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Abstract Title: Design and evaluation of a natural language tutor for force and motion
Abstract: We report on the design of a simple natural language computer tutor that targets student difficulties with the concepts of force and motion. The tutor prompts students to respond in free-response natural language to questions that address the relationships between the directions of net force, velocity, and acceleration. The tutor evaluates responses and provides immediate question-specific feedback. To examine the effectiveness of the natural language tutor, we compared the performance between four training conditions: natural language format, multiple choice format, natural language format without feedback (time-on-task control), and a no-training control. The natural language training and multiple choice training provided learning gains with effect sizes of d=0.60 and d=0.46 respectively. However, accounting for time spent on training, the multiple choice training was more efficient. Performance of the current natural language implementation is discussed in terms of language accuracy, the rate of false-positives, and evaluation of typical student answer patterns.
Abstract Type: Contributed Poster Presentation

Author/Organizer Information

Primary Contact: Ryan Badeau
The Ohio State University
1040 Physics Research Building
191 West Woodruff Avenue
Columbus, OH 43210-1117
Phone: 607-346-5196
and Co-Presenter(s)
Andrew Heckler

Contributed Paper

Contributed Paper: Download the Contributed Paper