Analyzing Student Notes and Questions to Create Personalized Study Guides (LAK14)

Type: Evidence | Proposition: A: Learning | Polarity: | Sector: | Country:

Abstract: In the foreseeable future it will be technically possible for instructors, advisors and other delegated representatives of a college or university to access student participation and performance data in near-real time. One potential benefit of this increased data flow could include an improved ability to identify students at risk of academic failure or withdrawal. The availability of these data could also lead to creation of new adaptive learning measures that can automatically provide students personalized guidance.

Overview from the Hub: a presentation about what LectureTools records with view of this being used to provide real time data to teachers. A ‘study guide’ is generated from student notes submitted (in the LectureTools software) and ‘Lecture Clouds’ provided to students. Anecdotal feedback is positive and student wanted the cloud to provide links to  resources to help them better understand concepts (e.g. to their etextbook). No systematic qualitative evaluation is in evidence but this example represents a description of a real case of how analytics could help and add value to the system.

Citation: Samson, P. (2014) Analyzing Student Notes and Questions to Create Personalized Study Guides. The 4th International Conference on Learning Analytics and Knowledge. March 24-28, 2014. Indianapolis, USA.

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