Specifying Rewrite Strategies for Interactive Exercises
Specifying Rewrite Strategies for Interactive Exercises
复制标题
指定交互式练习的重写策略
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
Alex Gerdes
中科院分区：
文献类型：
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作者：
B. Heeren;J. Jeuring;Alex Gerdes
策略指定了如何增量地解决各种练习，例如将逻辑命题转化为析取范式，减少矩阵或使用分数计算。在本文中，我们介绍了一种语言，指定策略解决练习。这种语言使得自动计算反馈变得更容易，例如当用户在计算中犯了错误时。我们可以自动生成计算出的示例，通过检查提交的中间答案来跟踪学生的进度，并在学生偏离策略时报告建议。因此，指定新的锻炼领域和该领域内的锻炼变得不那么劳动密集且不那么特别。策略描述重写规则的有效序列，将跟踪中间步骤转化为解析问题。这是一个很有前途的观点，在互动练习，因为它使我们能够利用多年的经验，在分析句子的上下文无关的语言，并转移这些知识和技术的逐步解决练习的领域。在本文中，我们逐步分析和解决练习之间的相似性，我们讨论了产生反馈的策略，和实现的策略识别器。
Strategies specify how a wide range of exercises can be solved incrementally, such as bringing a logic proposition to disjunctive normal form, reducing a matrix, or calculating with fractions. In this paper we introduce a language for specifying strategies for solving exercises. This language makes it easier to automatically calculate feedback, for example when a user makes an erroneous step in a calculation. We can automatically generate worked-out examples, track the progress of a student by inspecting submitted intermediate answers, and report back suggestions in case the student deviates from the strategy. Thus it becomes less labor-intensive and less ad-hoc to specify new exercise domains and exercises within that domain. A strategy describes valid sequences of rewrite rules, which turns tracking intermediate steps into a parsing problem. This is a promising view at interactive exercises because it allows us to take advantage of many years of experience in parsing sentences of context-free languages, and transfer this knowledge and technology to the domain of stepwise solving exercises. In this paper we work out the similarities between parsing and solving exercises incrementally, we discuss generating feedback on strategies, and the implementation of a strategy recognizer.