about ai in higher education.

Riding out the hype cycle

The Gartner Group is one of the leading thought leaders in tracking technology trends. One analysis that Gartner publishes is called the “Hype Cycle.” The cycle plots technology over time, looking at five stages of diffusion, starting with an innovation trigger and ending with fully productive technology deployed in the mainstream.

As Gartner notes, technology goes through a hype cycle before moving into the mainstream

In late 2022 Gartner published an updated hype cycle for artificial intelligence. What is telling about the latest analysis is that most ai applications are poised to enter the “Peak of Inflated Expectations,” which is followed by the “Trough of Disillusionment.” The positioning of the bulk of ai technologies in this part of the hype cycle is telling.

We’ve been here before—chasing the hype.

Education and higher education are not immune from jumping on a hype cycle with new ed-tech technologies. The benefits of learning management systems and “online learning” were overhyped at their introduction around two decades ago. Then, of course, there were the stories of how MOOCs were poised to displace the entirety of higher education.

Even ed-tech funding groups chase hype.

Recently, I was in conversations with an ed-tech incubator group in the U.S. We had submitted a proposal focused on supporting faculty through ai technologies to develop dashboards for academic coaching. The proposal was ultimately not funded, so we asked why. The answer amazed us. We were told that our proposal was not for an ed-tech “gadget” and thus was “not the right type of project.” We had made the “mistake” of involving “humans” paid a salary in the model to interpret data and work with students. We were amazed at the answer, but it illustrates how even funding sources follow hype cycles by chasing technology for the sake of technology.

To make sense of what ai may mean for higher education, we need to pull back from the hype and think of what may be some actual benefits.

Thinking constructively about ai in higher education

Professionals designing and delivering educational curricula can be hostile to new technology. As far back as refusing to allow pocket calculators, educators had looked to the past when developing courses. The resistance to change did not stop with calculators. It continued through areas as recent as opposing e-books, attempting to suppress mobile technologies in classrooms, and making wild claims that online learning could never match in-person classes. We need to move beyond technophobia and actively look for ways ai should be a part of designing what is taught and how students learn.

Technology amplifies what we do, whether it is good education practice or not. If the learning interactions are effective and engaging, technology accents the positive elements. If, however, learning interactions are boring, ineffective, and hapless, technology will make things even worse. If anyone has watched traditional faculty trying to replicate boring in-person lectures in Zoom meetings, the effects of technology amplification should be evident. When looking at the potential of ai, new opportunities should be leveraged to enhance learning interactions, not just automate existing practices (and end up amplifying what is wrong with them).

Looking at ai with a growth mindset is critical to leverage its potential in education.

Many articles decrying ai point to student papers written by tools such as ChatGPT as creating a snake pit of student cheating. Those same articles fail to note the positive and helpful use of ai is already in place. Tools such as Grammarly, Turnitin, and FeedbackFruits already use ai to assist with improving writing, checking for plagiarism, and providing rapid feedback. Ai can support and enhance a growth mindset of improvement and move beyond the outdated fixed mindset of “correcting” student work.

We think too narrowly about the nature of education.

Focusing on ed-tech or ai as a new “gadget” also neglects the reality that education is essentially a social matter. We learn and improve by relating to others, imitating others, and engaging in dialogue. Done right, education can be thought of as a societal version of the scientific method. Education should first look to explain what works and what does not and then spread that knowledge.

Ai done right can support and enhance the social nature of learning. Also, one of the exciting facets of education today is learning about how we learn or meta-cognition. Ai can support this society-wide version of the scientific method.

There are many difficult-to-solve issues in need of grounded solutions. Attempts to understand such issues are often made in isolation of siloed institutions. This isolated learning is often followed by a parochial approach to teaching what a teacher knows as “the truth.”

Ai, with its broad reach across internet resources, can become a bridging or meta-technology to move beyond parochial approaches to discovery and teaching. The speed of machine learning can also help tackle the tendency of education to address problems too slowly.

Decidedly different approaches to learning are needed to cope with and leverage ai. We need to look at what we teach (curriculum), how we teach (learning interactions), and how we are convinced that learners have learned (assessment). The power of ai points to the need to learn how to navigate knowledge rather than teach students as they are just a storage container of facts and figures.

Leveraging ai as a new ed-tech platform.

As noted above, ai is already in use in many ed-tech platforms. It already helps students rapidly improve writing through instant formative feedback. reasoning, and retention of complex concepts. It’s time to expand those uses and look for more.

Beyond current uses, technologies such as adaptive learning could see a major boost with more rapid adaptation. For example, tools such as Area9 Lyceum’s adaptive learning Rhapsode platform already offer highly advanced adaptive learning approaches. The addition of ai tools could allow more rapid, evidence-based adaptation of the learning materials.

The power of rapid adaptive learning also allows a course correction to avoid confusion, learning the wrong thing, or just abandoning learning. Ai could accelerate and enrich the process.

Closing note

In sum, it’s time to embrace and leverage new technologies rather than react too narrowly or with unnecessary resistance.

As a quick note, this article was not written by ChatGPT, should someone want to know. The tools of Grammarly, an ai-assisted writing tool, are used as I author these pieces. What may happen, however, is that this article on ai tools may end up sampled by ChatGPT and end up in a future ai-written article on the topic.

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If you enjoyed this content, please forward it to others and feel free to leave a comment. Please also jump over to Student360.Report for the next article on holistic assessment. In that article, we will explore how we can know what our students actually know and learn. As a hint—it’s more than tests and exams!

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In the past three years, higher education globally has survived epic disruption and change. The sector has moved from pre-Covid business-as-usual, through a pandemic remote-learning pivot, and now to the post-pandemic realities challenging nearly every aspect of the existing ways of working. A sector that takes pride in its slow pace of change is discovering that gradualist change is not enough. Facing existential disruption from changing generational demographics, unstable employment markets, and EdTech 3.0+ will require a different orientation.

Going forward into 2023, the focus of our two newsletters—Ex4Edu.Report and Student360.Report—will be refined yet remain with the purpose to support navigation of the changing world of higher education.

The Ex4Edu.Report will focus on significant trends and events at a macro level that impact the sector’s viability and ability to deliver value. The guiding idea is navigating change rather than attempting to manage unmanageable change. Understanding how to navigate change is one of the “5 Disciplines of Highly-effective Organizations” observed through years of observing and working with role-model, resilient organizations. The Ex4Edu.Report will focus on identifying and interpreting key trends from the viewpoint of how to navigate change effectively in higher education.

The Student360.Report will concentrate more on the nuts and bolts of delivering value from a student-lifecycle optic. The emphasis will be on good practices in designing, delivering, supporting, and evaluating learning in higher education. The term “good practice” is intentional and avoids the pitfalls of notions such as best practices—which are, in reality, mythical—and confusion of one-off successes—something that works in limited surroundings—with real solutions fit for multiple settings and cultures.

Both newsletters will remain free of charge for now. Our development of a cooperative venture in 2023 could lead us toward new, specific levels of subscriber content. The more specific desires and needs of those joining us in the co-op may suggest paid tiers as we co-create our economic model. Information will be provided as the developments unfold.

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We also plan to develop expert chat sessions—using the new feature of Substack—once we develop a sufficient subscriber base. For now, please enjoy the content of one or both newsletters. And, of course, your helpful comments on the topics posted are genuinely appreciated.

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Higher education as we have known it post-WWII, is reaching an inflection point. In places such as the U.S. and Europe, a demographic drought represents drastically declining enrollments. Estimates vary for when the system may drive over the cliff from “it has already happened,” to 2028. Highly populated countries such as China and India, counting on “demographic dividends” with young populations to provide a springboard into a knowledge-based economy, are discovering the realities of too many graduates for too few jobs. All of this does not mention the costs-out-of-control issue for many parents, students, and graduates.

Imbalances in higher education models, decades in the making, is more important than ever with estimates of 75% of new jobs requiring post-secondary or tertiary education.

The bigger picture issues of higher education institutions being adrift are well-known and documented. The existence of professional sports teams masquerading as college sports, universities profiting from massive regional medical systems, and what are essentially investment funds operating under the name of university endowments all call the form of modern universities into question. The solutions offered by many critics often amount to blowing up the whole system with disruptive restructuring or the allure of the next educational technology as the solution for all problems.

In this essay, a different approach from top-down restructuring, rationalization, or Wunderwaffen technologies is suggested. Instead, the thesis of the approach is to use democracy as the core of higher education. The model is one of the re-imagination of higher education as a grouping of hybrid cooperatives. What do we mean by a co-op in higher education? Do such things already exist? How might they work in practice? Let’s answer those questions.

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What is a hybrid cooperative?

Cooperatives or “co-ops” have been around in their modern forms since the first worker-owned varieties in the U.K. in the 1840s, designed to mitigate the harsh conditions of early capitalism. Most of us, if asked to name a co-op, would end up pointing to a customer or consumer co-op. There are hundreds of co-op food stores in most modern economies. In Switzerland, two customer-owned co-ops—Migros and Co-op—have consistently held more than 70% of the food market for decades. The U.S. has a plethora of electrical distribution co-ops dating to the New Deal electrification projects. Credit unions, as a form of financial co-op, started first in Germany in the 1800s, round out the frequent top-of-mind consumer co-ops.

The original co-ops were frequently a mixture of producers (workers) and consumers, not just customers. The evolution of the model has come to include a full range of models spanning the entire value chain of different economic activities and involving sharing of ownership by workers, householders, purchasers, and marketers. As it might be used in education, the idea of a co-op should not limit thinking to that of a consumer co-op.

The original co-ops were frequently a mixture of producers (workers) and consumers, not just customers. The models have further evolved to support all types of businesses and organizations.

Hybrid models of co-ops have emerged and can address the complex processes in an educational institution. France authorized a multi-stakeholder co-op in 1982 as the SCIC —Société coopérative d'intérêt collective (co-operative society of collective interest). SCICs can include different groups of owners, called colleges, that vote separately. U.S. states such as California and Colorado have authorized limited cooperative associations (LCAs), which allow an investor class of members with differing governance rights from the typical one-member, one-vote model. Platform co-ops, built around sharing on a digital platform, allow hybrid member types for producers, consumers, and artisans. Resonate is one such co-op operating in the music streaming sector.

The models for a co-op are certainly sufficiently robust to support organizing a higher education institution as a co-op or series of co-ops. So, has it already been done, and if so, did it succeed?

Yes, there are co-ops in higher education!

The use of co-ops in higher education can occupy a spectrum from the whole university as a co-op, to middle-ground areas such as support services, to using co-ops as a way to teach participatory management. Robust examples already exist.

The university as a co-op

Mondragon University in Spain has operated as a co-op university since 1997. In total, the university has over 5,000 students. It was formed by joining three existing “faculties,” engineering, business, and humanities, into a single university. Gastronomy was later added as a fourth program focus in 2011. Degrees are offered at the bachelor’s, master’s, and doctoral levels.

Democratic decision-making permeates the university with its cooperative structure. Key leadership positions are chosen by elections, representing the votes of co-op members. Compensation of the workforce is transparent and based on job type and skill level. Mondragon is a private university and thus enjoys more freedom of action than some publicly funded universities. The following example shows how co-ops can be installed even in public entities.

Ed co-ops for shared services - EDUSOs

Another potential model, suggested by the Minnesota regional co-operatives used in K-12 education, might be shared services organizations for multiple institutions. How this might work in practice could be guided by what has already happened with U.S. credit unions banding to form “credit union service organizations” or CUSOs. Authorized since 1934, CUSOs often fill gaps in lending products, customer service, or financial systems. The over 1,000 registered CUSOs in the U.S. illustrate the viability of this model.

EDUSOs or “education service organizations” could serve a similar role to that of CUSOs. These organizations, modeled after producer co-ops, could help smaller institutions pool resources and avoid expensive alternatives such as online program managers (OPMs), which often extract 50% of the tuition paid as the price of services.

Using co-ops to teach participatory management

The University of Applied Sciences in Jyväskylä, Finland, provides a different illustration of how co-ops can be used. The University’s entrepreneurship program, called Team Academy, features student team cooperatives as a part of its bachelor’s program. Students form the co-ops in the first year of their studies and then manage the companies over the duration of the degree program. The co-ops are an essential part of the curriculum and are used to foster education in a new way of non-hierarchical management. The Team Academy program has been replicated in multiple settings through a network of affiliated institutions.

Making co-ops work in modern higher education

The modernized legal forms of cooperatives such as the limited cooperative associations (LCAs) allow a more participatory, democratic way of doing business to be the basis for how higher education works. Options could run the gamut from whole universities recasting themselves as cooperatives to embedding the ideas of co-ops into the curriculum.

These models allow students and the workforce to sort out the offerings and administration through a one-person, one-vote governance system. The additional advantage of LCAs is that investors are allowed as a separate type of co-op member with limited voting rights.

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Higher education is in a state of flux. Although the stories differ among global regions, the stresses of falling new student counts and challenging placement rates are evident.

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Recent events suggest that a fire is smoldering below the surface with the adjunct faculty model. Articles describing strikes at The New School in New York and other institutions such as the University of California paint an interesting picture. The New York faculty reportedly earn $4,000 per course. At this rate, adjunct faculty would need to teach 14 courses per year to reach an average salary in the city, hardly a manageable workload.

It’s even worse at other institutions where the pay per course is often half of the amount reported above. According to studies by The New Faculty Majority, adjunct or contingent faculty are at least half of the total higher education faculty.

Taken together, the situation paints a picture of a highly-educated, underpaid, and over-worked workforce attempting to educate the key workers in tomorrow’s economy. This does not point to a positive future.

How did we get here?

The wave of using adjuncts began around 40 years ago and is no accident given the demographics of the time. At that time a large and well-educated generation, the Boomers, was entering the workforce. Many wanted higher education to advance their careers. The corporate penchant for downsizing and pay reductions also meant that there was a workforce looking for a side gig to fill the gap. That is changing.

More than anything, demographics may foretell the end of the adjunct model.

The successor generations to the Boomers are better educated yet have less economic mobility. For the Millennials and Gen Z, faith in higher education as a ticket to wealth and economic mobility has been broken by a succession of economic crises. Thus, the demand for higher education is falling.

Furthermore, corporate downsizing has moved on to the next phase to create the gig economy, where the side gig is now one’s entire job. Low-paying adjunct teaching may not be even as attractive as being a food delivery person or a YouTuber. The supply of eager adjunct faculty is lacking.

Being in the wrong 1%

A few years ago, I was teaching as an adjunct at a well-known national university. Over the years of my teaching, the number of students in my classes had steadily increased but my pay had not. There were plenty of reasons such as that ed-tech had made my job easier. Hardly!

At the time of teaching my last course with this university, I did a simple math calculation to compare the tuition paid by students for the course to my pay. The calculation showed me that I had arrived at the 1%, but not the one we might hope for!

The exclusive 1% group I had entered was that my pay was 1% of student tuition. My expensive advanced degrees and decades of teaching the subject were essentially valued as a rounding error. Student acquisition cost for those students, i.e. marketing and sales, was easily 10 times my pay. Nice!

A looming crisis of credibility

Understandably, the generations entering the majority of our societies are skeptical of the economic benefits of higher education. The low pay and high workloads of adjunct faculty only confirm and contribute to this negative narrative.

An educational sector that touts its ability to unlock opportunity yet provides none to its workers, faces a crisis of credibility.

Where to from here?

Falling enrollments, a workforce demographic dearth, and the crisis of credibility of the higher education sector all point to the need for change. It will no longer be credible to invite adjunct faculty to the 1% club that I entered.

So what is the answer?

As tenure has been destroyed, unions often seek to enter the mix. Such a move will shift the balance of power more towards adjunct and contingent faculty but may face limits. Faculty often see themselves, whether true or not, as elite and are reluctant to join a union regardless of potential benefits.

The intriguing idea of faculty forming worker-owned or worker- and stakeholder-owned cooperatives.

An intriguing idea is one of faculty banding together in what are essentially self-governing worker cooperatives. Although such a move may seem far-fetched, it has actually been around for quite some time. These coops are not the corner health food store, which is a customer-owned cooperative, but places where the workers are the owners, hold the capital, and direct the enterprise.

Teacher-powered schools have been described by Jackall and Levin going back decades in their book Worker Cooperatives in America. The Mondragon Cooperative University in Spain is comprised of three worker-owned coops and has been in existence since 1997.

In Minnesota in the U.S. the Minnesota Service Cooperatives (MSC), a series of stakeholder-owned coops, provides critical services to rural K-12 schools. It has evolved to its present form in 2001.

The adjunct model existing for the past few decades is perhaps “past the shelf life” of the idea. Promising new models including worker- and stakeholder-owned coops are solutions worth examining.

Making coops happen in higher education.

States such as Colorado and California have updated coop laws to allow new forms of coops such as the limited cooperative association, which allows investors and workers to share ownership. Exploring such a solution is needed and overdue.

More on that in the coming issues of the Ex4EDU.Report.

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The end of a calendar year is often a time of reflection and thinking about future transitions. This final 2021 issue of the Ex4EDU.Report will focus on frameworks to transition to a learning excellence-focused curriculum. 

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Learner-centric excellence: A P3T transformation

Academia is replete with references to “academic excellence” or “teaching excellence” or “high-quality research.” Each of those ideas suffers under a common fallacy of leaving out learning as an if not the essential purpose of education. These common ideas of excellence misplace their focus primarily on the institution and its workforce rather than on students. 

Transforming organizations is never easy and even more difficult in traditional-bound sectors such as higher education. A framework that has proven its worth over time is the people, process, and technology (PPT) model often used by change and transformation practitioners. The addition of “place” to the model to create 3PT creates a holistic foundation for change because humans and the places they inhabit, either physical or virtual, are inextricably linked.

• People — With a move to new learning models, more automation of learning paths, and the use of technology, the traditional faculty model of “doing it all” must change. The roles of delivering content, coaching performance, and evaluating student work may be performed by multiple people with specific skills and training rather than by a solo act faculty. Support services for student success must also be attuned to the whole student lifecycle, not just classroom interaction.

• Process — A degree program consisting of stackable credentials is a very different learning process than courses offered in a traditional degree model. Semesters and terms will have less or little meaning. Sequencing and scaffolding of learning will need to take place at the micro-content level focused on competencies rather than being viewed as a part of an academic degree program. Evaluating success must move far beyond traditional grading and assessment.

• Place — The traditional instructor-centric classroom or “chalk and talk” will be replaced with hybrid online, remote, and personalized experiences. The classroom of the future will include the ability to augment in-person experiences with engaging remote and online content delivery using a whole new generation of digital facilitation platforms, devices, and technology configurations.

• Technology — Technology is shown last because it should serve the 3Ps rather than the other way around. A post-traditional degree world will rely on much more than just an online learning system as the technology platform. The use of adaptive learning tools and rich engaging multi-media will be the norm rather than a sideshow.

Learning model transformation: CLAS™

The CLAS™ model presents a full-cycle framework to describe what is needed to transform learning programs to a world where the degree programs of today give way to learning programs of the future. The acronym of the model denotes curriculum, LearningScapes™, assessment, and the scholarship of teaching and learning.  The elements are described below.

• Curriculum — Curriculum in a post-traditional degree world plays out differently. The end result will be learning pathways designed to achieve mastery of competency sets rather than the attainment of a degree. The starting point will be designing around competencies with varying degrees of knowledge half-lives. Competencies go far beyond job-ready skills and include enablers of personal and team productivity.

• LearningScapes™ — LearningScapes add the “how” to the “what” of the curriculum. The approach taken to supporting and delivering learning will vary by what is taught and to whom it is directed. Looking at learning with such an optic allows moving towards context-rich techniques such as experiential, collaborative, and social learning.

• Assessment — Notions of assessment must evolve beyond a fixation on testing. The success of learning programs should be gauged based on more than exam results. Approaches incorporating overall performance evaluation and external validation are critical to the new world of multiple learning pathways assisting learners to master competencies.

• SoTL — Academia often follows the paradox of the cobbler’s children who have no shoes. The profession is supposedly all about learning, except, it seems, when it comes to learning about learning. The inclusion of the scholarship of teaching and learning in the CLAS model is designed to ensure that curriculum, learning, and assessment improve continuously. SoTL provides a discipline of improvement that is so often lacking in the design and delivery of educational programs.

We are well past the “best-by” date of today’s academic degree model. The next evolution of higher education learning will involve changes in both institutions and what those institutions offer.  The existential challenges to today’s higher education model require acting and acting now rather than hoping for a future resembling the past.

About the Ex4EDU.Report

This report is offered as a free-of-charge contribution by Lone Tree Academics, LLC, an educational services company focused on enabling excellence in higher education. Our services are focused on excellence-based practices for the development of institution and program strategies, curriculum design, and engaging LearningScapes™.

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For more information visit www.ltacademics.com

Special edition of the Ex4EDU.Report for the SEAA Trust 14th IAC 2021

As described in the prior issue of the Ex4EDU.Report, there are many signs of pending disruptive change to the academic degree. Declining demand and desirability of current higher education products will drive change and several trends are already evident. A few of those trends having a strong impact on the future of the academic degree are described below.

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1. Focus on standards-based quality 

Institutions by and large will be a need to demonstrate standards-based quality as a “ticket to entry” to the higher education playing field. The historical pillars of quality assurance have been governmental authorization and accreditation. Both are increasingly influenced and driven by standards such as a growing list offered by the International Organization for Standardization (ISO). 

Standards allow transparent evaluation of institutional quality with a holistic view— balancing inputs, processes, and outcomes—and extending beyond the limited factors used in school rankings. The days of accreditation agencies as clubs of nobles will be over. Accreditation agencies will need to raise their game to demonstrate quality with a focus on the improvement of student outcomes and adhering to independent, verifiable standards.

2. Running on reputation 

Elite institutions relying on reputational quality and rankings will likely weather the storm better than undifferentiated offerings from under-resourced schools. Those elite institutions, however, make up a small part of the mix of higher education student populations. Using the U.S. as an example, such institutions represent less than 5% of total students as noted in an earlier edition of the Ex4EDU.Report. The public reputation of such institutions creates substantial amounts of “news” but far less impact on overall educational attainment.

Despite the limited enrollments of the elite schools, many non-elite institutions unwisely divert enormous resources into chasing university rankings to play a game of catch-up. Whether university rankings have any correlation with improved student outcomes has been called into question by research conducted at the Stanford University Graduate School of Education in a paper entitled A “Fit” over Rankings. In the end, engagement around student outcomes matters much more than rankings.

3. Unbundling of institutions

Ryan Craig’s book College Disrupted. The Great Unbundling of Higher Education makes the case that complex higher education institutions represent an endangered species. The multi-headed crises of affordability, lack of consumer confidence, and intransparent quality will provide openings to focused providers not offering the whole complex product. 

A case in point is the recent initial public offering of Udemy, which raised in excess of $400 million. The presence of such educational content and service providers is set to grow substantially and displace the markets of many higher education institutions.

4. The classroom comes to the community 

The Covid-19 lockdowns, often resulting in the almost overnight deployment of online remote learning, acted as a catalyst for a variety of online learning solutions. This trend is expected to continue and lessons will be learned about what works with online modalities will drive more targeted use of the technologies. 

We should not forget the historical reason for the gathering of scholars in a location, i.e. the university, was access to the library and having a place to conduct student meetings. The pandemic drove almost universal use of remote online learning tools and accelerated the process of getting broadband to more corners of the world. For higher education, the result will be that the classroom of the future will no longer be only at the institution but now in students’ homes and communities.

5. Alternative credentials take off 

Micro-credentials are perhaps the greatest existential threat to today’s cornucopia of academic degrees and existing higher education institutions. Credential Engine, a credential registry in the U.S., lists over 900,000 credentials representing $1.9 trillion in training expenditures, both of which dwarf the academic degree market. Credentials offer flexible pathways to learning and can be stacked or aggregated to signify the achievement of the equivalent of an academic degree. 

Assuring the integrity of credentials will itself become a business and may branch into the realms of badges and blockchain. Technology companies such as Salesforce, Google, and Mozilla’s Open Badges are on the front lines and are joined by the MOOC providers such as Udemy, Coursera, edX, and Udacity.

Any one of the trends described above signifies substantial disruption. Taken together, they point to a major shake-up and shake-out in higher education.

Some thoughts on how to rise to meet these challenges will be covered in the next issue of Ex4EDU.Report.

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About the Ex4EDU.Report

The Ex4EDU.Report is offered as a free-of-charge contribution by Lone Tree Academics, LLC, an educational services company focused on enabling excellence in higher education. Our services are focused on excellence-based practices for the development of institution and program strategies, curriculum design, and engaging LearningScapes™.

For more information visit www.ltacademics.com

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Special edition of the Ex4EDU.Report for the SEAA Trust 14th IAC 2021

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A model rooted in the middle ages

The academic degree has a long and complex history. Some scholars place its origins dating back to 1179 at the Lateran III ecclesiastical conference in Rome. The purpose of those first degrees was to grant the right to teach and interpret the Bible. 

Several centuries of changes in higher education have resulted in the introduction of a hierarchy of degrees of bachelor’s, master’s, and doctoral degrees.  In the U.S. it is estimated that there is a cornucopia of at least 1,500 variations of types of degrees. This plethora of degrees may be an indicator that time has come for a different model.

Are degrees as a concept past their “best-by” date?

When we purchase products in a shop, there is often a date on the product that says something such as “best-by” indicating the expiration of when the product can be safely sold or consumed. It may be time to ask if the current approach to degree-based higher education is past its best-by date.

The number and diversity of degrees belie a crisis of confidence in the value of higher education and increasingly the worth of a degree. Results of a survey by Third Way, a U.S.-based Think Tank, surveying over 2,000 interviews of students and caregivers suggested that only 1/3 of felt that higher education was worth the cost. 

The value of a degree is also questioned on multiple fronts. First, the cost of higher education has been increasing for decades at rates far in excess of general inflation. These increases have created an affordability problem for many students. 

Second, despite evidence to show that degrees continue to improve lifetime earnings, the added value has been shrinking when measured in terms of wealth accumulation. Research by the U.S. Federal Reserve Bank of St. Louis found that the wealth premium of university graduates declined precipitously over recent years from 247% to only 42% against non-graduates. This is likely due to the higher cost of attaining a degree, the associated debt load, and diminished earning potential.

Last, the currency or shelf life of the knowledge obtained in a degree program has drastically shrunk. The mantra of 4 years studying for a 40-year career is a relic of history. Authors Douglas Thomas and John Seely Brown in their book ​​A New Culture of Learning categorize the half-life of knowledge in university degrees as perishable skills—a half-life of less than 2.5 years,  semi-durable skills—a half-life of 2.5 to 7.5 years, and durable skills—a half-life of more than 7.5 years. The more durable tend to be soft skills while the less durable—and often more frequently the mainstay in higher education—are the technical skills. 

The declining attractiveness of university or college degrees is also reflected in what has been a decade-long fall in higher education enrollments in many countries. According to the National Student Clearinghouse Research Center, higher education enrollment in the U.S., for example, has seen two years of significant pandemic-related declines following a 10-year trend of decline. Projections by McKinsey & Co. do not paint a good picture for the future, either, with demand for higher education seen as entering a significant decline mid-decade.

These issues clearly indicate that degrees and academic programs as we now understand them may be past their “best-by” dates. There are some clear indicators of what may come next. 

Some thoughts on those trends and indicators will be covered in the next issue of Ex4EDU.Report.

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About the Ex4EDU.Report

This report is offered as a free-of-charge contribution by Lone Tree Academics, LLC, an educational services company focused on enabling excellence in higher education. Our services are focused on excellence-based practices for the development of institution and program strategies, curriculum design, and engaging LearningScapes™.

For more information visit www.ltacademics.com

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Understanding, assessing, and communicating quality are some of the most confused topics in higher education. The confusion is somewhat understandable given the wide range of stakeholders and the diversity of institutions. Although understandable, the lack of clarity is unforgivable in a sector proud of having the best and brightest. All told, it is often a painted mess.

A set of current and developing ISO standards foretell change from the tangled notions of quality in higher education.

A standards-based approach

ISO or the International Organization for Standardization is an international organization based in Geneva, Switzerland, and is the world's largest developer of voluntary international standards. Since its founding in 1947 ISO has issued nearly 24,000 standards ranging from technical standards for measurement to quality processes in a range of economic sectors.

Different types of standards focus on product or service characteristics, processes, or an entire organizational management system. Some of the best-known standards include ISO 9001, issued in the 1980s and often used in manufacturing and services industries to define quality processes. Anyone using a major internet service provider will likely encounter another commonly used standard, ISO 27001 on information security management. 

ISO 21001:2018 (Educational organizations — Management systems for educational organizations — Requirements with guidance for use), is a management system standard. That means it provides guidance for the management of an educational institution. It is not a standard focused on product or service quality or only on organizational processes. The painted mess of quality in higher education often comes in large part from thinking of quality as a product or service attribute rather than the management system supporting the delivery of quality outcomes.

Standards and the future of higher education

Higher education is at a turning point. The current model of an academic degree offered as a bundled product by an institution is near or past its expiration date. The Covid 19 pandemic only accelerated a trend towards remote delivery of educational services not tied to a specific location. 

In the near future, an academic degree may consist of several certificates stacked as components to create the needed threshold for awarding a degree. An analysis we prepared of certificate programs in the U.S. identified over 100 certificate programs in healthcare alone. Google offers numerous job-ready certificates under its Grow with Google program.

The traditional bundled model is also challenged by the rise of full-standing corporate universities. A 2013 report by the Boston Consulting Group estimated the existence of 4,000 corporate universities worldwide. This sector is poised to grow given the workforce generational changes and the challenge to retain talent.

Four of the current ISO standards will help ensure that the educational experience in traditional higher education, certificate programs, and corporate universities use consistent good practices:

• ISO 21001:2018 Educational organizations — Management systems for educational organizations; 

• ISO 29992:2018 Assessment of outcomes of learning services;

• ISO 29993:2017 Learning services outside formal education; and

• ISO 29994:2021 Education and learning services — Requirements for distance learning.

These standards help identify the outlines of effective organizational approaches to the delivery of quality educational services. The ISO standards are agnostic towards whether an institution is a traditional or alternative provider. This contrasts with accreditation and institutional authorization, which are the common systems of quality assurance for higher education. The standards-based approach thus broadens the scope beyond traditional higher education institutions.

But, doesn’t accreditation already provide the needed standards?

The answer is yes and no. Accreditation typically does mandate certain management systems but often contains subject-specific requirements. Accreditation is also country-specific and can vary by subject area. For example, the accreditation of a medical school is much different than that of a business school or a liberal arts college. 

Accreditation by and large also does not address non-traditional programs such as certificates or the emerging set of new providers such as corporations or corporate universities. The ISO standards establish a baseline of elements of a management system regardless of whether an institution or provider is a traditional or a new entrant.

The specific coverage of distance learning and assessment allows a consistent focus on key areas of ensuring online learning system quality and measurement of learning outcomes. The rapid pivot to remote learning during the Covid 19 pandemic has accelerated trends toward online education and associated challenges and illustrates yet again the needs addressed by the standards.

How will the standards fit in with accreditation?

In my recent analysis published as “ISO Alongside, Instead, or Inside? The potential of ISO 21001:2018 to change and challenge higher education accreditation” three scenarios were identified. 

• Alongside would involve educational regulators requiring ISO certification in addition to accreditation or licensure. 

• Instead could involve a substitution of ISO certification for accreditation.

• Inside might involve an accreditation body using ISO certification as a part of its recognition process.

It is likely that all three scenarios will exist for different types of providers and programs. 

The next time you sign up for a course, perhaps you may want to look for an ISO-certified logo?

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About the Ex4EDU.Report

This report is offered as a free-of-charge contribution by Lone Tree Academics, LLC, an educational services company focused on enabling excellence in higher education. Our services are focused around excellence through focused market knowledge, strategies, and Learningscapes™  built on solid foundations of curriculum and assessment.

For more information visit www.ltacademics.com

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2021:1

Welcome to the Ex4EDU.Report!

This report will explore topics of excellence in higher education. 

What is excellence in higher education?

First, let’s debunk a few of the misdirected ideas about excellence in higher education.

An all-to-common notion is an idea that excellence equates to exclusivity. In other words, the more exclusive the institution the higher the quality. Such an idea is essentially rooted in nostalgia and out of step with today’s reality of the needs for higher education. 

For example, in the U.S. around 3% of the population in 1920 attained a bachelor’s degree. By 2019 that figure was nearly 36% and increasing (National Center for Education Statistics, 2019).  Limiting our notions of excellence to an entitled few is not in line with the realities of the 21st Century.

Of the nearly 20 million students in U.S. higher education in 2019, the Pew Institute estimates only 3.4% are in institutions with highly competitive admissions or what could be considered “exclusive”. It makes little sense to say that excellence does not exist for the 96 out of 100 students attending all other institutions.

Another idea equates excellence to transactional customer delight. Such concepts often rely on customer satisfaction measures such as net promoter scores, which are often better suited for sales and services transactions. For tuition-dependent institutions, excellence can mean little more than enrolling and keeping students to capture tuition fees.  At residential institutions, excellence as customer delight can translate into the idea of a need for facilities like a resort. 

Excellence is often equated with awards and accreditation collection. Business schools commonly advertise being excellent through receiving three accreditations, often called a triple crown. The problem is that collecting awards for the sake of awards does not clearly deliver student excellence.

These ideas of excellence have a lack of focus on student success, which should be front and center.

Student success as the focus

In this report, we will examine higher education excellence across a range of topics but always with the optic of student success. This idea of success is not at a single point in time, through a single interaction,  and is a complex journey over time. 

Perhaps a good analogy of student success is one related to me by a leading graduate school director in France. Her concept was that excellence is like a ray of light hitting a prism.

The input is a single beam but the outcome is an array of colors and perspectives. The simple analogy would see success as an opening of perspectives, finding new opportunities, and a brighter and more enriching future. 

About the Ex4EDU.Report

This report is offered as a free-of-charge contribution by Lone Tree Academics, LLC, a company focused on enabling excellence in higher education. Our services are focused around excellence through focused market knowledge and strategies, Learningscapes™  built on solid curriculum and assessment foundations and implementing excellence at the department and institutional level.

For more information visit www.ltacademics.com

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