chapter.fin.jan14 - Institute for Creative Technologiesprojects.ict.usc.edu/.../Sugrue_Clark_Media_Sel_fin.doc · Web viewWilbur Schramm, Big media, little media, 1977, p. 15 Introduction

Media Selection for Training 1

Published as: Sugrue, B. & Clark, R. E. (2000), Media Selection for Training. In S. Tobias & D. Fletcher (Eds.), Training & Retraining: A Handbook for Business, Industry, Government and the Military. New York: Macmillan.

Media Selection for Training

Brenda Sugrue,

The University of Iowa

and

Richard E. Clark,

Rossier School of Education

University of Southern California

The process of [media] selection is a complex and difficult one asking for better theory than we actually have, for a gathering and analysis of experience, and for an examination of the economic and administrative aspects of the choice. The corner where the media intersect education is a location where every informed passerby moves cautiously. And it should be described less as a streetcorner than as a point on the ocean directly above one of the deeps. In years to come, let us hope, more sophisticated research will tell us what lies below, but for the time being it behooves any educator or media expert to be humble about putting forth elaborate guidelines.

Wilbur Schramm, Big media, little media, 1977, p. 15

Introduction

Lack of adequate theory has not impeded the construction of elaborate models to guide the selection of the "most appropriate" media to deliver training (e.g., Anderson, 1983; Reiser & Gagne, 1983). These selection models have given an illusion of rationality and scientific precision to what have been, at best, decisions driven by practical and economic considerations and, at worst, decisions based on invalid assumptions about learning, learners, and the effects of media on them. In 1989, Heidt suggested that, apart from practical quantifiable factors, such as cost, the application of criteria recommended for the selection of media depends on the subjective judgment of the individual instructor or designer.


In addition to practical considerations, such as size and location of audience, or cost of development and delivery, it has become customary for media selection models to advocate that media should vary depending on:

the type of task being trained,

the type of trainees being trained, and

the element of training (i.e., instructional event) being delivered.

In spite of the fact that there is little theoretical or empirical basis for many of the rules suggested (Heidt, 1975, 1979; Schramm, 1977; Seels & Richey, 1994), even the most recent instructional design textbooks (e.g., Gagne & Medsker, 1996; or Smith & Ragan, 1993) continue to promote existing models. Even if these models were appropriate for the media configurations commonly available ten or twenty years ago, the models seem less appropriate for the kind of sophisticated delivery systems now available (e.g., the world-wide web, or two-way desktop video). Existing media selection models also seem inadequate for making decisions about which media to use for which elements of, for example, an interactive multimedia learning environment, an electronic performance support system, or an intelligent tutor.

No new media selection models have appeared since 19881. The models published that year (Cantor, 1988; Romiszowski, 1988) gave more space to criteria for matching media to functions or elements of training than did previous models. However, no model has linked those elements of training, and related media selection decisions, to cognitive components of the learning process. Although research has failed to establish any direct causal links between media and learning (Clark, 1983, 1994), it is possible to select media for their ability to deliver external support for particular cognitive processes. We propose such a cognitive approach to media selection in the second half of this chapter. The cognitive approach (a) conceives of training as a collection of methods that support specific cognitive processes essential to learning and transfer, and (b) treats media as collections of attributes that facilitate the delivery of those methods.

The chapter is organized as follows. In the first section we consider current approaches to media selection. Within that section we highlight the dearth of information on how media are actually selected for training in the real world. We clarify important distinctions which have been blurred in existing approaches to media selection, particularly the distinctions among media, media attributes, and instructional methods. We describe and comment on the rules that a representative sample of media selection models advocate for matching media to tasks, individual differences, and instructional events. We also discuss the practical factors existing models consider important when selecting media.

In the second section of the chapter we describe our cognitive approach to media selection which involves selecting methods and media attributes before selecting media. We begin by adopting a six-part model of the cognitive processes involved in learning. Then we describe how instructional methods can be selected to support each of the six processes. Next we explain how media attributes can be matched to methods. We propose guidelines for selecting media or mixes of media with attributes that will deliver various combinations of instructional support. We give an example of how our approach


could be applied in the context of developing a multimedia instructional program. Finally, we discuss potential future scenarios for both the contexts in which media selection decisions must be made, and the rules that might drive those decisions.

Current Approaches to Media Selection

How are Media Really Selected?

Little valid information exists on media usage for training or the process by which media are selected in corporate America. Surveys such as Training magazine's "Annual Industry Report" (Froiland, 1993; Industry Report, 1994) draw superficial conclusions about media usage. These conclusions give no information about how different media are used in the training process, or why particular media are used more than others. For example, the 1994 report concluded that the most commonly used medium to deliver training in American industry in 1994 was videotape, followed by lecture, and one-on-one instruction. This conclusion is based on the percentage of respondents who indicated whether each of a list of media was used for any training in the organization. In addition to providing no information on the quantity or type of training delivered with each medium, Training magazine's survey illustrates the fuzzy thinking that permeates the conceptualization of what constitute media in the training field. Media (such as videotape) are confused with media-independent instructional events or methods (such as lecture and one-on-one instruction).

Surveys such as Training magazine’s (Froiland, 1993; Industry Report, 1994) do bear out informal observations of an increasingly complex array of media being employed to deliver training. In particular, computer-based multimedia/interactive videodisc systems are growing in popularity in corporate and military training (Fletcher, 1990; Nowakowski, 1994; Froiland, 1993; Industry Report, 1994). However, there is great variation among programs that bear the label "multimedia". While some principles for designing interactive multimedia instruction are appearing (Park & Hannafin, 1993; Schank & Jona, 1991), there are currently no models to guide the micro-level media choices that must be made in order to produce a multimedia program. For example, how should designers decide which parts of a program should employ video, which information should be displayed in text, what material should come from audio narration, and which parts of a trainee's performance should be recorded?

No one has conducted a cognitive analysis of how expert training managers and designers make decisions about media; therefore, we do not know how training managers and designers really arrive at decisions regarding which media will be used to deliver particular training programs or components of programs. Neither do we know of any data on when decisions about media are made in the training design process. Most linear instructional design models (for example, Dick & Carey, 1990) include media selection as a post-design, pre-development activity. In our experience, the primary medium is often selected before the start of design, either because an organization has committed to one delivery system for all training, or because a company wants to be seen to be employing the latest technology. What might appear to be premature acts of media


selection fit a new general theory of decision making proposed by Langer (1994). She suggests that calculated decision making (in any domain) may be a myth. Langer argues that

the processes that are most generally understood as leading to decisions, such as integrating and weighing information in a cost-benefit analysis, most often are postdecision phenomena, if they occur at all. Instead, ... information gathering is undertaken to make options that appear the same, look different. The information search ends when one reaches a cognitive commitment. Cognitive commitments are frozen or rigidly held beliefs that unwittingly are unmodulated by context. Once a cognitive commitment is reached, choice follows mechanically, without calculation. (p. 34)

“Objective” Approaches to Media Selection

Kemp, Morrison, and Ross (1994) suggest that there are three different approaches to media selection: (a) selection based on what is readily available; (b) selection on the basis of what a trainer is most familiar with or most comfortable using (this assumes that a human trainer is the principal medium); and (c) selection on a more objective basis whereby some guidelines can be followed so that selection can be justified in a nonsubjective manner. The problem is that most existing objective guidelines are questionable. Even the authors of popular media selection models emphasize the lack of theory and research to support their recommendations. For example, Anderson (1983) prefaces the second edition of his book on media selection with the statement that "Media selection is NOT (and may never be) a precise science...charts are simply intended to organize that activity in a more systematic and thorough manner" (p. ix). Romiszowski (1981) states that there is no reason why the reader should agree with the selections he makes for particular examples in his book, "as some of the questions [to be answered during the decision-making process] call for value judgments" (p. 354). Kemp, Morrison and Ross (1994) state that "although each of us might answer a question differently and end at a different place in a diagram, the decision would be acceptable as long as you can justify the answer to each question as you proceed" (p. 220). Gagne (1965) suggested that "most instructional functions can be performed by most media" (p. 363). Schramm (1977) also argued that most media have "a wider spectrum of usefulness than is sometimes appreciated" (p. 268).

Media selection rules based on anything other than practical considerations are difficult to justify because there is no evidence that any medium either (a) makes a unique contribution to learning or motivation or (b) cultivates unique or transferable cognitive skills (Clark & Salomon, 1986; Clark & Sugrue, 1989; Clark 1994). Any measured achievement gains found in media studies can be attributed to uncontrolled differences in the novelty of the media, the content of the programs being delivered, and the instructional methods embedded in the programs. Taking the most extreme position on media, one might be tempted to suggest that if media do not matter in terms of instructional effectiveness, then perhaps how media are selected may not matter either, as long as the organization can bear the cost of the media selected.

One would like to think that organizations applying systematic or objective approaches would make "better" decisions than organizations making decisions based largely on intuition or experience. Unfortunately, there is little research evidence to


support the superiority of systematic selection. The only two published studies we find that have attempted to examine the relative merits of media selection models and intuitive approaches (Braby, 1973; Romiszowski, 1970) produced conflicting results. Romiszowski found that novices using media selection models made "better" decisions about training media (as judged by educational technology experts) than advanced experts who used their past experience. Braby found that an intuitive approach was judged to be as "useful" as the most useful of the ten systematic models compared.

Existing Media Selection Models

There have been no studies of the relative value or utility of different media selection models. However, it is generally agreed that there are more similarities than differences among existing models. We refer the reader to Reiser and Gagne (1982), Romiszowski (1988), Main and Paulson (1988), and Heidt (1989) for comprehensive reviews of existing models. Heidt (1989) concluded his review of existing approaches as follows:

None of the models developed to date can be regarded as an easy-to-handle satisfactory instrument. Some only identify factors, which should enter the decision-taking process, while others suggest procedures, in which usually a sequence of difficult operations ends in some commonsense decision. Research so far has not been successful in discovering how the factors commonly agreed upon as relevant should enter the selection process nor what the consequences of alternative media decisions really are. Because of the complexity of educational situations, the selection remains a matter or subjective good judgment based on the consideration of a large list of potentially relevant factors. (p. 397)

Companies such as AT&T (American Telelphone and Telegraph Company, 1987) and the military (Main & Paulson, 1988) have documented their approaches to media selection. Some organizations have created menu-driven computerized tools based on existing paper-based flowcharts, matrices, worksheets and checklists. However, whether paper-based or computer-based, there is often a dissociation among the media selection inputs, outputs, and the process of matching the inputs to the outputs. Often factors recommended as inputs are not included in the decision-making tools. For example, Reiser and Gagne (1983) recommended matching media to different events of instruction, but they did not include events as decision points in the flowchart and worksheet they provide for implementing the process. AT&T's (1987) approach to media selection includes factors such as objectives, tests, and instructional strategies as inputs, but how media might be matched to these is not discussed. With such gaps in the documented procedures, one wonders how users fill in the gaps as they move through the stages of the selection process.

Two-stage process of media selection. Existing media selection models generally conceive of media selection as a two-stage process. The first stage involves the selection of a set of candidate media to match task, trainee, and instructional event characteristics. The second stage involves selecting among the candidates based on practical considerations such as relative cost and convenience. Before describing in more detail the selection criteria and rules embodied in existing media selection models, we will first consider how these models portray the outputs of the selection process, (i.e., how they


depict what is being selected). We will argue that there has been a tendency to blur the distinctions among media, media attributes, and methods, and that the first step toward a more rational approach to media selection involves clarifying those distinctions.

What is being selected? Most media selection models conceive of their outputs as subsets of a laundry list of alternatives that mix individual delivery devices such as radio, chalkboard, human trainer, or computer; gross categories of media such as broadcast media, print media or multimedia; and media capabilities or attributes such as audio, motion, or two-way communication. Many lists of media options also include items that refer to either what is being delivered (e.g., demonstrations, simulations, diagrams, or concrete models), or the kind of activity in which the trainee is engaged (e.g., problem-solving, role plays, or discussions). Some authors divide the list into categories. For example, Cantor (1988) used a three-level categorization which consisted of twelve generic categories (such as television, audio, and computer-assisted instruction), some major variants within each category (for example, variants within the television category were video cassette with linear playback, video disc, and interactive television with logic), and finally, specifically identifiable devices or processes within each variation. Seels and Richey (1994) classified media into four types: print media (which present text and graphics), audiovisual media (which present auditory and visual messages), computer-based media, and integrated media (which encompass several forms of media under the control of a computer).

Twenty years ago, Heidt (1975) highlighted many of the problems inherent in attempts to list or classify media that might constitute options for delivering training. He noted cases where categories were too broad; for example, he thought that still pictures neglected instructionally important differences between an illustration in a book, a slide, or an overhead projector transparency. Heidt also noted superfluous distinctions such as the distinction between film-strip and slide. He pointed out cases where some of the media listed could not exist independent of other media, for example programmed instruction. Heidt suggested that some approaches allowed for hardly any specific discrimination between media and non-media.

Recently, variables such as interactivity, learner-control, linearity, and learner-centeredness have been associated with particular media or categories of media (e.g., Seels & Richey, 1994). Interactivity is often associated with computers, but not other media. Computers certainly permit immediate two-way communication between trainees and the system; however, two-way communication can be accomplished by a combination of what might traditionally be regarded as one-way (i.e., non-interactive) media. For example, a trainee could complete a hands-on assignment and be videotaped while doing it; the videotape could be mailed to a human who views the videotape and generates an oral, written, or videotaped critique, which gets delivered to the trainee at a later date. While this use of media may seem cumbersome and an inefficient way to provide coaching, there is evidence that such delayed feedback may in fact be more effective than immediate feedback, if retention and transfer (as opposed to speed and accuracy of performance during training ) are the goals (Schmidt & Bjork, 1992).

Linearity of presentation and use is often associated with print and audiovisual media, while non-linearity is portrayed as a feature of computer-based and integrated


media. Linearity is really a two-dimensional attribute, one dimension pertaining to the linearity of the format in which the material is stored, the other dimension pertaining to the extent to which the material can be accessed randomly. Instructional material may be stored in a fixed sequence, for example in a book or an audiotape, but the information can be accessed in a non-linear manner. Learner control is also a multidimensional construct, encompassing dimensions such as control over sequence and pacing, control over information access, and control over number and type of contexts for practice.

One media classification system which avoids the association of variables such as interactivity and learner control with particular media is that of AT&T (1987). AT&T divides media into six categories: visual media, audio media, printed media, physical objects, human and situational resources, and computers. The only problem with this scheme is that computers can deliver audio and visual material and so encompass audio and visual media. Humans can also deliver audio material, or at least verbal material orally. What distinguishes humans and computers from other media is their ability to monitor a students' behavior, and generate or prescribe a response to that behavior.

Media, media attributes, or methods. In our view, there are two main sources of confusion in lists of media options and attempts to categorize them. The first source of confusion is a lack of distinction between media and methods; the second is a lack of distinction between media and media attributes. It is important to separate instructional methods, media attributes, and media because one cannot make direct links between media or media attributes and the psychological processes involved in learning. However, one can link instructional methods to cognitive activity. Figure 1 indicates what aspects of training can be directly linked to media and methods. Media influence access to training, cost of training (development and delivery costs), and efficiency of training in terms of time to learn; methods primarily influence learning and motivation, although they may also influence efficiency of learning. For example, providing immediate feedback (an instructional method) may increase the speed with which learning occurs (Anderson, Corbett, Koedinger, & Pelletier, 1995). Clark (1994) has argued that all methods can be formatted for delivery in a wide variety of media, with different consequences in terms of access, cost, or time to learn, but with similar learning consequences.

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Insert Figure 1 here

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Instructional methods. An instructional method is an external representation or activity that supports an internal cognitive process necessary for learning (Clark, 1983, 1994). Different levels of support are possible depending on the extent to which one wants to reduce the cognitive processing burden on the learner. A method can only be defined in terms of the cognitive process or processes it targets. For example, a key cognitive process in learning is the compilation of procedures by analogy to examples (Anderson, 1993; Anderson & Fincham, 1994; Chi, Bassok, Lewis, Reimann, & Glaser, 1989; Sweller & Cooper, 1985). The presentation of worked examples or demonstrations during training are methods that facilitate this process. Another key


cognitive process in learning is the ongoing monitoring of the state of one's knowledge in relation to a goal (Corno & Mandinach, 1983). The provision of practice activities and the detection and reflection of errors in performance are methods that support this process (Anderson, Corbett, Fincham, Hoffman, & Pelletier, 1992; Regian & Schneider, 1990).

A cognitive process that optimizes the investment of effort during learning is the maintenance of a perception of the task as a moderate challenge (Lepper, Woolverton, Mumme & Gurtner, 1992; Salomon, 1984). Methods can monitor and modulate both objective and subjective perceptions of difficulty. Objective difficulty can be adjusted by adapting the complexity of the task a trainee works on, or the amount of scaffolding provided during task performance as a function of performance on the current task, so that the current task is most likely to be just at the edge of the trainee's zone of proximal development (Vygotsky, 1978). Subjective perceptions of difficulty can be monitored by asking students direct questions (Boekaerts, 1987) or watching for verbal and physical cues from the learner (Lepper et al., 1992). Verbal strategies, such as commenting on the difficulty of an upcoming task can be used to manipulate the trainee's subjective perception of challenge (Lepper et al., 1992). None of the methods previously described are media-specific, but they do require media that can permit the ongoing monitoring and adaptation of what is presented to trainees, that is, media that possess the "attribute" of adaptability to individual trainee performance.

Media attributes. According to Levie (1989), a media attribute is a functional feature of a medium that allows the medium to transmit particular kinds of information, and to process particular kinds of trainee responses. For example, ability to transmit audio, to display motion, to display text, to give non-linear access to information, to monitor performance, and ability to deliver individualized feedback are all media attributes. Levie suggested five categories of media attributes: sensory modality (e.g., visual, auditory, tactile), symbolic modality or symbol systems (e.g,, verbal, nonverbal), design cues and codes (e.g., color, motion, shading, music), locus of control (i.e., extent to which trainees can control pace and sequence), and interactivity (i.e., extent of coordination between student responses and feedback). Kozma (1991, 1994) suggested three categories of media attributes or capabilities: technology capabilities (physical, mechanical, or electronic), symbol system capabilities (e.g., spoken language, printed text, pictures, numerals, musical scores, maps, graphs) and processing capabilities (e.g., display, reception, storage, retrieval, organizational, translation, transformation, and evaluation). A media selection process based on media attributes would match attributes to instructional requirements and then search for a set of media that possessed the necessary attributes.

Media. A medium is an instructional resource that incorporates a cluster of media attributes or capabilities (Kozma, 1991). Different media combine different sets of attributes. Some media have a broader range of attributes or capabilities than other media. For example, "multimedia" consists of a computer-based integration of a large number of information presentation attributes, such as video, audio, graphics, and text; a narrower range of response processing attributes, such as acceptance of selections from presented options on the screen, or acceptance of verbal responses; and all of the capabilities of the computer to analyze trainees' actions and generate responses to those


actions. Interactive video combines the information presentation attribute of video with the monitoring, analysis and adaptive capabilities of the computer.

Links to cognition. A medium does not have any influence on cognition; neither do its attributes (Clark, 1983). A medium’s attributes merely permit the delivery of some method that has cognitive consequences. Some authors have suggested that media or media attributes can have cognitive consequences (Salomon, 1979; Salomon, Perkins, & Globerson, 1991; Kozma, 1991, 1994). However, Clark (1994) argues that any learning benefits that have been attributed to media or media attributes can be traced to media-independent methods. Each new wave of media spawns a group of proponents who attempt to attach cognitive consequences to the newer media or newer media attributes rather than to methods which are the real source of the hypothesized cognitive effects. Interactive video (Cognition and Technology Group, 1992) and hypermedia (Jonassen & Wang, 1993; Spiro, Feltovich, Jacobson, & Coulson, 1992) are two of the latest media types that have been associated with learning benefits. Hypermedia are media that share the attributes of non-linear structuring of and/or access to information. This information can take many forms including text, pictures, video and audio, depending on the other attributes of the particular medium. Books are a form of hypermedia since they provide non-linear access to information, but recent interpretations of hypermedia have associated this type of media almost exclusively with computerized banks of information.

If we categorize non-linear structuring of and access to information as media attributes, then we should be able to identify an instructional method or methods those attributes can deliver. Two different instructional methods have been linked to the non-linear structure and access attributes of hypermedia. Spiro et al. (1992) suggested that having learners explore the same units of information from multiple perspectives induces the acquisition of a denser, more flexible network of knowledge about that particular domain. Thus, the instructional method facilitated by hypermedia might be support for acquisition of dense, flexible knowledge. The media attribute that facilitates delivery of this method is non-linear access. Another instructional method facilitated by hypermedia, according to Jonassen and Wang (1993), is support for acquisition of expert-like knowledge structures. By structuring information in a set of hyperlinks that reflect the semantic network of experts, learners are likely to internalize a similar semantic network.

The Cognition and Technology Group (1990, 1993) have used interactive video as a means to deliver anchored instruction, facilitating learners' acquisition of knowledge that is situated in contexts similar to those in which they will be expected to use that knowledge. The interactive video portions of their programs, for example, the Jasper Woodbury mathematics series, could be delivered in other media. The critical media attribute in this case is the ability to present scenarios or problems in a realistic situation. The goal-based scenarios employed extensively in Andersen Consulting's training programs were adopted as a non-media-specific approach (Campbell & Monson, 1994; Schank, 1994); however, Andersen Consulting is increasingly using multimedia environments as an efficient way to combine the attributes necessary to present realistic scenarios, provide on-line informational resources, and to monitor and coach trainees when necessary.


Before outlining a media selection model where media attributes are linked to separate components of training, we will first consider how existing media selection models advocate matching their lists of media options to tasks, trainees, and instructional events. Figure 2 summarizes the main characteristics of existing media selection models and the limitations of the models.

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Matching media to task types. Many media selection models, for example, Reynolds and Anderson (1991), and AT&T (1987), advocate matching media to Bloom's (1956) three-way categorization of learning tasks: cognitive, psychomotor, and affective. However, the distinction is not sustained in the flowcharts and diagrams to guide the decision-making process, giving the impression that task differences make no difference to the kinds of media that could be used to train them. Flowcharts, diagrams and checklists, which accompany the models, focus on matching media to instructional requirements of tasks in general, requirements such as the need for interaction or motion visuals. No guidance is given on what might lead one to decide that a particular task requires the use of motion or still visuals. This is not surprising given the inconsistency of research on the effects of different types of presentation on learning (Wetzel, Radtke, & Stern, 1994), and the fact that most studies do not examine the differential effects of different media or presentation modes on different types of learning outcome.

Recent research (for example, Mayer & Sims, 1994; Mousavi, Low, & Sweller, 1995) indicates that it is the manner in which types or modes of presentation are combined (and not the mere presence or absence of a particular mode) that influences cognitive load and processing during the encoding of information. For example, presenting the commentary on a diagram in auditory mode rather than in text beside the diagram seems to reduce the load on working memory (Mousavi et al., 1995). Mayer and Sims suggest that concurrent presentation of two representations facilitates the making of more referential connections between the visual and the verbal representation, which in turn facilitates transfer. This dual-coding theory is not dependent on task type.

In general, there is little empirical evidence that any particular type of information is absolutely necessary for the learning of any task. For example, it is not clear if is it necessary to see a real demonstration of a procedure; a stylized sequence of still images might be enough to convey the nature and sequence of the steps to a trainee. A trainee may be able to fill in the gaps and attempt to do the procedure after seeing only the still images, or possibly having seen only a verbal description of the steps. In fact, less complete representations may induce deeper cognitive processing.

Theories of situated cognition would suggest that the greater the authenticity of the context in which a trainee practices the skills being learned, the greater the potential for transfer (Brown, Collins, & Duguid, 1989). However, the extent to which a practice activity should have physical and functional fidelity to the real situation is unclear (Alessi, 1988). In the first stage of learning a skill, that is, the stage of controlled

Media Selection for Training 11processing (Fitts & Posner, 1967; Ackerman, 1989), less fidelity may facilitate the construction of appropriate procedures for task performance. During the second stage of skill learning, where sequences of actions and decisions become associated with task stimulus conditions, greater fidelity may aid transfer of the procedures (Anderson et al., 1992). Thus, it may be that media attributes need to be selected to match different stages of learning (regardless of task type) rather than to different types of task.

Reiser and Gagne (1983) suggested matching media to Gagne's five categories of learning task: verbal information, intellectual skills, psychomotor skills, cognitive strategies, and attitudes. However, Reiser and Gagne's specific recommendations for media were related not to five task types but to a two-way distinction between tasks that require a trainee to learn to do something (intellectual, psychomotor and cognitive strategy objectives), and tasks whose objectives are that the trainee should be able to state or believe something (verbal information or attitude objectives). This two-way categorization of tasks is similar to the distinction between declarative and procedural knowledge (Anderson, 1993). Declarative knowledge can be thought of as knowledge “about” things or knowledge “that” something is the case. Declarative knowledge helps one answer “what” and “why” questions. Procedural knowledge is knowledge that links goals to conditions and actions for achieving the goals. Procedural knowledge helps one take actions and make decisions in particular situations.

According to Reiser and Gagne, tasks with "do something" objectives require media that permit precise corrective feedback. Reiser and Gagne listed portable equipment, simulations, computers, programmed texts, and interactive TV as media appropriate for training intellectual and motor skills. They recommended motion picture, slide/tape, TV, filmstrip, printed text, surface layouts, models, mockups, and audio as media suitable for training attitudes and verbal information. Reiser and Gagne assumed that the learning of verbal information (or declarative knowledge) did not require monitoring and precise feedback; thus, a medium that could deliver information only would be sufficient.

In contrast, we would suggest that all tasks require information presentation and practice, and that media selection decisions should be based on the type of information and practice a particular task requires. For example, if the task being trained is how to operate a piece of machinery, then some medium will be needed to provide information on how to operate the machine. In addition, either the machine itself or a computerized simulation of the machine will be required for practice, and some medium will be needed to provide feedback during or after the practice. If the task being trained involves stating reasons why a customer should purchase a particular item, then a medium that can provide information about the reasons, and a medium that can facilitate and monitor the practice of communicating these reasons to customers will be needed. Thus, a simple classification of tasks as “doing” versus “stating” does not lead to clear media choices.

Considering each task separately is preferable to classifying the task in order to narrow media choices. Some tasks may have elements that involve using particular senses (i.e., touch, hearing, sight, taste, or smell). For example, when troubleshooting a problem in a car engine, one may have to distinguish among different sounds that might come from the engine; therefore, a medium capable of reproducing those sounds may be

Media Selection for Training 12required during information presentation and during practice to facilitate transfer to the real situation. On the other hand, if the task requires a trainee to handle customer complaints in a telephone company, it may not be necessary to present visual and auditory representations of the customer. The text of the customer's verbal responses may be substituted during both demonstration and practice. Thus, the range of media for presenting information and providing opportunity to practice is extended for this particular task.

Matching media to individual differences among trainees. Most media selection models recommend matching media to individual differences among trainees. However, the models differ in the number of individual difference variables they consider important. Only two learner characteristics, reading ability and experience, are considered important in Reiser and Gagne's (1983) model. Certainly, reading ability should determine the amount and level of textual material included in a training program, which in turn may suggest different media. However, the idea of matching media to trainee's "experience" is less clear-cut. Reiser and Gagne defined experience as level of accumulated knowledge and cognitive strategies. Taken together, these probably indicate the extent to which a trainee can learn in a particular domain without external support. That this is what Reiser and Gagne had in mind is evident in their recommendation of more self-instruction via computers, programmed text and interactive TV for trainees with more "experience" and use of a live instructor for trainees with less experience. This assumes that a live trainer can and will provide more of the kind of support required by trainees with less prior knowledge and cognitive strategies than can other media. That may or may not be the case. For example, intelligent tutoring systems may be equally (or more) capable of monitoring individual trainees' performance, and adapting the training accordingly on an individual basis, than a human trainer (Anderson et al., 1992).

Cantor (1988), like Reiser and Gagne, recommended matching media to the prior knowledge and processing resources of trainees. Cantor suggested that learners with low prior knowledge and/or processing resources require more graphical presentation of information and concrete illustrations. We are not aware of any research to support such a specific recommendation. Research suggest that lower ability students benefit from greater elaboration of information during instruction, and such elaboration can take a number of forms (Mayer, 1980; Wetzel, Radtke, & Stern, 1994).

Romiszowski (1988) proposed a long list of individual differences that should influence media selection. In addition to "experience with the topic", he included IQ, motivation, ability to learn from verbal or visual material, mechanical ability, preferences for visual versus verbal information, understanding of particular symbolic language, attention span, and physical disabilities as trainee characteristics that may restrict media choices. From that list, physical disabilities are the only learner characteristics that clearly limit the choice of media. The other variables relate to cognitive and affective differences among learners. The interactions between these "aptitude" variables and any instructional variables are extremely complex, and few, if any, are media-specific. For example, learners with lower general ability learn more in structured learning environments because such environments have been found to reduce the cognitive-processing burden on the learner (Snow, 1994). However, structure can be provided in any medium.


Romiszowski (1988) acknowledged that we do not know enough to make recommendations about which media are appropriate for different learners. Nevertheless, he made many specific recommendations. First, he suggested that learners with below average IQ or a lack of prior experience related to the topic should be given more realistic representations (e.g., working models or films rather than still visuals) of phenomena than learners with average or above average IQ or learners with relevant prior experience. Romiszowski also suggested offering options so that learners who have preferences for audio or visual presentation can select the medium they prefer. Recent research by Plass, Chun, Mayer, and Leutner (1996) supports Romiszowski's recommendation. Plass et al. found that presentation modes interact with learner preferences to influence both encoding and retrieval processes; only learners with a preference for visual information benefited from having access to visual information in addition to verbal information. This suggests that for information presentation, the choice of media should be reserved for the learner. However, this would increase the cost of development, since more than one representation of the same information would have to be created.

One problem with matching instruction to learner preferences is that a trainee may prefer a particular medium or mode of information representation, but may underestimate the amount of mindful effort required to master the learning goals in that medium (Clark, 1982; Salomon, 1984). In general, trainees benefit from instructional presentations and activities that lead them to engage in cognitive activity that is essential to acquisition and application of the knowledge involved in task performance. For example, if one suspects that trainees will not pay attention to critical changes in a system as some operation is performed on the system, then those changes should be highlighted in some way, (e.g, either with verbal or graphic cues). Many media might facilitate such cueing (Clark & Sugrue, 1988). If a trainee is unlikely to recognize the naivete of a personal theory about the relationship between two variables, (e.g., force and motion), then the trainee should be confronted with evidence to contradict that naive theory as a first step toward acquiring a more accurate theory (White, 1992). Such instructional support for cognitive processing can be provided by a variety of media.

Decisions regarding which trainees need more or less support for cognitive processing in a given program are important because trainees who do not need support may learn less when an attempt is made to replace their idiosyncratic and successful cognitive strategies with less familiar competing strategies (Clark, 1988; Lohman, 1986). When the strategies employed in instruction match a student's own strategies, then learning is increased (Shute, 1992). Thus, interventions supporting cognitive processing should only be given to those who need them, and should not be in conflict with a student's own strategies. This suggests that one of the key attributes that should be included in any mix of media selected to deliver training will be the capability to monitor performance and adapt interventions to the needs of individual trainees. Research on adaptive instruction indicates that such instruction can (a) reduce training time by up to fifty percent and (b) is more effective and efficient when the adaptation is based on trainees' performance on recent tasks within the training, rather than on global or pre-task estimates of ability (Tobias, 1989).


Matching media to instructional events. The most productive and valid approach to media selection, in our view, is to select media based on their ability to support essential components of training (often called instructional events), which in turn support essential cognitive activities. Various models of instructional events have been suggested, for example, Gagne's (1965) classic nine events of instruction:

gaining attention,

informing the learner of the objective,

stimulating recall of prerequisite learning,

presenting stimulus material,

providing learning guidance,

eliciting performance,

providing corrective feedback,

assessing performance, and

enhancing retention and transfer.

Romiszowski (1988) proposed a simpler distinction among three essential elements of instruction:

transmission of information about the task to the learner,

transmission of information about the learner's current state of expertise in relation to the goal back to the system (based on the learners' performance on practice activities), and

provision of corrective feedback to the learner.

While many authors have recommended matching media to events of instruction, few have elaborated on how that might be done.

The most common events of instruction to be analyzed and matched to media are the presentation of information, and practice activities. Romiszowski (1988) and Cantor (1988) both matched media to type of information, particularly the sensory channels through which information must be encoded during task performance. For example, if sounds were an integral part of the task, then a medium capable of transmitting live or pre-recorded sound would be required. Cantor (1988) distinguished among twenty-one physical characteristics of the information that could be presented during training. He grouped these twenty-one characteristics into six categories: visual form, movement, color, scale, audio, and "other". The "other" category consisted of three characteristics: tactile cues, external stimulus motion cues, and internal stimulus motion cues. In a chart, Cantor indicated which types of media are capable of delivering information with each of the twenty-one physical characteristics. This level of detail seems unnecessary for decisions that are fairly obvious. For example, if you want trainees to view some still pictures of different types of chemical processes, then any medium that can deliver pictures can be used; if color is an important component of the process, then a medium that can display color pictures may be necessary.


As for the aspects of practice that dictate media, both Romiszowski's and Cantor's models suggest matching media to response types. However, they differ in how they classify response types. Romiszowski distinguished among three types of responses: motor responses and perceptions; verbal responses (including naming, identifying, discriminating, and classifying); and complex verbal responses (including induction, problem solving, and deduction). The theoretical basis for this set and classification of response types is not clear. For example, why is problem solving classified as an instance of a complex verbal response? Would a verbal response be the only way to demonstrate problem-solving ability? Why would simple verbal responses require different media than do complex verbal responses?

Cantor distinguished among ten types of response modes during practice that would influence the selection of media. Those response modes are covert response, multiple choice, short answer, free style written, decision indicator, voice, fine movement manipulative, broad movement manipulative, tracking, and procedural manipulative. It is not clear why one should distinguish between these particular types of responses in order to select appropriate media. Neither is it clear what all of the media recommended as appropriate for different types of responses have in common. For example, the media checked as appropriate for handling decision responses are instructor, telephone conference, interactive television, teaching machines, simulator, computer-assisted instruction, and real environment. It is not clear how these media differ from the media recommended for handling multiple-choice responses: instructor, printed material, audio tape, still film, television, teaching machines, and computer-assisted instruction.

In addition to matching media to types of trainee response during practice, Cantor matched media to the form, content, and timing of feedback. Romiszowski did not offer specific guidelines for matching media to feedback variables. Cantor's finer distinctions among feedback variables are confusing; for example, the difference between diagnostic data and correct response data is not clear. Neither is it clear why "branching printed material" would permit feedback based on "correct response data", but would not permit feedback based on "diagnostic data". Could not correct (and by implication, incorrect) response data serve as diagnostic data?

Romiszowski's and Cantor's models are useful in that they represent a first step toward a new generation of media selection models that will focus on matching media to components of training. What they lack is a theory of cognitive process, instructional method and media attributes that could guide and justify links between media and functions of training.

Selecting media based on cost and other practical considerations. In existing media selection models, the final stage occurs once one has narrowed the options based on the requirements of the tasks, trainees, and training events for a particular training program. A final selection is made from the short-list based on the practicalities of development, delivery, and maintenance -- practicalities such as time, resources, and budget. Existing media selection models vary in the level of guidance they give regarding compilation and analysis of information relating to practical factors. Some models (e.g., Reiser & Gagne, 1983; Romiszowski, 1988) merely list questions or factors that should guide final selection. Other models (e.g., Braby, Henry, Parrish, & Swope,

Media Selection for Training 161975; Collins, Hernandez, Ruck, Vaughn, Mitchell, & Rueter, 1987) provide worksheets and computerized tools to aid data compilation and analysis of the relative cost of media mixes on the short-list of candidates. Since monetary value can be attached to development and delivery time as well as resources, the final selection of media boils down to an analysis of the relative cost of each alternative media mix.

Any analysis of practical factors is based on projected rather than actual costs since the analysis occurs before development and implementation. The reliability of estimates of time, resources and costs will increase as an organization gains experience with development and delivery via different media configurations. However, when considering a newer set of media, it is difficult to make reliable estimates, and to make valid comparisons with an older set of media for which mechanisms and facilities are already in place for development and delivery (Carnoy & Levin, 1975). It is also difficult to provide context-independent guidelines on the relative time and costs of development and delivery of different media mixes. Variables such as the content and design of a particular program, size and location of audience, life span of the program, suitability of existing facilities, experience of personnel, and salaries of developers and trainees will influence the cost for a particular program. The cost of producing and delivering the same training program for the same set of media will vary from company to company. The cost of producing and delivering two different programs with the same set of media within the same company may also vary.

Given that costs must be estimated on an individual case basis, the most useful approach is Levin's (1983) ingredients method. Ingredients are resources required to develop and deliver a particular training program to a designated trainee audience. This method involves identifying all ingredients in the development and delivery of the training, for each alternative media configuration. Then a cost or value is attached to each ingredient (even those that appear to be "free"). Finally, the costs are summed for each media mix. Levin advocates categorizing ingredients as personnel, facilities, equipment, materials and supplies, and all other resources. The "all other resources" category can include maintenance of hardware, updating of materials, and training of personnel. Equipment costs, Levin suggests, should be amortized over their projected lifetime. Lost opportunity costs are also included as ingredients; for example, a value should be placed on classroom space since it could have alternative uses were it not being used for training. In addition, cost of trainees' salaries for the training period should be included as an opportunity cost since trainees are not working during this period.

Head and Buchanan (1981) suggested a method similar to Levin's ingredients method, whereby student costs, instructor costs, facilities costs, administrative costs, and development costs are calculated separately, then totaled to obtain an estimate of the overall cost of a particular training program. One can arrive at a total cost for the program given a particular number of trainees, or one can generate a cost per trainee, as is done by Hewlett Packard in a computerized package that prompts the user to enter development and delivery resource costs for alternative media (D. Blair, personal communication, April 17, 1995).

Summary of Existing Media Selection Models


Existing media selection models divide media selection into two stages. The first stage is based on the assumption that different training tasks, trainees, and training components require different media. The second stage is based on the assumption that different mixes of media will deliver training with equal effectiveness but with different costs. In the first stage of the process, these models have attempted to simplify and mechanize decisions that require complex chains of reasoning. The outputs of the selection process have been confused, and decisions have been made contingent on unanswerable questions. There are many gaps and inconsistencies in the models. These gaps and inconsistencies stem from the impossibility of making direct links between media and tasks, trainees, and training events. Attempts to match media to tasks with different cognitive demands, or to trainees with different cognitive and affective characteristics, assume that it is possible to link media directly to cognitive consequences.

The only reason one medium might be more suitable than another for a particular training task is because the task requires the presentation of some information or practice activity that calls for particular media attributes. The only reason some media might be more appropriate than other media for some trainees is because those media have attributes that can deliver the particular level of external support those trainees need to engage in the cognitive processes necessary for learning. The only way to justify selection of one particular medium or media mix over another (beyond relative costs and practicalities of implementation) is in terms of the media’s ability to support the kind of cognitive activities deemed necessary to attain the targeted task performance.

The best approach to media selection, in our view, is one that advocates selecting media based on their relative abilities to perform different instructional functions. This approach has been obscured in past models by a focus on matching media to task types and trainees. In the next section, we describe a system for media selection which operationalizes a "training function" approach. Functions of training are defined in terms of the cognitive components of learning they support. We recommend that media be selected based on their ability to deliver the level of external support required to compensate for trainees' inability or unwillingness to engage in the cognitive processes necessary for learning. Focusing on support for cognitive activity during training can not only drive the process of media selection, but can also help clarify what exactly is being selected at various stages of the process.

A Three-Stage Cognitive Approach to Media Selection

Our approach to media selection involves three stages:

1. selection of methods to support the cognitive processes necessary for trainees to acquire the task performance that is the target of the training;

2. selection of a set of media attributes that can support the type, amount, timing, and control of methods selected for the training; and

3. selection of the most economical and convenient set of media that possess all of the required attributes.

Media Selection for Training 18This three-stage process is depicted graphically in Figure 3. The first stage of this process is the concern of much theory and research in the field of instructional technology -- theory and research focused on the effects of instructional variables on cognition, motivation and subsequent performance. The second stage requires that categories of media attributes be aligned with characteristics of methods.

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One problem with this approach is that our knowledge of the cognitive processes involved in learning and performance is neither stable nor integrated. Research continues to address both macro and micro-level processes. There are, for example, models of the stages of skill acquisition (Anderson, 1983, 1993; Shiffrin & Schneider, 1977); models of the acquisition and structuring of declarative knowledge in memory (Rumelhart, 1980); theories of multiple learning mechanisms (Rumelhart & Norman, 1981; Kyllonen & Shute, 1989); theories of the components and development of expertise (Chi, Glaser, & Farr, 1988; Ericsson & Smith, 1991); models of the acquisition of procedural knowledge (Anderson, 1993; Schank, 1994); models of situated cognition (Brown et al., 1989); models of metacognitive processes that monitor and control the processes involved in knowledge acquisition and performance (Corno & Mandinach, 1983; Pintrich & De Groot, 1990); models that describe mechanisms that underlie motivation (Bandura, 1989; Dweck, 1986; Weiner, 1986); and models that attempt to integrate a variety of processes in a person-situation interactionist paradigm (Snow, 1994).

Any model of the cognitive processes involved in learning that one might adopt, as a basis for the design of instruction and media selection, will be incomplete. However, any attempt toward a theoretically grounded approach to media selection must adopt some model of cognition. Such a model should at least include the three main categories of processes related to learning and performance: motivation, metacognition, and knowledge acquisition/construction. We will now describe a six-part model of the cognitive components of learning which we will then relate to the selection of instructional methods, media attributes and media.

A Six-Part Model of the Cognitive Processes Involved in Learning

To drive the selection of methods, media attributes, and media, we suggest a six-part conceptual division of the cognitive processes involved in learning:

Interpretation of the targeted performance goal

Encoding of task-relevant declarative knowledge and/or retrieval of task-relevant declarative and procedural knowledge

Compilation and execution of new procedural knowledge, that is, production rules relating sequences of actions and decisions to task goals and conditions

Monitoring of performance

Diagnosis of sources of error in performance

Media Selection for Training 19Adaptation of goal interpretation, retrieval/encoding of declarative, or retrieval/compilation of procedural knowledge to improve performance.

This model is based on Glaser's (1992) model of the cognitive components of expertise, Anderson's (1993) theory of learning, and theories of the components of self-regulated learning (Corno and Mandinach, 1983; Flavell, 1979; McCombs, 1988; Pintrich & DeGroot, 1990; Salomon, 1984). A trainee can perform all six cognitive processes without external aid, or the external environment can compensate for weaknesses in any or all of the processes. When a trainee is able and willing to control his or her own learning, he or she will first make an interpretation of a given training goal, or will select a goal. The trainee will also make an initial estimation of the value and demands of the task and the amount of effort that will be required to achieve it (based in part on a perception of his or her own abilities in relation to the perceived demands of the task). The trainee's interpretation of the goal will drive selection of declarative knowledge, either retrieved from long-term memory or encoded from some external source. Interpretation of the goal will also trigger retrieval of procedural knowledge already in memory. Procedural knowledge cannot be directly encoded from external sources since, by definition, it must have gone through an internal process that has resulted in automation (Anderson, 1993). A list of the steps required to perform a procedure is NOT procedural knowledge; rather, a list of steps is declarative knowledge about the procedure. Thus, declarative knowledge can come from either external sources or from memory.

Having accessed declarative and/or procedural knowledge, a trainee will attempt to compile a new procedure for the current task by attempting to perform the task. The trainee will monitor his or her first attempt at the task, and analyze that performance to diagnose sources of error. Sources of error could be inaccurate estimation of the value or demands of the task , gaps in declarative knowledge, or gaps in knowledge of prerequisite procedures. The trainee will attempt to correct errors in performance by reinterpreting the goal, consulting/retrieving additional pieces of declarative knowledge, and/or practicing a prerequisite procedure before attempting the original task again. The trainee will keep cycling through this process until he or she is satisfied that the goal has been reached.

Six Categories of Instructional Methods

At a minimum, the external training environment will need to provide a description/representation of the initial task goal, sources of information (from which declarative knowledge can be encoded), and opportunities, either real or simulated, in which the student can practice the task. Such minimal support assumes that the trainee is capable of monitoring his or her own performance, diagnosing the sources of errors, and correcting those errors unaided. Figure 4 illustrates the six-part model of internal cognitive processes involved in learning and the minimum external resources required to support them (goals, information, and practice opportunities).

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The training environment can also compensate for weaknesses in trainees' ability to execute the other three cognitive processes involved in learning: monitoring, diagnosis, and adaptation. Thus, a fully-supportive training environment would

elaborate on the goal of the task and its demands

provide information related to the task

provide practice tasks and contexts

monitor trainee performance

diagnose sources of error in performance

adapt goal elaboration, information and practice tasks.

Since we defined an instructional method as an external support for an internal cognitive process, these six types of external support become six categories of instructional methods. We label the six categories of instructional methods as follows: Goal Elaboration, Information, Practice, Monitoring, Diagnosis, and Adaptation. We use these labels to refer to the six instructional methods for the remainder of this chapter.

Selecting Training Methods to Support Cognitive Processes

Each of the six instructional methods can vary in type, amount, timing, and locus or distribution of control. Locus of control is the extent to which a method is controlled by the external environment/system and/or is under the trainee's control. For example, different types and amounts of information about a task can be provided, the timing of presentation of that information can vary, and presentation of that information can be controlled by the system or by the trainee, or control can be shared. Depending on the type of information, the amount of it, the timing of its delivery, and the distribution of control, different media attributes will be required.

Before outlining which characteristics of methods call for particular media attributes, we will first discuss media-independent options for types, amount, timing, and control of each of the six methods already defined. We will suggest some criteria for selecting the type, timing, amount, and control of each method, but only if there is a sound theoretical or empirical basis for such criteria. More often than not, we will conclude that there is no empirical evidence that any of the alternatives differ in their effectiveness or efficiency, making the choice arbitrary. Figure 5 summarizes the main options for the type, timing, amount and control of each of the six methods. For all methods, the amount of support can be fixed in a range from low to high, or can be flexible so that different amounts of support could be prescribed for or selected by different trainees. Timing of support can be fixed or flexible; and support for diagnosis and adaptation can be immediate or delayed. For all methods, control of their deployment can rest solely with the trainee or solely with the system, or control can be shared. We will now describe in more detail the options for types of methods.

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Instructional methods for goal elaboration. The goals of training are tasks that some group of persons (trainees) should be able to perform but currently cannot perform. There are two types of methods for communicating task goals to trainees: description methods and demonstration methods. Description methods include providing a description of the outcome or product of the task, a description of the process of accomplishing the task, or a description of the criteria used to judge attainment of the goal of the task. Demonstration methods involve demonstrating how the task goal is accomplished or showing the outcome or product of the task. For example, one could tell trainees (i.e., describe in written text or orally) that the goal of a training session is that they will be able to use the style function in the word-processing program Microsoft Word. Alternatively, one could show trainees (i.e., demonstrate) a document in which the style function was used, or one could demonstrate how a style is created and used to produce a piece of text. In addition to describing or demonstrating the goal of the task, the value and demands of the goal can also be highlighted/elaborated.

One can provide a fixed high amount of information about the goal of a task, or a fixed low amount, or the amount can be varied for different trainees. Elaboration of the goal can occur before and/or during training, either when requested by a trainee or when deemed necessary by the system (based on analysis of trainee performance). Control over support for goal interpretation can reside entirely with the system, or can be shared between the system and the trainee.

Instructional methods for information. A variety of methods can be used to support the encoding and retrieval of declarative knowledge relevant to a task. Information about the context of the task and analogies to other tasks can activate prior knowledge that is relevant to the task. Each trainee enters a training situation with a different amount and structure of declarative knowledge stored in memory. Thus it is difficult to predict what information will be needed from the external environment. There are two basic types of information that can be stored and accessed externally by trainees either before or during task practice: descriptions and demonstrations. Descriptions of, for example, procedures, rules, processes, definitions, examples, cases, or solutions can be provided. Demonstrations of procedures, processes, worked examples, or cases can be provided. When information is provided during practice, that information is generally referred to as "help", "feedback" or "hints". When information is provided in a form that can be accessed and used on the job it is often called a "job aid", "electronic performance support system", or an "expert system".

Traditional instructional design models make specific recommendations about the type of information appropriate for particular kinds of tasks. For example, for tasks that involve distinguishing among objects or events that belong to different categories (called concept identification tasks), most instructional designers would recommend the presentation of definitions and examples of each category/concept (Merrill, Tennyson, & Posey,1992). For tasks involving the performance of a sequence of steps, most instructional designers would recommend provision of a list and demonstration of the steps (Smith & Ragan, 1993). For tasks requiring the selection and novel application of a set of rules and procedures, the common instructional design recommendation would be to present rules and worked solutions to a set of prototype problems in which those rules and procedures apply.


Current constructivist approaches to instruction are less prescriptive regarding the types of information that should be presented during training. Schank (1994) is the most explicit about what types of information should be provided. He advocates that information should be given in the form of stories from experts who have taken the action or decision that the trainee has taken. These experts comment on the potential success of that action or decision, and the reasons why it is or is not a good approach in the context of the current scenario. In addition to story-like responses to trainee actions, Shank also builds into his programs help systems where a trainee can at any time ask for information on what to do next, how to do it, and why it should be done, which effectively separates information about a task into three types.

The amount of information provided/available during training can be fixed (anywhere from low to high) or can vary based on the individual needs of trainees. It may be difficult to anticipate how much information will be needed; therefore, one may need to have more information available than will be used. It is not clear who needs more information: more expert or more novice trainees. Giving novices too much information may make it difficult for them to select what is most relevant for the task at hand; however, by limiting their access to information, one may discourage them from becoming more self-directed learners. Experts may require less information in order to perform a new task in the domain; however, a training task might be made more challenging for more expert trainees by having them select relevant information from a large body of information. Ultimately, the amount of information required by particular trainees will be dictated by the type and number of errors they make during task performance, or by trainees' own interests and perceived needs.

The timing of information presentation can vary. Information can be given before, during, or after a practice activity. Traditional instructional design approaches stress the up-front provision of information. Models of instruction based on theories of situated learning combine both up-front and just-in-time information giving. For example, in the cognitive apprenticeship approach (Brown et al., 1989), the modeling of performance before trainees try it themselves is an up-front provision of information; the coaching that the expert gives trainees as they attempt the task on their own is just-in-time information. Hints and feedback given to trainees during or after practice constitute information that trainees will use to improve their performance. The conditions under which different timing of information may be most effective or efficient are not clear. Like most other instructional variables, the effects of timing of information delivery may depend on the cognitive and affective composition of the trainee at the time of training.

Trainees can control access to information, or the system can decide when information should be presented. However, the extent to which a trainee should have control over access to information during training is unclear. There is much debate in the literature on the topic of learner control (Chung & Reigeluth, 1992; Hannafin & Sullivan, 1995). Research in this area has not produced consistent results regarding the effects of different combinations of system and learner control on learning and performance. The source of this inconsistency lies in the use of study designs which have not permitted the examination of the effects of different levels of learner control over different elements of instruction, or the effects of increased delegation of control on learners with different ability and affective characteristics. Aptitude-treatment interaction research indicates

Media Selection for Training 23that learners with low ability, high anxiety, and low self-efficacy may not be capable of assuming control of their learning (Lohman, 1986).

The ideal approach to controlling the type, amount and timing of information during training is an approach that is flexible enough to adapt the level of system control depending on trainee performance. To implement such an approach, the system must monitor a trainee's level of performance under the initial/default control-sharing arrangement. If a trainee's performance is errorless, then the balance of control can be shifted more toward the trainee; as soon as a trainee begins to make errors, then the system can assume more control over the type and timing of information presented until the trainee's performance resumes a less errorful pattern.

Instructional methods for practice. The training designer's job is to find out what behaviors and thought processes constitute ability to perform the targeted performance tasks (using cognitive task analysis procedures) and to create a set of practice and information resources that will enable novices to acquire knowledge structures and thought processes similar to experts. Trainees should ideally learn to perform a task by performing the task, or simplified versions of the task, in contexts similar to those in which they will be expected to perform the task on the job. Practice activities can vary in the extent to which they mirror the physical context of the real task (contextual authenticity) and in the extent to which they require the trainee to engage in the cognitive processes employed by expert performers (cognitive authenticity). All practice activities should have high cognitive authenticity, but the level of contextual authenticity can vary. An example of a task that has low contextual authenticity but high cognitive authenticity would be one where trainees are given a written description of a number of customers and are asked to select or suggest a sales technique that might work with each customer. Although the trainees are not meeting the customers in a live situation, they are engaging in thought processes similar to those they would exercise in a more realistic situation.

The most contextually authentic practice is, of course, on the job itself. Even if one conducts training away from the job setting, when a trainee returns to the job, he or she is still in "training". The trainee is now performing tasks with perhaps less external monitoring, and has access to whatever declarative and procedural knowledge he or she remembers, plus on-line or paper-based job aids, or more expert workers on the job. In terms of contextual authenticity, the current trend is to make each practice problem during training as realistic as possible (Norman & Schmidt, 1992; Collins, 1994), the theory being that actions and decisions are linked to the contextual cues that will be expected to trigger them on the job. However, cognitive authenticity and opportunity to practice in varied contexts appear to be more critical than replication of superficial conditions (Schmidt & Bjork, 1992).

Practicing a task facilitates the process of compiling task-relevant procedures. Practice methods with high contextual authenticity include problems, cases, or scenarios in simulated environments similar to those encountered on the job. Practice methods with low contextual authenticity usually involve written or oral exercises where scenarios are described, and students make decisions by selecting from lists of options, or describing what they would do next, either orally or in writing.


The amount of practice provided will depend on (a) the novelty and variety of contexts to which the trainee is expected to transfer skills being learned (the more novel and varied the contexts, the more practice on a variety of tasks), and (b) the speed and accuracy of a trainee's current performance. Training can provide a fixed amount of practice for all trainees, or can vary the amount of practice for different trainees based on the trainees' performance or trainees' requests. Timing of practice and its intermingling with information remains an arbitrary decision. Some theorists advocate providing information before any practice activities (Anderson, 1993); others advocate making practice the first training event a trainee encounters, with information being given or accessible during that practice (Barrows, 1989; Schank, 1994). Novices in a domain may need more information prior to the first practice task than do trainees with more expertise.

In the context of practice, as was the case with information, the ideal control condition would be one where the system can share with trainees control over the amount and timing of practice, and can adjust the balance of control depending on trainee performance on practice tasks. Trainees should always have as much control as they indicate (through accurate task performance) they can handle, and a secondary goal of training should be to increase the extent to which they can direct their own learning. However, one can have training programs where the type, amount, and timing of practice are totally controlled by the system, or where the trainee is given total control.

Instructional methods for monitoring. There are two main types of methods through which the external training environment can provide support for monitoring:

data collection on aspects of trainees' performance and perceptions, and

guidance and tools to help trainees do their own monitoring or monitor each other's performance.

Guidance can be in the form of descriptions or demonstrations of strategies for monitoring one's own or a peer's performance. An example of providing guidance for self-monitoring in description form would be telling trainees to review their own performance on a practice activity (which might have been videotaped so they can play it back), and to count the number of instances of commonly-made errors. Trainees could be given some chart or form to help them keep track of time, errors, problems, or questions that arise during practice. Trainees could also take turns monitoring each other's performance using similar tools.

Alternatively, the system can record aspects of performance such as the following:

trainees' actions and selections during practice,

products that are generated as a result of task performance,

verbalizations during task performance,

time on task, and/or

amount and type of information accessed before and during task performance.

Media Selection for Training 25Anderson's (1993) cognitive tutors record every action taken by a learner as he or she works on exercises related to, for example, LISP programming. These data are used to calculate the probability that a student knows particular rules essential to expertise in the domain. The computer-based problem-solving environments developed by Stevens, McCoy, & Kwak (1991) record the sequence of information items/options a student accesses, and the time spent in each information item. This facilitates detailed analysis of the problem-solving activity of individuals and groups of students. The analysis is displayed visually, revealing, for example, that students who performed poorly on a problem were consistently accessing a particular set of irrelevant information options.

Since poor performance can stem from a lack of effort as well as from a lack of relevant declarative and procedural knowledge related to the task, the system can also monitor trainees' perceptions of the value and demands of the task, and relate these to time on task. To monitor trainees' perceptions of the task one can ask direct questions and record trainees' oral, written or selected responses to the questions. If a trainee performs poorly, spends less time on the practice task than most other trainees, and also indicates that the task has little value or is either too easy or too difficult, then the system can target intervention at the value or demands of the task, rather than at task-related declarative and procedural knowledge.

The amount of monitoring (either data collection or guidance for self-monitoring) can be fixed (anywhere from low to high) or can vary. One can start with a high degree of monitoring support and gradually reduce it, or one can start with a low amount of monitoring and increase it if a trainee is making many errors during practice, so that one has enough data to identify the source(s) of those errors. One can choose to monitor every practice activity or to record performance and perceptions on a sample of tasks. For example, one could allow trainees to attempt the first practice activity unmonitored, and then monitor their performance and perceptions during a second similar task. The timing of monitoring can be fixed or flexible. The system can control all aspects of monitoring, or trainees can be given control over when and what is monitored by the system or how much guidance they want for self-monitoring. Control can also be shared with the trainee, the amount of system control increasing or decreasing depending on the accuracy of trainee performance on practice activities.

Monitoring is treated here as a distinct category of support, separate from the analysis of the data recorded, because (a) the media that are used to record data on performance and perceptions can be different from the media used to analyze the data or adapt the level of support for other processes based on that analysis; and (b) external support for learning could stop at this point. Data on performance might simply be reflected back to the trainee who would have complete responsibility for interpretation of the data and correction of errors in performance. According to Collins and Brown (1988), by reflecting back to a trainees the process by which they carried out a task, and also providing a model of accurate task performance, trainees can themselves discover elements that need improving. In addition, trainees are learning to monitor and diagnose sources of errors their own performance.

Instructional methods for diagnosis. The external training environment can provide two types of support for error diagnosis. The system can analyze data gathered

Media Selection for Training 26during monitoring or can offer guidance for students to do their own (or each others') analysis and diagnosis of sources of errors. Providing guidance for self-diagnosis and peer-diagnosis might involve giving trainees checklists which would describe the most likely causes of particular errors in performance. Another example of guidance for self-monitoring would be to replay the trainee's performance alongside an expert's performance on the same task, and have the trainee note differences between his own and the expert's performance.

Performance data can be analyzed in conjunction with data on trainees' interaction with information resources, and trainees' perceptions. A range of quantitative and qualitative/logical analysis procedures can be applied to the data that has been gathered on trainee performance and perceptions. The goal is to link patterns of errors in performance to gaps in goal interpretation, or declarative and procedural knowledge so that the trainee can be directed to the goal elaboration, information or practice most likely to help him or her correct the error. For example, if a trainee practicing a technique for conflict resolution constantly omits the final step where the persons in conflict agree on their responsibilities as part of an action plan to solve the problem that is causing the conflict, then we have a clear indication that this trainee needs additional information on the final part of this technique, and maybe also a separate practice activity that focuses on this step of the procedure. If a trainee constantly misclassifies examples of one of ten components of an engine, then the trainee needs to review information on that component. It a trainee's pattern of errors seems random, then it may indicate that the trainee was generally not investing effort and needs more elaboration on the value of the goal and demands of the task. Analysis of perception data can confirm this hypothesis. Analysis of perceptions is important because if a trainee's perception of the value of a task is low or if the perception of difficulty is too high or too low, then the first line of intervention to improve performance should target these perceptions rather than particular pieces of declarative and procedural knowledge.

Analysis of the manner in which a trainee interacted with available information before and during a practice activity may confirm an initial diagnosis of gaps in declarative knowledge based on errors in performance. For example, it may turn out that a trainee, whose errors all involved selection of incorrect cables when practicing installation of telecommunication networks, spent very little time viewing information on cables. This would increase one's confidence in the diagnosis of the source of the trainee's poor performance and would make the prescription for adaptation clear; the trainee could be directed to review information on cables, or information on cables could be retrieved and displayed by the system.

In addition to analyzing data for individual trainees, data can be aggregated and patterns of errors and perceptions across groups of trainees can be analyzed to identify common sources of those errors. If many trainees are making similar errors or have maladaptive perceptions of a task, then this may indicate a need for a global change in the program; for example, it may be that more information needs to be provided up-front on a particular aspect of the task. If many trainees question the value of a task, then some up-front discussion of the value of the task might be built into the next version of the program, or the intervention to correct errors might involve a group discussion on the value of the task.


The amount of analysis that should be done on data gathered while trainees are performing practice tasks will depend on the resources available to do such analysis and on the extent of errorful performance; the more errors being made by a group of trainees, the greater the need for analysis. However, no more analysis should be done than is necessary to maintain accurate performance for all trainees. The more detailed and individualized the analysis, the more efficient and effective will be the training, since it will be possible to give appropriate support for correction of errors only to those trainees who need the support.

The timing of analysis/diagnosis is related to the timing of system adaptation or guidance for adaptation. Data on performance and perceptions do not have to be analyzed immediately. The training designer must decide whether to provide immediate individualized adaptation, immediate group adaptation, delayed individualized adaptation, or delayed group adaptation. There are advantages and disadvantages to different timings of analysis and adaptation; therefore, the timing of analysis is an arbitrary decision. Recent research indicates that immediate corrective feedback may improve performance during training, but immediate feedback has a negative effect on retention and transfer because it reduces the trainees' depth of processing during learning (Schmidt & Bjork, 1992). However, to avert the development of enduring misconceptions or an increase in the perceived difficulty of a task, immediate adaptation may be preferable if a trainee is making consistent and frequent errors.

The system can control how much support should be given for diagnosis, and when it should be given, or it can be left to the trainees to ask for guidance or for analysis of their performance. The system can decide how much analysis of performance data it will do, or how much guidance to give trainees to help them self-diagnose. Alternatively, analysis might only be provided if a trainee requests it. If control is shared between system and trainees, then the system might gradually decrease the amount of diagnosis it does or the amount of guidance it gives for self-diagnosis.

Instructional methods for adaptation. Methods can be provided to adapt instruction for trainees based on diagnosis of the sources of errorful performance, or guidance can be given for trainees to do their own adaptation, or to help each other improve their performance. External support can be provided to adapt a trainee's goal interpretation, and task-relevant declarative knowledge and procedural knowledge. Thus, there are three types of adaptation methods: adaptation of goal elaboration, adaptation of information, and adaptation of the practice components of training. When a trainee has performed poorly on a practice task, new information can be presented, or information the trainee has already seen can be presented again. New simpler practice tasks can be prescribed, or more scaffolding can be provided to complete the current task or a similar task. New information on the goal of the task, its value, and difficulty can also be presented.

We suggested earlier that analysis of errors in performance should identify the most likely information, or adjusted practice that would lead the trainee to correct errors. We also suggested that the source of poor performance may not be a lack of specific declarative or procedural knowledge, but rather a lack of effort resulting from either a perception of the value of the task that is too low, or a perception of the task as too easy

Media Selection for Training 28or too difficult. If the data indicate maladaptive perceptions, then the first line of intervention or adaptation of the training would be to target the trainee's perceptions of the task goal so that he or she sees value in it and perceives it as a moderate challenge (Keller, 1983; Lepper et al., 1993). Value can be increased by exposing the trainee to a story from or about a person the trainee identifies with and respects. The story should emphasize the high value the "role model" places in this task. Lepper et al. (1993) and Keller (1983) have described strategies for increasing or decreasing the perceived difficulty of a task; for example, to decrease the perceived difficulty of a task, it can be broken down into smaller pieces or more hints can be given during task performance. To increase the perceived difficulty of a task, stories can be told about how difficult other trainees have found the task and how much effort they spent to complete it.

Depending on trainees' error patterns, extra elaboration on the goal of the task can be provided, or a trainee can be instructed to review particular pieces of information, or to complete a simpler task, or to spend more time on the task because "most people find this task very difficult and need to spend longer working on it than they anticipated". The amount of adaptive intervention for a particular trainee will at first be fairly arbitrary, but as a record of the trainee's performance is compiled, then the amount can be tailored more precisely, increasing and decreasing as the trainee's performance improves or declines. The timing of adaptation can be immediate or delayed. Adaptation can occur as soon as an error is detected, or intervention can be delayed until a consistent pattern of errors has been observed and a likely source identified. The system can control the amount and timing of adaptation or trainees can be given the option of requesting "help" when they think they need it.

Summary of Training Methods Selection

We have separated the strategies or methods that are commonly used in training into six categories based on the cognitive activity they support. We have suggested that methods used to externally support any cognitive component of the learning process can vary in type, timing, amount and in terms of who or what is controlling their deployment. As a first step toward selection of media, designers should select the type, amount, timing, and control of methods that will be used in a particular training program. Figure 6 summarizes the sequence of steps a designer would need to follow when implementing the "method-selection" phase of media selection.

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If a program has already been designed, the designer can use this model to review the design and identify how each of the six cognitive components of learning is being supported in that program. If the final combination of media has already been selected, this activity will serve as a check to confirm (a) that adequate external support for all cognitive processing has been designed into the training, and (b) that the media selected are capable of delivering the selected type, timing, amount, and control of that external support. Essentially, one is asking the following questions about the training:

How will information about the goal of the training be communicated to the trainees?

Media Selection for Training 29How will information related to the training task(s) be delivered or made available?

How will opportunities to practice be provided?

How will trainees' performance be monitored?

How will performance data be analyzed and sources of errors diagnosed?

How will the training be adapted for individual trainees so that errors in performance are corrected?

One can make an assumption prior to design that trainees will be able to do much of the processing for themselves, in which case the amount of external support will be less. However, the training should be designed so that performance under conditions of low support is monitored closely initially, to confirm the hypothesis that the trainees are capable of regulating their own attainment of the goals. If monitoring reveals that there are some trainees who are performing poorly in the low-support environment, then there needs to be a way to increase the level of support for those trainees. Alternatively, one can make a decision to begin with a high level of system support for all cognitive processes and withdraw support as trainees indicate (through accurate performance) that they can assume more of the burden themselves. In either case (low support with monitoring and increase if necessary, or high support with monitoring and decrease as necessary), external monitoring of trainee performance will be an essential component of the training. Figure 7 illustrates the flexible nature of a model of training where control is shared between the system and the trainee, and where the amount, type and timing of support can vary.

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Once methods have been selected, the next stage of the media selection process involves the selection of media attributes that are necessary to supply the selected type, amount, timing, and control of methods. The next section describes how to select media attributes.


Selecting Media Attributes to Facilitate Delivery of Training Methods

The methods specified for a training program will dictate the media attributes or capabilities necessary to deliver that program. Although it may turn out that the same medium will be employed to deliver a number of components of a training program, we recommend that the designer/selector begin by selecting separately the media attributes/capabilities/requirements for each of the six categories of external support (methods). Based on Levie's (1989) and Kozma's (1991) categorization of attributes, we think that it is useful to classify media attributes into five types: transmission, storage, recording, processing, and retrieval. Transmission attributes are capabilities for transmitting different types of information such as visual, audio, or textual information, and also for transmitting contexts for practice. Storage attributes are capabilities for storing different types and amounts of information. Recording attributes are a medium's ability to record different types of trainee inputs. Processing attributes are capabilities for analyzing different types of trainee inputs and manipulating stored resources. Retrieval attributes are capabilities for accessing stored information.

Different attribute categories are more relevant to particular instructional method categories. Figure 8 summarizes the media attributes most closely related to each of the six methods that can be incorporated into training. We will take each category of methods in turn and indicate what media attributes are most important given particular method decisions. Attributes needed for goal elaboration and information methods are similar since both of those methods involve providing either descriptions or demonstrations; therefore we combine our discussion of selecting media attributes for those two methods.

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Selecting media attributes for goal elaboration and information methods. The categories of media attributes most closely related to the goal elaboration and information components of training are transmission, storage, and retrieval. We identified two main types of methods for supporting goal interpretation and encoding of declarative knowledge about a training task: provision of descriptions about the goal or the task, and provision of demonstrations that illustrate the goal or how the task is performed. If a training program only provides descriptive information, then any medium that can transmit verbal information (written or audio) will be capable of transmitting goal elaboration and task-relevant information. If demonstrations are part of the training design, then media capable of transmitting visual as well as verbal information will generally be required. However, there are situations where a non-visual demonstration would be possible or appropriate, for example, an audio demonstration of a particular style of playing a musical instrument, or a tactile demonstration of a physical procedure for visually-impaired trainees.

The actual information transmitted will be dictated by the performance goal. For example, if the performance goal is that the trainee should be able to select the most appropriate mix of people for project teams, then descriptive information might include

Media Selection for Training 31definitions and examples of different types of team members, criteria for classifying people as different types, and rules about what mix of types of people work well on different types of projects. Information in the form of demonstrations related to the same task might include some acted-out sample cases showing how managers formed teams for different projects, with perhaps narrated commentary on the thought processes the managers were going through in order to make the selections.

The amount of information to be presented or available during training will require a medium that can store that amount and type of information. If the amount and timing of information to be delivered is to be variable, and controlled by the trainee, then a medium capable of processing trainee searches and retrieving appropriate information will be required. On-line databases, books, and user phone hotlines with a human on the end of the phone delivering relevant information in response to user queries are examples of media capable of processing trainee requests for information. An example of a medium with the combined attributes of storage of a large amount of visual information, variable trainee-controlled retrieval of that information, and transmission of visual information would be interactive video. Examples of media capable of storage of a large amount of verbal information, processing of trainee requests, and rules for retrieval based on student responses would be computers or human trainers. Printed materials with indexes to the information in them could store a large amount of both verbal and static visual information, allow trainee-controlled retrieval, and even have simple rules to direct the trainee to particular parts of the materials depending on their performance (self-monitored) on practice tasks. The user manuals that accompany computer software are an example of such printed materials.

Selecting media attributes for practice methods. The category of media attributes that is most relevant to the practice component of training, is transmission. The medium selected for this component of training must be able to transmit the level of authenticity of context prescribed in the training design. The more contextually authentic the practice tasks, the more they will require media capable of replicating on-the-job conditions. Thinking of media as environments capable of providing contexts for task practice which are more and less authentic requires a broad notion of what constitute media. The real job environment becomes a medium. A room in which trainees can role-play interpersonal situations becomes a medium. A flight simulator becomes a medium. A kit of materials for building a kitchen cabinet and a room that will serve as the simulated kitchen become a medium/environment for authentic practice. The entire environment for practice should be considered a medium, and an important feature of that environment is its contextual authenticity.

Regardless of the level of contextual authenticity of practice, the amount, timing, and control of practice activities will indicate additional media attributes. As was the case with goal elaboration and information, if the amount and timing of practice to be delivered is to be variable, and controlled by the trainee, then a medium capable of processing trainee requests for particular practice activities and retrieving those practice tasks will be required.

Selecting media attributes for monitoring methods. The category of attributes most relevant to facilitating the monitoring function of training is the recording attribute.

Media Selection for Training 32If trainees are expected to do their own monitoring, with external guidance for self-monitoring provided, then any medium capable of storing and transmitting descriptions or demonstrations of self- or peer-monitoring will do. A wide range of media can be used to provide guidance, for example, print, video, human, computer. If tools for self-monitoring or peer-monitoring are part of the training design, (for example, a chart where a trainee can keep track of how many practice tasks he or she has completed, or how many instances of particular errors he or she has made), then media capable of storing and transmitting those tools will also be required.

If the system is to monitor performance, then media capable of recording whatever types and amounts of data were specified in the design will be required. For example, if the design specifies that all trainee actions will be recorded while trainees are working on practice activities, then media capable of recording trainee actions will be required. A video camera could be used or a human trainer might observe and make notes, or a computer might record an "audit trail" as a trainee performs a task. If the products of trainee practice are to be monitored, then a wider range of media can be used. Perception data can be recorded by any combination of media capable of posing questions to trainees and recording their responses. For example, a human trainer might ask trainees to write down some reasons why the task they are learning to perform is important, or to indicate their perceived difficulty of particular tasks on a scale from one to five (either on paper or on a computer screen).

Selecting media attributes for diagnosis methods. The category of attributes most relevant to delivery of Diagnosis instructional methods is processing attributes. As was the case with monitoring, if trainees are to be guided in their own efforts to diagnose sources of error, then any medium capable of storing and transmitting advice (descriptions or demonstrations of how to do self- or peer-diagnosis) may be used. If, in addition to advice, tools to aid in self-diagnosis are specified in the design, then media capable of delivering those tools will be required. If the training design specifies that the system will go beyond guidance to actual analysis of trainees' performance data, then media capable of processing and analyzing those data will be required. Currently, only two media are capable of data processing/analysis, either immediate or delayed: humans and computers. Thus, any training program that plans to be diagnostic and adaptive to trainee needs has to employ computers or humans in the analysis of performance data. Similarly, any training program NOT employing computers or humans as either the sole delivery medium, or as part of a more diverse combination of media, CANNOT provide more than guidance for trainees' own monitoring and diagnostic processes.

Processing of performance data can be either immediate or delayed. An example of delayed processing would be when trainees' work is collected and reviewed some time later by a human trainer. If trainees are given control of delayed analysis, then a variety of media can be used to request such analysis. For example, trainees might use electronic mail or voice mail to request analysis of their work. However, a human or a computer will still be required to perform the analysis.

Selecting media attributes for adaptation methods. The category of attributes most relevant to adaptation is that of retrieval. The design for a training program can specify that trainees be given guidance regarding how to correct their errors, or that the

Media Selection for Training 33system should intervene and retrieve specific goal elaboration, information, or practice activities for the trainee. If adaptation is to be immediate, then a medium capable of monitoring, analyzing and adapting simultaneously is called for. Thus, the media attributes of recording, processing, and retrieving must all be present. Only computers and humans have this capability. If the design of a training program specifies delayed adaptation, then the range of media capable of delivering adaptation is increased. For example, upon analysis of trainee performance, a set of materials can be retrieved from storage and transmitted to a trainee; these materials should include information and/or practice tasks that are likely to help the particular trainee achieve the goal. In another case, a trainee might simply receive a delayed written critique (perhaps via electronic mail) of his or her performance or a delayed face-to-face consultation with a human trainer during which the trainee is directed to review particular pieces of information and do another practice task.

Trainee control of available adaptation and guidance gives the trainee the option of requesting help, either while they practice or some time later. Many computer-based/multimedia training programs have "help" buttons and menus which allow trainees to retrieve information that they think they need. If on-demand help, rather than system-generated help is specified in the training design, then a medium with the ability to retrieve task-relevant information on demand will be needed.

Summary of Media Attributes Selection

We have proposed five categories of media attributes and indicated how different instructional methods are related to these attributes. The media attributes most relevant to goal elaboration and information methods are transmission, storage, and retrieval. The attribute most relevant to practice is transmission. The attribute most relevant to monitoring is recording. The attribute most relevant to diagnosis is processing; and the attribute most relevant to adaptation is retrieval. The amount, timing, and control of methods will dictate the need for other media attributes. Figure 9 lists the steps necessary to match media attributes to the methods specified for a particular training program.

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Selecting A Final Combination of Media

Once a training designer has identified the media attribute requirements for the training methods selected, then he or she can proceed to the last stage of the media selection process which involves selecting the most economical and accessible mix of media that includes all of the attributes needed to deliver the training program. Earlier we suggested that the selection of training methods influences the extent to which trainees will learn and be motivated to learn, and in some cases, the efficiency (time to learn) of the training. We suggested that the choice of media influences access to training and its cost and efficiency (see Figure 1). When selecting media, as opposed to selecting methods or media attributes, the goal should be to maximize access and efficiency, while minimizing the costs of training.


Required media attributes that restrict media options. There are just a few media attribute requirements that restrict the range of media that can be used to deliver particular components of training. First, a human or computer will be required if a medium capable of processing student actions and retrieving appropriate adaptations to goal elaboration, information, or practice is needed. If the specifications for a training program do not include system diagnosis and intervention to correct errors, or system control of variability in amount or timing of other methods, then the training can be formatted for delivery in virtually any medium or mix of media. If the training will only give guidance and some tools for trainees to do their own diagnosis and adaptation, then a computer or human will not be necessary. If amount and timing of goal elaboration, information, practice, and monitoring are fixed (and controlled by the system), or if trainees are expected to control their own progress through available information and practice activities, then computers or humans will not be necessary. An example of fixed amount and timing of information and self-control of practice would be a training situation where all trainees watch a live one-way video demonstration of a welding technique and then go back to their jobs and practice the technique, using a checklist to monitor their own performance.

The second restriction on media occurs if a medium capable of transmitting a contextually authentic practice environment is required. In that case, either the real job environment, or some "virtually real" environment, or computer-based simulation of the real environment will be needed. The third and final restriction on the choice of media arises if a medium capable of transmission of visual demonstrations is required; in that case, either a human who can perform a live demonstration, or a "visual medium" that can transmit a pre-recorded demonstration will be required.

Interchangeable media. Any medium or mix of media can provide fixed or optional access to descriptive information about goals and tasks, cognitively authentic practice tasks (or directions for setting up contextually authentic tasks), and guidance and tools for self- or peer-monitoring, diagnosis, and adaptation. All of these methods can be delivered in print, video, audio, or by humans or computers. One might have to be creative about the kinds of practice activities one could deliver/describe, for example, on audiotape, but it would not be impossible to train someone to cook, dance, run a business, or fly an airplane using, for example, only radio, as long as that trainee was able and willing to do the following:

1. translate some of the information given in one medium into a medium that could be consulted later to review information that might help correct errors in performance (for example, recording a live radio broadcast or making written notes during the broadcast),

2. set up the environment necessary to carry out whatever practice tasks are described or demonstrated (for example to practice a cooking technique, the trainee would have to assemble all of the necessary ingredients and utensils),

3. do his or her own monitoring and diagnosis, and seek out the information needed to correct errors, and

4. invest the effort required to master the task.


Schramm (1977) described many instructional programs in operation around the world where single media, such as radio or television, or combinations of media, such as correspondence with home-study kits, were used to teach skills with equal effectiveness (for those who completed the courses) as traditional classroom-based programs. However, the number of students who participated seriously and actually completed the "media-extended" programs was generally only a fraction of the total number who enrolled initially. High drop-out rates are a problem in most distance learning programs. We hypothesize that the more support that is given for each of the six processes involved in learning, the more students will complete distance learning programs. Many distance learning programs provide minimal support for monitoring, diagnosis and adaptation; therefore only students who can perform these processes for themselves are likely to succeed. The most successful distance learning programs have been those that relied heavily on "study groups" where small groups of trainees meet, listen or view material, discuss it, and practice (Schramm, 1977). The group provided a mechanism for peer-monitoring, diagnosis, and adaptation.

Cost and ease of access. As the media available for distance learning, and on-the-job training become more and more sophisticated, the "best use" and combination of technologies such as two-way video conferencing with old-fashioned media such as print can be guided by selecting the least expensive and most accessible media that will give the level of external support for cognitive processing selected for the training. If one opts for a newer medium, then one should at least be clear about which functions of training it can and cannot deliver, and use it for functions that it renders more accessible or less costly. For example, two-way video technology makes access to an expert human tutor easier. The distant human tutor can tune in and monitor trainees located in various places around the world as they practice the same tasks in slightly different job environments, providing immediate diagnosis and adaptation to improve performance. A two-way audio link during a live broadcast might make it easier for students to access relevant information since they can ask questions of the remote, live trainer.

A computer might make it easier and less expensive to provide a practice environment that simulates real task conditions. A computer might also make it easier to access large amounts of descriptive information and demonstrations related to the tasks being trained. A CD-ROM might make access quicker and easier than access to the same information over local or global computer networks. A CD-ROM or videodisk will make access to segments of video easier than videotape.

The relative costs of different media combinations will be influenced by the size of the audience for the training and the extent and efficiency of the development systems and facilities available. If the audience for training is small, then media that require less time-consuming up-front development, for example, human trainers with some print materials may be preferable to computer-based training. However, if a company has shells or templates for creating computer-based/multimedia training that embodies appropriate types and amounts of external support, then computer-based training may always be the least expensive option in that organization. Rather than repeat here procedures for calculating the relative costs of different media for delivering training, we refer the reader to Levin (1983).

Media Selection for Training 36Summary of Final Stage of Media Selection

The third stage of media selection boils down to making a decision regarding whether or not a computer or human "trainer" will be required for diagnosis, and adaptation, whether or not a visual medium will be required for demonstrations, and whether a medium that can provide contextually-authentic practice will be required. Those decisions will be based on the methods and media attributes that have been selected in the previous stage of the media selection process. Once decisions regarding humans, computers, visuals and practice environments have been made, then almost any medium or mix of media could embody any remaining attributes required. The final selection of media should be based on ease of access for the target audience, and cost of development and delivery. Figure 10 summarizes the steps and criteria for making final media selections. We will now illustrate how the three-stage process of media selection could be applied to selection of media for a multimedia development project.

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Applying the Model to Select Media for a Multimedia Training Environment.

Multimedia training is training that is delivered via computers, but incorporates almost every other medium, including video, audio, still and animated graphics, and text. Thus, it is possible to find every conceivable combination of media attributes that might be required to deliver a training program in a multimedia system, with the exception of the actual job environment for practice (unless, of course, the tasks being trained happen to be tasks that are performed with a computer).

Assuming that multimedia will be the delivery system for a program to train newly-hired chemical plant workers in plant safety regulations and procedures, the focus turns to more micro-level decisions such as which components of the program should use video, or which should use text. Applying the three-stage media-selection model to this situation, we would first make decisions regarding the type, timing, amount, and control of goal elaboration, information, practice, monitoring, diagnosis, and adaptation methods for this program. Then we would identify the attributes needed to support our method selections, and finally we would select the media components that would be least expensive to develop and deliver, and would permit the easiest access within the multimedia system.

Types of methods. For this training program, we chose descriptive methods to present the goals, a mixture of descriptive and demonstration methods for information, low contextually authentic methods for practice, collection of product data for monitoring, and guidance methods for diagnosis and adaptation. We assumed that the trainees would be able to do their own diagnosis and adaptation with some guidelines and tools provided by the system. We also assumed that as long as the practice activities engaged cognitive processes similar to those required in real situations, and as long as the trainees were exposed to a representative range of situations, both in demonstrations and practice scenarios, then transfer of training would occur (Anderson, Reder, & Simon, 1996).


Amount, timing, and control of methods. To verify that the trainees were capable of self-diagnosis and adaptation, we specified a high level of monitoring in the early stages of the program. Those trainees who were not initially succeeding with the level of support provided were to receive additional training in self-regulated learning skills. We decided to provide a fixed amount of practice at fixed times during the program with optional access to information and goal elaboration during those practice activities. The system was to control the collection of data. Students' final decisions (selected from menus of alternative decisions) in safety-related scenarios and exercises were to be recorded, and the system was to inform the student of the correctness of his or her decisions. No recording of the process by which the student reached a decision was specified (for example, the system should not monitor what information the trainee consulted while working on a scenario, or the system should not probe the trainee for the reasoning behind a selection). The system was not to analyze a trainee's pattern of responses and was only to give general guidance regarding how to correct errors in performance. For example, trainees could be told at the beginning of the program that when they made an incorrect selection in a practice activity, they should review whatever information they considered relevant before attempting the practice activity again.

Selecting media attributes to match methods. Since we opted to simply describe the goal of each safety-related task, we needed a medium or media that could present verbal information (written or oral). For information, we had specified a mixture of descriptive and demonstration methods; therefore, we needed a medium or media that could show visually the safety procedures and their outcomes. Since we wanted to give optional access to information during practice tasks, we needed the system to be able to store information, process trainee queries, and retrieve the appropriate information immediately. For practice, we did not want a high level of contextual authenticity; therefore, we only needed a medium capable of transmitting a description or demonstration of a scenario and a medium capable of allowing the trainee to select from a menu of options what he or she would do or decide regarding safety in the scenario.

For monitoring, we needed the system to record student selections at the end of practice scenarios, and to tell the trainee if the selection was correct or incorrect. We needed the system to also transmit some general advice to students on how to improve their performance, for example, that they should keep track of the errors they made and see if there was a pattern to their errors, or that they should search through the information bank for information that would clarify why a particular decision they made was less than optimal. Such guidance could be delivered verbally, via text or audio. We had specified more intense monitoring of trainees in the first part of the training, and so we would temporarily need the system to record more data on the trainees' actions, and to identify students who need additional training in self-regulation before proceeding with such low-support training.

Selecting media. The only restrictions on our final selection of media were the need for a computer or human to monitor trainee decision-making during practice, and the need for transmission of visual demonstrations. The relative costs of developing, storing, and transmitting visual demonstrations of safety procedures in different media within the multimedia system was calculated and it was decided that sequences of still photographs rather than full motion video or computer-generated animations of

Media Selection for Training 38procedures would be the least expensive option. Color, graphics, and text overlays would be used to highlight important elements of a demonstration.

Since we wanted to give optional access to information during practice, we needed a medium with appropriate storage, processing, and retrieval capabilities; the computer had all of the attributes we needed. Furthermore, the cost of repurposing existing paper- and video-based material on safety regulations and procedures for computer storage and retrieval was less than providing all of the print and video materials to each trainee.

Since the training was to be computer-based anyway, we already had a medium with the ability to record student selections. The computer would be programmed to record more data during the first module of the training, and to automatically terminate the program if a trainee was making consistent errors, and not accessing appropriate information before attempting the activity again. A message would appear on the screen telling the trainee that he or she should sign up for some self-regulation/self-directed learning skills training. The use of a multimedia system to deliver training does not rule out the use of a human for some elements of the training. Thus, we could have opted to use human trainers to monitor student progress in the early part of the program. Human trainers could have reviewed the data recorded by the computer and decided which trainees were not capable of learning in such a low-support environment. However, the computerized monitoring was less expensive to deliver and more accessible than human monitors, and so humans were not selected.

We had specified a low level of contextual authenticity for practice; therefore, we did not need the real job environment to provide external support for compilation of procedural knowledge. We did not even need the full capabilities of the computer to transmit realistic scenarios; the scenarios and selection options could have been conveyed through print or through a human trainer. However, given that (a) we wanted to record trainees' decisions and give them immediate feedback on their accuracy, and (b) we wanted trainees to access information during practice, we decided to make all of the practice activities computer-based. Video clips depicting practice scenarios were considered, but would have been more expensive to stage, record, edit and store in computer memory than computer-generated graphic images, text, and audio segments representing the same situations. For example, a computer animation could depict a scenario in which there was a spill of a hazardous chemical during the night shift with only one operator on duty. A narrator could describe what the operator did and ask the trainee if the operator had made the correct decision; the trainee would indicate his or her answer by clicking the mouse on a "yes" or "no" button. Alternatively, the trainee could be asked to select (by clicking the mouse on the appropriate box) which of a number of actions the operator should take.

The final media selections for the safety training program did not include video, but included text, still and animated graphics, audio, all stored and accessible via the computer. The recording capabilities of the computer were also used to monitor student performance. If the original decision to create multimedia training had not been made, then we would have had more media options, and it might have been less expensive to provide information and practice scenarios on videotape, with print materials for

Media Selection for Training 39recording student responses, and human trainers monitoring trainee performance. The advantage of the multimedia system is that parts of the training (particularly the information bank) could also provide electronic performance support on the job if an employee had access to a computer terminal.

Summary. In the example just described, even though it had been decided a priori that the training would be multimedia, there were still media selections to be made. We were able to go through the three-stage process in order to arrive at a set of media recommendations for each component of the training. We were also in a position to justify each choice by referring to an instructional method decision which, in turn, called forth particular attributes, some of which restricted our choices of media. When choices remained, final decisions were made based on ease of access, given restricted media choices that had already been made, and relative costs of development and delivery. This may seem like a rather laborious process to go through to arrive at what might seem fairly obvious and intuitive selections. However, it is a procedure which, like any other procedure, becomes automated with repeated application. At least it has its origin in a cognitive view of learning and instruction, and is more internally consistent than previous media selection procedures.

Future Scenarios

Training is becoming less and less separated from other aspects of organizational development (Dubois, 1993; Robinson & Robinson, 1995). The role of the training department in an organization is changing from design, development, and delivery of training products to analysis of the environmental conditions and personal competencies that maximize or compromise the performance of humans in the organization. The analysis of conditions and competencies leads more often to prescriptions for selection of employees and tools to enhance their performance while doing the job, than to prescriptions for training. Thus, in the future, media selection will occur in the context of designing performance support systems rather than in the context of designing training programs.

If we abandon a traditional view of training, the focus of our media choices shifts to selection of media for monitoring human performance and the conditions in which it occurs, and media for delivering the kinds of resources that support and enhance the development and exercise of human competence. Decisions regarding media for monitoring performance, either for selection or identification of competence on the job, are similar to selection of media for monitoring performance during training. Some mechanism for recording the process and/or the products of task performance will be required.

The kinds of resources normally provided to support human performance on the job include easily accessible information banks, and mentoring/coaching. These two types of resources can provide external support for the cognitive processes required to develop expertise. The coach/mentor can serve all the functions of training: goal elaboration, information, assignment of practice tasks (real tasks being thought of as practice tasks), monitoring of performance, identification of sources or errors, and suggestions for improving performance. Most online help systems do not provide support for all of the cognitive processes required for performance, although they could

Media Selection for Training 40do so. A help system could provide a demonstration of task performance, could talk the trainee through a practice task, could monitor the trainee's performance, could diagnose error sources and prescribe some new task or information search.

Moving from event-based training to embedded performance support does not change the cognitive processes that need to be engaged to progress from novice to expert. Thus, a media selection model which selects media to deliver support for different cognitive processes in the context of training can transfer easily to the context where performance support tools rather than training materials are being designed. Designers of performance support systems can consider

what type, amount, timing, and control of goal elaboration, information, practice, monitoring, diagnosis, and adaptation should be provided on the job

what kinds of transmission, storage, retrieval, recording, and processing capabilities the system will require

the most accessible and least expensive options for delivering the type and level of support selected.

If the trend toward more trainee control over learning in a higher-stakes environment (i.e., on the job) continues, then organizations will need to invest in more training or on-the-job support for self-regulation or self-directed learning skills. There is no reason why media selection decisions related to delivery of programs and tools for self-regulation should be different from the decisions that need be made for other domains. Learners need self-regulation goals and information about how to, for example, monitor their own performance or correct errors. Learners need opportunities to practice self-regulation skills such as planning, selecting relevant information, and monitoring their own performance. In addition, learners who are just beginning to develop self-regulation skills will need to be monitored, have their weaknesses in self-regulation diagnosed, and have the "training" adapted if necessary.

In the future, media selection decisions will be made in the context of increasingly interconnected, and increasingly fast networks of media. The two primary anchors for all delivery systems will be computer networks and humans, with an increasing codependence between the two anchors. If we keep in mind that we need to support multiple cognitive processes with our performance support/training systems, then we will exploit the full range of capabilities of new media systems.

Conclusion

Media selection for training may still be less of a scientific endeavor than we would like. However, rather than following rules with little theoretical or empirical basis, we have suggested that media be selected for their ability deliver various types and amounts of support for cognitive processing during learning. If many media are capable of delivering one component of a training program, then we advocate choosing the most accessible to trainees and the least expensive that will do the job. Ideally, one would postpone the final selection of media until one had designed the methods to support whichever of the processes involved in learning are to be supported in a particular

Media Selection for Training 41program. Then one could list the attributes or capabilities that the delivery media would need to have in order to implement the training as designed. However, we are not so naive as to think that media selection will not continue to occur at other times and for other reasons in the real world.

In situations where media might be selected even before training is designed, one can at least review the pre-selected media to make sure that they possess all of the attributes that the design requires for implementation. If the initial choice is not capable of delivering some element of the design, then a medium that has the missing attribute can be added. Ultimately, if the design is sound (i.e., provides the right amount of external support for learning), and the selected media can deliver it, then trainees will achieve the performance goals, regardless of how high-tech or expensive the media happen to be.

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Footnote1 The third edition of Anderson's (1976) book titled "Selecting and Developing Media for Instruction" appeared in 1991 (Reynolds & Anderson, 1991), but it does not count as a new model.


Figure 1. Aspects of training influenced by media and methods.

AccessCost

(Development and Delivery)

Efficiency(Time to Learn)

Learningand

Motivation

Media X X X

Methods X X

Figure 2. Characteristics and limitations of existing media selection models.

Characteristics Limitations

Two stages:

Task/trainee/instructional events matched to media

Practical considerations

No sound basis for matching media to tasks and trainees

Not enough focus on matching media to instructional events

Instructional events not cognitively defined and linked to media attributes

Media lists and categories

Media mixed with non-media

Media-independent variables associated with particular media

Figure 3. Three-stage process involved in media selection.


Selectinstructional

methods

Selectmedia

attributes

Selectmedia

Figure 4. Minimum external resources to support six internal cognitive processes.

Interpretgoal

Encode/retrievedeclarative/procedural

knowledge

Compile newproceduralknowledge

Monitorperformance

Diagnosesources of

error

Adapt toimprove

Goal

Practiceopportunities

Information

Media Selection for Training 51Figure 5. Method Options

MethodType of External Support

Amount of External Support

Timing of External Support

Control of External Support

Goal Elaboration

Description

Demonstration

Low High

Fixed Flexible

Fixed Flexible

Before During

System, Trainee Shared

Information Description

Demonstration

Low High

Fixed Flexible

Fixed Flexible

Before practice

During

System Trainee Shared

Pactice Level of Contextual Authenticity

Low High

Fixed Flexible

Fixed Flexible


Monitoring Data collection (performance/ perceptions)

Guidance (self- or peer- monitoring)

Low High

Fixed Flexible

Fixed Flexible


Diagnosis Data Analysis (individual/ group)

Guidance (self or peer)

Low High

Fixed Flexible

Fixed Flexible

Immediate Delayed


Adaptation Prescription (individual/ group)

Goal Elaboration

Information Practice

Low High

Fixed Flexible

Fixed Flexible

Immediate Delayed



Figure 6. Procedure for method selection

Instructional Method Selection Procedure

Step 1

Step 2

Step 3

Step 4

Step 5

Step 6

Step 7

Step 8

Step 9

Select:

Type of goal elaboration (description and/or demonstration)

Type of information (description and/or demonstration)

Type of practice (high and/or low contextual authenticity)

Type of support for monitoring (data collection or guidance)

Type of support for diagnosis (analysis or guidance)

Type of adaptation (goal/information/practice; or guidance)

Amount of each method (low or high; fixed or variable)

Timing of each method (fixed or variable; immediate or delayed)

Locus of control for each method(system, trainee, or shared)


Figure 7. Model of components of a flexible training environment.

ProblemsCasesScenarios

Materials

Exercises

Analysis

ResourcesInformation Practice

MonitoringSelf/Peer System

RulesDefinitions

Directions

Examples

SimulationsCases

StoriesCommentaries

Demonstrations

PERFORMANCEGOAL

Resources

PerformancePerceptions

SolutionsHints

On-the jobSimulated

Diagnosis

Data

Adapt Adapt

Media Selection for Training 54Figure 8. Media attributes related to instructional methods.

TransmissionGoal Elab.

Information

Practice

Monitoring

Diagnosis

Adaptation

Recording

Processing

Retrieval

Transmission

Transmission

Storage

Retrieval

Type Amount Timing

Storage

Storage Retrieval

Retrieval

Processing

Storage

Control

Processing

Processing

RecordingRecording

Processing

Retrieval

Processing

Retrieval

Processing

Retrieval

Methods

Media Selection for Training 55Figure 9. Procedure for media attribute selection

Media Attribute Selection Procedure

Step 1

Step 2

Step 3

Step 4

Step 5

Select:

Transmission requirements for Goal Elaboration, Information and Practice

Storage requirements for Information and Practice

Recording requirements for Monitoring

Processing requirements for Diagnosis

Retrieval requirements for Information and Adaptation

Figure 10. Final Media Selection Procedure

Final Media Selection Procedure

Step 1

Step 2

Step 3

Step 4

Select:

Computer or human if processing attributes required for diagnosis or adaptation

Visual medium if transmission of visual demonstrations required

Real job environment, computer simulation of job environment, or other medium to simulate job environment if high level of contextual authenticity specified for practice

Least expensive or most accessible media that possess the remaining transmission, storage, recording and retrieval attributes required to deliver the methods specified in the training design

Documents

chapter.fin.jan14 - Institute for Creative Technologiesprojects.ict.usc.edu/.../Sugrue_Clark_Media_Sel_fin.doc · Web viewWilbur Schramm, Big media, little media, 1977, p. 15 Introduction