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  • 4C/ID and Multimedia 1 THIS ARTICLE WILL BE PUBLISHED IN R. E. MAYER (IN PRESS), THE CAMBRIDGE HANDBOOK OF MULTIMEDIA LEARNING. NEW YORK: CAMBRIDGE UNIVERSITY PRESS. The Four-Component Instructional Design Model: Multimedia Principles in Environments for Complex Learning Jeroen J. G. van Merriënboeri and Liesbeth Kester Open University of the Netherlands Abstract The Four-Component Instructional Design model claims that four components are necessary to realize complex learning: (1) learning tasks, (2) supportive information, (3) procedural information, and (4) part-task practice. This chapter discusses the use of the model to design multimedia learning environments and relates 14 multimedia principles to each of the four components. Students may work on learning tasks in simulated task environments, where relevant multimedia principles primarily facilitate a process of inductive learning; they may study supportive information in hypermedia systems, where principles facilitate a process of elaboration and mindful abstraction; they may consult procedural information in Electronic Performance Support Systems (EPSS), where principles facilitate a process of knowledge compilation; and, finally, they may be involved in part-task practice with drill & practice Computer Based Training (CBT) programs, where principles facilitate a process of psychological strengthening. Research implications and limitations of the presented framework are discussed. Introduction design prescribe how to develop educational pro- grams, which contain a mix of educational media Theories about learning with multimedia can be po- including texts, images, speech, manipulative mate- sitioned at different levels. At a basic level, psycho- rials, and networked systems. Well-designed educa- logical theories describe memory systems and cog- tional programs take both human cognitive architec- nitive processes that explain how people process ture and multimedia principles into account to en- different types of information and how they learn sure that learners will work in an environment that with different senses. Examples of such theories are is goal-effective, efficient and appealing. Paivio’’s dual coding theory (1986; Clark & Paivio, 1991) and Baddeley’’s working memory model with The main goal of this chapter is to present a theory a central executive and two slave systems, the visu- that is positioned at the third level, namely, the four- ospatial sketchpad and the phonological loop (1992; component instructional design model (for short, 1997). At a higher level, theories for instructional 4C/ID-model; van Merriënboer, Jelsma, & Paas, message design identify multimedia principles and 1992; van Merriënboer, 1997; van Merriënboer, provide guidelines for devising multimedia mes- Clark, & de Croock, 2002; van Merriënboer, Kir- sages consisting of, for instance, written text and schner, & Kester, 2003), and to discuss how this pictures, spoken text and animations, or explanatory theory is used to design multimedia learning envi- video with a mix of moving images with spoken and ronments for complex learning. Such complex written text. Examples of such theories are Mayer’’s learning explicitly aims at the integration of knowl- generative theory of multimedia learning (2001) and edge, skills and attitudes; the ability to coordinate Sweller’’s cognitive load theory (2004; Sweller, van qualitatively different constituent skills; and the Merriënboer, & Paas, 1998). At an even higher transfer of what is learned to daily life or work set- level, theories and models for course and curriculum tings. The 4C/ID-model views authentic learning i Correspondence concerning this article should be addressed to Jeroen J. G. van Merriënboer, Educational Tech- nology Expertise Center, Open University of the Netherlands, P.O. Box 2960, 6401 DL Heerlen, The Netherlands. Email: jeroen.vanmerrienboer@ou.nl
  • 4C/ID and Multimedia 2 tasks that are based on real-life tasks as the driving 3. Procedural information. Information that is pre- force for learning and thus the first component in a requisite to the learning and performance of routine well-designed environment for complex learning –– a aspects of learning tasks. This information provides view that is shared with several other recent instruc- an algorithmic specification of how to perform tional theories (for an overview, see Merrill, 2002). those routine aspects. It is best organized in small The three remaining components are supportive in- information units and presented to learners precisely formation, procedural information, and part-task when they need it during their work on the learning practice. tasks. While the 4C/ID-model is not specifically devel- 4. Part-task practice. Additional exercises for rou- oped for the design of multimedia environments for tine aspects of learning tasks for which a very high learning, it has important implications for the selec- level of automaticity is required after the instruc- tion of——a mix of——suitable educational media as tion. Part-task practice is only necessary if the learn- well as the presentation of information and ar- ing tasks do not provide enough repetition for a par- rangement of practice and feedback through these ticular routine aspect to reach the required high media. This chapter will first present a general de- level of automaticity. scription of how people learn complex skills in an environment that is built from the four blueprint Learning tasks Part-task practice components. Second, the relationship between the •• Task description (e.g., worked-out example, completion task, conventional task) •• Practice items •• Guidance four components and the assumed cognitive archi- tecture is explained, focusing on the role of a lim- ited working memory and a virtually unlimited long term memory for schema construction and schema automation –– processes that lay the foundation for meaningful learning. Third, educational media and Supportive information Procedural information •• How-to instructions (exemplified by 14 multimedia principles are related to each of the •• Domain models (illustrated by case studies) demonstrations) •• Prerequisite information (exemplified by •• Systematic approaches to problem solving four components. The chapter ends with a discus- (illustrated by modeling examples) •• Cognitive feedback instances) •• Corrective feedback sion that reviews the contributions of the 4C/ID- model to cognitive theory and instructional design, indicates the limitations of the model, and sketches Figure 1. A schematic overview of the four components directions for future research. in the 4C/ID-model and their main elements. How Do People Learn Complex Skills? The basic message of the 4C/ID-model is that well- Figure 1 provides a schematic overview of the four designed environments for complex learning can components. The learning tasks are represented as always be described in terms of four interrelated circles; a sequence of tasks serves as the backbone blueprint components: of the course or curriculum. Equivalent learning tasks belong to the same task class (in Figure 1, the 1. Learning tasks. Meaningful whole-task experi- dotted rectangles around a set of learning tasks). ences that are based on real-life tasks. Ideally, the Learning tasks within the same task class are learning tasks ask the learners to integrate and coor- equivalent to each other in the sense that they can be dinate many if not all aspects of real-life task per- performed on the basis of the same body of knowl- formance, including problem-solving and reasoning edge –– but they are different on the dimensions that aspects that are different across tasks and routine also vary in the real world such as the context in aspects that are consistent across tasks. which the task is performed, the way the task is pre- 2. Supportive information. Information that is sup- sented, the saliency of defining characteristics, and portive to the learning and performance of problem so forth. Each new task class is more difficult than solving and reasoning aspects of learning tasks. It the previous task classes. Students receive much describes how the task domain is organized and support and guidance for their work on the first how problems in this domain can best be ap- learning task in a class (in Figure 1, this is indicated proached. It builds a bridge between what learners by the filling of the circles), but support smoothly already know and what may be helpful to know in decreases in a process of scaffolding as learners ac- order to fruitfully work on the learning tasks. quire more expertise. One type of——product- oriented——support is embraced in the task descrip-
  • 4C/ID and Multimedia 3 tion: For instance, worked examples provide maxi- to perform particular routine aspects of learning mum support because they present both a problem tasks. This removes the need for memorization be- and an acceptable solution that must only be studied forehand. Procedural information primarily consists or evaluated by the learners; completion tasks pro- of how-to instructions, rules that algorithmically vide medium support because they present a prob- prescribe the correct performance of the routine as- lem and a partial solution that must be completed by pects of learning tasks. They are formulated at the the learners, and conventional tasks provide no sup- level of the lowest-ability learner, so that all stu- port at all because they present a problem that must dents can correctly perform them. How-to instruc- be solved independently by the learners. Another tions may be exemplified by demonstrations that are type of——process-oriented——support has the form of preferably given in the context of the whole, mean- guidance: This is information in the form of process ingful task. Second, procedural information may worksheets or guidelines that lead the learner pertain to prerequisite information, that is, informa- through the problem-solving process. In general, tion that learners must know to correctly perform students work without any support on the final the how-to instructions. This information may be learning tasks in a task class; these conventional exemplified by so-called instances. For example, a tasks without guidance may also be used as test how-to instruction may state that ““You now connect tasks for the assessment of students' performance. the digital device to one of the USB ports””. Related prerequisite information for carrying out this in- The supportive information is linked to task classes, struction may give a definition of what a USB port because this information is relevant to all learning is, and an instance may show a photograph of the tasks within the same class (see the L-shaped, light USB ports of a personal computer. Finally, correc- gray shapes in Figure 1). For each subsequent task tive feedback may be given on the quality of per- class, the supportive information is an addition to or formance of routine aspects. Such feedback indi- an embellishment of the previously presented in- cates that there is an error, explains why there is an formation, allowing learners to do things that they error, and gives hints that may help the learner to could not do before. It is the information that teach- get back on the right track. If learners start to master ers typically call ‘‘the theory’’ and consists out of the routine aspects, the presentation of the proce- three parts. First, it describes domain models, dural information quickly fades away in a process of answering questions like ““what is this?”” (conceptual fading. models), ““how is this organized?”” (structural mod- els), and ““how does this work”” (causal models). Part-task practice is indicated in Figure 1 by the These models are typically illustrated with case small series of circles, representing practice items. studies. Second, supportive information describes Often, the learning tasks provide sufficient practice Systematic Approaches to Problem solving (SAPs) for routine aspects of performance to obtain the de- that specify the successive phases in a problem solv- sired level of automaticity. But for routine aspects ing process and the rules-of-thumb that may be that are very basic or that are critical in terms of helpful to successfully complete each phase. SAPs safety additional part-task practice may be neces- may be exemplified by modeling examples, which sary, such as musicians practicing musical scales, show an expert who is performing a task and simul- children drilling multiplication tables, or air traffic taneously explaining why s/he is doing what s/he is controllers practicing the recognition of dangerous doing. Third, supportive information pertains to the air traffic situations from a radar screen. Part-task cognitive feedback that is given on the quality of the practice for a selected routine aspect never starts learner’’s task performance. Because there is no before this aspect has been introduced in a whole, simple correct or incorrect behavior for the problem meaningful learning task, so that there is an appro- solving and reasoning aspects of performance, cog- priate cognitive context. It is preferably intermixed nitive feedback will often invite students to criti- with learning tasks, so that there is distributed or cally compare their own solutions with expert solu- spaced practice of routines. Drill & practice on a tions or solutions of their peers. vast set of practice items is an effective instructional method to obtain a very high level of automaticity. The procedural information is represented in Figure 1 by dark gray rectangles with upward pointing ar- Complex learning requires that students work on rows, indicating that information units are explicitly whole, meaningful learning tasks. The tasks may coupled to separate learning tasks. This information have different descriptions (e.g., worked examples, is preferably presented exactly when learners need it completion tasks, conventional tasks) and different
  • 4C/ID and Multimedia 4 levels of guidance. To be able to perform the prob- either related to the construction of schemata, in- lem solving and reasoning aspects of those tasks cluding the formation of new schemata and the em- and to learn from them, students consult and study bellishment of existing schemata, or to the automa- domain models and SAPs and receive cognitive tion of schemata. feedback on the quality of their performance. Dur- Memory Systems ing task performance, how-to instructions specify how to perform the routine aspects of the task. Pre- To begin with, all novel information must be proc- requisite information ensures that learners can carry essed in working memory to construct cognitive out those instructions and corrective feedback is schemata in long-term memory. This processing is given if errors are made. Finally, part-task practice heavily limited by the fact that only a few elements may offer a large set of practice items for the addi- can be simultaneously active in working memory: tional training of routine aspects. About seven distinct elements that need to be stored or about two to four elements and their interactions From this description, it should be clear that people if the elements need to be interrelated to each other. learn from words, pictures and other representations Furthermore, it is assumed that working memory (realia, smell, touch etc.) in many different ways. can be subdivided into partially independent chan- On the one hand, each of the four components itself nels or processes (Baddeley, 1992). One channel may require that learners combine representations: consists of a phonological loop to deal with verbal Learning tasks may ask learners to simultaneously material based on an auditory working memory; read displays, process spoken text, and operate con- another channel consists of a visual-spatial scratch trols; supportive information may include a video pad to deal with diagrammatic or pictorial informa- recording of an expert modeling a problem-solving tion based on a visual working memory. Using both process and explaining why he is doing what he is the visual and auditory channels rather than either doing; procedural information may include a quick one channel alone increases the effective working reference guide with written instructions for operat- memory capacity (Penney, 1989). Long-term mem- ing a complex device as well as pictures of this de- ory alters the characteristics of working memory by vice, and part-task practice may include operating a reducing or even eliminating its limitations. Human software program with texts and icons. Further- expertise is the result of the availability of rich and more, procedural information is typically presented automated cognitive schemata, not from an ability to learners while they are working on learning tasks to engage in reasoning with many elements that yet or performing part-task practice, yielding two need to be organized in long-term memory. Human sources of information (““how-to”” information and a working memory simply does not support this type task for which this information is relevant) that of many-elements processing. must be mentally integrated by the learner in order to successfully complete the task. For each situa- Expertise develops through two complementary tion, another set of multimedia principles applies processes, namely, schema construction and schema because there are different learning processes in- automation. Schema construction refers to the—— volved. This will be further explained in the next often conscious and mindful——formation of increas- section. ing numbers of ever more complex schemata, by combining elements consisting of lower-level Cognitive Architecture and schemata into higher-level schemata. These sche- Meaningful Learning mata organize and store knowledge, but also heavily The 4C/ID-model assumes that all human knowl- reduce working memory load because even highly edge is stored in cognitive schemata. It further sup- complex schemata can be dealt with as one element poses a cognitive architecture that is broadly ac- in working memory. Thus, a large number of ele- cepted in the psychological literature and for which ments for one person may be a single element for ample empirical support is available. This architec- another, more experienced person, who already has ture distinguishes a working memory with a very a cognitive schema available that incorporates the limited capacity when dealing with novel informa- elements. As a result, novel information may be tion as well as an effectively unlimited long term easy to understand by someone with relevant ex- memory, holding cognitive schemata that vary in perience, and very hard to understand by someone their degree of richness (i.e., number of elements without this experience. and interconnections between those elements) and their level of automation. Learning processes are
  • 4C/ID and Multimedia 5 Schema automation occurs if a task performer re- The elaboration of new supportive information re- peatedly and successfully applies a particular cogni- fers to those cognitive activities that integrate new tive schema. As is the case for schema construction, information with cognitive schemata already avail- automation can free working memory capacity for able in memory (see Willoughby, Wood, Des- other activities because an automated schema di- marais, Sims, & Kalra, 1997). When learners elabo- rectly steers the routine aspects of behavior, without rate new supportive information, they first search the need to be processed in working memory. As a their memory for general cognitive schemata that direct consequence, instructional designs for com- may provide a cognitive structure for understanding plex learning should not only encourage the con- the information in general terms, and for concrete struction of problem-solving and reasoning sche- schemata or cases that may provide a useful anal- mata, but also the automation of schemata for those ogy. These schemata are connected to the new in- aspects of a complex skill that are consistent across formation, and elements from the retrieved sche- problems or tasks. In a learning environment that is mata that are not part of the new information are developed according to the 4C/ID-model, learners’’ now related to it. Thus, learners use what they al- work on learning tasks and study of supportive in- ready know about a topic to help them structure and formation helps them to construct cognitive sche- understand the new information. mata; their consultation of procedural information, With regard to schema automation, a distinction is repeated performance of routine aspects of learning made between knowledge compilation, which refers tasks, and drill on part-task practice helps them to to the preliminary automation of schemata on the automate schemata. Thus, meaningful learning is basis of procedural information (component 3), and the result of both schema construction and schema strengthening, which refers to the development of automation. very high levels of automaticity through part-task Cognitive Processes that Lead to Meaningful practice (component 4). Knowledge compilation Learning refers to the process by which procedural informa- tion is embedded in automated schemata that di- The 4C/ID-model makes a further division in learn- rectly steer behavior, that is, evoke particular ac- ing processes that are directly coupled to the four tions under particular conditions. Newly acquired components of the model. With regard to schema schemata or worked examples may be used to yield construction, a distinction is made between induc- an initial solution, and compilation is the process tion through experiential learning, which refers to that creates highly specific schemata from this solu- the construction of schemata by——often mindfully—— tion (Anderson, 1993; Anderson & Lebiere, 1998). abstracting away from concrete learning tasks After the knowledge is compiled, the solution is (component 1), and elaboration, which refers to the generated by directly coupling the actions to the construction of schemata by relating already exist- conditions in the specific schema. This greatly ing knowledge in long term memory to new suppor- speeds up performance. tive information (component 2). Induction is at the heart of complex learning and refers both to the Finally, strengthening makes it possible for learners generalization and discrimination of cognitive to perform a routine aspect of a complex skill, after schemata (see Holland, Holyoak, Nisbett, & Tha- it has been separately trained in a process of part- gard, 1989). When learners generalize or abstract task practice, at a very high level of automaticity. It away from well-designed learning tasks, they con- is usually assumed that an automated schema has a struct schemata that leave out the details so that they strength associated with it, determining the chance apply to a wider range of events or to events that are that it applies under the specified conditions as well less tangible. Discrimination is just the opposite of as how rapidly it then applies. While knowledge generalization. A more specific schema may be con- compilation leads to highly specific schemata, structed if a set of failed solutions is available for a which are assumed to underlie accurate performance class of related tasks. Then, particular conditions of the skill, they still have a weak strength. may be added to the schema and restrict its range of Strengthening is a straightforward learning mecha- use. Induction is typically a strategic and controlled nism. It is simply assumed that automated schemata cognitive process, which requires conscious proc- accumulate strength each time they are successfully essing from the learners (also called ‘‘mindful ab- applied. The improvement that results from straction’’; Perkins & Salomon, 1989). strengthening requires long periods of ‘‘overtraining’’ (Palmeri, 1999).
  • 4C/ID and Multimedia 6 Table 1 Examples of Prominent Multimedia Principles for Each of the Four Components of the 4C/ID-Model Multimedia Principle Example Learning Tasks and Learning in Simulated Task Environments 1. Sequencing principle For physics students who learn to troubleshoot electrical circuits, start with circuits with only very few elements (e.g., a lamp, battery and switch) and continue with circuits with increasingly more elements. 2. Fidelity principle For medical students who learn to diagnose patients, start with textual case de- scriptions, continue with computer-simulated patients or patients played by peers, go on with simulated patients played by actors, and end with real patients in an internship in hospital. 3. Variability principle For law students who learn to prepare pleas to be held in court, make sure that learning tasks ask them to prepare pleas for different fields of law (civil law, criminal law), different clients (guilty, not guilty), different courts (police court, law court, supreme court), and so on. 4. Individualization principle For computer science students who learn to write computer programs, continu- ously assess with which programming constructs they have difficulties and select new learning tasks that offer optimal opportunities to remedy their misconceptions. 5. Training-wheels principle For accountancy students who learn to make budgets with a spreadsheet program, first block all toolbars and menu options that are not strictly necessary to perform the task, but only add these when they become necessary because students pro- gress to making more complex budgeting tasks. 6. Completion-strategy principle For students in architecture who learn to design constructional blueprints, first let them evaluate the qualities of blueprints of existing buildings, then let them re- design blueprints for the renovation of buildings, and finally let them design blue- prints for new buildings. Supportive Information and Learning from Hypermedia 7. Redundancy principle For students in econometrics who learn to explain periods of economic growth, first present a qualitative model (allows them to predict if there will be any growth) and only then present a more encompassing quantitative model (laws that may help them to compute the amount of growth) –– but without repeating the qualitative information as such. 8. Self-explanation principle For medical students who learn to diagnose malfunctions in the human cardiovas- cular system, present an animation of how the hart works and provide prompts that provoke them to explain the underyling mechamisms to themselves or their peers. 9. Self-pacing principle For students in psychotherapy who learn to conduct intake conversations with de- pressed clients, show video-examples of real-life intake conversations and give them the opportunity to stop/replay the recording after each segment in order to reflect on this particular segment. Procedural Information and Electronic Performance Support Systems 10. Temporal split-attention principle For students in web design who learn to develop web pages in a new software en- vironment, tell them how to use the different functions of the software environ- ment precisely when they need them to implement particular aspect of their design –– instead of discussing all available functions beforehand. 11. Spatial split-attention principle For social science students who learn to conduct statistical analyses on their data files with SPSS, present procedural information describing how to conduct a par- ticular analysis also on the computer screen and not in a separate manual. 12. Signaling principle For students in car engineering who learn to disassemble an engine block, animate the disassembling process in a step-by-step fashion and always put a spotlight on those parts that are loosened and removed. 13. Modality principle For students in instructional design who learn to develop training blueprints by studying a sequence of more and more detailed blueprints, explain the blueprints with narration or spoken text instead of visual (on-screen) text. Part-task Practice and Drill & Practice CBT Programs 14. Component-fluency principle For students in air traffic control who learn to direct incoming aircraft, provide additional and extensive part-task practice on immediately recognizing potentially dangerous air traffic situations from the radar screen.
  • 4C/ID and Multimedia 7 Meaningful Multimedia Learning According to results are consistent with the findings of Pollock, the 4C/ID-Model Chandler and Sweller (2002), who found that for high-element interactivity materials first presenting As discussed in the previous section, the four com- isolated elements and only then the interrelated ponents (learning tasks, supportive information, elements is better than presenting all elements si- procedural information, part-task practice) aim at multaneously, and of Clarke, Ayres and Sweller (in the facilitation of different learning processes, with press), who found that for learning mathematics clear implications for the selection of suitable edu- with spreadsheet applications, especially for low- cational media and relevant multimedia principles. expertise learners it is important to present and prac- These media and principles are discussed in the next tice enabling, technological skills (i.e., using sections. spreadsheets) before practicing the ultimate skills Learning Tasks and Learning in Simulated Task the training is aiming at (i.e., mathematical skills). Environments Kester, Kirschner and van Merriënboer (2003; in Learning tasks primarily aim at schema construction press a; in press b) studied the sequencing principle through inductive learning. The educational medium in the context of the 4C/ID-model. In the domain of must allow learners to work on those tasks and typi- electronics troubleshooting, they found that present- cally takes the form of a real or simulated task envi- ing high-element interactivity supportive informa- ronment. One may think of a project room, a simu- tion either before or after low-element interactivity lated office, a physical simulator, or an internship in procedural information, led to better transfer test a real company. In multimedia learning, the heart of performance. The 4C/ID model primarily uses task the learning environment will typically consist of a classes to accommodate the sequencing principle. computer-simulated task environment. For many Task classes and their related supportive informa- complex skills, such as holding a plea in court, con- tion range from simple to complex, while the learn- ducting psychological experiments, or troubleshoot- ing tasks within the same task class are equally dif- ing a chemical factory, current multimedia technol- ficult. The basic guideline of the 4C/ID-model is to ogy does not yet offer the possibilities that are start with a task class where the learning tasks can needed for high-fidelity simulation (i.e., missing be solved on the basis of a simple domain model or input-output facilities, lack of simulation models SAP, and to continue with task classes where the that can run in the background, etc.). The opportuni- supportive information pertains to increasingly ties will be better in the near future thanks to Virtual more complex and elaborated domain models or Reality (VR), broadband technology, and new input SAPs (i.e., mental model progression, van Merriën- and output devices such as VR-helmets and data boer, Kirschner, & Kester, 2003). gloves. Although the necessary multimedia technol- Fidelity principle. Learning tasks are performed in ogy to implement optimal instructional methods is some kind of task environment. While the learning not always available, many multimedia applications tasks are based on real-life tasks, they can yet be already offer the opportunity to perform learning performed in an environment that is very close to tasks that are somehow based on real-life tasks. Ta- the real task environment (i.e., high fidelity) or in an ble 1 summarizes the main multimedia principles environment that merely offers to opportunity to (1-6) that should be taken into account in simulated perform the tasks, with no attempts to mimic the task environments and provides for each principle real task environment (i.e., low fidelity). The fidel- an example of how it could be applied. ity principle indicates that for novice learners, a Sequencing principle. The sequencing principle in- high fidelity task environment often contains irrele- dicates that it is often better to sequence learning vant details that may deteriorate learning. This prin- tasks or complex pieces of information from simple ciple is in agreement with the finding that there is to complex, than to present them in their full com- better transfer when interesting but irrelevant mate- plexity at once. Mayer and Moreno (2003) refer to rials, such as background music and non-essential this as a ‘‘pretraining’’ effect, when they review stud- video clips, are excluded from a training program. ies showing better transfer test performance when Students perform better on transfer tests after re- students must first study which components make ceiving a concise narrated animation instead of an up a system (i.e., a conceptual model) and only then embellished narrated animation (Mayer, Heiser, & how the system works (i.e., a causal or functional Lonn, 2001; Moreno & Mayer, 2000). For a web- model, Mayer, Matthias, & Wetzell, 2002). These based course, Gulikers, Bastiaens and Martens (in press) found that novices perform better in a low-
  • 4C/ID and Multimedia 8 fidelity, text-based environment than in a high- timal transfer does not always require a high vari- fidelity environment where multimedia features are ability of learning tasks within each task class, as used to mimic the real task environment. Harp and long as the variability is sufficiently high for the Mayer (1998) also report that ‘‘seductive details’’ learning tasks in the whole set of task classes (i.e., that are not directly relevant for learning deteriorate in the whole training program). performance. According to the 4C/ID-model, train- Individualization principle. Recent studies show ing should best start with task classes in which the that adaptive training systems, which dynamically learning tasks are performed in a low-fidelity envi- select learning tasks based on the characteristics of ronment, which only represents those aspects of the the individual learner, yield higher transfer than real environment that are necessary to perform the non-adaptive training systems, which present a task. There is a high psychological fidelity because fixed sequence of tasks that is identical for all learn- the learning task is representative for a real-life task, ers (Salden, Paas, & van Merriënboer, in press). In but there is no or little physical correspondence with these adaptive systems the dynamic selection of the the real environment. Only in later task classes and next learning task is typically based on performance with more advanced learners, it becomes necessary (i.e., accuracy and/or speed), but it can also be to perform the learning tasks in a high fidelity or based on the amount of mental effort invested in real environment (see also Maran & Glavin, 2003). performing the previous task(s), on a combination Variability principle. The variability principle indi- of performance and mental effort (for examples, see cates that learning tasks must be sufficiently differ- Camp, Paas, Rikers, & van Merriënboer, 2001; Ka- ent from each other to allow for the construction of lyuga & Sweller, in press; Salden, Paas, Broers, & general, abstract schemata that make transfer of van Merriënboer, 2004), or on a qualitative student learning possible. Ideally, learning tasks should dif- model (e.g., van Merriënboer & Luursema, 1996). fer on all dimensions that also vary in the real The individualization principle typically takes dif- world, such as the conditions under which the task ferences between learners into account by selecting is performed, the way of presenting the task, or the learning tasks in such a way that the task difficulty saliency of defining characteristics. Several studies and/or the available level of support is adjusted to showed that a high variability across learning tasks the learner. This fits in very well with the 4C/ID- yields superior transfer test performance (e.g., model. For each learning task, performance needs to Quilici & Mayer, 1996; Paas & van Merriënboer, be assessed in order to give cognitive feedback to 1994). Van Merriënboer, Schuurman, de Croock the learners (Straetmans, Sluijsmans, Bolhuis, & and Paas (2002) and de Croock, van Merriënboer van Merriënboer, 2003). This assessment informa- and Paas (1998) studied contextual interference, tion can also be used to select a new task: If per- which is a special type of variability referring to the formance is low, an equivalent task with a higher way in which differences between tasks are divided level of support will be selected from the same task across acquisition tasks. Suppose that students learn class or, in the worst case, an easier task will be se- to diagnose three types of errors: A, B and C. Low lected from a previous task class; if performance is contextual interference may then be produced by a high, an equivalent task with a lower level of sup- blocked practice schedule, in which the skills neces- port will be selected from the same task class, or, if sary for diagnosing one type of error are practised all performance criteria have been reached, the before continuing to another type of error (e.g., learner is allowed to move on to the next task class AAA, BBB, CCC). High contextual interference from which a more difficult task with a high level of may be produced by a random practice schedule, in support is selected. which different errors are sequenced in a random Training-wheels principle. Even performing rela- order (e.g., CABBCABAC). High contextual inter- tively easy learning tasks in a low-fidelity environ- ference prohibits a quick and smooth mastery of the ment is difficult for novice learners, because it are skills being trained, but yields higher transfer test still ‘‘whole’’ tasks that require the coordination of performance because learners are promoted to con- many different constituent skills. One way to help struct general cognitive schemata. The 4C/ID-model learners is to provide either process-oriented worked takes the variability principle into account and sug- examples that show an expert who is performing the gests including in each task class, learning tasks that task (van Gog, Paas, & van Merriënboer, 2004) or exhibit high variability and high contextual interfer- to give process worksheets that ask leading ques- ence. Recent research of Gerjets, Scheiter and Ca- tions that guide the learners step-by-step through the trambone (2004), however, seems to imply that op-
  • 4C/ID and Multimedia 9 problem solving or reasoning process (e.g., Nadol- lyuga, Ayres, & Chandler, 2003). Thus, novices ski, Kirschner, & van Merriënboer, 2001). How- benefit more from studying worked examples but ever, a potential drawback of these methods is that experienced learners profit more from solving the learners must divide their attention between the task equivalent conventional problems. The completion and the support, which may negatively affect learn- strategy accommodates the findings on the expertise ing (van Merriënboer, Kirschner, & Kester, 2003). reversal effect and proved to be very effective in An additional way to support learners is to con- facilitating transfer of learning (Renkl & Atkinson, strain their performance, that is, to make sure that 2003; Renkl, Atkinson, & Grosse, 2004). In the they cannot perform actions that are not necessary 4C/ID-model, the completion-strategy principle is to reach the performance goals. A metaphor for included as one way to decrease support for learning these performance constraints is provided by the tasks within one task class. In the beginning of a training wheels on children’’s’’ bikes, which prevent task class, high support may provided by the use of them from falling over (Carroll, 2000). Dufresne, worked examples; then, increasingly lesser support Gerace, Thibodeau-Hardiman and Mestre (1992) may be provided by completion tasks for which the studied the training wheels principle for a problem- learners have to generate larger and larger parts of solving task in physics. Students’’ performance was the solution; and finally, conventional tasks provide constrained in such a way that they had to mimic an no support at all. expert’’s approach to problem solving, which had Supportive Information and Learning from Hyper- positive effects on their transfer test performance. In media another study, Leutner (2000) also found positive effects of training wheels on test performance, but Supportive information mainly aims at schema con- his study also indicated that both too many con- struction through elaboration, that is, connecting straints and too little constraints might produce new information to knowledge that is already avail- suboptimal effects on learning. In the 4C/ID-model, able in long-term memory. Traditional media for the training wheels principle is included as one way supportive information are textbooks, teachers and to decrease guidance for learning tasks within one realia. Textbooks contain a description of the ‘‘the- task class. While the learning tasks in the same task ory’’, that is, the domain models that characterize a class are equally difficult, they start with high guid- field of study and, alas, often in a lesser degree the ance and guidance decreases until none as expertise SAPs that may help to solve problems and perform increases. non-trivial tasks in the domain. Teachers typically discuss the highlights in the theory (lectures), dem- Completion-strategy principle. In contrast to the onstrate or provide expert models of SAPs, and pro- training-wheels principle, which primarily concerns vide cognitive feedback on learners' performance. guidance or process support, the completion- Realia or descriptions of real entities (‘‘case studies’’) strategy principle concerns support that is implied are used to illustrate the theory. Hypermedia and by the task description. The completion strategy hypertext systems may take over——part of——those (van Merriënboer, 1990; van Merriënboer & de functions. They may present theoretical models and Croock, 1992) starts with worked examples that concrete cases that illustrate those models in a must be studied by the learners, continues with highly interactive way, and they may explain prob- completion tasks that present partial solutions that lem-solving approaches and illustrate those ap- must be completed by the learners, and ends with proaches by showing, for example, expert models conventional tasks for which the learners must in- on video. As indicated before, it is critical that stu- dependently generate whole solutions. Many studies dents elaborate and deeply process this information. indicate that novice learners learn more from study- On the one hand, hypermedia may well help to ing worked examples (for an overview, see Atkin- reach this goal, because their structure reflects the son, Derry, Renkl, & Wortham, 2000) or from per- way that human knowledge is organized in elements forming completion tasks that require them to com- (called ““nodes””) and non-arbitrary relationships be- plete partial solutions (for an overview, see Sweller, tween those elements (called ““links””). But on the van Merriënboer, & Paas, 1998) than from solving other hand, it is of utmost importance to provoke the equivalent conventional problems. In addition, deep processing through asking questions, stimulat- Kalyuga, Chandler, Tuovinen and Sweller (2001) ing reflection, and promoting discussion. Principles and Tuovinen and Sweller (1999) found that this 7-9 in Table 1 summarize the main multimedia effect reverses for more experienced learners, which principles that should be taken into account in hy- is an example of the ‘‘expertise reversal effect’’ (Ka-
  • 4C/ID and Multimedia 10 permedia systems and provide illustrations of their and direct elicitation of self-explanation by prompt- application. ing the learners had some beneficial effects on transfer. Stronger evidence for the facilitation of Redundancy principle. This principle indicates that transfer by self-explanation was found in a study the presentation of redundant information typically with the completion strategy (Atkinson, Renkl, & has a negative impact on learning (for an overview Merrill, 2003). In this study, prompts were designed of studies, see Sweller, van Merriënboer, & Paas, to encourage learners to identify the underlying 1998). It is a counter-intuitive principle, because principles illustrated in worked-out solution steps, most people think that the presentation of the same and these prompts had beneficial effects on transfer information, in a somewhat different way, will have test performance. Similar results were found in a a neutral or even positive effect on learning. How- study by Mayer, Dow, and Mayer (2003), who ever, learners have to find out that the information found positive effects on learning by using preques- from different sources is actually redundant, which tions to guide self-explanation; Aleven and Koed- is a cognitively demanding process that does not inger (2002), who found better transfer by using a contribute to meaningful learning. In recent studies, cognitive tutor to guide self-explanation in a class- Mayer, Heiser, and Lonn (2001), Moreno and room setting, and Moreno and Valdez (in press), Mayer (2002), and Leahy, Chandler and Sweller who found positive effects on transfer of postponing (2003) presented visual information to learners feedback so that learners had to evaluate their own (e.g., an animation) and a concurrent narration that actions. For the presentation of supportive informa- explained this visual information. Negative effects tion, the 4C/ID-model stresses the importance of on learning were found when the concurrent narra- instructional methods that promote elaboration and tion was duplicated by a——redundant——on-screen schema construction. Prompting for self-explanation text. Kalyuga, Chandler and Sweller (2000) related of domain models and SAPs, as well as illustrations the redundancy principle to the expertise reversal of them by case studies and modelling examples, is effect. They found that information that is helpful one particularly important instructional method to for novice learners is detrimental to more experi- reach this. enced learners, because it is redundant with what they already know. The 4C/ID-model relates the Self-pacing principle. The self-pacing principle in- finding that the presentation of redundant informa- dicates that giving learners control over the pace of tion may seriously hamper learning primarily to the the instruction may facilitate elaboration and deep distribution of supportive information over task processing of information. Elaboration is an effort- classes. The supportive information for each new ful, time-consuming process and especially ‘‘stream- task class is always an addition to, or embellishment ing’’ or transient information (video, dynamic ani- of, the information that has been presented for pre- mation etc.) may leave learners insufficient time for vious task classes. While the conceptual link be- this type of processing. Mayer and Moreno (2003) tween the new information and the previous infor- report higher transfer test performance if informa- mation should be pointed out to the learners, it is tion is presented in learner-controlled segments important not to repeat the information from previ- rather than as one continuous unit, an example of ous task classes in order to prevent negative effects the self-pacing principle they called the ‘‘segmenta- of redundancy. tion effect.’’ In an experiment of Mayer and Chan- dler (2001), learners who were allowed to exercise Self-explanation principle. Salomon (1998) dis- control over the pace of a narrated animation per- cusses the so-called ‘‘butterfly defect’’ in hypermedia formed better on transfer tasks compared with and web-based learning: ““... touch, but don’’t touch, learners who received the same narrated animation and just move on to make something out of it””. at normal speed without any learner control. Tab- Multimedia may act as an affordance to relax (cf., bers (2002) found the same result for visual text watching television) –– while for meaningful learn- accompanying diagrams: Self-paced presentation of ing to occur they should be associated with deep the instructional texts led to higher transfer test per- processing and invite learners to ‘‘self-explain’’ in- formance than system-paced instructional texts. In formation. Renkl (1999) introduced the self- the 4C/ID-model, ‘‘streaming’’ information will often explanation principle in the context of learning from refer to case studies (e.g., an animation illustrating a worked examples. The degree to which learners ex- particular dynamic domain model) and modeling plain the solution steps in worked examples to their examples (e.g., a video of an expert modeling a par- selves is a good predictor for learning outcomes, ticular problem solving process or SAP). For this
  • 4C/ID and Multimedia 11 type of multimedia information presentation, it is Sims, 1994; Mayer, Moreno, Boire, & Vagge, important to give learners control over the pace in 1999). In the context of the 4C/ID model, the tem- which the information is presented to them. The poral split-attention principle is particularly impor- self-pacing principle allows them to pause and bet- tant for the presentation of procedural information, ter reflect on the new information in order to couple which refers to how-to instructions for performing it to already existing cognitive structures. the routine aspects of the learning task the learner is working on. If this information is presented just in Procedural Information and Electronic Perform- time, precisely when the learner needs its, all ele- ance Support Systems ments necessary for knowledge compilation to oc- Procedural information primarily aims at schema cur are available in working memory at the time the automation through knowledge compilation. The skill is practiced. Kester, Kirschner and van Mer- traditional media for procedural information are the riënboer (2003; see also Kester, Kirschner, & van teacher and all kinds of job and learning aids. The Merriënboer, in press a) compared the just in time teacher's role is to walk through the classroom, presentation of procedural information with a split- laboratory or workplace and to watch over his attention format (i.e., first present the information learners' shoulder (the teacher's name is Aloys –– the and then practice the task) and found beneficial ef- Assistant Looking Over Your Shoulder), and to give fects on transfer test performance of the simultane- directions for performing the routine aspects of ous presentation. learning tasks (e.g., "No –– you should hold that in- Spatial split-attention principle. The spatial split- strument like this...", "Watch, you should now select attention principle, which is also called the ‘‘spatial this option……"). Job aids may be the posters with contiguity effect’’ (Mayer & Moreno, 2003), refers frequently used software commands that are stuck to the finding that higher transfer test performance on the wall of a computer class, quick reference is reached when mutually referring information guides next to a piece of machinery, or booklets sources are physically integrated with each other in with safety instructions for interns in industry. In space. Extensive research has been carried out multimedia learning environments, these functions showing the beneficial effects of integrating pictures are mainly taken over by Electronic Performance with explanatory text: the text that refers to the pic- Support Systems (EPSSs) such as on-line job aids ture is typically split up in smaller segments so that and help systems, wizards, and (intelligent) peda- the text segment that refers to a particular part of the gogical agents (Bastiaens, Nijhof, Streumer, & figure can be linked to this particular part or be in- Abma, 1997). Such systems provide procedural in- cluded in the picture (e.g., Chandler & Sweller, formation on request of the learner (e.g., on-demand 1991; Chandler & Sweller, 1992; Kalyuga, Chan- help) or on their own initiative (e.g., pedagogical dler, & Sweller, 1999). In the context of the 4C/ID- agent), preferably precisely when students need it model, Kester, Kirschner and van Merriënboer (in for their work on the learning tasks. Table 1 summa- press b) studied the integration of procedural infor- rizes the main multimedia principles (10-13) that mation in the task environment, in such a way that it should be taken into account in EPSSs and provides was physically integrated with the learning tasks some examples of how they can be applied. students were working on. Specifically, they inte- Temporal split-attention principle. The temporal grated the procedural information in electronic cir- split-attention principle originally indicates that cuits students had to troubleshoot. This also resulted learning from mutually referring information in higher transfer test performance, a finding that is sources is facilitated if these sources are not sepa- in agreement with Cerpa, Chandler, and Sweller rated from each other in time, that is, if they are pre- (1996), who demonstrated that students learning a sented simultaneously. Mayer and Moreno (2003) computer application learned better if all of the ma- refer to the principle as the ‘‘temporal contiguity terial was placed on the computer screen, as op- effect’’ and review several studies that report higher posed to having a manual and computer on which to transfer test performance for the simultaneous pres- work. Combining both information sources prevents entation of mutually referring pictures and text than spatial split-attention between the task environment for their consecutive presentation. The same is true (i.e., the computer screen) and the procedural in- for the concurrent presentation of animation and formation in the manual (see also Sweller & Chan- corresponding narration, which yields better transfer dler, 1994; Chandler & Sweller, 1996). In general, than their successive presentation (Mayer & Ander- procedural information should thus be presented in son, 1991; Mayer & Anderson, 1992; Mayer &
  • 4C/ID and Multimedia 12 such a way that it is optimally integrated with the text. With regard to the 4C/ID-model, procedural learning tasks and the task environment. information that just-in-time specifies how to per- form routine aspects of learning tasks can thus bet- Signaling principle. The signaling or attention- ter be spoken by a teacher or other pedagogical focusing principle indicates that learning may be agent than be visually presented. improved if the learner’’s attention is focused on the critical aspects of the learning task or the presented Part-task Practice and Drill & Practice Computer information. It reduces the need for visual search Based Training and so frees up cognitive resources that may then be With regard to the fourth component, part-task prac- devoted to schema construction and automation, tice aims at schema automation through strengthen- with positive effects on transfer test performance. ing. Especially for this component, the computer Jeung, Chandler and Sweller (1997) and Tabbers, has proved its worth in the last decades. Drill & Martens and van Merriënboer (in press) found bene- practice Computer Based Training (CBT) is without ficial effects on learning from the synchronous use doubt the most successful type of educational soft- of explanatory spoken text and cues in complex pic- ware. The computer is sometimes abused for its use tures, that is, the moment a particular part of the of drill, but most critiques seem to miss the point. complex picture was explained it was highlighted or They contrast drill & practice CBT with educational color-coded. Kalyuga, Chandler, and Sweller (1999) software that focuses on rich, authentic learning found similar positive effects of signaling with vis- tasks. But according to the 4C/ID-model drill & ual-only instructions. Furthermore, Mautone and practice will never replace meaningful whole-task Mayer (2001) found positive effects of signaling on practice; it merely complements the learners’’ work transfer test performance when it was used in on rich learning tasks and is applied only when the printed text, spoken text, as well as spoken text with learning tasks themselves cannot provide enough corresponding animation. In the 4C/ID-model, sig- practice to reach the desired level of automaticity naling is particularly important if procedural infor- for selected routine aspects. If such part-task prac- mation is related to routine aspects of task perform- tice is necessary, the computer is probably the most ance. For instance, if a teacher instructs a learner suitable medium because it can make drill effective how to operate a piece of machinery it is useful to and appealing through giving procedural support; point a finger at those parts that must be controlled, compressing simulated time so that more exercises and if a video-based example is used to demonstrate can be done than in real time; giving knowledge of particular routine aspects of performance it is help- results (KR) and immediate feedback on errors, and ful to focus the learners’’ attention through signaling using multiple representations, gaming elements, (e.g., by spotlighting hand movements) on precisely sound effects and so further. Table 1 gives an ex- those aspects. ample of the application of the component fluency Modality principle. The modality principle indicates principle (14), that is, the most important multime- that dual-mode presentation techniques that use dia principle in drill & practice CBT programs. auditory text or narration to explain visual diagrams, Component-fluency principle. The component- animations or demonstrations, result in better learn- fluency principle indicates that drill & practice on ing than equivalent, single-mode presentations that one or more routine aspects of a task may have posi- only use visual information. Moreno and Mayer tive effects on learning and performing the whole (1999) and Tindall-Ford, Chandler and Sweller task. Strengthening may produce a very high level (1997) present results that provide empirical support of automaticity for routine aspects, which frees up for the modality principle. The positive effect of cognitive capacity because these automated aspects dual-mode presentation is typically attributed to an no longer require resources for conscious process- expansion of effective working memory capacity, ing. As a result, all available cognitive capacity can because for dual-mode presentations both the audi- be allocated to the non-routine, problem-solving and tory and visual subsystems of working memory can reasoning aspects of whole-task performance. Carl- be used rather than either one subsystem alone. This son, Sullivan and Schneider (1989) and Carlson, hypothesis was confirmed by Tabbers, Martens and Khoo and Elliot (1990) found evidence for the com- van Merriënboer (2001), who found that students ponent fluency principle, but only when part-task who studied complex diagrams explained by spoken practice took place after the learners were intro- text reported lower perceived mental effort than duced to the whole task, that is, when it was pro- students who studied the same diagrams with visual vided in an appropriate ‘‘cognitive context’’. For this
  • 4C/ID and Multimedia 13 reason, the 4C/ID-model is reserved with the appli- ing on the basis of real-life tasks can only be de- cation of part-task practice and, if it is used at all, scribed in terms of qualitatively different learning suggests starting part-task practice for particular processes that often simultaneously occur. routine aspects only after the learners have been With regard to instructional design and, in particu- introduced to these aspects in the context of whole lar, theories at the level of message design, the con- learning tasks. Only then, the learners are able to tributions of the 4C/ID-model are more straightfor- identify the activities that are required to integrate ward. Traditional design models analyze a learning the routines in the whole task. domain in terms of distinct learning objectives. A Discussion common premise is that different objectives can best be reached by the application of particular in- The 4C/ID-model provides guidelines for the design structional principles (the ‘‘conditions of learning’’, of environments in which complex learning takes Gagné, 1985). The optimal principles are chosen to place, that is, learning directed towards the integra- design the ‘‘message’’ for each objective; the objec- tion of knowledge, skills, and attitudes, the ability to tives are taught one-by-one; and the general educa- coordinate qualitatively different constituent skills, tional goal is believed to be met after all messages and the transfer of what is learned to real-life situa- have been conveyed. In the early 1990’’s, authors in tions. This model was elaborated for the design of the field of instructional design started to question multimedia learning environments. Such applica- the value of this approach because it yields instruc- tions are typically build around a simulated task tion that is fragmented and piecemeal (e.g., Gagné environment that offers the opportunity to perform & Merrill, 1990). For real-life tasks, there are many learning tasks (component 1). They may further interactions between the different aspects of task contain hypermedia that allow learners to actively performance and their related objectives. Integrated study supportive information (component 2), EPSSs objectives should not only aim at the ability to ef- with procedural information specifying how to per- fectively perform each aspect of a complex task in form routine aspects of complex tasks (component isolation, but also pay attention to the ability to co- 3) and, finally, drill & practice CBT programs that ordinate these different aspects in real-life task per- provide opportunities for overlearning selected rou- formance. An important contribution of the 4C/ID- tine aspects that need to be performed at a very high model is that is provides a whole-task methodology level of automaticity after the training (component to deal with such integrated objectives. At the same 4). Each of these four components relates to another time, the four components provide an organizing set of prominent multimedia principles. framework for instructional methods, including In the Introduction to this chapter, theories about multimedia principles (cf. Table 1). At least, the learning with multimedia were positioned at three 4C/ID-model points out to designers under which different levels: The psychological level, the mes- conditions, and for which components of a learning sage design level, and the course design level. As a environment, particular multimedia principles theory at the level of course and curriculum design, should be considered. the 4C/ID-model yields no direct contributions to The framework discussed in this chapter has several cognitive theory in the sense that it provides a new limitations. First, the 4C/ID-model may well be perspective on human cognitive architecture or un- used to design multimedia learning environments, covers new cognitive processes. We believe, how- but if this is actually desirable in a particular situa- ever, that it indirectly contributes to cognitive the- tion is yet another question. Many factors determine ory by synthesizing many different findings and the selection of media in instructional design, in- showing the importance of the psychological study cluding constraints (e.g., manpower, equipment, of real-life complex task performance. Learning time, money), task requirements (e.g., media attrib- processes such as inductive learning, elaboration, utes necessary for performing learning tasks and knowledge compilation and strengthening have each required response options for learners), and target been thoroughly studied in many experimental stud- group characteristics (size of the group, computer ies, often using relatively straightforward laboratory literacy, handicaps). The 4C/ID-model does not tasks. No doubt, this is vital research but in addition provide guidelines for this process of media selec- it is becoming more and more important to study tion. Second, when positioned in the general different types of learning processes in connection ADDIE model (Analysis, Design, Development, with each other. The 4C/ID-model tries to do so, Implementation and Evaluation), the 4C/ID-model and our results clearly indicate that complex learn-
  • 4C/ID and Multimedia 14 clearly focuses on analysis and design activities, and knowledge that advanced networked multimedia does neither provide specific guidelines for the de- systems enable people to learn in ways that were velopment, production and construction of multi- inconceivable in the past. In order to make scientific media materials nor for their implementation and progress in the field of multimedia learning, we evaluation. And third, while we focused our discus- should both study how good old-fashioned learning sion on the most prominent multimedia principles principles inform the design of artifacts and how for each of the four blueprint components, this does implicit design principles in advanced technological not imply that particular principles cannot be impor- artifacts affect the way in which people learn. tant for other blueprint components. For instance, the fidelity principle is particularly References important to sequence learning tasks from working in low-fidelity to working in high-fidelity environ- Aleven, V. A. W. M. M., & Koedinger, K. R. (2002). An ments, but it may also be relevant to all other three effective metacognitive strategy: Learning by doing components that, after all, also determine aspects of and explaining with a computer-based cognitive tutor. Cognitive Science, 26, 147-179. the learning environment. Likewise, the training- wheels principle and the individualization principle Anderson, J. R. (1993). Rules of the mind. Hillsdale, NJ: are not exclusively useful for the design of learning Lawrence Erlbaum. tasks, but may also be applied to gradually relax Anderson, J. R., & Lebiere, C. (1998). The atomic com- performance constraints and to control learner’’s ponents of thought. Mahwah, NJ: Lawrence Erlbaum. progress during part-task practice. The self-pacing Atkinson, R. K., Derry, S. J., Renkl, A., & Wortham, D. principle is particularly important to the design of (2000). Learning from examples: Instructional princi- supportive information, but may also be useful for ples from the worked examples research. Review of the presentation of procedural information (e.g., Educational Research, 70, 181-214. giving students control over the pace of a demon- stration, so that they can view it step-by-step, is Atkinson, R. K., Renkl, A., & Merrill, M. M. (2003). Transitioning from studying examples to solving more effective then presenting the demonstration as problems: Effects of self-explanation prompts and one uninterrupted streaming video). And finally, fading worked-out steps. Journal of Educational Psy- split attention, signaling and modality principles are chology, 95, 774-783. particularly important for the presentation of proce- dural information, because this is typically pre- Baddeley, A. D. (1992). Working memory. Science, 255, sented while the learners work on their learning 556-559. tasks, but the same principles may also be relevant Baddeley, A. D. (1997). Human memory: Theory and to the design of complex pieces of supportive in- practice (Rev. Ed.). Hove, UK: Psychology Press. formation. Bastiaens, Th., Nijhof, W. J., Streumer, J. N., & Abma, To conclude, psychological knowledge about how H. J. (1997). Working and learning with electronic people learn with multimedia is rapidly increasing performance support systems: An effectiveness study. Training for Quality, 5(1), 10-18. and many findings from cognitive theory have been incorporated in instructional theories that yield use- Camp, G., Paas, F., Rikers, R., & van Merriënboer, J. J. ful guidelines for the design of instructional mes- G. (2001). Dynamic problem selection in air traffic sages. Less is known about how to apply those control training: A comparison between performance, guidelines in environments for complex learning mental effort and mental efficiency. Computers in Human Behavior, 17, 575-595. that try to reach integrated learning goals by using a mix of traditional and new educational media. Fu- Carlson, R. A., Khoo, H., & Elliot, R. G. (1990). Com- ture research must identify the real-life conditions ponent practice and exposure to a problem-solving under which particular principles do and do not context. Human Factors, 32, 267-286. work and, especially, develop higher-level princi- Carlson, R. A., Sullivan, M. A., & Schneider, W. (1989). ples that help designers to stretch multimedia design Component fluency in a problem solving context. from the message design level to the course design Human Factors, 31, 489-502. level, where simulated task environments, hyper- Carroll, J. M. (2000). Making use: Scenario-based design media, EPSSs, drill & practice CBT programs and of human-computer interactions. Cambridge, MA: other (traditional) media should seamlessly link up MIT Press. with each other. Future research should also ac-
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  • 4C/ID and Multimedia 18 Elaboration. A category of learning processes by which tion has a positive effect on elaborative learning and learners connect new information to knowledge that transfer. they already have available in memory. It is a form of Self-explanation principle. Prompting learners to self- schema construction that is especially important for explain new information by asking them, for instance, learning supportive information using, for instance, to identify underlying principles has a positive effect hypermedia. on elaborative learning and transfer. Fidelity principle. Sequencing learning tasks in such a Self-pacing principle. Giving learners control over the way that they are first performed in an environment pace of instruction, which may have the form of tran- that does not try mimic the real task environment (i.e., sient information (e.g. animation, video), has a posi- low fidelity) and later performed in environments that tive effect on elaborative learning and transfer. more and more resemble the real environment (i.e., increasing fidelity) has a positive effect on inductive Sequencing principle. Sequencing learning tasks from learning and transfer. simple to complex, instead of presenting them in their full complexity at once, has a positive effect on Individualization principle. Adapting the difficulty and inductive learning and transfer. the amount of available support of learning tasks to the level of expertise of individual learners has a posi- Signaling principle. Focusing learners’’ attention on the tive effect on inductive learning and transfer. critical aspects of learning tasks or presented informa- tion reduces visual search and has a positive effect on Induction. A category of learning processes, including knowledge compilation and transfer. generalization and discrimination, by which learners mindfully abstract away from their concrete experi- Spatial split-attention principle. Replacing multiple ences. It is a form of schema construction that is es- sources of information (frequently pictures and ac- pecially important for learning from learning tasks in companying text) with a single, integrated source of real or simulated task environments. information has a positive effect on knowledge com- pilation and transfer. Knowledge compilation. A category of learning processes by which learners embed new information in highly Strengthening. A category of learning processes respon- domain-specific schemata that directly steer behavior. sible for the fact that domain-specific schemata ac- It is a form of schema automation that is especially cumulate strength each time they are successfully ap- important for learning procedural information from, plied. It is a form of advanced schema automation for instance, electronic performance support systems that is especially important for (over)learning on the (EPSS). basis of part-task practice with, for instance, drill & practice computer based training. Learning task. A meaningful whole-task experience that is typically based on a real-life task and promotes in- Supportive information. Information that is relevant for ductive learning. Learning tasks are performed in a learning the problem-solving and reasoning aspects of real or simulated task environment. learning tasks through elaboration and understanding. This information is typically presented before learners Modality principle. Replacing a written explanatory text start to work on the learning tasks, by hypermedia and another source of visual information such as a that stress relations between pieces of knowledge. diagram (unimodal) with a spoken explanatory text and a visual source of information (multimodal) has a Temporal split-attention principle. Presenting multiple positive effect on knowledge compilation and trans- sources of information (e.g., mutually referring pic- fer. tures and text) at the same time, instead of one by one, has a positive effect on knowledge compilation Part-task practice. Additional exercises to train a particu- and transfer. lar routine aspect up to a very high level of automa- tion through strengthening. Drill & practice com- Training wheels principle. Sequencing learning tasks in puter-based training is a suitable medium for part-task such a way that learners’’ performance is first con- practice. strained (i.e., unproductive actions are blocked), and then slowly loosening the constraints until none has a Procedural information. Information that is relevant for positive effect on inductive learning and transfer. learning the routine aspects of learning tasks through knowledge compilation. This information is typically Variability principle. Organizing learning tasks in such a presented during task performance by electronic per- way that they differ from each other on dimensions formance support systems (EPSS). that also differ in the real world has a positive effects on inductive learning and transfer. Redundancy principle. Replacing multiple sources of information that are self-contained (i.e., they can be understood on their own) with one source of informa-