Learning analytics of humanities course: reader profiles in critical reading activity

Research and Practice in Technology Enhanced Learning

Rwitajit Majumdar¹  Brendan Flanagan¹  Hiroaki Ogata¹  Geetha Bakilapadavu²  Mei-Rong Alice Chen³  Reek Majumder⁴ 

[1] Academic Center for Computing and Media Studies, Kyoto University, Kyoto, Japan;Department of Humanities and Social Science, BITS Pilani Goa Campus, Pilani, India;National Taiwan University of Science and Technology, Taipei, Taiwan;School of Computing, Clemson University, Clemson, USA;

关键词: Learning analytics;    Humanities course;    BookRoll;    Critical reading activity;    Process mining;    Engagement score;    Reader profiles;   

DOI  :  10.1186/s41039-021-00164-w

来源: Springer

【 摘 要 】

This study investigates learner’s reading behaviors in a critical reading task in humanities course using learning analytics techniques. A Critical Analysis of Literature and Cinema course was selected as a context. The course activities evolved over 10 years, and for this instance, some face-to-face classroom critical reading activities were migrated to online mode by using BookRoll, a learning analytics enhanced eBook platform. Students (n=22 out of the 50 registered) accessed Hayavadana, an Indian play uploaded on BookRoll, and attempted to identify performative elements and cultural references in the text and highlight them. In this study, we analyze learner’s reading logs gathered in the learning record store linked to BookRoll during that activity. We extend our previous work where we identify four online reading profiles: effortful, strategic, wanderers, and check-out, based on learner’s clickstream interactions and time spent with the content. We validate the profiles with qualitative interview data collected from the learners and illustrate the quantified learning behaviors of each of those profiles based on an engagement metric. Our work aims to initiate further discussion related to the application of learning analytics in humanities courses both to probe into the learning behaviors of the students and thereby enhance the experiences with the use of interactive learning environments and data-driven services.

【 授权许可】

CC BY