Effect of worked examples on mental model progression in a computer-based simulation learning environment
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Abstract
In a diagnostic problem solving operation of a computer-simulated chemical plant, chemical engineering students were randomly assigned to two groups: one studying product-oriented worked examples, the other practicing conventional problem solving. Effects of these instructional strategies on the progression of learners’ mental models were examined by comparing representations of their mental models with those of experts at three segments of the instruction. Progression of mental models for the worked example group was significantly greater than those using the problem-solving strategy. However, this progression did not manifest itself in learners’ troubleshooting performance measured by number of correct diagnosis and first time correct diagnosis. The implications of these results for designing instruction tailored to learners’ domain knowledge are discussed.
Keywords
Mental models Worked examples Complex learning SimulationReferences
- Anderson, J. R. (1982). Acquisition of cognitive skill. Psychological Review, 89, 369–403.CrossRefGoogle Scholar
- Atkinson, R. K., Derry, S. J., Renkl, A., & Wortham, D. W. (2000). Learning from examples: Instructional principles from the worked examples research. Review of Educational Research, 70, 181–214.Google Scholar
- Chase, W. G., & Simon, H. A. (1973a). The mind’s eye in chess. In W. G. Chase (Ed.), Visual information processing (pp. 215–281). New York: Academic Press.Google Scholar
- Chase, W. G., & Simon, H. A. (1973b). Perceptions in chess. Cognitive Psychology, 4, 55–81.CrossRefGoogle Scholar
- Cooper, G., & Sweller, J. (1987). Effects of schema acquisition and rule automation on mathematical problem-solving transfer. Journal of Educational Psychology, 79, 347–362.CrossRefGoogle Scholar
- Darabi, A., Nelson, D. W., & Palanki, S. (2007). Acquisition of troubleshooting skills in a computer simulation: Worked example vs. conventional problem solving instructional strategies. Computers in Human Behavior, 23(4), 1809–1819.CrossRefGoogle Scholar
- Ericsson, K. A., & Charness, N. (1994). Expert performance: Its structure and acquisition. American Psychologist, 49, 725–747.CrossRefGoogle Scholar
- Gobet, F. (2005). Chunking models of expertise: Implications for education. Applied Cognitive Psychology, 19, 183–204.CrossRefGoogle Scholar
- Jonassen, D. H., & Ionas, I. G. (2008). Designing effective supports for causal reasoning. Educational Technology Research and Development, 56, 287–308. doi: 10.1007/s11423-006-9021-6.CrossRefGoogle Scholar
- Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003). The expertise reversal effect. Educational Psychologist, 38(1), 23–31.CrossRefGoogle Scholar
- Kalyuga, S., Chandler, P., Tuovinen, J., & Sweller, J. (2001). When problem solving is superior to studying worked examples. Journal of Educational Psychology, 93(3), 579–588.CrossRefGoogle Scholar
- McClelland, J. L., Rumelhart, D. E., & Hinton, G. E. (1986). The appeal of parallel distributed processing. In J. L. McClelland, D. E. Rumelhart, & The PDP Research Group (Eds.), Parallel distributed processing: Explorations in the microstructure of cognition (Vol. 1, pp. 3–44). Cambridge, MA: MIT Press.Google Scholar
- Newell, A. (1994). Unified theories of cognition. Cambridge, MA: Harvard University Press.Google Scholar
- Paas, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38, 1–4.CrossRefGoogle Scholar
- Paas, F., Renkl, A., & Sweller, J. (2004). Cognitive load theory: Instructional implications of the interaction between information structures and cognitive architecture. Instructional Science, 32, 1–8.CrossRefGoogle Scholar
- Seel, N. M. (2001). Epistemology, situated cognition, and mental models: ‘Like a bridge over troubled water’. Instructional Science, 29, 403–427.CrossRefGoogle Scholar
- Seel, N. M., Darabi, A. A., & Nelson, D. W. (2006). A dynamic mental model approach to examine schema development in performing a complex troubleshooting task: Retention of mental models. Technology, Instruction, Cognition, and Learning, 4(4), 273–299.Google Scholar
- Snow, R. E. (1989). Toward assessment of cognitive and conative structures in learning. Educational Researcher, 18(9), 8–14.Google Scholar
- Sweller, J., & Cooper, G. A. (1985). The use of worked examples as a substitute for problem solving in learning algebra. Cognition & Instruction, 2(1), 59–89.CrossRefGoogle Scholar
- Sweller, J., van Merriënboer, J. J. G., & Paas, F. G. W. C. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251–296.CrossRefGoogle Scholar
- Van Gog, T., Paas, F., & van Merriënboer, J. J. G. (2004). Process-oriented worked examples: Improving transfer performance through enhanced understanding. Instructional Science, 32(1–2), 83–98.Google Scholar
- Van Gog, T., Paas, F., & van Merriënboer, J. J. G. (2008). Effects of studying sequences of process-oriented and product-oriented worked examples on troubleshooting transfer efficiency. Learning and Instruction, 18, 211–222.CrossRefGoogle Scholar
- van Merriënboer, J. J. G. (1997). Training complex cognitive skills: A four-component instructional design model. Englewood Cliffs, NJ: Educational Technology Publications.Google Scholar
- van Merriënboer, J. J. G., Clark, R. E., & de Croock, M. B. M. (2002). Blueprints to complex learning: The 4C/ID model. Educational Technology Research and Development, 50(2), 39–64.CrossRefGoogle Scholar
- van Merriënboer, J. J. G., Kirschner, P. A., & Kester, L. (2003). Taking the load off a learner’s mind: Instructional design for complex learning. Educational Psychologist, 38(1), 5–13.CrossRefGoogle Scholar