PathViewer: Visualizing Pathways through Student Data

論文URL:http://dl.acm.org/citation.cfm?doid=3025453.3025819

論文アブストラクト:Analysis of student data is critical for improving education. In particular, educators need to understand what approaches their students are taking to solve a problem. However, identifying student strategies and discovering areas of confusion is difficult because an educator may not know what queries to ask or what patterns to look for in the data. In this paper, we present a visualization tool, PathViewer, to model the paths that students follow when solving a problem. PathViewer leverages ideas from flow diagrams and natural language processing to visualize the sequences of intermediate steps that students take. Using PathViewer, we analyzed how several students solved a Python assignment, discovering interesting and unexpected patterns. Our results suggest that PathViewer can allow educators to quickly identify areas of interest, drill down into specific areas, and identify student approaches to the problem as well as misconceptions they may have.

日本語のまとめ:

545人の生徒にPythonの課題を出し,どんなアプローチで問題を解決しているかを可視化した.どのテストケースを通過したのかをプログラムを実行する度に保存し,通過したテストケースの変化から困っている生徒の特定が可能になる.

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