Innovations in Instructional Technology

Essays in Honor of M. David Merrill

J. Michael Spector, Celestia Ohrazda, Andrew Van Schaack, David A. Wiley, J. Michael Spector, Celestia Ohrazda, Andrew Van Schaack, David A. Wiley

• Editore: Routledge
• Anno: 2006
• ISBN:
  9781135616366
• Edizione: 1
• Argomento: Informatica
• Categoria: Modellazione e design di dati

M. David Merrill has been active in the field of instructional technology for almost 40 years. His contributions range from basic instructional principles and instructional design theory to development and implementation of learning environments. Innovations in Instructional Technology is a collection of original essays written by leading scholars and practitioners who have worked with and been inspired by Professor Merrill. The chapters in this book represent a sampling of key innovations in the instructional technology field and include knowledge of how people learn, how people solve problems, how designers conceptualize learning spaces, how teachers implement learning activities, and how evaluators assess outcomes.This volume is divided into five basic areas of research in instructional technology, mirroring the diverse contributions of Dr. Merrill's work:
*four chapters on learning objects and the notion of reusable components;
*three chapters that discuss fundamental aspects of learning and the design of instruction;
*three chapters that address innovations in the area of assessment, evaluation, and model validation;
*three chapters that concern theories of learning and instruction; and
*three chapters on instructional design practice.The book concludes with a chapter outlining Dr. Merrill's responses to challenges, comments, and questions on the future of the field--ranging from the notion of initial passions with regard to instructional technology to connections between theory and practice to questions of conscience--from an expert panel comprised of many of the contributors to the book.As Dave Merrill's work will continue to be required reading for students of instructional technology, Innovations in Instructional Technology is a book that will appeal to students, researchers, and practitioners in the field.

Chapter
1

Learning Objects in Public and Higher Education

David A. Wiley

Utah State University

REUSE IS NOTHING NEW

Reuse of educational materials is not anew idea in education; all teachers are familiar with resource reuse. To varying degrees we reuse journal articles, lecture notes, slides, textbooks, overheads, lesson plans, stories, visual aids, and construction-paper bulletin-board letters in our teaching. Students are more familiar than we might expect with the notion of reuse of educational materials. Occasionally one can be heard to complain that reuse is occurring on too grand a scale (“he’s been using the same lecture notes for ten years?!?”).

The reason most teachers would prefer to teach a class they’ve taught several times rather than a class they have never taught before stems solely from the virtues of reuse. If materials exist from a previous version of the course, preparation of the new course can be faster (i.e., development efficiency can increase). Course materials can be better, as existing materials are improved based on experience with their prior use (i.e., development effectiveness can be increased). Additionally, because there are fewer new materials to be developed, more attention can be paid to these new materials (i.e., development effectiveness can be increased further). In short, teachers do not want an entirely new preparation because they have nothing to reuse. Every teacher knows and appreciates the benefits of reuse, so why are teachers excited by the idea of knowledge objects or learning objects?

THE CONVENTIONAL VIEW OF LEARNING OBJECTS

There is a saying in commercial instructional development that those who would contract for the design and creation of educational materials must pick two of the following three contract criteria: cheap, fast, and good. Materials can be developed quickly and with high quality, but only at high cost; materials can also be developed quickly and inexpensively, but only at low quality, and so on.

Learning objects promise to enable the fulfillment of all three criteria simultaneously by making educational resources more reusable. Learning objects are generally defined as educationally useful, completely self-contained chunks of content. The most popular operationalization of this definition is a three-part structure comprised of an educational objective, instructional materials that teach the objective, and an assessment of student mastery of the objective.

Once a collection of such learning objects exists, and has been stored and cataloged in a digital library or other storage and indexing facility, instructional designers may select and aggregate learning objects from within the collection. Intelligent or automated systems may also be designed that select and aggregate learning objects according to given criteria for individual use.

The threefold structure enables a number of innovative uses of learning objects. For example, designers or systems may utilize assessments from the learning object structure to create pretests. For all individual assessments that learners pass, designers or systems may then remove associated instructional materials, lengthening the time and cost of an individual’s instructional program. As another example, designers may develop several learning objects that teach to the same educational objective, varying only aesthetic aspects of the objects. Designers, systems, or learners themselves may then choose one of several instruction-function-equivalent objects based on preference. This strategy can enable basic learner choice without jeopardizing instructional designers’ intents.

There has been significant interest in using intelligent systems together with learning objects in order to address scalability issues relating to instruction. When intelligent systems are used to select and organize media, as well as provide feedback and grading, enrollment bottlenecks due to the perpetuation of conventional teacher-to-student ratios into online environments may be overcome. In previous writing I have called this bottleneck the teacher bandwidth problem (Wiley, 2002). The largest problem with scaling distance education up to thousands or more students is not a bandwidth problem of how much data may be served through scarce Internet connection resources, but rather a bandwidth problem of how many students may be served through scarce teacher resources. Intelligent systems attempt to alleviate this bandwidth problem by replicating teacher functionality in software—for example, automating the grading of student work or the process of assembling educational resources for student use.

Merrill’s instructional transaction theory (ITT) and knowledge objects exemplify this idea of intelligent, automated instruction (Merrill, Li, & Jones, 1991). ITT simulations both can be built from reusable components and can automatically teach, coach, and assess learners. The future described in Merrill’s (and others’) vision is an educational technology “wonderland.” It may even be achievable. However, wonderland is quite a conceptual distance from where mainstream educators are right now, and very few have proven willing to jump down the rabbit hole. The next section describes some reasons why.

PROBLEMS WITH THE CONVENTIONAL VIEW

The popular definition of learning objects as educationally useful, completely self-contained chunks of content, together with the three-fold operationalization already described, is problematic in each of its three components.

Educational Usefulness

The educational usefulness of a learning object is not guaranteed by its strictly following a design template (e.g., having an objective linked to instruction and an assessment). Conforming to an architectural standard does not guarantee that an artifact like a learning object will be educationally useful. This would be like implying that a piece of music that conforms to the sonata structure will be good art, and is simply not the case. There are many compositions that conform to the sonata structure which are not particularly artful at all. On the other hand, there are many artful compositions that do not follow the sonata structure at all.

The reader may quickly desire to point out that art is to some extent in the eye of the beholder, and indeed it is so. Likewise, educationally useful “is in the eye of the learner.” If a learning object teaches something a learner has already learned, or something a learner has no immediate desire to learn, then the resource will not be educationally useful to the learner despite its structure and organization. However, if a resource relates directly to a topic a learner has an immediate desire to learn, then the resource will likely be educationally useful to the learner, despite its architecture.

Of course, educational usefulness is also “in the eye of the teacher.” A digital library full of downloadable sets of weather and geographical information system data will be of little interest to the middle school music teacher. Likewise, an online catalog of song lyrics and guitar accompaniments will not likely satisfy the needs of the graduate chemistry professor.

Complete Self-Containment

Assuming that learning objects are completely self-contained educational re sources implies that, aside from their use, nothing else is necessary for student learning—including social interaction. This rejection of the importance of human interaction is extremely problematic for teaching and learning. Collaboration (Nelson, 1999), cooperation (Johnson & Johnson, 1997; Slavin, 1990), communities (Brown, 1994), social negotiation (Driscoll, 1994), and apprenticeship (Rogoff,1990) are core instructional strategies for achieving a variety of learning outcomes.

If we believe Gagné’s (1985) position that different learning outcomes require different instructional conditions, and we believe that Bloom and Krathwohl (1956) identified a useful hierarchy of learning outcomes, then we may combine these two insights in the following way: The family of instructional strategies that will most likely facilitate learning is different for each family of learning outcomes in Bloom’s taxonomy.

It seems to me that one of the ways in which the conditions change as one “climbs” Bloom’s “ladder” of learning outcomes is that social interaction becomes increasingly important. For example, a learner does not need to engage in small-group negotiation activities to learn (memorize) the capitals of the 50 states. Individual drill and practice exercises will provide effective, efficient mastery. However, we would not expect students to learn to make complex ethical decisions (evaluations) through isolated drilling with flashcards. We would generally imagine this type of outcome being learned in a small-group setting where discussion, argument, and debate played key instructional roles.

It therefore makes sense to believe that learning objects as conventionally understood—completely self-contained educational experiences—will perform well for outcomes at the bottom of Bloom’s taxonomy and decrease in efficacy as higher order outcomes are taught. This may be one reason why learning objects have not been used widely in higher education. Higher educators like to believe that their role is to teach problem solving, critical thinking, and complex reasoning skills. Whether or not this occurs in classroom practice is a separate issue. In the many talks and workshops I have given on learning objects, my experience has been that when faculty members first encounter the idea, many intuitively grasp this weakness of the conventional learning objects approach to reuse and balk on grounds that the paradigm does not provide sufficient pedagogical flexibility.

Chunks of Content

The term learning object is synonymous with content. However, Merrill’s component display theory attempted to steer the field in another direction—toward reusable strategy objects. His analogy went like this: “Think of the to-be-taught content as data for a computer program to operate on, and think of instructional strategies as the algorithms that manipulate data in the computer program.” It is an insightful critique of instructional design and technology curricula that while computer science programs always teach data structures and algorithms together, our programs largely exclude detailed instruction in content-specific or domain-specific areas.

Roschelle and colleagues (2000) pointed out that we should not expect to find that learning objects are highly reused, because research has shown that the struc tures on which they are modeled—the software objects of object-oriented programming (OOP)—have failed to be significantly reused for decades now. Although Roschelle accurately called to our attention that significant reuse of educational components is not occurring, this need only be a problem for instructional technologists if we confine our conception of learning objects to content.

The issues that public school and university educators have with learning objects, like those just described, are in some ways unsurprising. The majority of work done on learning objects has happened in military and corporate settings, and the conventions of corporations and the military are not the same as higher and public education’s conventions, although I believe these educational groups have much more in common than they have that divides them. A great need exists for individuals to step forward and rethink learning objects in terms of the conventions of public and higher education.

LEARNING OBJECTS IN PUBLIC AND HIGHER EDUCATION

This section explores potential resolutions to the problems already raised.

Changing the Conventional View of Learning Objects

For public and higher education audiences, we need to at least enable the kind of reuse that is already occurring in offices around the world. Who would adopt an innovation whose proponents proclaimed, “It doesn’t do much yet, but one day soon this technology will really enable a lot of things you want! I should warn you, though, that once you adopt it you won’t be able to do any of the things you currently do.” Until the learning objects paradigm at least speeds up preparing a course, as described in the introduction to this chapter, no teacher or professor will want to use it.

Going back to the list from the beginning of the chapter, none of the journal articles, lecture notes, slides, textbooks, overheads, lesson plans, stories, visual aids, or construction-paper bulletin-board letters are made up of an objective coupled with instruction coupled with an assessment. Public and higher education need a definition of learning object that encompasses the types of resources they already use—not one that excludes them as the conventional definition does. Wiley and Edwards (2002) suggested another definition for learning object: Any digital resource that can be reused to mediate learning is a learning object. Although teachers may not be currently using digital versions of the resources in the list given earlier, they could be. There are compelling reasons to encourage them to make this one change to their practice.

South and Monson (2000) explained why it is important to encourage faculty to get their materials out of their filing cabinets and onto servers—if an individual faculty member gets such great benefit from reusing their materials, could not another faculty member get similar benefits from those materials? South and Monson described a nightmare of instructional media stored in a central location on campus that had to be somehow located by the professor, scheduled for use, wheeled across campus on a cart, set up in the classroom, and finally used, only to have the entire process reversed at the end of class. When these resources were digitized and placed on a central university server, location became a matter of Web searching, scheduling, and the cart simply disappeared, and setup became a matter of “bookmarking.” Now 15 professors could use the resource at the same time from classrooms where computers and proje...

Indice dei contenuti

• Cover
• Half Title
• Full Title
• Copyright
• Photo
• Contents
• Foreword
• Preface
• Acknowledgments
• About the Authors
• Innovations in Instructional Technology: An Introduction to This Volume
• 1 Learning Objects in Public and Higher Education
• 2 Authoring Discovery Learning Environments: In Search of Reusable Components
• 3 Supporting the Mobility and the Adaptivity of Knowledge Objects by Cognitive Trait Model
• 4 A Holistic Pedagogical View of Learning Objects: Future Directions for Reuse
• 5 Designing Model-Centered Learning Environments: Hocus-Pocus or the Focus Must Strictly Be on Locus
• 6 Problem Solving: The Enterprise
• 7 Elementary Principles of Design Languages and Design Notation Systems for Instructional Design
• 8 Teamwork Skills: Assessment and Instruction
• 9 Design Science as a Frame for Evaluation of Technology in Education and Training
• 10 Validating Instructional Design and Development Models
• 11 Cognition and Instructional Design for Problem-Based Learning
• 12 New Instructional Theories and Strategies for a Knowledge-Based Society
• 13 Learning Theories and Instructional Design: A Historical Perspective of the Linking Model
• 14 Foundations for Instructional Design: Reclaiming the Conversation
• 15 Instructional Design Is Not Peanuts
• 16 Confessions of a Practitioner
• 17 The Role of Mentoring: Slaying Dragons-An Interview With Dr. Merrill
• Epilogue: Questioning Merrill
• Glossary
• Author Index
• Subject Index