Conceptual and Procedural Knowledge of Algebra

I have also worked with an interdisciplinary team (psychologists, computer scientists, and educators) to study how to enhance algebra learning through the integration of key concepts and problem-solving procedures. Our team tackled this question using a software-based intelligent tutoring system (ITS), which uses artificial intelligence to provide detailed and targeted guidance that adapts to students’ errors, strategies, and developing algebra knowledge. We are testing the effects of variations in the ITS on middle-school students’ learning about linear equations.
In one study, students completed a pretest, a brief computer-based lesson about linear equations using the ITS, three worked examples with explanations, and a posttest. We found that expressing concepts when explaining worked examples helped to activate and strengthen conceptual knowledge, particularly for learners with low prior knowledge.
In another study, we tested whether implementing specific instructional approaches (diagrams, warm-up activities, and worked examples) in the ITS lead to gains in conceptual understanding.
In earlier work, I spearheaded an independent project exploring gesture and algebra learning. In this research, I examined whether students mimic the gestures produced by a computer-animated pedagogical avatar during a mathematics lesson. Students varied in their gesture rates, and some students produced gestures that were similar in form to the avatar’s gestures. Students who produced gestures that aligned with the teacher’s gestures scored higher than those who did not produce such gestures.

Selected Works:
Vest, N. A., Silla, E. M., Bartel, A. N., Nagashima, T., Aleven, V., & Alibali, M. W. (2022, July). Self-explanation of worked examples integrated in an Intelligent Tutoring System enhances problem solving and efficiency in algebra. Proceedings of the Annual Conference of the Cognitive Science Society. Toronto, Canada. [paper]

Vest, N. A., Silla, E. M., Bartel, A. N., Nagashima, T., Aleven, V., & Alibali, M. W. (2021, April) Learning from worked examples: Conceptually rich explanations predict conceptual gains. [Poster] Biennial Meeting of the Society for Research in Child Development. [poster]

Vest, N. A., Fyfe, E. R., Nathan, M. J., & Alibali, M. W. (2020). Learning from an avatar video instructor: The role of gesture mimicry. Gesture. [paper]