Facilitating the Development and Use of Interactive Learning Environments

Charles P. Bloom, R. Bowen Loftin

• Publisher: CRC Press
• Year: 2020
• Print ISBN: 9780805818512
• eBook ISBN: 9781000723748
• Edition: 1
• Topic: Psicología
• Subtopic: Psicología aplicada

Intelligent tutoring technology is on the verge of a breakthrough into the mainstream of training and education. Over the past 25 years, researchers have learned not only what it takes to develop an effective intelligent tutoring system (ITS), but also what it takes to deploy and use one--the true barometer of a technology's success. This volume brings together a cross-section of ITS researchers from academia, industry, and the government to talk about their experiences in ITS development and technology transfer, both successful and unsuccessful. Section 1 is devoted to detailed descriptions of tools and methods ITS developers can employ during development to facilitate technology adoption. It includes discussions of the paradigmatic change in learning and instructional design that ITS fosters, techniques for gathering design information for ITS domains where empirical or knowledge-based methods are inappropriate, and the conduct of cost-benefits analyses to facilitate ITS funding decisions. Sections 2 and 3 offer numerous case studies of ITS deployment from both industry and the government. All of these case studies--regardless of outcome--provide valuable insights into the dos and don'ts of ITS technology transfer. This volume will be an invaluable resource for all researchers and developers of ITS, as well as for managers and personnel in education and training organizations who must adopt and use ITS technology, and information systems and computing support organization professionals who must support it if it is to succeed.

PART

I

TOOLS OF THE TRADE

CHAPTER
1

DEVELOPING LEARNING TECHNOLOGY IN PRACTICE

William J. Clancey

Institute for Research on Learning

The US West workshop on Intelligent Tutoring Systems (ITSs)¹ examined the state of the art of instructional programs, focusing on the design and deployment of systems using Artificial Intelligence (AI) programming methods. Our objective was to appraise the progress in bringing advanced research ideas to practice and to understand the barriers and opportunities for using ITS technology in industry today.

ITSs were presented from US WEST, NYNEX, Bellcore, NASA, Galaxy Scientific, Honeywell, and the Universities of Massachusetts, Colorado, and Pittsburgh. Applications included the troubleshooting of electronic circuits, customer telecommunications operations, COBOL programming, space shuttle payload operation, introductory kinematics, cardiac arrest diagnosis and treatment, and kitchen design. These programs are distinguished from conventional computer-based training (CBT) by the use of qualitative modeling techniques to represent subject material, problem-solving procedures, interactive teaching procedures, and/or a model of the student’s knowledge (Clancey, 1986, 1987, 1989; Self, 1988).

This chapter is based on a summary talk prepared during the meeting for presentation the afternoon of the last day to stimulate group discussion. The stance is critical and yet confident about a new beginning: As ITS research struggles in a world of more limited research funding, affordable multimedia technology makes it possible to realize the early 1970s vision of IT assistants. My primary observation is that ITS technologists have a dual objective: to develop flashy multimedia models that can be used for instruction, and to change fundamentally the practice of instructional design. This second objective—promoting organizational change—is rarely mentioned and lies outside the expertise of most academic design teams. Reflecting the maturity of the technical methods, presentations at the workshop showed an emerging interest in effective design processes for everyday business, school, and government settings. Researchers are beginning to consider how difficulties in getting people to understand and adopt ITS methods are problems of organizational change, not just technical limitations.

On the other hand, researchers understand that the greatest value of ITS technology will not be realized if AI methods are used merely to replace existing lectures or computer-based training and, consequently, evaluated solely by the standards of existing training. Indeed, many ITS designers in corporations are pressed to adopt the metrics of cost and efficiency that fit a transfer view of learning and static view of organizational knowledge. If the traditional views of learning and assessing instructional methods are applied alone, the value of ITS approaches for changing classroom instruction may not be accepted or realized.

Creatively exploiting ITS technology—to change the practice of instructional design—requires a better understanding of how models relate to human knowledge. Relating the insights of the cognitive, computational, and social sciences involves changing how scientists, corporate trainers, and managers alike think about models, work, and computer tools. Broadly speaking, models comprise simulations, subject-matter taxonomies, scientific laws, equipment operational procedures, and corporate regulations and policies. Instructional designers and developers of performance support tools must better understand how the interpretation in practice of such descriptions is pervaded by social concerns and values (Ehn, 1988; Floyd, 1987; Greenbaum & Kyng, 1991). Social conceptions of identity and assessment influence choices people make about what tools to use, methods for gaining information, and who should be involved in projects. Judgments about ideas reflect social allegiances, not just the technical needs of work. This broader perspective on how participation and practice relate to technology moves ITS research well beyond the original focus in the 1970s on how to create models that represent different kinds of processes in the world. If we are to inquire about what models should be created and who should create and use them, we must consider new research partnerships, new design processes, and new computational methods for facilitating rather than only automating conversations.

HOW DO WE MOVE TECHNOLOGY INTO THE MAINSTREAM?

Participants in the US West workshop experienced a striking paradox: Their instructional programs are based on methods developed over nearly 25 years in internationally known computer science and psychology research laboratories, but, effectively, no one in the multibillion-dollar industry of corporate training uses this methodology. Instead, computer-based training is barely beyond the page-turning quiz generators of the 1960s, giving all computer approaches a problematic reputation.

Technically, there is a substantial gap between academic laboratory software and most training systems used in business today. Even off-the-shelf multimedia tools are at least a decade behind ITS representation and modeling techniques. Fortunately, the movement to object-oriented or component-based commercial software provides a means for sharing tools and models, but both the technological and collaboration infrastructures are still misaligned in these two cultures: Industry is only now accepting the windows and menus interface familiar to scientists in 1980 and still views Lisp, an established tool for three decades in academia, as a foreign language. Research funding was often conceived by corporations as throwing water on someone else’s garden, without establishing ways of learning new methods and perspectives (epitomized by Xerox’s failure to commercialize the personal computer). Ironically, funding for AI in general contracted in the 1980s under a general complaint that the work was overhyped and not relevant to pressing problems. Such complaints bring out the real mismatch between past research and everyday business, constituting a gap in current understanding:

• Does industry understand the generality of qualitative modeling methodology to science and engineering, or is the ITS approach viewed as just a smarter page turner?

• When development costs for ITS are appraised as being too high, are the multiple uses and reusability of models considered?

• Is it surprising that ITS programs are not immediately embraced by users when participation in the projects has not included conventional instructional designers, graphic artists, workers, and managers?

There are many reasons why the ITS methods of the mid-70s are not in use today. Indeed, the reasons are overwhelming:

• The computational methods are new, a radical departure from numeric programming.

• Graphic presentations required a change in hardware and software from traditional suppliers (especially IBM).

• The use of workstations in research applications predated their availability in industry by nearly 15 years (when prices dropped by more than tenfold).

• The view of knowledge and learning in 1970s’ cognitive science (and embedded in the design of ITS) is not congruent with the views of workers and managers (Nonaka, 1991).

• A “delivery” mentality for software engineering in academia and industry alike prevents a participatory relation between researchers and their sponsors.

• In the late 1980s, the workforce became more distributed, with separate business units and “integrated” (nonspecialized) employees, making centralized classroom training less appropriate.

Of all these considerations, one of the most important is the shift in how knowledge and learning are conceived. From the well-known situated-learning perspective, learning is viewed as something occurring all the time and having a tacit component (Lave & Wenger, 1991; Clancey, 1995, in press). Concepts are not merely words and definitions but ways of coordinating what we see and how we move. Understanding is spatially, perceptually, and socially embedded in activity. Activities are not merely tasks but roles, identities, and ways of choreographing interpersonal interaction. Problems are constructed by participants, not merely given. “Trouble” is defined in conversations about values, how assessments will be made, and who is participating. In these terms, documents and tools are not specified and given but open to interpretation, having new meanings and uses in changing circumstances—according to workers’ experience, not merely packaged by teachers and rotely digested. Communication with coworkers is viewed as central, especially by informal relationships of friendship, developing through meetings and chance encounters (Stamps, 1997).

None of this makes the articulation of principles, rules, and policies in written text irrelevant. Rather, this situated-cognition analysis reveals how such descriptions of the world and behavior are created, in what sense they are shared, and how they are given meaning in practice. The result is that both creation of work representations, or tools, and their use must be understood in the context of work activity. Put concisely, one participant at the US West workshop said, “Classroom learning should be modeled after workplace learning, not vice versa.” Crucially, we don’t want to fall into an either-or mentality and impose one view on another, such as bringing CBT to the desktop or bringing on-the-job training to the classroom (indeed, this occurs!). Instead, we must ask: How do formal descriptions and training facilitate everyday recoordination and reinterpretation (Wenger, 1990)? The workplace is not just a context for learning; we are not shifting an activity from one place to another. Rather, we must reconceive what is being learned—beyond the curriculum—what problem solving is actually done on the job? Is a worker’s problem to learn a rule, to interpret it, or to improvise around it? Work must be viewed systemically: How does one person’s solution create a problem for someone else? Again, the shift is from formalized procedures applied in narrow, functional contexts to conversation, anticipation, broad understanding, and negotiation.

Researchers with systems in use are aware that the issues are not all technological. Broadly speaking, instructional design must include understanding and configuring interactions that occur in practice among people, systems (and tools in general), and facilities. Table 1.1 summarizes the shift from a technology-centered perspective to a view of the total system of interactions in practice.

TABLE 1.1
Shift From ITS Technology-Centered Development to Design for Everyday Use

Tool Design View	Design for Everyday Use
Technology-Centered	Practice-Centered
Teachers and students as subjects.	Users as partners in multidisciplinary design teams (participatory design).
Delivering a program in a computer box.	Total system perspective, designing the context of use: organization, facilities, and information processing.
Promoting research interests.	Providing cost-effective solutions for real problems.
Automating human roles (teacher in a box) (represent what’s routine).	F...

Table of contents

• Cover
• Half Title
• Series Page
• Title Page
• Copyright Page
• Table of Contents
• Preface
• Part I: Tools of the Trade
• Part II: Case Studies From Industry
• Part III: Case Studies From Government
• Author Index
• Subject Index