Summary writing is a useful instructional tool for learning. However, summary writing is a challenge to many students. This mixed‐method study examined the potential of the Student Mental Model Analyzer for Research and Teaching (SMART) system to help students produce summaries that reflect key concepts and relations in a text. SMART uses the students' summary to generate a multi‐dimensional 3S (surface, structure, semantic) evaluation of the students' mental model. This model is then used to drive feedback to help students revise their summary. The current study is an initial investigation examining whether writing and revising in SMART improves students' summary quality. Students (n = 38) in a graduate‐level online course used SMART for seven reading assignments. The 38 students submitted a total of 357 summaries in response to the seven readings. In 47 cases, students produced both an initial draft and a modified revision. These 47 cases were selected for analysis. In the quantitative phase, MANOVA results indicated that students' summaries improved along the 3S dimensions from initial draft to revision. In the qualitative phase, inspection of exemplar cases revealed how students' mental models changed towards more robust and cohesive knowledge structure for texts.

中文翻译：

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在技​​术增强的学习环境中，通过形成性反馈来改善摘要写作

摘要写作是学习的有用指导工具。但是，总结写作对许多学生来说都是一个挑战。这项混合方法的研究探讨了研究与教学用学生心理模型分析器（SMART）系统的潜力，该系统可帮助学生产生可在文本中反映出关键概念和关系的摘要。SMART使用学生的摘要来生成对学生心理模型的多维3S（表面，结构，语义）评估。然后，该模型用于驱动反馈，以帮助学生修改其摘要。当前的研究是一项初步调查，研究在SMART中进行写作和修订是否可以提高学生的总结素质。学生（n= 38）在研究生级别的在线课程中，使用SMART进行了七个阅读作业。38位学生针对这7份读物共提交了357份摘要。在47个案例中，学生制作了初稿和修订版。选择这47例进行分析。在定量阶段，MANOVA结果表明，学生的总结从最初的草稿到修订，都沿着3S维度得到了改善。在定性阶段，对典型案例的检查揭示了学生的心理模型如何朝着更健壮和凝聚力的文本知识结构转变。