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Learning Analytics of Humanities Course: Reader Profiles in Critical Reading Activity

Title: Learning Analytics of Humanities Course: Reader Profiles in Critical Reading Activity
Language: English
Authors: Majumdar, Rwitajit (ORCID 0000-0003-4671-0238); Bakilapadavu, Geetha; Majumder, Reek; Chen, Mei-Rong Alice; Flanagan, Brendan; Ogata, Hiroaki
Source: Research and Practice in Technology Enhanced Learning. 2021 16.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: N
Page Count: 18
Publication Date: 2021
Document Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Descriptors: Learning Analytics; Humanities; Critical Reading; Electronic Publishing; Drama; Behavior Patterns; Profiles; Interaction; Undergraduate Students; Foreign Countries
Geographic Terms: India
DOI: 10.1186/s41039-021-00164-w
ISSN: 1793-7078
Abstract: 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.
Abstractor: As Provided
Entry Date: 2021
Accession Number: EJ1303412
Database: ERIC