Abstract
Note-taking has a long history in educational settings. Previous research has shown that note-taking leads to improved learning and performance on assessment. It was therefore hypothesized that note-taking could play an important role in narrative-centered learning. To investigate this question, a note-taking facility was introduced into a narrative-centered learning environment. Students were able to use the facility to take and review notes while solving a science mystery. In this paper we explore the individual differences of note-takers and the notes they take. Finally, we use machine learning techniques to model the content of student notes to support future pedagogical adaptation in narrative-centered learning environments.
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McQuiggan, S.W., Goth, J., Ha, E., Rowe, J.P., Lester, J.C. (2008). Student Note-Taking in Narrative-Centered Learning Environments: Individual Differences and Learning Effects. In: Woolf, B.P., Aïmeur, E., Nkambou, R., Lajoie, S. (eds) Intelligent Tutoring Systems. ITS 2008. Lecture Notes in Computer Science, vol 5091. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69132-7_54
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DOI: https://doi.org/10.1007/978-3-540-69132-7_54
Publisher Name: Springer, Berlin, Heidelberg
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