The Impact of Granularity on Worked Examples and Problem Solving.

Project No.
1432156
PI Name
Min Chi
Institution
NCSU



Abstract 1

The Impact of Granularity on Worked Examples and Problem Solving.

Presentation Type
Poster
Team
Min Chi, NCSU


Need

In this paper, we explored the impact of two types of instructional interventions, worked examples and problem solving, at two levels of granularity: problems and steps. This study relied on an existing Intelligent Tutoring System (ITS) for Probability called Pyrenees and involved 266 students who were randomly assigned into five conditions. All students experienced the same procedure, studied the same training problems in the same order, and used the same ITS. The conditions differed only in how the training problems were presented. Our results showed that when the domain content and required steps are strictly equivalent, different granularities of pedagogical decisions can significantly impact studentsメ time on task. More specifically, the fine-grained step level decisions can have a stronger pedagogical impact than the problem-level ones.

Unexpected Challenges

Not much so far.

Citations

B. Mostafavi, G. Zhou, C. F. Lynch, M. Chi, and T. Barnes. モData-driven Worked Examples Improve Retention and Completion in a Logic Tutorヤ. In: Proceedings of the 17th International Conference on Artificial Intelligence in Education (AIED 2015). 2015, pp. 726 ヨ729.

Mostafavi, B., Liu, Z. and Barnes, T. (2015) Data-driven Proficiency Profiling. In Proceedings of the 8th International Conference on Educational Data Mining (EDM 2015), In Press.

Mostafavi, B., Eagle, M. and Barnes T (2015, March). Towards Data-driven Mastery Learning. In Proceedings of the Fifth International Conference on Learning Analytics and Knowledge (LAK 2015), pp. 270-274. ACM.

C. F. Lynch, T. W. Price, M. Chi, and T. Barnes. モUsing the Hint Factory to Analyze Model-Based Tutoring Systemsヤ. In: Proceedings of the Second International Workshop on Graph-Based Educational Data Mining (GEDM 2015). (in press). CEUR-WS, 2015.

T. W. Price, C. F. Lynch, T. Barnes, and M. Chi. モAn Improved Data-Driven Hint Selection Algorithm for Probability Tutorsヤ. In: Proceedings of the 8th International Conference on Educational Data Mining (EDM 2015). International Educational Data Mining Society, 2015. pp 610 - 611

Michael Eagle, Drew Hicks, and Tiffany Barnes. モInteraction Network Estimation: Predicting Problem-Solving Diversity in Interactive Environments.ヤ In Proceedings of the 8th International Conference on Educational Data Mining (EDM 15), Madrid, Spain, 2015

Michael Eagle, Drew Hicks, Barry Peddycord III, and Tiffany Barnes. モExploring Networks of Problem-Solving Interactions.ヤ In Proceedings of the 5th International Learning Analytics and Knowledge Conference (LAK 15), Poughkeepsie, New York, 2015

Zhou, G., Price, T. W., Lynch, C., Barnes, T., & Chi, M. (2015). The Impact of Granularity on Worked Examples and Problem Solving. In Proceedings of the 37th Annual Meeting of the Cognitive Science Society. (PP. 2817-2822) [Oral Presentation]