Peter T. Ewell
National Center for Higher Education Management Systems (NCHEMS)

Draft Prepared for Discussion at the 1997 AAHE Summer Academy at Snowbird

Over the past decade deliberate, institution-wide instructional improvement efforts have become prominent at American colleges and universities.  In part, this is because external pressure for some kind of “improvement” has become unavoidable.  Employers, politicians, and citizens have growing doubts about what is really learned in college and, more importantly, what good it is in actually preparing individuals for the complex world of work.  In addition, we now know a lot more about what can be done to improve higher learning.  Solid research on how learning really occurs, on how it can best be facilitated, and on how the organizations that foster it should be structured has burgeoned over the last ten years—especially in the revolutionary field of cognitive science.

Our limited success in actually improving collegiate learning has thus not been for want of trying.  Nor, at bottom, is it a result of our not really knowing quite a bit already about what works and what doesn't.  Instead, limited impact is the result of two key conditions that characterize most of the approaches to instructional improvement that we have actually tried:

  • they have for the most part been attempted piecemeal both within and across institutions,
  • they have been implemented in the absence of a broadly discussed and well-articulated understanding of  what “collegiate learning” really means in a particular collegiate community, and of the specific circumstances and strategies that are likely to promote it. 

The first condition means that often—significant investments of time and resources in such areas as curriculum reform, faculty development, and the use of instructional technology—however well-motivated—don’t fit together very well.  The second condition, in turn, means that we occasionally persist in doing things that are at least partially wrong—initiatives that emerging research tells us either won’t work at all, or that will yield only limited returns in comparison with what might be done instead.

The purpose of this Reader—and the change efforts that we hope that it can inform—is to address both these conditions.  Its contents were chosen because, taken together, they begin to provide collective insight into what we know about how deep and lasting learning actually occurs, and about the organizational and educational factors that research suggests are needed most to foster it.  The readings included, however, come from at least five different traditions; symptomatic of our problem, they are rarely read together:

  • human learning and development.  Resident principally in the discipline of educational psychology, this clinical/experimental research tradition centers on how individuals think and learn from a behavioral and structuralist perspective.  Prominent themes emerging from this tradition that bear directly on collegiate learning include notions of meta-cognition (Halpern and Associates 1994) and “double-loop learning” that emphasize the self-management of learning, “situational cognition” that stresses the role of specific contexts in determining what in fact is learned (Seely Brown, Collins and Duguid 1993), as well as theories of “multiple intelligence” that define important individual differences among learning strategies and styles (e.g. Gardner 1983).
  • teaching improvement.  Largely an applied literature—and far more extensively developed at the K-12 than at the collegiate level—this tradition concentrates on approaches that individual teachers can use to directly improve their instruction.  Important concepts at the collegiate level center on matters like promoting greater student involvement in-class and providing more frequent feedback to students.  Familiar collegiate examples within this tradition can be found in the “Seven Principles of Good Practice in Undergraduate Education” (Chickering and Gamson 1987) and in the development of classroom research (Angelo and Cross 1993).
  • curriculum and instructional design.  Also a literature of practice clustered predominantly at the elementary and secondary levels, this well-established tradition addresses the manner in which instructional experiences ought to be sequenced, structured, and delivered for maximum effect.  At the collegiate level, salient concepts include curricular coherence, interdisciplinary integration, and the importance of collaboration.  Easily-recognizable examples within this tradition highlight the First Year Experience (Upcraft, Gardner and Associates 1989), general education (Gaff 1996), and “Integrity in the College Curriculum” (AAC 1985).
  • organizational re-structuring and continuous improvement. With its origins largely outside education, this tradition draws on both research and practical experience on how to transform organizations to achieve higher performance.  A central objective is to create “learning organizations” with the will and the capacity to continuously monitor core processes, and to improve their outcomes as a result.  Familiar examples applied to higher education are the concepts of organizational culture and effectiveness and “Continuous Quality Improvement” (Seymour 1991, AAHE 1994).
  • cognitive science.  Probably the newest of these five bodies of work, this experimental tradition bridges the gap between psychology and biology by directly examining brain function and structure in connection with various forms of human behavior. Significant breakthroughs in technology have enabled researchers to observe the brain at work under various real-life conditions, and consequently to make inferences about how it actually processes and organizes information (Sylwester 1997).  Originally applied to memory loss caused by degenerative brain diseases such as Alzheimer’s and Parkinson’s, this line of inquiry is now beginning to reveal most of the reasons why the findings uncovered by the other four traditions are effective (Kotulak 1996).

Although these five distinct traditions of discourse developed independently, they have much in common.  More importantly from the perspective of institutional change, any one of them can provide a campus with effective pathways into the task of improving learning.  An understanding of some important principles and themes that undergird them all, however, should provide institutions with an especially well-grounded place to begin.  This initial edition of the Reader is designed to provide campuses with some “raw materials” for doing so drawn directly from each of these different literatures.  This introduction, in turn, attempts to draw together a few insights that resonate across all of them.  Together, we hope that these materials can be used immediately by campus teams to help forge a compelling local synthesis to undergird a specific institutional action agenda.

Why is a Synthesis Needed?  Wider discussion and synthesis of what is known about learning, about how to “teach” for it, and about how to build organizational settings that support it, can assist those involved in campus-level efforts in several ways.  Most prominently, it can help colleges and universities of all kinds to:

  • close the gap between current levels (and kinds) of student learning, and the kinds of learning that the external world is increasingly demanding and that we know can be achieved. Employers are increasingly calling on colleges and universities to graduate individuals with a deep understanding of how to diagnose unfamiliar problems and develop workable and innovative solutions.  At the same time, we are constantly confronted with examples of how other nations can outperform us in areas like mathematics and science, although the time they devote to schooling is the same or less.  Experimental studies in college settings here at home confirm these perceptions: getting better at learning is something that we can do (Wiggins 1996).
  • achieve greater “learning productivity” by designing and implementing approaches that are known to have the greatest impacts on learning.  American colleges and universities are living in a period of scarcity that is likely to endure for the foreseeable future.  Prior “improvements,” undertaken under periods of plenty, have occurred through accretion—adding new initiatives to old structures with little thoughts about trade-offs.  Future improvements, in contrast, need to be built through substitution—by systematically finding the approaches that work best, and ceasing to invest in others (Zemsky, Massy, and Oedel 1993).  This requires that we have the knowledge to make such choices effectively in the form of  “big ticket” items for learning.  It also requires us to think systemically about how our various “learning-producing” activities interact. 
  • develop a truly integrated campus change strategy that multiplies the individual impacts of discrete instructional “reform” efforts.  Well-motivated attempts to remedy perceived problems in higher education have tended to come to us in successive “movements,” each with its own rhetoric, vocabulary, tools and techniques, and sources of support.  Recent examples have included strategic planning in the seventies, curricular coherence and assessment in the eighties, and CQI and instructional technology in the nineties.  Within particular streams of innovation, moreover, distinct “schools” often arise—each competing for air time and diverting campus attention from core issues and problems.  Rather than cutting across all aspects of campus functioning, therefore, each such “innovation” tends to become a train on its own track, isolated from its fellows and from the real ways the institution does business.  As a result, each either fades away fast as the latest fad or must quickly find an organizational home of its own, which behaves like all the rest.
  • recognize specific and effective organizational levers for change that can be used to further such approaches.  Instructional improvement initiatives at most colleges and universities have not only been implemented piecemeal, but on the margin as well.  Few are supported by existing incentive structures like pay, promotion, and tenure for individual faculty members; or like budget making, political position, or reputation for academic units and institutions. However well-founded, each innovation must therefore cut across the grain of existing institutional incentives and structures, with scant chance of long-term success.
  • address commonly expressed faculty frustrations about lack of student motivation, attention, and levels of achievement.  Despite public perceptions, evidence is strong that the majority of faculty in American colleges and universities care a lot about teaching and are genuinely interested in improving student learning (Astin 1993, Fairweather 1996).  But they also know little about what actually is needed to improve, and they certainly aren’t much rewarded for trying to find out.  As a result, increasing numbers of faculty are growing unhappy with both the students with whom they are confronted and with a largely immutable instructional system that makes it impossible for them to perform any better.
  • to harness powerful and inevitable transformations that are occurring anyway in order to deliberately promote better learning. More real transformation in higher education has probably occurred in the last few years due to the need to respond to fiscal shortfalls than has come out of the many “reform” movements of the past two decades.  Added to re-structuring efforts already under way in response to budget shortfalls are new initiatives centered on instructional technology and distance delivery—both of which promise to fundamentally transform the way higher education happens.  These changes will occur, and we cannot stop them. What we can do is to work consciously to ensure that these strong disintegrative forces are effectively channeled, so they are consistent with what we know about good practice.  We also can try to be ready to exploit the many opportunities for productive change that will inevitably arise in the wake of these changes.

These are certainly grand objectives, and the task of organizing for learning will involve many unknowns.  What we can say for sure, however, is that embarking on this task at all will require broad campus discussion and a deepening collective understanding of the core issues at stake.

What We Know About Learning.  As members of a collegiate community, we like to think that there is something different about “higher” learning—and indeed there is.  A decade of research in the cognitive science and human learning traditions confirms what we have felt all along.  There are indeed big differences between those students who can promptly produce the “answers” that we ask for and those who demonstrate deeper forms of understanding.  But these research results push us beyond simple “either/or” distinctions as well.  Taken together, they force us to recognize that all learning is rich, complex, and sometimes unpredictable.   Building effective environments within which it can happen must rest on a growing inquiry into and knowledge about this complexity. 

Doing justice to what we are discovering about learning succinctly is a challenge.  But the following eight insights, drawn primarily from the cognitive science and human learning research traditions, seem both inherently compelling and immediately suggestive to those who are contemplating change:

  • that the learner is not a “receptacle” of knowledge but rather creates his or her learning actively and uniquely.  The literature on teaching emphasizes that the “higher” learning that ought to occur at the college level is as much about “transforming” existing knowledge and skill elements as it is about “adding” new ones (Angelo 1993).  The resulting learner is intended to be a flexible thinker, “one who is able to deploy a variety of frameworks and stand outside them” (Harvey and Knight 1996).  Learning at this level is also seen essentially as a creative act—its proof in the learner’s ability to go beyond the “reproduction” of what has been previously learned to engage in an “active search for understanding” (Oxford Centre 1992).  While this point appears at first glance to demote the importance of traditional disciplinary content in relation to cross curricular skills, ready dichotomies between “knowledge” and “understanding” are also misleading.  Instead, the two go hand in hand, with deeper understanding requiring wider and wider domains of content to relate and restructure.  The notion of “meta-cognition,” drawn from the human learning tradition, also resonates with this conception of “higher learning”—referring to the human brain’s built-in (and trainable) ability to monitor its own functioning (Diamond 1996).  Knowledge of one’s own strengths and weaknesses as a learner, and the ability to derive a workable tailored “learning strategy” for a given situation are key elements of functioning here—sustained by a considerable body of experimental literature (Halpern and Associates 1994).  Perhaps the most gripping single image of higher learning of this kind portrays the learner asan “epistemologist”—actively constructing unique ways of knowing and finding things out, even as he or she adds to a particular “stock of knowledge” (Bruner 1997).  Insights of this kind, of course, run decisively counter to the current dominant model of instruction as “knowledge transmission.”  At the same time, they help to explain why established instructional approaches so often fail to produce results beyond the simple recall of transmitted information.
  • that learning is about “making meaning” for an individual learner by establishing and re-working patterns, relationships, and connections.  The psychological foundation of learning, at the most basic level, involves actively creating linkages among concepts, skill elements, people, and experiences.  The kinds of “understandings” noted above as hallmarks of “higher learning,” therefore, turn out to be mostly about the specific structures of these relationships and how they change.  “Connection-making” has, of course, long been advanced by the literature on higher education as both an important outcome of college and a core curricular design principle (AAC 1985).  But our rhetoric in this regard is sustained by some interesting new biology that reveals “connection-making” to be  the core of both mental activity and brain development.  The brain at birth contains “an overabundance of the same or similar cells and connections between them” and then “needs to learn how to make itself work” (Kotulak 1996).  This is done through synaptic connection, which occurs a lot early in life, but which is never entirely over.  More importantly, traces of the resulting “neural networks” survive almost indefinitely, and are often re-used to deal with new situations (21st Century Learning Initiative 1997).  This accounts, in part, for individual differences in structure: different things end up being stored in very different places in each individual brain, with each network of synaptic connection also being unique (Bradshaw 1995).  At the psychological level, it is manifested in the quite different “mental models” that individuals create and call on to “make meaning” out of specific situations.  On the one hand, this phenomenon accounts for quite striking differences in individual abilities, learning styles, and dispositions (Gardner 1983).  At the same time, this mechanism helps to explain the often astounding durability of “primitive” ideas and organizing principles—even in the face of new evidence that they are wrong (Gardner 1991).
  • that every student can learn—and does learn all the time—with us or despite us.  For the human brain, moreover, connection-making is not something discretionary but something that happens constantly by default.  As one researcher puts it, “humans go around looking for opportunities to create new response functions” (Richardson 1995).  An obvious, but often-overlooked, implication of this capacity is to recognize all situations and events as learning opportunities—whether or not we explicitly construct them as such—and to harness them wherever they occur.  An equally obvious downside is that students may frequently be learning “wrong” things naturally, based on the circumstances in which they find themselves, and over which we have little or no control.  An important related point is that much (and perhaps most) of learning is implicit, deriving from direct interaction with a complex local environment and a range of cues given by peers and mentors that go well beyond what is explicitly being “taught.”  Observing classic apprenticeship situations, Seely Brown and Duguid (1993) strikingly label this kind of learning “stolen knowledge”—picked up surreptitiously and carefully hoarded for later use beyond the sight of the Master.
  • that direct individual experiences decisively shape individual understandings.  Relating and reacting to very particular and highly unpredictable patterns of environmental stimulation is the brain’s fundamental stock-in-trade.  This property can be observed directly, as different regions of cortex physically change in proportion to stimulating environments (Kotulak 1996) and is frequently claimed as the key survival mechanism for the human species as a whole (Sylwester 1996).  On the one hand, this insight highlights the overwhelming importance of built-in opportunities for active engagement when designing collegiate learning environments (Chickering and Gamson 1987).  And it further emphasizes that these environments are local and unique—each likely to produce a somewhat different learning outcome.  Proponents of “situated learning,” use this observation to claim, essentially, that the majority of learning is so embedded in a particular context that it allows little possibility of transferability beyond it (Perkins 1995; Seely Brown, Collins and Duguid 1989).  Others dispute these claims, maintaining that transfer can effectively occur through reflection and through providing proper cues about the circumstances under which cross-applications are appropriate (Anderson, Reder and Simon 1996; Sheckley and Keeton 1997).  Working both sides of this argument is the powerful notion of “mental models”—the particular array of working abstractions that each of us constructs to “make meaning” out of complex stimuli.  On the one hand, the contents of our “mental models” are decisively shaped by past experiences, which create “patterns of expectation” that are difficult to break out of even when they are demonstrably false (Bruner and Postman 1949; Halpern and Associates 1994).  On the other, most of our “mental models” are sufficiently robust and are constructed at a high enough level of abstraction that they can, under the right conditions, be effectively harnessed to gain insights into new situations (Sheckley and Keeton 1997).
  • that learning occurs when the learner is “ready” to learn. The most familiar construction of this insight, of course, is in terms of prior skill development and previous levels of understanding.  In physiological terms, because so much investment is made in building neural networks in the first place, the brain attempts to continually re-use existing connections for new purposes (Kotulak 1996).  This again highlights the amazing durability of “primitive theories” about how the world works (Gardner 1991) and the consequent importance of making deliberate opportunities to “unlearn” them.  A more subtle but equally important construction of “ready” is in terms of felt need.  Research on meta-cognition in the human learning tradition, for example, emphasizes the role of “thinking dispositions” in deciding whether to take advantage of—or even notice—a particular stimulus as an opportunity for learning in the first place.  Dispositions “reorganize thinking through the sensitivity to detect occasions calling for a particular pattern of thinking and the inclination to follow through” (Perkins 1995).  The concept of “disposition” is also prominent in the pedagogy of developing critical thinking, where it often proves as challenging to get students to actually use critical faculties as to acquire them in the first place (Facione 1990).  In this way, “dispositions” are themselves a kind of mental model, but applied to the act of learning itself and how much to invest in it.  A telling example, cited by Harvey and Knight (1996), is the decisive importance of students’ belief in their own capacities: if they once become convinced that they cannot learn, they cease to try.
  • that learning occurs best in the context of a compelling “presenting problem.”  This insight combines elements of points made earlier about the importance of direct experience and about motivational readiness.  But it adds a new wrinkle in its implication that there is a careful balance of challenge and opportunity in any learning situation.  Effective “presenting problems” are of interest to students because their solutions are perceived to have real consequences, and because they are sufficiently complex and challenging to be interesting.  But effective “presenting problems” are also not so hard, or the consequences of failure so extreme, that posing the problem causes complete mental “shut down” and frustration.  This ability of a particular “presenting problem” to decisively shape a given learning opportunity stems directly from the brain’s role in human evolutionary survival (Sylwester 1996). On the plus side, high challenge yields high emotion and attention—a brain-state labelled “beta-level” activity and characterized by vigorous neural operations (Bradshaw 1995).  Because of the relative implications of these abilities for sheer survival, the brain becomes very good at “[quickly] conceptualizing ambiguous problems and weak at anything that requires sustained attention or precision” (Sylwester 1996).  Learning for recall, or for forging the new connections among the concepts that will actually be used in future high-challenge situations—instead requires considerable periods of “alpha-level” activity or “reflection.”  Indeed, absent the opportunity for reflection, the successful solution of a “presenting problem” is likely to end a given learning encounter immediately, at a point well short of the re-organization of thinking that “deep” learning requires.  Seely Brown, Collins, and Duguid (1989) aptly term this learning behavior “satisficing”—typical of the activities of “Just Plain Folks” in everyday problem-solving situations—and it emphasizes an important down-side of any completely “experience-based” learning situation.  Another caution, of course, is that the “presenting problem” must be seen as actually amenable to solution.  Too much stimulation turns challenge into threat, and the brain simply “turns itself off” (21st Century Learning Initiative).
  • that the results of learning atrophy if they are not exercised, while frequent feedback multiplies the already-strong learning effects of practice.  This double-barreled insight is also directly related to survival because particular kinds of “presenting problems” vary in both their relative importance and in their frequency of occurrence.  As either of these diminish, the brain’s flexibility allows the neural networks that were constructed to address such problems to be quickly reworked to deal with more pressing matters (Kotulak 1996).  This underlying physiology explains what we see actually happens to infrequently-exercised skills in college—especially in areas like mathematics and foreign languages.  Without frequent opportunities for practice, even well-learned abilities go away (though recovery is not as difficult as initial acquisition).  At the same time, learning is influenced not only by the number of interactions with a particular environmental stimulus (say a person or a task), but also by the quality of the information that the learner gets back.  Especially valuable here is information that reveals specific, readily-correctable, mistakes or discrepancies in current practices, or in the “mental models” that lie behind them.  Even more effective is information that contains explicit cues about how to do better, such as that provided deliberately (or unconsciously) by a mentor or peer (Seely Brown and Duguid 1993).
  • that learning occurs best in a cultural and interpersonal context that supplies a great deal of enjoyable interaction and considerable levels of individual personal support.  Following the last point made, this final insight emphasizes the crucial roles played by other people in shaping individual paths of learning and development.  At the level of basic biology, this point is emphasized by the fact that the human birth process physically requires the brain to be “incomplete,” and therefore demands a social structure of nurture from the outset for the species to be viable (21st Century Learning Initiative 1997).  But this necessary social context is also actively and extensively utilized for learning through activities like play, ritual, and the various types of apprenticeship that occur repeatedly in traditional cultures (Geertz 1997).  Most learning of this kind is group-oriented and oral, with frequent opportunities for practice and feedback embedded directly into peer/mentor interactions, or occurs as a form of “storytelling” in which broader levels of meaning are made out of recent events and experiences (Bruner 1997).  An important ingredient of this social milieu is direct personal support for manageable risk-taking and its occasional negative consequences—a condition that exercises an important “liberating effect” on learning that comes from “being trusted and working harmoniously with others” (Vygotsky 1988). In summing up his case for the primacy of social participation as a learning device, Bruner puts it best: “the fact that we learn [a particular] culture as readily as we do must give us pause—considering how poorly we do at certain artificial, ‘made-up’ subjects that we teach in schools and whose use is not embedded in any established cultural practice” (Bruner 1985). 

Taken individually, each of these insights about how learning occurs isn’t much of a surprise—especially to teaching faculty.  After all, as Sylwester (1997) emphasizes, faculty have been watching student behaviors for generations and have learned a great deal from what they have seen.  Taken together, though, they paint a picture of “learning” strongly at variance with the ways in which our classrooms and institutions are currently organized.  One implication is that we should use what we now know about learning to legitimate what amounts to a natural understanding on the part of faculty that learning is a complex, multi-faceted, active and interactive process that really is difficult to pull off in extant pedagogical and organizational settings.  A second implication is that we can begin to harness the resulting energy to begin to envision alternative settings that are explicitly designed around what we know. 

What We Know About Promoting Learning.  Institutions of higher education can in many ways be characterized as “novice cultures” in their approaches to improving learning.  Rather than being guided by an overall vision established through systematic research and the wisdom of practice—primary hallmarks of an “expert culture”—reform and improvement efforts tend to be particularistic and mechanical.  This is in part due to lack of broad understanding about the nature of the goal to be achieved—collegiate learning itself.  Individual instructional improvement efforts (e.g. assessment, faculty development, curriculum reform, etc.) typically begin with a ready-made “method” or set of  “goals to be achieved” without fuller understanding of the complex character of learning and the learning process.  At the same time, institutions are currently organized against deep learning of this kind at every level—most prominently in their discipline-based departmental structures, established systems of faculty roles and rewards, in-place curriculum designs and frequently used pedagogies, and the lack of legitimate decision-making and organizational processes to re-vision or change any of the preceding conditions.

Not surprisingly, all five literatures also have many things to say about what can be done about these current conditions and, looked at collectively, they are remarkable in their consistency.  Primary insights can again be presented in terms of a few main headings. Although the distinction is in some ways artificial, it is useful to present them in two related groups—those having most to do with what faculty do in the realm of curriculum and instruction, and those having most to do with what leadership does in molding institutional cultures and strategies.  A final exercise, though, sustains the consistency: some of the same metaphors that describe individual learning most effectively can also be used to promote the process of institutional change.

At the level of curriculum and instruction, what we know from research suggests that the following lines of activity are “big ticket items” in producing learning gains:

  • approaches that emphasize action and experience.  Typical academic activities in college are notoriously “arid” when it comes to experience, and students are quick to notice it.  Because they see little direct utility in what they are learning and have few opportunities to try things out in “hands-on” ways, much of the subject matter that they actually acquire takes the form of “ritual knowledge.”  At one level, this means that a lot of what is learned is formulaic and is quickly forgotten.  More important, because the classroom is in fact a “survival experience” in miniature, what they do learn well is “various discursive devices through which they try to keep the teacher happy” (Edwards and Mercer 1987).  Instead, the focus of pedagogy needs to be placed on the “total student learning experience” (Harvey and Knight 1996), which includes more than formal academic events and exercises.  Important hallmarks of this experience, furthermore, are powerful learning environments that contain encounters designed explicitly to “expand and diversify experiences of reality” (Sheckley and Keeton 1997). At minimum, this means far closer integration between curriculum and co-curriculum than is currently the case at most institutions.  At a higher level, it means structuring learning opportunities that feature active engagement in real-world problems or circumstances as an integral part of classroom work.  At the highest level, it means giving students periodic assignments entirely outside an academic setting in the form of internships, practice, and service-learning opportunities (or taking deliberate advantage of experiences that they inevitably encounter in their own workplaces or communities). An important caution at all levels, though, is to avoid treating “experience” as an add-on to traditional pedagogy.  On the one hand, it is important for students to find solutions and tools to the real world problems that they encounter in experiential settings “just in time” through their regular academic work.  On the other, it is critical to include deliberate opportunities for reflection on experience, in order for it to have maximum value for learning.
  • approaches in which faculty constructively model the learning process.  Current classrooms are also characterized by a prominent instructor role that emphasizes status based on expertise, and are consequently organized for the maximum “dispensing of knowledge.” In most cases, this turns out not to work very well. Instead, the most powerful classroom learning environments are those based on a model of the student-faculty relationship in which faculty continuously model what it means to be a learner.  One objective here is to gradually “initiate” the student into the “alien world” of expert knowledge and practice which the faculty member actively embodies and to which the student should aspire (Farnham-Diggory 1994).  Captured in the powerful metaphor of “cognitive apprenticeship” (Seely Brown and Duguid 1993), the essence of this approach is to engage students in an expanding range of  “legitimate peripheral participation” in what the instructor is doing.  To make this happen effectively, however, the work of the student has to be seen as consequential as well as just applied.  As a group of researchers on effective professional education puts it, “what helps most is being taught by someone who models how to understand and deal with [ill-defined, complex and risky professional situations] and who then guides the learners’ attempts to do the real thing” (Farmer, Buckmaster and LeGrand 1992).  Consequential participation also helps to establish the importance of high standards.  On the one hand, students can immediately grasp the importance of such standards and why they need to be enforced.  On the other, faculty behavior actively models “expert” practice, making such standards far more visible than in traditional teaching situations (Wiggins 1989).  Opportunities for “legitimate peripheral participation” of this kind certainly occur most frequently in applied disciplines, but they are by no means impossible elsewhere—a point made nicely by the demonstrated effectiveness of undergraduate participation in faculty research (Strassburger 1995).  At the same time, collaboration, group problem-solving sessions, and active discussion of unresolved issues provide direct opportunities for faculty in any discipline to build classroom environments that are “knowledge-creating” instead of “knowledge-dispensing.”
  • approaches that emphasize “concept mapping.”  If effective learning is essentially about making connections among concepts, students need both the tools to make such connections and powerful “cues” from instructors about how to do so.  Research on “analogical mapping” strongly confirms the utility of explicitly designing instructional approaches that involve recording and analyzing the similarities among several quite different situations or experiences, and then using the resulting constructs to gain insight into new problems (Gick and Holyoak 1983).  “Reasoning by analogy” in this way, of course, is a well-known problem-solving heuristic (e.g. Polya 1957), but it is rarely applied systematically by instructors in pedagogical situations.  Research results suggest that deliberate use of analogical mapping approaches of this kind can markedly increase problem-solving in a new situation.  But the best gains occur when both the “raw materials” for mapping and actively-supplied “cues” about how to use these materials are given to learners (Sheckley and Keeton 1997).  The importance of this cuing role certainly recalls apprenticeship, but it especially stresses the instructor’s role in eliciting from students new or creative answers and solutions (Richardson 1995).  This approach on the one hand depends decisively on the student encountering new problem situations that are at least partially recognizable as a familiar pattern.  On the other hand it demands instructional approaches that go beyond simply “telling” students how to use existing mental models in the new situation.  Instead, students must actively confront the mapping task themselves—using supplied cues to consciously reconstruct their previous understandings (Sheckley and Keeton 1997). 
  • approaches that emphasize interpersonal collaboration. Because the principal objective is construed as producing “knowledgeable individuals,” established college-level instructional paradigms overwhelmingly feature individual work—especially in their approaches to assessment.  At best, under this paradigm, working together is seen as inefficient; at worst, it is viewed as “cheating,” as individual weaknesses can be hidden in group performances.  In contrast, research results on the effectiveness of collaborative learning are overwhelmingly positive (e.g. Wenger 1996).  Partly this is because “hidden” deficiencies are actively uncovered and corrected through peer interaction.  Indeed, much of the demonstrable effectiveness of collaboration lies with the low-stakes opportunities it provides for feedback and correction (Light 1990).  At the same time, group-work is efficient: allowing peers to provide the bulk of immediate feedback not only multiplies the amount of it that can be given, but allows instructor time to be more effectively used in assessment and periodic intervention to provide appropriate cues.  It is also useful to remember that verbal interaction and group narrative activities are the way basic socialization into any culture occurs, and with it much of what we really mean by “learning” (Bruner 1997).  This point highlights the particular value of collaboration in first-year or transitional experiences, through which students are indeed initiated into “whole new worlds” (Tinto et al. 1997).  A final application of this insight is curricular—creating explicit structures such as “learning communities” that bring students together across diverse disciplines and courses on a regular basis to reflect on commonalities and to engage in specific projects with faculty designed to synthesize their understanding (Gabelnick, MacGregor, Matthews, and Leigh Smith 1990; McLaughlin and MacGregor 1996).  Not surprisingly, in sum, collaborative approaches are often able to capitalize far more on what we know about how people learn naturally than our current pedagogical designs.  As the report of the 21st Century Learning Initiative (1997) puts it, “formal so recent (five or six generations in most places) that it is unlikely to have had any impact on our inherited predisposition to learn in ways that our ancestors found so useful.”  Collaboration among peers and various forms of active apprenticeship and initiation, of course, are among the most prominent of these traditional forms (Bruner 1997).
  • approaches that emphasize rich and frequent feedback on performance.  Useful feedback can come from many sources including experience, peers, mentors, and oneself.  As currently practiced, though, it tends to concentrate on a single source: faculty assessments that occur infrequently and that have significant consequences if student performance is not satisfactory.  At one level, this observation in itself provides useful points of attack in changing current practice.  We know that the ways in which students are assessed powerfully affects the ways in which they study and learn (Angelo 1993, Harvey and Knight 1996, Wiggins 1989).  This is not surprising, given that it is the high-stakes assessments themselves—rather than the material to be learned—that constitute the “presenting problem” for students in a traditional classroom situation.  Surviving them successfully, rather than learning from the inevitable mistakes that are made, becomes the principal immediate imperative.  Managing the frequency and the consequences associated with such assessments—by using weekly quizzes or non-graded practice assignments, for instance—can thus pay immediate dividends for students because they can quickly see areas in which they might improve (Light 1990).  Carrying this process farther, though, begins to subtly alter the instructor’s role from “teaching” to “coaching” (Wiggins 1989).  Rather than emphasizing content coverage, the focus of instruction is placed on creating an iterative series of opportunities for students to try out skills, to examine small failures, and to receive advice on how to correct them (Astin 1991).  Finally, the effectiveness of feedback in any form is noticeably multiplied if students are also trained to reflect and self-assess (Alverno College Faculty 1976).  Journals and “narrative self-assessments” in which students produce critical commentary on their own engagement with particular learning situations—and therefore demonstrate and hone their own meta-cognitive abilities—can be particularly powerful in this respect (Kramp and Humphries 1995a, 1995b).
  • approaches to curriculum design that are coherent and that consistently develop a relatively limited set of cross-disciplinary skills that are clearly identified and are publicly held to be important.  Finally, the extent to which we design curricula as intentional “learning plans” (Stark and Lowther 1986) can matter a lot.  Especially at the lower division, most of the curricula now in place at American colleges and universities lack any detectable design principle at all.  Where such a principle is visible, it is usually to maximize content coverage—either of multiple disciplines across a general education program or of myriad subtopics within a particular field.  In contrast, curriculum structures can be effective in producing higher learning only if they are consciously integrated both horizontally and vertically.  Horizontal integration emphasizes the consistent practice and development of a few key skill areas in quite different contexts—for instance, in the familiar “writing across the curriculum” approach.  Vertical integration means designing-in explicit vectors of development on each of these skills, so that successive course experiences visibly require, practice, and deepen the results of prior learning (e.g. Farmer 1988).  Both, of course, depend critically on collective decisions about what is important to learn in the first place—a conversation which on most campuses has yet to take place.  One powerful way into all three design tasks, though its impact is supposed to come later, is preparing for assessment.  On the one hand, initial engagement in assessment forces institutions to be much more precise about intended outcomes.  On the other, it automatically raises questions about whether existing curricular designs are in fact “acted out” as intended by either students or faculty.  As a result, many institutions have found that the most immediate result of seriously beginning assessment is curricular restructuring (Banta and Schneider 1988).

At the level of Organizational Structure and Culture, what we know from the literatures on organizational re-structuring and continuous quality improvement suggests a number of important properties of successful change initiatives.  Those particularly salient in “organizing for learning” include the following:

  • change initiatives require a fundamental shift of perspective for both the organization and its members.  Current academic programs have been conceived principally as “delivery systems” to transmit to students previously constructed bodies of knowledge. This dominant blueprint places “knowledge” itself—and the mechanisms for “delivering” it—at the center of the institution’s design.  As a result, it decisively constructs what its members think “they are supposed to do.”  What we know about learning and effective instructional approaches demands a basic shift of perspective that turns this model “inside out and upside down” (21st Century Learning Initiative 1997).  Instead of beginning with academic “programs” and their requisite resources and structures, alternative design visions need to start with students and what they need to be successful as learners (Barr and Tagg 1995).  This fundamental shift of thinking is analogous to that required by corporations in their attempts to become more responsive to “customers” (AAHE 1994, Seymour 1991).  Put simply, it requires examining every function, structure and activity that defines the organization from a new point of view.  But the “customer” analogy must not be misunderstood.  In organizing an institution for learning, beginning with the learner emphatically does not mean catering blindly to every student desire.  Instead it implies that educational environments and experiences be deliberately constructed to provide challenging and rigorous opportunities for students to learn actively and creatively, consistent with what we know about how learning occurs.  What kinds of implications follow from this shift of perspective?  One set centers on the design of learning experiences themselves.  Virtually all now appear in the form of formal classes of similar structure, rigidly organized around an institution-wide academic calendar designed to maximize the “efficient” use of faculty time.  Emerging experience with technology-based delivery, in contrast, suggests that even greater “efficiencies” can be achieved by turning the process around. Asynchronous self-directed learning opportunities—even if delivered at a distance—appear quite capable of providing the kind of challenging, actively involving, academic problems that we know are most conducive to individual learning (Daniel 1997).  This shift of perspective also means determining student goals and needs in far greater detail than we now do, and attempting to shape programs that respond to what are often quite different kinds of student requirements and rhythms of participation.  It also means monitoring student progress more proactively and helpfully—especially if, as is increasingly the case, students “take” the curriculum in unusual ways or attend multiple institutions to attain a degree.  Both these points have significant implications for the way we design university information systems.  “Student-centeredness” finally means substantially erasing the great divide between “academic” and “student affairs” prominently present on most campuses.  Re-thinking all functions from the perspective of student learning means treating all contacts with students as potential learning opportunities—including faculty encounters out of class, student activities, residence life experiences, and the campus social environment.  As numerous studies have demonstrated, this can pay off handsomely in the form of both increased learning and in student retention (e.g. Astin 1993). 
  • change initiatives need to be thought about systemically. Most “movements” aimed at improving collegiate learning—including assessment, faculty development, curricular design, or instructional technology—are for the most part advanced as distinct “activities to be engaged in” by the institution and its members. Little thought is therefore given to the manner in which each, if really taken seriously, will fundamentally affect all components of the institution and the relationships among them. “Systems thinking” of this kind, the latest literature on organizations tells us, is basic to developing a successful change initiative (Senge 1990, Vaill 1996).  Looked at in this manner, it is not enough for us to examine each current function individually from the point of view of student learning.  We must instead build a conception of how these components interrelate and how they fundamentally condition one another’s operation.  A useful point of departure here is to conduct a systematic formal “audit” of policies and statements, established practices, and current behaviors to determine their collective alignment with making student learning a high priority (O’Bannion 1994).  Such an examination, moreover, needs to go beyond structures and practices to reveal the underlying values and incentives that kept them in place.  The meaning of scholarship at the institution (Boyer 1990), how faculty are regarded and rewarded (Guskin 1994b), and how and for what the staff is held accountable (National Center for Connected Learning 1997) are particularly important elements of institution culture to examine from this point of view.  Systemic thinking with student learning as its point of departure will also likely reveal substantial deficiencies in the ways colleges and universities are organized.  Among the specific implications it may uncover is the need to re-examine disciplinary departments as the fundamental building-block of academic organization.  Currently, such units house and support faculty, serve as fundamental budgetary accounting units, and are the primary unit of instructional delivery.  Yet institutions have already experimented with alternative “matrix” structures that break these functions apart to allow more flexible partnerships and initiatives to be rewarded (Guskin 1996).  Funding the “general education” component of the curriculum separately, and allowing it the freedom to “purchase” from disciplinary departments only those learning experiences that meet pre-set specifications, nicely illustrates the kinds of structural alternatives that might emerge (Ewell 1994).
  • change initiatives require people to re-learn their own roles. In the decentralized environments that constitute colleges and universities, learning to think this way is admittedly not easy.  As Vaill (1996) emphasizes, this is partly because it requires as a prerequisite that those engaged in change efforts become continuous, open learners themselves—a condition he terms “learning as a way of being.” While largely inconsistent with current academic behavior, this notion is certainly not outside the bounds of academic values.  In simple terms, it means applying core values of scholarship recursively to ourselves.  At the most immediate level, this implies substantial investment in staff development.  At most colleges and universities, development and training efforts tend to be considered auxiliary to core institutional functions—engaged in at the discretion of the individual and largely unconnected to one another or to any collective vision for change. In contrast, the organizational literature emphasizes staff training as a primary key to transformation—often advocating mandatory across the board training in quality processes as a starting point for systemic change (Gitlow and Gitlow 1987).  From the point of view of organizing for learning, moreover, staff development—especially for faculty—requires a special character.  On the one hand, it must emphasize providing faculty with a “view of learning” that is more than “naive theories that are the product of personal experience,” and be conducted in a manner that requires application of the same principles of good learning as in educating students (Harvey and Knight 1996).  On the other, it must work toward imbuing in faculty a sense of collective accountability for learning and the learning process (Wiggins 1996) of the same character and depth as they now assume for valued research products.  At the same time, institutions need to create visible forums, symposia, and other settings and occasions through which to share ideas, discuss strategies, and celebrate successes with respect to learning (Guskin 1996).  Not only do such mechanisms provide a conduit for much-needed cross-functional communication, but they also provide important occasions for the campus to recognize a new collective identity as a learning community—one that is “recursive and reflexive at all levels including the learner, instructor, staff, and organizational setting” (Harvey and Knight 1996).
  • change initiatives require conscious and consistent administrative and leadership support.  Creating and sustaining change of this kind also requires a re-visioned approach to leadership.  On the one hand, it requires assembly of a “critical coalition” composed of top leadership and a relatively small band of individuals drawn from throughout the organization who immediately grasp and are clearly committed to the implications of organizing for learning (O’Bannion 1997).  It is up to this group to become “leading learners” in proposing and testing systemic visions for change, and to actively model the process of “learning as a way of being” (Vaill 1996).  The next (and in some ways simultaneous) task is to systematically involve relevant stakeholders in evolving the vision—primarily by showing them specific ways in which proposed alternatives impinge on the ways they must do their jobs. As O’Bannion (1997) also emphasizes, a principal role of leadership at this stage is to “round up innovations,” systematically identifying the current range of disconnected change initiatives present inside the institution (and beyond) and finding ways to create synergies among them.  Finally, leadership needs to concretely sustain these initiatives through the visible commitment of resources and adequate administrative support.  Certainly, many such resources will be fiscal and physical, but visible recognition and honor for change participants can be equally important in building support (National Center for Connected Learning 1997).  Above all, leadership should continually recognize that organizational transformation is fundamentally about individual people and their relationships.  In transforming organizations, as Glasser (1996) revealingly puts it, “managers manage as though the quality of the lives that they manage is important.”
  • change initiatives require systematic mechanisms for the institution to continuously monitor how it is doing at every level.  Building a “learning organization” also involves creating institutional capacities for gathering and interpreting data at all levels.  Again, in part, this means applying widely proclaimed academic values of systematic investigation and reasoned deliberation “recursively” to colleges and universities themselves. All too often, for instance, activities like “assessment” are seen as consistent only with the research interests of Education departments, and thus outside the ken (and probably beneath the dignity) of more traditional disciplines.  Building capacity, in turn, requires attention at every level of the organization.  At the highest level, “institutional research” needs to be re-captured for learning purposes.  Currently, such functions largely generate data for accountability purposes and add little value to internal conversations about learning and re-structuring.  Ironically, though, “institutional research” as an organizational function actually began with learning research—embodied in the mid-1930s in such organizations as the Examiner’s Office at the University of Chicago, the Bureau of Institutional Research at the University of Minnesota, or the Division of Educational Reference at Purdue (Pace 1979).  We need to recreate this capacity explicitly, in order to systematically evaluate the learning effects of change.  At successively lower organizational levels, in turn, the need to develop concrete mechanisms for data-gathering, and the impulse to use them, is equally important.  As Seymour (1991) emphasizes, it is the urge to record—and to see each question that arises as an “empirical” question—that lies at the heart of continuous improvement.  At the level of the individual instructor, classroom research (Angelo and Cross 1993) may be critical in fostering such “habitual” data‑gathering.  For administrative functions, it may require more systematic documentation of processes and the establishment of continuous monitoring mechanisms to check on how they are working (Seymour 1991; Sherr and Teeter 1991).  Building a “culture of evidence” (WASC 1992) also requires more than just data-gathering capacity—even if the resulting “data” are indeed focused on learning.  In addition, the symbolic value of information in reinforcing central visions needs to be recognized explicitly. Current models of “accounting” higher learning cast in “seat-time” terms, for instance, subtly reinforce the dominant “content transmission” model, and must be critically examined.  As Barr and Tagg (1995) suggest, an arresting alternative might be a new unit of productivity, “cost per unit-of-learning produced.”  Finally, the ways in which information about performance are actually used in decision making will ultimately be decisive.  As in any learning situation, if feedback about performance is used frequently in high-stakes situations to evaluate individuals, instead of being used to understand and improve collective activities, nothing useful will occur.
  • change initiatives require a visible “triggering” opportunity or event.  A final useful insight is that change initiatives rarely start from scratch.  Like learning itself, which is often initiated or sustained by a powerful “presenting problem,” the most successful organizational transformations begin with a felt need—fiscal constraint and the consequent need to re-structure (Guskin 1996) or a particular instance of deficient performance that is highly visible and hard to avoid.  Part of the art of transformational leadership, as O’Bannion (1997) points out, is to recognize and capitalize on such “triggering events” when they occur.  Certainly one of the most promising in organizing for learning is the advent of technology. By fundamentally exploding traditional categories of instructional delivery such as “classes,” “semesters,” “teachers,” and “disciplinary content,” technology provides specific mechanisms for creating learner-centered learning opportunities (Rush and Oblinger 1997).  At the same time, the advent of technology on any campus creates priceless opportunities for faculty to fundamentally re-conceive their roles in helping to facilitate learning (Chickering and Ehrmann 1996).

As Senge (1990) among others cogently observes, every system is perfectly constructed to produce the results that it achieves.  The fact that higher education is now underperforming—both in its own eyes and in those of others—should come as no surprise given our current organizational structures, values, and patterns of communication.  Fundamental to change at both the instructional and organizational levels is recognition that the current system is a system—intact and self-perpetuating because of a complex network of existing values and supports.  Only by beginning from a fundamentally different point of departure and thinking systemically about alternatives can we hope to break out of the constraints on both thinking and action that it imposes.  In the last analysis, this is what “organizing for learning” is all about.

Some Final Themes and Continuities.  A final advantage of examining all five traditions of inquiry together is that a collective reading suggests some intriguing parallels at quite different levels of activity.  Many of the specific insights we can construct about how individuals learn, drawn from the human learning and cognitive science traditions, have direct counterparts in the other three literatures in the kinds of organizational changes and pedagogical approaches that are most effective.  Although such analogies can surely be overdrawn, three of these themes are striking.  If they are properly sustained, they can serve as tools to bring greater continuity to the kinds of institutional conversations that are needed.  Among these potential cross-cutting themes are the following:

  • a vision of “improvement” as transformational instead of additive.  Understanding that learning involves individual learners, actively transforming their own previous understandings as they are exposed to new situations, is fundamental to this conversation. Structural transformation appears equally compelling as a guiding metaphor for improving both instructional forms and the wider organizational systems in which they reside.  Initiatives at any level that promise simply to add to existing capacity, rather than thoroughly re-examining all elements and how they work in combination, have little promise.
  • the need for continuous feedback and reflection on performance.  As noted repeatedly, good learning requires both frequent feedback and structured opportunities to reflect on what it means.  New instructional approaches and curricula must incorporate such mechanisms from the outset in their design.  But collective feedback and opportunities for community reflection are equally necessary for sustaining institutional change.  They must not be overlooked.
  • the need for explicit structures for collaboration and support.  We have discovered that good learning is often group learning.  At the same time, we are finding models of instruction that foster active collaboration between students and faculty—breaking down barriers between “expert” and “novice”—to be especially powerful in fostering the kinds of learning that we want. Such models rest strongly on notions of colleagueship and support that are equally indispensable when embarking on large-scale organizational change.

Above all, however, these literatures suggest that change is unlikely to happen unless the problems with established ways of doing things are recognizable and explicit.  At the level of individuals, we know that the best learning sometimes occurs when we discover and notice the unexpected.  At the level of instruction, we know that anomaly and counter-example can work well as devices for promoting learning.  At the organizational level, by implication, we must recognize that change is unlikely unless there is a felt need to change—visible in a concrete problem or set of problems that compel collective attention.

Most institutions currently lack such a specific point of departure, largely because most of their members don’t see what the problem is.  The principal challenge, then, is to identify one or more concrete “presenting problems” in each institutional setting that can serve as the basis for leveraging organizational attention and, therefore, for beginning the process of systemic thinking about needed transformations.  Identifying a few specific opportunities of this kind in the current situation, like recognizing a “teachable moment” in pedagogy, is thus perhaps the task most immediately required of institutional leadership to begin the process of organizing for learning.


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