用最终答案反推错误步骤，解决多步合并难题
Buggy rule diagnosis for combined steps through final answer evaluation in stepwise tasks
- 通过最终答案逆向诊断学生合并步骤的错误
- 在1939个案例中诊断出29.4%的错误步骤
- 与教师判断一致率达97%，适合教育系统优化
许多智能辅导系统可帮助学生完成分步任务。当学生将多个步骤合并为一步时，连续输入间的可能路径数量会急剧增加，导致错误诊断困难。利用最终答案进行诊断可缓解这一组合爆炸问题，因为错误最终答案的数量通常远少于错误解题路径。通过根据任务求解策略自动补全中间输入并诊断该解法，本研究探索了基于最终答案的自动化错误诊断潜力。我们设计了一项服务，用于诊断学生合并多个步骤的情况。为验证方法有效性，我们在一个现有数据集（n=1939）上应用该服务，该数据集包含学生求解二次方程时无法被传统单规则连接诊断的服务识别的唯一步骤。结果显示，最终答案评估可诊断其中29.4%的步骤；进一步在子集（n=115）上对比生成诊断与教师诊断，两者一致性达97%。这些结果为该方法的后续探索提供了基础。
原文摘要 · Abstract (English)
Many intelligent tutoring systems can support a student in solving a stepwise task. When a student combines several steps in one step, the number of possible paths connecting consecutive inputs may be very large. This combinatorial explosion makes error diagnosis hard. Using a final answer to diagnose a combination of steps can mitigate the combinatorial explosion, because there are generally fewer possible (erroneous) final answers than (erroneous) solution paths. An intermediate input for a task can be diagnosed by automatically completing it according to the task solution strategy and diagnosing this solution. This study explores the potential of automated error diagnosis based on a final answer. We investigate the design of a service that provides a buggy rule diagnosis when a student combines several steps. To validate the approach, we apply the service to an existing dataset (n=1939) of unique student steps when solving quadratic equations, which could not be diagnosed by a buggy rule service that tries to connect consecutive inputs with a single rule. Results show that final answer evaluation can diagnose 29,4% of these steps. Moreover, a comparison of the generated diagnoses with teacher diagnoses on a subset (n=115) shows that the diagnoses align in 97% of the cases. These results can be considered a basis for further exploration of the approach.
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