Assessing Learner’s Scientific Inquiry Skills Across Time: A Dynamic Bayesian Network Approach
In this article, we develop and evaluate three Dynamic Bayesian Network (DBN) models for assessing temporally variable learner scientific inquiry skills (Hypothesis Generation and Variable Identification) in INQPRO learning environment. Empirical studies were carried out to examine the matching accuracies and identify the models’ drawbacks. We demonstrate how the insights gained from a preceding model have eventually led to the improvement of subsequent models. In this study, the entire evaluation process involved 6 domain experts and 61 human learners. The matching accuracies of the models are measured by (1) comparing with the results gathered from the pretest, posttest, and learner’s self-rating scores; and (2) comments given by domain experts based on learners’ interaction logs and the graph patterns exhibited by the models.
KeywordsScientific Inquiry Skills Dynamic Bayesian Networks
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- 1.Paolucci, M., Suthers, D.D., Weiner, A.: Automated advice-giving strategies for scientific inquiry. In: Frasson, C., Gauthier, G., Lesgold, A. (eds.) Lecture Notes In Computer Science, pp. 372–381. Springer-Verlag, NewYork, NY (1996)Google Scholar
- 3.Pryor, A., Soloway, E.: Foundation of Science: Using Technology to Support Authentic Science learning (1997) http://hi-ce.eecs.umich.edu/papers/
- 4.Veermans, K., van Joolingen, W.R.: Combining Heuristics and Formal Methods in a Tool for Supporting Simulation-Based Discovery Learning. Intelligent Tutoring Systems, pp. 217–226 (2004)Google Scholar
- 5.Reiser, B.J., Tabak, I., Sandoval, W.A., Smith, B., Steinmuller, F., Leone, T.J.: BGuILE: Stategic and Conceptual Scaffolds for Scientific Inquiry in Biology Classrooms. In: Carver, S.M., Klahr, D.(eds.): Cognition and Instruction: Twenty five years of progress. Erlbaum, Mahvah, NJ.Google Scholar
- 8.Murray, R.C., VanLehn, K., Mostow, J.: Looking ahead to select tutorial actions: A decision-theoretic approach. International Journal of Artificial Intelligence in Education 14, 235–278 (2004)Google Scholar
- 12.Schafer, R., Weyrath, T.: Assessing Temporally Variable User Properties with Dynamic Bayesian Networks. In: UM97. User Modeling: Proceedings of the Sixth International Conference, Vienna, New York, pp. 377–388. Springer, New York (1997)Google Scholar