Deep Learning for a Digital Age: Technology's Untapped Potential to Enrich Higher Education / Edition 1

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Deep Learning for a Digital Age outlines a new paradigm for using technology to bring depth and dimensionality to the classroom. In this important book, Van B. Weigel introduces his "depth education" model that blends classroom-based education with e-learning to enrich higher education. Deep Learning for a Digital Age

  • Introduces a workgroup approach to the classroom that uses virtual teams to build skills in critical thinking and knowledge management
  • Offers a strategic assessment of the opportunities and challenges associated with the broadband virtual classroom
  • Outlines the campus infrastructure requirements of depth education
  • Describes the educational vistas made possible by e-learning
  • Explains how to implement the knowledge room framework of depth education
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Product Details

Meet the Author

Van B. Weigel is professor of ethics and economic development at Eastern College in St. Davids, Pennsylvania. He is author of a Choice Outstanding Academic Book, A Unified Theory of Global Development and Earth Cancer.

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Table of Contents

Tables, Figures, and Exhibits xi
Preface xiii
The Author xix
1 Beyond the Virtual Classroom 1
2 The Commoditization of Instruction 30
3 Transforming the Classroom into Knowledge Rooms 60
4 Building an Infrastructure for Depth Education 102
5 New Horizons for Higher Education 127
Notes 143
References 149
Index 163
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First Chapter

Chapter One

Beyond the Virtual Classroom

"For on-line education to become mainstream is kind of a depressing thought, because it is such a crappy experience. The bottom line is that learning on-line is a soul-destroying experience. It really, really stinks. It's always second best" (Hamilton, 2001, p. R32). These words, published recently in the Wall Street Journal, were not spoken by an irate faculty member or a closet Luddite. The speaker, Marc Eisenstadt, is the chief scientist of the Knowledge Media Institute of the United Kingdom's Open University. The Open University has used on-line education to supplement its extension courses and correspondence programs since the mid-1990s, and Eisenstadt's institute conducts research on distance education and virtual classrooms. His blunt assessment is part of the larger reassessment of the Internet that has been taking place since the fall of the NASDAQ in April 2000 and the dot-com meltdown that followed. The business community, confronting the sobering reality of stock valuations that have fallen to sub-basement levels, is returning to the old-fashioned virtue of economic performance over market potential. E-learning must be scrutinized with the same healthy skepticism. Will e-learning really deliver, or will it turn out to be just another casualty of the overblown expectations of the late 1990s?

This book is about a simple idea. Technology should enrich the experience of learning. E-learning technologies may save some costs and add a measure of convenience, but if they do not deepen the learning experiences of students, they are not worth much.

John Chambers, CEO ofCisco Systems, the company most responsible for supplying the electronic plumbing that runs the Internet, hails e-learning as "the next big wave in Internet-based applications" (D'Amico, 1999). More recently, Sean Maloney, executive vice president of Intel, proclaimed that e-learning "will be the killer application over the next two to three years" (Mannion, 2001). They may be right. But e-learning will fall far short of its potential if it merely repackages our current educational models in digital format. Instead, it should enable students to become more proficient learners.

Nearly all varieties of distance education have failed to bring depth and dimensionality to the experience of learning. With the exception of a few innovative firms like Cognitive Arts and, most distance education providers are serving up variants of a "post-a-lecture" and "host-a-discussion" approach. The differences between them are not worth mentioning. The basic idea is to port the classroom to the Internet in the most efficient way possible--not unlike software engineers porting software programs to different operating environments. One company even promises to put entire campuses on-line in sixty business days! Could something that is really valuable be accomplished that quickly? One suspects that many distance education initiatives are the result of little more than an impulsive game of keeping up with the Joneses--motivated more by the primordial fear of being left behind than by a desire to apply sound pedagogical method.

Even popular classroom-based instructional technologies (the ubiquitous PowerPoint presentation, for example) have treated the computer as little more than an overhead projector with bells and whistles. It may be argued that compelling graphics and arresting slide transitions help keep the attention of students in a lecture hall (unless they are sitting in a darkened classroom right after lunch). But if a technology can secure a student's heightened interest in a lecture, does it also enhance his or her ability to learn? That student may have more accurate and well-organized lecture notes or be better able to recall material during an exam, but is this what learning is all about?

Deep Learning and the Construction of Knowledge

Deep learning finds its inspiration in a school of educational thought known as constructivism, and in particular, the branch of constructivist thought known as social constructivism.

Stemming from the work of Jean Piaget and Lev Vygotsky, and drawing inspiration from John Dewey's focus on active learning, constructivism holds that all knowledge is constructed based on the experiences and cognitive structures that are available to us. Reality becomes sensible and coherent because we construct it. Knowledge is not something that bombards our consciousness and is absorbed; rather, it is something that we actively construct to make the world meaningful. Learning involves a search for new knowledge--or "new territory"--that is strongly related to the activities of play, discovery, and problem solving. According to the constructivist standpoint, instructors cannot walk into the classroom and presume anything like a preexisting thirst for knowledge. Instead, they must create a discovery-based learning environment that launches students on a search for new territory.

The best place to see constructivist thinking at work is not in the classroom but in those high-tech firms that encourage playfulness to induce creativity. In a survey of the work environments of high-tech firms that he carried out for the Washington Post, Dale Russakoff (2000) observed that from "workers sprawled on their stomachs using laptops, to employee playrooms full of Legos and easels, to the rebellion against hierarchy, the culture of the new economy makes work feel unmistakably like play. Consciously or unconsciously, it recalls the atmosphere of early childhood--the stage of human life when the learning curve is the steepest and the pace of learning is unrivaled."

Knowledge constructions, or what Piaget called schema, are the central building blocks of constructivism. They refer to ways of perceiving and thinking that make the world meaningful to us. Our knowledge of the world is based entirely on these knowledge constructions; we have no other avenue for accessing information about the world. Because each person's experiences are unique, the knowledge constructions that each person creates to bring understanding and coherence to the world may differ significantly from the knowledge constructions of others. For example, people who speak the same language and have received formal training in mathematics may have similar knowledge constructions when it comes to the ordering of words or manipulation of numbers. But such similarities fade quickly when the discussion turns to spiritual experience or moral obligation.

Constructivism, therefore, presumes that people will process new information differently and places great value on dialogical processes. Differences in perspectives are approached with a presumption of humility. In this respect, there are many similarities between constructivism as an educational philosophy and postmodernist thought.

Learning, according to Piaget (1970), takes place through the interplay of two polar forces: assimilation and accommodation. These forces are kept in balance by an adaptive and dynamic process of equilibration (Piaget, 1977). Assimilation refers to the process by which the learners incorporate new information and experiences into the framework of their preexisting knowledge constructions, thereby rendering the unfamiliar familiar. When learners have new experiences or are exposed to ideas that cannot be squared with their knowledge constructions, they must explore new territory in an effort to resolve the dissonance or contradiction in their minds. Doing this requires some thought. Accommodation takes place when learners accommodate these new experiences or ideas by bringing their knowledge constructions in line with the new information.

Lev Vygotsky (1978, 1986), a Russian developmental psychologist, brought a distinct social dimension to constructivism. Vygotsky focused on the way that language, culture, and social interactions affect learning processes. He distinguished between what he called spontaneous and scientific concepts. Spontaneous concepts are similar to Piaget's notion of knowledge structures. These ideas and understandings bubble up spontaneously from the learner's own reflections on everyday life. Scientific concepts, by contrast, are more formal and abstract in character and can be conveyed through classroom instruction. Scientific concepts work their way down into the learner's consciousness by supplying the learner with conceptual resources that assist him or her in constructing spontaneous knowledge structures that are more comprehensive and adequate.

The meeting place between spontaneous and scientific concepts is what Vygotsky referred to as the zone of proximal development. Because each learner brings different sets of spontaneous concepts into the classroom, this zone will vary from one individual to the next. It is in this zone that the learner's ability to solve problems independently is enhanced through "collaboration with more able peers" (Vygotsky, 1978, p. 86). Hence, Vygotsky recognized the important contributions of both teacher and learning community in intellectual development.

It is hardly a coincidence that the ancient model of apprenticeship not only relies on the observation of expert performance by the novice but also rests upon considerable interactions among peers. As Barbara Rogoff (1990, p. 39) notes, "The apprenticeship model has the value of including more people than a single expert and a single novice; the apprenticeship system often involves a group of novices (peers) who serve as resources for one another in exploring the new domain and aiding and challenging one another. . . . Hence the model provided by apprenticeship is one of active learners in a community of people who support, challenge, and guide novices as they increasingly participate in skilled, valued sociocultural activity."

The familiar debate over process versus content loses relevance in a constructivist perspective (Marlowe and Page, 1998). Content is the medium for knowledge construction and the springboard for learning. But merely possessing information does little to advance the goals of education. Learning, from the standpoint of constructivism, takes place when students act on content, when they shape and form it. Content is the clay of knowledge construction; learning takes place when it is fashioned into something meaningful. Creativity, critical analysis, and skillful performance are inextricably linked to the process of creating more viable and coherent knowledge structures.

Defining Deep Learning

The broad concepts of constructivism have gained ample support through research over the past thirty years in developmental psychology, cognitive psychology, and more recently, neuroscience. It is now possible to speak credibly of an emergent science of learning. The Committee on Developments in the Science of Learning of the National Research Council has assembled and analyzed the primary conclusions of this research in an elegant volume entitled How People Learn, published by National Academy Press (Bransford, Brown, and Cocking, 1999).

The recent developments in neuroscience are particularly striking. Technologies such as positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) have extended our understanding of some of the brain's learning mechanisms. Because of this work, we now know that learning actually modifies the physical structure of the brain. Among the most basic rules of learning is that "practice increases learning and that there is a corresponding relationship between the amount of experience in a complex environment and the amount of structural change in the brain" (Bransford, Brown, and Cocking, 1999, p. xvi; see also pp. 102-115).

Drawing on the core themes of How People Learn, I define deep learning as learning that promotes the development of conditionalized knowledge and metacognition through communities of inquiry. Throughout this book I use the term depth education to refer to the particular model of deep learning developed in this book.

Although there is no intrinsic connection between deep learning and e-learning, the two are intertwined in the depth education model presented here. From a practical standpoint, deep learning and e-learning are inseparable. It is simply not economically feasible to provide a broad cross section of students with depth educational curricula unless Internet technologies are used. If medical schools and top-tier Ph.D. programs are seen as examples of how deep learning can be successfully embedded into a traditional academic curricula, then our experience to date is that deep learning does not come cheap. Hence, technology becomes a critical factor.

Deep learning is rooted in the formation of conditionalized knowledge, metacognition, and communities of inquiry.

Conditionalized Knowledge

Conditionalized knowledge refers to knowledge that specifies the contexts in which it is useful. It is knowledge that recognizes its own limitations. Students gain conditionalized knowledge only when they have the opportunity to apply disciplinary concepts and methodologies to varied contexts and knowledge domains.

Surface learning, by contrast, focuses on mere description and textbook application of disciplinary concepts and methodologies. It offers little opportunity for students to discern when those concepts and methodologies are relevant to more realistic problems and other knowledge domains. The authors of How People Learn note, "Many forms of curricula and instruction do not help students conditionalize their knowledge. . . . It is left largely to students to generate the condition-action pairs required for solving novel problems" (Bransford, Brown, and Cocking, 1999, p. 31).

Problem-based learning is a key instructional strategy for the development of conditionalized knowledge. It not only has the advantage of introducing ideas "when students see a need or reason for their use" (Bransford, Brown, and Cocking, 1999, p. 127) but also emphasizes the relevance of course content to real life, thus imbuing instructional objectives with instant credibility. For example, the physician's ability to diagnose medical problems is enhanced when medical students are exposed to problem-based learning, in place of traditional lectures, during the first year of medical school (Hmelo, 1995). It is no coincidence that forward-looking distance learning initiatives--like Cognitive Arts (working with Columbia and Harvard) and (involving Carnegie Mellon University, Columbia University, the London School of Economics and Political Science, Stanford University, and the University of Chicago)--use a problem-solving format for their courses instead of traditional lectures and readings (Carr, 2000d; Gajilan, 2001; McCormick, 2000).

If faculty understand their teaching responsibilities primarily in terms of "covering the material," that leaves them with little time and energy to help students to conditionalize their knowledge of a discipline. This sacrifice of depth for breadth is a prominent characteristic of most higher education curricula. Textbook publishers who seek to differentiate their offerings in the marketplace by adding new and more advanced topics to each successive edition exacerbate this problem. Even sensible instructors who respond to this kind of content inflation by making selective use of textbook material do not have the advantage of building out from a depth treatment of a discipline.


Metacognition refers to the ability to think about thinking--the art of thinking. It involves being able to monitor and reflect on one's level of understanding, to know when this understanding is not adequate, and to know how to remedy this inadequacy (Bransford, Brown, and Cocking, 1999). Metacognition is about developing students' own self-awareness as learners and empowering them to manage their own development as learners--learning how to learn. The development of critical thinking skills and the ability to articulate and reflect on ideas are foundational to the art of thinking. Furthermore, students who develop their meta-cognitive skills are better able to transfer learning that takes place in one knowledge domain to other domains.

Communities of Inquiry

I use the term communities of inquiry to refer to communities of practice (or learning communities) in academic settings (see Wenger, 1998). Much learning in everyday life takes place in communities of practice (Lave and Wenger, 1993; Wenger, 1998; Wenger and Snyder, 2000). These formal and informal communities criss-cross the entirety of social life and are particularly important for the experience of learning (Brown and Duguid, 1996).

One could argue that the genius of the residential college experience is that it places students in a rich array of intersecting communities of practice organized around the themes of intellectual, social, and personal development. As Gregory Farrington (1999), the president of Lehigh University, notes:

Undergraduate life at a residential college is as much about learning to live as it is about learning from books. What is most impressive about the residential college experience is that it works so well and achieves both goals so effectively. Eighteen-year-old students nervously tiptoe onto campus at the start of their first year, and four years later they march out--sometimes after a bit of prodding, to be sure, but generally with the motivation, education, and confidence needed to take on the world. The transformation is remarkable and is as much the product of the general intellectual and social experience on-campus as the result of what goes on formally in the classroom. For these students, late-night discussions are much of what college is about, and the role of the football team is truly important.

Although older students in traditional graduate programs or nontraditional adult education programs hardly require the diverse array of communities of practice that are found in an undergraduate environment, it would be a serious mistake to discount the value of more focused communities of inquiry for their educational experience. From graduate students debating an arcane disciplinary issue over a pitcher of beer to a close-knit cohort of working professionals in an accelerated MBA program, communities of inquiry play an important role in adding depth to and contextualizing an academic curriculum.

As Brown and Duguid (2000) emphasize, learning involves a process of "enculturation" that engages students with concepts and communities of practice. "Teaching and education, from this perspective, are not simply matters of putting students in touch with information. . . . Rather, they are matters of putting students in touch with particular communities. The university's great advantage is that it can put learners in touch with communities that they don't know about" (p. 220).

It is interesting that Carole Fungaroli, author of Traditional Degrees for Nontraditional Students (2000), urges working adults to attend college but warns students against distance education. The on-line students whom she has encountered report an educational experience marked by discouragement and isolation: "They hated what they were doing, but they just wanted to get those three credit hours" (" New Book Says," 1999, p. A47). The virtual campus, according to Fungaroli, fails to deliver the most important aspect of higher education--inspiration.

"At its best, the traditional campus can make you fall in love with something. One of the things missing from the distance learning area is passion. . . . When you get on campus, you might find out that you're all fired up about something that you might not have thought about before. Distance learning allows you to stay in your rut" (p. A47).

Deep Learning and Cognitive Apprenticeship

Cognitive apprenticeship is the learning methodology best suited to achieve the aims of deep learning. This approach attempts to integrate the salient features of the apprenticeship model--which has proven so effective in transmitting skills down through the generations--into the structure of a formal curriculum. From the perspective of cognitive apprenticeship, the art of thinking is no different than the art of becoming a musician or a surgeon.

In their seminal article on cognitive apprenticeship, John Seely Brown, Allan Collins, and Paul Duguid (1989) observe that the development of knowledge proficiencies is very similar to the manner in which artisans learn to use a tool. One does not become an artisan by merely possessing a tool and being acquainted with its function, and the same is true for those who acquire knowledge (that is, facts, definitions, concepts, and methodologies) but really cannot use it.

People who use tools actively rather than just acquire them . . . build an increasingly rich implicit understanding of the world in which they use the tools and of the tools themselves. The understanding, both of the world and of the tool, continually changes as a result of their interaction. . . .

Learning how to use a tool involves far more than can be accounted for in any set of rules. The occasions and conditions for use arise directly out of the context of activities of each community that uses the tool, framed by the way members of that community see the world. . . . Because tools and the way they are used reflect the particular accumulated insights of communities, it is not possible to use a tool appropriately without understanding the community or culture in which it is used. [p. 33]

The concept of cognitive apprenticeship modifies the traditional apprenticeship model in three important respects. First, cognitive apprenticeship is focused on the development of cognitive skills, or the art of thinking, and not on skills associated with a specific craft or attached to particular roles in the workplace. Second, cognitive apprenticeship encourages the application of knowledge and skills in a variety of contexts, enabling students to abstract general principles from their experiences of learning by doing. Third, unlike the traditional apprenticeship model, the elements of cognitive apprenticeship can be integrated into a formal curriculum and are not confined to workplace exigencies or the latest fashion in business trends (Collins, Brown, and Newman, 1989). Graduate programs in the sciences are perhaps the closest approximation of the cognitive apprenticeship model in higher education (Brooks, 1996).

Collins, Brown, and Newman (1989) have identified six teaching methods that facilitate cognitive apprenticeship: modeling, coaching, scaffolding, articulating, reflecting, and exploring (see also Collins, 1991; Jonassen, 1996; and Teles, 1993).


Modeling is the externalization of internal cognitive processes. Essentially, the teacher puts her mind on display, walking her students through her approach to a problem and making explicit the internal steps she took and strategies she used along the way. Modeling is about teaching students how to think, by means of observation, in order to disclose patterns of thinking and approaches to problem solving. Modeling need not be confined to the teacher's own problem-solving approaches; it should also highlight successful problem-solving approaches developed by students. One might think of modeling as storytelling about problem solving, critical analysis, or the creative development of alternatives.


When coaching, the teacher becomes the classroom observer. Whereas modeling emphasizes the student's role as observer, coaching requires teachers to observe students in the performance of some task or skill (usually in the context of problem solving) and to ask questions or to offer feedback on the student's performance. Coaching resembles Socrates' dialogical method in that the teacher adapts her approach based on something that is said or done by the student.


Scaffolding is a concept drawn from constructivism. It refers to the supporting roles of the teacher and the student's learning community in facilitating the construction of knowledge. This can take the form of a teacher helping a student complete a task that he is unable to perform or building a structure for hints and helps in the curriculum. Scaffolding can also take the form of participating in a community of inquiry that supports the student in the knowledge construction process (Hogan and Pressley, 1997). In this respect, scaffolding can be thought of as building opportunities for student-to-student modeling and coaching in the curriculum.


The process of articulation allows students to practice their skills in converting tacit knowledge to explicit knowledge. The effect is to draw out the internal reasoning processes of students by encouraging them to articulate their response to an idea or their approach to a problem. Articulation has other benefits besides the intrinsic rewards of learning how to make tacit knowledge explicit; for example, it makes knowledge more readily available so that it can be employed in different tasks, it helps students apply similar problem solving strategies in different contexts, and it encourages students to see an idea from the perspective of another student (Collins, 1991). Articulation also allows the teacher to draw on the thinking of students to serve as a model for their classmates. In this way, the students' own knowledge contributions become a subject for classroom analysis.


The process of reflection is essentially a debriefing process that can take the form of comparing notes or conducting an "abstracted replay" of one's thought processes. Because reflection encourages students to note the ways in which their performance differs from other students, it helps them compare their own approaches to critical analysis and problem solving with those of other students, as well as the teacher. It is a highly beneficial teaching tool because it makes what the student says or does the object of instruction.


Exploring, the final method of cognitive apprenticeship, encourages students to tackle new knowledge domains and problems on their own. One can think of exploration in terms of the progressive withdrawal of the scaffolding intended to support the students. The teacher's role is to encourage students to set achievable goals, to form and test hypotheses, and to make discoveries on their own (Collins, 1991). This responsibility of educators to set students on the search for new territory--in Piaget's words--requires us to reexamine the important role of curiosity in learning.

Deep Learning and Intellectual Curiosity

Curiosity is a fundamental learning skill. Yet it is perhaps the most underrepresented skill in higher education curricula.

It may seem odd to consider curiosity a skill, and yet it is certainly no less a skill than listening, speaking, or writing. Intellectual curiosity--like skills in articulation, reflection, and critical thinking--is learned through observation and practice. One learns (or more accurately, relearns) curiosity by being in the company of the curious. No lecture, textbook, computer program, or Web site can impart this skill. It is learned only through apprenticeship experiences with skillful thinkers and through participation in a community of inquiry.

The lecture, an exceptionally efficient mechanism for conveying information, has many liabilities when it comes to developing the skill of intellectual curiosity. Content is usually presented in pre-packaged doses in a take it or leave it fashion. Consequently, learning in class often becomes little more than an information transaction, where the teacher deposits information into the accounts of students (Freire, 1995).

The use of multimedia technologies in the classroom, like PowerPoint presentations, has only intensified the perception that knowledge is neatly portioned and served up in small bulleted points. The instructor's desire to get through the slides can easily crowd out opportunities to engage students in critical dialogue about the material. Students usually ask questions of clarification instead of probing the overall relevance or adequacy of the discussion at hand. More often than not, the question What will be on the exam? overshadows the larger questions: Why is this material important to me? What are the built-in limitations of this material? How will this material enhance my current skills and knowledge base?

It could be argued that Internet services that pay students to take extensive notes on a professor's lecture in order to make them available to other students on their Web site are responding to a situation created by educators themselves. The furor over posting lecture notes on Web sites is probably related more to the frustration that students can pass a course without attending class than to concerns over theft of intellectual property. Unlike the medieval scholars who lectured in darkened rooms so that their students could not take notes, in order to protect their intellectual property (Shapiro and Varian, 1999), contemporary professors are rarely concerned with students stealing their ideas. Most feel deeply flattered by assiduous note-takers--at least until now.

If class attendance is merely about an information transaction between teacher and student, then posting lecture notes on the Internet makes perfect sense. Students' skipping class and getting notes from the Internet is more intellectually honest than the teacher force-feeding information to students and looking the other way while students multitask the classroom environment.

Multitasking means doing several things at once. One has to spend only a few minutes in a typical lecture class--particularly a large one--to observe that attentive listeners and note-takers are in short supply. Daydreaming, reading assignments for other classes, writing notes to friends, and catching up on needed sleep are more common classroom activities. High-tech classrooms may be more appealing, but they also provide more sophisticated multitasking opportunities. For example, it is not unheard of for students at Columbia University's School of Business to interrupt a lecture with whoops of joy or anguished sighs. Yet the content of the professor's lecture has nothing to do with these outbursts. Instead, students are responding to the stock trades they are conducting on their computers (Wilgoren, 2000). A professor at Yale Law School recently lamented in the editorial pages of the New York Times that his students "went ballistic" when he requested that laptop computers be used for note-taking and not for playing video games or surfing the Web (Ayres, 2001).

Often the only real opportunity to set one's curiosity free in the traditional college classroom is while writing a research paper. Although most professors welcome papers that are creative, innovative, and show some risk-taking, the die is cast by the time the student gets around to choosing a topic and writing the paper. All the incentives are in place to reward those who pick manageable topics--which translates roughly to "It's been done hundreds of times before" and "It's best to play it safe."

It is not surprising that such research exercises have become so superficial that it is easy to get prepackaged research papers over the Internet from term paper mills. These sites allegedly offer materials for background research, but Internet URLs like and leave nothing to the imagination. There are even Web-based services, like or IntegriGuard (, that analyze student papers against a broad database of sample research papers for the purpose of alerting professors to plagiarized material (Carnevale, 1999c; Guernsey, 1998b).

What is remarkable about all this is not that some students seek the easy way out but rather the pronounced lack of imagination in the design of research assignments, which permits the recycling of the same material year after year with little difficulty. Educators' attempts to cope with the problem by using electronic plagiarism services will ultimately have a corrosive effect by extending the hermeneutic of suspicion to the teacher-student relationship.

Deep Learning and Embedded Assessment

A robust assessment strategy is required in order to build vital communities of inquiry. Apart from the process of honest and constructive feedback, talk of learning community is vacuous, amounting to little more than a support group of the ten-steps variety. An assessment strategy that focuses on summative evaluation, rather than formative assessment, denies students meaningful opportunities for intellectual challenge and growth.

Depth education uses an assessment model that I call embedded evaluation. Embedded evaluation proceeds from three foundational principles: (1) learning to assess others can be just as helpful as receiving assessment; (2) assessment should have both a private and a public dimension; and (3) evaluations should not be anonymous.

First Principle

The first principle of embedded evaluation emphasizes the value of giving and getting criticism in a respectful and gracious manner. This is no small task! There is an abundance of anecdotal evidence that electronic exchanges of a critical nature between students often appear harsh and inconsiderate. The emotional restraints built into face-to-face communication are largely absent from such exchanges, and in addition, the resources of gesture, voice, and inflection are not there to soften the rough edges of critical words. Because no one cares to be insulted, individuals who are adept at using words to convey both the intended meaning and a respectful tone will have a better than even chance of succeeding in the collaborative atmosphere of the twenty-first-century workplace. Gartner predicts that by 2004, virtual teams will be doing 80 percent of the knowledge-related work in the world's 2000 largest companies (Prencipe, 2001). Even if videoconferencing becomes widespread, it will only supplement--not supplant--text-based electronic communication. The ability to use text-based communication to assert opinion, offer recommendations, and convey nuance will only grow in importance in the coming years.

Second Principle

The second principle of embedded assessment is that assessment should have both a private and a public dimension. The evaluation of individual work must necessarily be "for your eyes only"--accessible only to the instructor and the student who is being evaluated. By contrast, the evaluation of collaborative work products should be a kind of community property of the entire class. Such a peer-to-team assessment model also facilitates the use of guest evaluators (for example, selected alumni, faculty from other departments) to add depth and diversity to the evaluation process.

Third Principle

The third principle of embedded assessment is that neither individual nor group evaluations should be anonymous. The primary failing of anonymous evaluations is that they do not facilitate responsible feedback and prepare students for performance evaluations in the real world. In addition, they limit the instructor's ability to factor the quality of a student's evaluation of others into his or her own course grade. In order to reduce the natural discomfort associated with submitting an evaluation with one's name on it, the instructor should emphasize the importance of constructive feedback in the learning process and the need to balance negative assessments with positive comments and suggestions.

The Shortcomings of Standard Assessment

Because embedded evaluation seeks to measure a student's progress in developing conditionalized knowledge and metacognitive skills, it places considerable weight on the student's ability to articulate and reflect on his own developing knowledge base. This is quite different from standard assessment tools, such as the multiple choice exam, that are inherently indifferent to how and why students arrive at a particular answer. Although well-designed multiple choice exams occasionally succeed in evaluating the reasoning behind an answer, the strategic focus of most students in taking such exams is to stimulate recall and eliminate options. This approach rewards those who are able to absorb and recall information quickly. Such tests send the message to students that the important thing is to recognize the correct answer. This is the "payoff " of a student's tool-box of skills and concepts. Hence, the process of evaluation seems more like a contrived game than an invitation for growth. From this perspective, the well-known tendency of students to forget information quickly after a test is perfectly rational. Why clutter your mind with details whose usefulness largely disappears once you take the exam?

One could argue that distance education programs are well positioned to lead the way in developing effective mechanisms for assessment--particularly project-based assessment tools (Carnevale, 2001a). Yet a pronounced bias in favor of standard assessment tools is evident among distance education providers who boast about the array of nifty tools to create and grade exams of the true-false, multiple choice, matching, and fill-in-the blank varieties. These tools are really only viable for developing practice tests. Graded tests must necessarily be administered in a proctored environment; otherwise, there is nothing to prevent students from keeping their textbook or lecture notes right in front of them when they take the exam. While there is no doubt that practice tests are helpful in preparing for a graded exam, is this really what we mean by formative assessment? Should formative assessment be focused on enhancing a student's exam-taking skills? Or should the focus be placed on how well a student understands a particular knowledge domain and manages the process of learning?

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