Logo image
Back
Visualizing Intelligent Tutor Interactions for Responsive Pedagogy
Conference proceeding   Open access   Peer reviewed

Visualizing Intelligent Tutor Interactions for Responsive Pedagogy

Adit Gupta, Grace Guo, Aishwarya Mudgal Sunil Kumar Kumar, Adam Coscia, Chris Maclellan and Alex Endert
AVI '24: Proceedings of the 2024 International Conference on Advanced Visual Interfaces, pp 1-9
03 Jun 2024
DOI: https://doi.org/10.1145/3656650.3656667
Featured in Collection :   Research Supported by Drexel Libraries' OA Programs
url
https://doi.org/10.1145/3656650.3656667View
Published, Version of Record (VoR)Open Access via Drexel Libraries Read and Publish Program 2024CC BY V4.0,  Open

Abstract

Artificial Intelligence or Cybernetics
Intelligent tutoring systems leverage AI models of expert learning and student knowledge to deliver personalized tutoring to students. While these intelligent tutors have demonstrated improved student learning outcomes, it is still unclear how teachers might integrate them into curriculum and course planning to support responsive pedagogy. In this paper, we conducted a design study with five teachers who have deployed Apprentice Tutors, an intelligent tutoring platform, in their classes. We characterized their challenges around analyzing student interaction data from intelligent tutoring systems and built VisTA (Visualizations for Tutor Analytics), a visual analytics system that shows detailed provenance data across multiple coordinated views. We evaluated VisTA with the same five teachers, and found that the visualizations helped them better interpret intelligent tutor data, gain insights into student problem-solving provenance, and decide on necessary follow-up actions – such as providing students with further support or reviewing skills in the classroom. Finally, we discuss potential extensions of VisTA into sequence query and detection, as well as the potential for the visualizations to be useful for encouraging self-directed learning in students.

Metrics

1 File views/ downloads
37 Record Views

Details

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Collaboration types
Domestic collaboration
Web of Science research areas
Computer Science, Cybernetics
Computer Science, Theory & Methods
Logo image