Visual representations are a powerful tool used for teaching and learning across many STEP domains. However, it has been reported that visuals are not universally effective – students having low prior knowledge and ability often do not benefit from learning with visuals.
To tackle this problem, we’ve created an intelligent tutoring system (ITS) for algebra that provides scaffolding support so that students with lower prior knowledge can easily and effectively use the visual support to make sense of the problem and the solution steps. In the tutor, students are asked to self-“explain” their solution steps in the form of diagrams, which we call diagrammatic self-explanation. We tested the effectiveness of this approach on student learning, particularly learning of conceptual knowledge in algebra. Our recent controlled classroom study confirmed that diagrammatic self-explanation helped students who had lower prior knowledge in solving algebra problems gain conceptual knowledge.
The design of diagrams is based on research findings from our earlier user research with teachers and middle school students, which involved semi-structured interviews, low-fi (physical) and high-fi (digital) prototypes, think alouds, and a survey.
- Nagashima, T., Bartel, A. N., Silla, E. M., Vest, N. A., Alibali, M. W., & Aleven, V. (2020). Enhancing conceptual knowledge in early algebra through scaffolding diagrammatic self-explanation. In Proceedings of the International Conferences of the Learning Sciences (ICLS2020), Nashville, TN. [pdf]
- Nagashima, T., Yang, K., Bartel, A. N., Silla, E. M., Vest, N. A., Alibali, M. W., & Aleven, V. (2020). Pedagogical Affordance Analysis: Leveraging teachers’ pedagogical knowledge for eliciting pedagogical affordances and constraints of instructional tools. In Proceedings of the International Conferences of the Learning Sciences (ICLS2020). Nashville, TN. [pdf]