When engaging with a textbook, students are inclined to highlight key content. Although students believe that highlighting and subsequent review of the highlights will further their educational goals, the psychological literature provides little evidence of benefits. Nonetheless, a student’s choice of text for highlighting may serve as a window into her mental state—her level of comprehension, grasp of the key ideas, reading goals, and so on. We explore this hypothesis via an experiment in which 400 participants read three sections from a college‐level biology text, briefly reviewed the text, and then took a quiz on the material. During initial reading, participants were able to highlight words, phrases, and sentences, and these highlights were displayed along with the complete text during the subsequent review. Consistent with past research, the amount of highlighted material is unrelated to quiz performance. Nonetheless, highlighting patterns may allow us to infer reader comprehension and interests. Using multiple representations of the highlighting patterns, we built probabilistic models to predict quiz performance and matrix factorization models to predict what content would be highlighted in one passage from highlights in other passages. We find that quiz score prediction accuracy reliably improves with the inclusion of highlighting data (by about 1%–2%), both for held‐out students and for held‐out student questions (i.e., questions selected randomly for each student), but not for held‐out questions. Furthermore, an individual’s highlighting pattern is informative of what she highlights elsewhere. Our long‐term goal is to design digital textbooks that serve not only as conduits of information into the reader’s mind but also allow us to draw inferences about the reader at a point where interventions may increase the effectiveness of the material.

中文翻译：

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亮点作为学生理解力和兴趣的早期预测指标

在阅读教科书时，学生倾向于突出关键内容。尽管学生认为突出重点和随后回顾重点会促进他们的教育目标，但心理学文献几乎没有提供任何好处的证据。尽管如此，学生选择突出显示的文本可以作为了解她心理状态的窗口——她的理解水平、对关键思想的掌握、阅读目标等。我们通过一个实验来探索这个假设，在这个实验中，400 名参与者阅读了大学水平的生物学课本中的三个部分，简要回顾了课文，然后对材料进行了测验。在最初的阅读过程中，参与者能够突出显示单词、短语和句子，这些突出显示在随后的复习中与全文一起显示。与以往的研究一致，高亮材料的数量与测验表现无关。尽管如此，突出显示模式可以让我们推断读者的理解和兴趣。使用突出显示模式的多种表示，我们构建了概率模型来预测测验性能和矩阵分解模型来预测一个段落中将突出显示其他段落中的哪些内容。我们发现，对于留校学生和留校学生问题（即为每个学生随机选择的问题），通过包含突出显示数据（约 1%–2%），测验分数预测准确性可靠地提高，但是不适用于悬而未决的问题。此外，一个人的突出显示模式可以为她在其他地方突出显示的内容提供信息。