Research on Cognitive Load Theory and Its Design Implications for Problem Solving Instruction
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The purpose of this study was to develop the problem solving instruction facilitating novice learner to represent the problem. For the purpose, we mainly focused on three aspects of problem solving. First, learner should represent the targeted problem and its solutions for problem solving. Second, from crucial notions of cognitive load theory, learner's mental load should be optimized for problem representation. Third, for optimizing students’ mental load, experts may support making their thinking more visible and mapping from their intuition to expert practice. We drew the design principles as follows. First, since providing worked examples for the targeted problem has been considered to minimize analogical errors as well as reduce cognitive load in problem representation at line of problem solving and instructional research, it is needed to elaborate the way of designing. The worked example alternatively corresponds to expert schema that consists of domain knowledge as well as strategies for expert-like problem representation and solution. Thus, it may help learner to represent what the problem is and how to solve it in problem space. Second, principle can be that expert should scaffold learner’s selfexplanations. Because the students are unable to elicit the rationale from worked example, the expert’s triggering scaffold may be critical in that process. The unexplained and incomplete parts of the example should be completed not by expert’s scaffold but by themselves. Critical portion of the expert’s scaffold is to explain about how to apply and represent the given problem, since students’ initial representations may be reached at superficial or passive pattern of example elaboration. Finally, learner’s mental model on the designated problem domain should be externalized or visualized for one’s reflection as well as expert’s scaffolding activities. The visualization helps learner to identify one’s partial or incorrect model. The correct model of learner could be constructed by expert’s help.
Abstract
The purpose of this study was to develop the problem solving instruction facilitating novice learner to represent the problem. For the purpose, we mainly focused on three aspects of problem solving. First, learner should represent the targeted problem and its solutions for problem solving. Second, from crucial notions of cognitive load theory, learner's mental load should be optimized for problem representation. Third, for optimizing students’ mental load, experts may support making their thinking more visible and mapping from their intuition to expert practice. We drew the design principles as follows. First, since providing worked examples for the targeted problem has been considered to minimize analogical errors as well as reduce cognitive load in problem representation at line of problem solving and instructional research, it is needed to elaborate the way of designing. The worked example alternatively corresponds to expert schema that consists of domain knowledge as well as strategies for expert-like problem representation and solution. Thus, it may help learner to represent what the problem is and how to solve it in problem space. Second, principle can be that expert should scaffold learner’s selfexplanations. Because the students are unable to elicit the rationale from worked example, the expert’s triggering scaffold may be critical in that process. The unexplained and incomplete parts of the example should be completed not by expert’s scaffold but by themselves. Critical portion of the expert’s scaffold is to explain about how to apply and represent the given problem, since students’ initial representations may be reached at superficial or passive pattern of example elaboration. Finally, learner’s mental model on the designated problem domain should be externalized or visualized for one’s reflection as well as expert’s scaffolding activities. The visualization helps learner to identify one’s partial or incorrect model. The correct model of learner could be constructed by expert’s help.
참고문헌 (47)
- Anderson, J. R., "The analogical origins of errors in problem solving", A paper presented at the 21st Carnegie Symposium on Cognition (1989)
- Anderson, J. R., "The role of examples and rules in the acquisition of a cognitive skill", Journal of Experimental Psychology: Learning, Memory, and Cognition, 23, pp.932~945 (1997)
- Anderson, J. R., "Acquisition of problem solving skill. in: Cognitive skills and their acquisition" (1981), LEA
- Atkinson, R. K., "Learning from examples: Instructional principles from the worked examples research", Review of Educational Research, 70(2), pp.181~214 (2000)
- Bell, P., "Using argument map representations to make thinking visible for individuals and groups. in: CSCL 2, carrying forward the conversation", pp.449~486 (2002), LEA
- Bielaczyc, K., "Training in self-explanation and self regulation strategies: Investigating the effects of knowledge acquisition activities on problem solving", Cognition and Instruction, 13, pp.221~252 (1995)
- Bruer, J., "Schools for thought: A science of learning in the classroom" (1993), MIT Press
- Catrambone, R., "The subgoal learning model: Creating better examples so that students can solve novel problems", Journal of Experimental Psychology, 127(4), pp.355~376 (1998)
- Chi, M. T. H., "Learning from examples via self-explanations. in: Knowing, learning, and instruction: Essay in honor of Robert Glaser", pp.251~282 (1989), LEA
- Chi, M. T. H., "Selfexplanation: How students study and use examples in learning to solve problems", Cognitive Science, 13, pp.145~182 (1989)
- Chi, M. T. H., "Eliciting selfexplanations improves understanding", Cognitive Science, 18, pp.439~477 (1994)
- Chi, M. T. H., "Categorization and representation of physics problems by experts and novices", Cognitive Science, 5(2), pp.121~152 (1981)
- Chi, M. T. H., "Expertise in problem solving", Advances in the psychology of human intelligence, 통권 : 1 (1982), LEA
- Chi, M. T. H., "The content of physics self-explanations", Journal of the Learning Sciences, 1, pp.69~105 (1991)
- Cooper, G., "Effects of schema acquisition and rule automation on mathematical problem solving transfer", Journal of Educational Psychology, 79, pp.347~362 (1987)
- Dillenbourg, P., "The evolution of research on collaborative learning. in: Learning in humans and machine: Towards an interdisciplinary learning science", pp.189~211 (1996), Elsevier
- Ericsson, K. A., "Long-term working memory", Psychological Review, 102, pp.211~245 (1995)
- Feltovich, P. J., "Collaboration within and among minds: Mastering complexity, individually and in groups. in: CSCL: Theory and practice of an emerging paradigm", pp.25~44 (1996), LEA
- Gerjets, P., "Goal configurations and processing strategies as moderators between instructional design and cognitive load: Evidence from hypertext-based instruction", Educational Psychologist, 38(1), pp.33~41 (2003)
- Hausmann, R. G. M., "Learning from collaborative problem solving: An analysis of three hypothesized mechanisms", A paper presented at the 26th Annual Conference of the Cognitive Science Society (2004)
- Hewitt, J., "From a focus on tasks to a focus on understanding: The cultural transformation of a toronto classroom. in: CSCL 2, carrying forward the conversation" (2002), LEA
- Kalyuga, S., "Expertise reversal effect", Educational Psychologist, 38, pp.23~31 (2003)
- Development of CAI prototypes for problem solving, "Kim, D.", KEDI, ~, pp.No. RR92- 17 (1992)
- ID model, "Instructional design model: 4C", pp.2005, Kim, D.
- Kirschner, P. A., "Cognitive load theory: Implications of cognitive load theory on the design of learning", Learning and Instruction, 12, pp.1~10 (2002)
- Lin, X., "Metacognition: Implication for research in hypermedia-based learning environment", Proceedings of the 1994 National Convention of the AECT, 통권 : 16, pp.483~502 (1994)
- Linn, M. C., "Computers, teachers, peers" (2000), LEA
- Neuman, Y., "Is self-explanation while solving problems helpful? The case of analogical problem-solving", British Journal of Educational Psychology, 68, pp.15~24 (1998)
- Paas, F., "Training strategies for attaining transfer of problem solving skill in statics: A cognitive load approach", Journal of Educational Psychology, 84, pp.429~434 (1992)
- Paas, F., "Cognitive load theory: Instructional implications of the interaction between information structures and cognitive architecture", Instructional Science, 32, pp.1~8 (2004)
- Ploetzner, R., "Learning by explaining to oneself and to others. in: Collaborative learning: Cognitive and computational approaches", pp.103~121 (1999), Elsevier
- Renkl, A., "Learning from worked-out examples: A study on individual differences", Cognitive Science, 21, pp.1~29 (1997)
- Renkl, A., "Structuring the transition from example study to problem solving in cognitive skill aquisition: A cognitive load perspective", Educational Psychologist, 38(1), pp.15~22 (2003)
- Renkl, A., "Learning from worked-out examples: The effects of example variability and elicited self-explanations", Contemporary educational psychology, 23, pp.90~108 (1998)
- Stark, R., "Conditions and effects of example elaboration", Learning and Instruction, 12, pp.39~60 (2002)
- Suthers, D., "Representations for scaffolding collaborative inquiry on ill-structured problems", A paper presented at the conference of the American Educational Research Association (1998)
- Suthers, D., "The effects of representation on students' elaborations in collaborative inquiry", A paper presented at the Proceedings of Computer Support for Collaborative Learning (2002)
- Sweller, J., "Evolution of human cognitive architecture. in: The psychology of learning and motivation (Vol. 43)", pp.215~266 (2003), Academic Press
- Sweller, J., "Cognitive architecture and instructional design", Educational Psychology Review, 10(3), pp.251~296 (1998)
- van Bruggen, J., "External representation of argumentation in CSCL and the management of cognitive load", Learning and Instruction, 12(1), pp.121~138 (2002)
- van Merrienboer, J. J. G., "Training complex cognitive skills: A four-component instructional design model for technical training" (1997), Educational Technology Publications
- van Merrienboer, J. J. G., "Taking the load off a learner's mind: Instructional design for complex learning", Educational Psychologist, 38(1), pp.5~13 (2003)
- VanLehn, K., "Integration of explanation-based learning of correctness and analogical search control. in: Machine learning methods for planning" (1993), Morgan Kaufmann
- Vygotsky, L. S., "Mind in society: The development of higher psychological processes" (1978), Harvard University Press
- Ward, M., "Structuring effective worked examples", Cognition and Instruction, 7, pp.1~39 (1990)
- Zhang, J., "The nature of external representations in problem solving", Cognitive Science, 21(2), pp.179~217 (1997)
- Zhu, X., "Learning mathematics from examples and by doing", Cognition and Instruction, 4(3), pp.137~166 (1987)