An Integrated Platform for Studying Learning with Intelligent Tutoring Systems: CTAT+TutorShop
Vincent Aleven, Conrad Borchers, Yun Huang, Tomohiro, Nagashima, Bruce McLaren, Paulo Carvalho, Octav Popescu, Jonathan, Sewall, Kenneth Koedinger

TL;DR
The paper introduces CTAT+Tutorshop, an integrated platform that supports the entire research lifecycle of intelligent tutoring systems, enabling data collection, system development, and experimental studies across diverse educational settings.
Contribution
It presents a comprehensive platform that uniquely combines authoring, data logging, and analysis tools for ITS research, facilitating new insights into student learning and system effectiveness.
Findings
Used in 147 research studies across various educational settings
Supports authoring of ITS components and whole systems
Enables analysis of learner challenges and system improvements
Abstract
Intelligent tutoring systems (ITSs) are effective in helping students learn; further research could make them even more effective. Particularly desirable is research into how students learn with these systems, how these systems best support student learning, and what learning sciences principles are key in ITSs. CTAT+Tutorshop provides a full stack integrated platform that facilitates a complete research lifecycle with ITSs, which includes using ITS data to discover learner challenges, to identify opportunities for system improvements, and to conduct experimental studies. The platform includes authoring tools to support and accelerate development of ITS, which provide automatic data logging in a format compatible with DataShop, an independent site that supports the analysis of ed tech log data to study student learnings. Among the many technology platforms that exist to support learning…
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Taxonomy
TopicsIntelligent Tutoring Systems and Adaptive Learning
