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

Rwitajit Majumdar,Brendan Flanagan,Hiroaki Ogata,Reek Majumder,Geetha Bakilapadavu,Mei-Rong Alice Chen

doi:10.1186/s41039-021-00164-w

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.

Highlights

IntroductionBackground and motivationLearning analytics as a domain has evolved over the last decade to apply various computational techniques to collect, analyze, and understand data related to teachinglearning experiences and thereby enhance them
Background and motivationLearning analytics as a domain has evolved over the last decade to apply various computational techniques to collect, analyze, and understand data related to teachinglearning experiences and thereby enhance them
Overview of interactions and time spent on learning task In LAViEW, the learning analytics dashboard, the overview of the content engagement is aggregated

Summary

Introduction

Background and motivationLearning analytics as a domain has evolved over the last decade to apply various computational techniques to collect, analyze, and understand data related to teachinglearning experiences and thereby enhance them. Tools like AcaWriter (Knight et al, 2020) have implemented LA techniques to support both students to provide feedback and teachers to assess critical writing assignments across various disciplines such as law, pharmacy, and accounting. In this pilot attempt, we focus on a humanities course with critical reading as the activity. It can potentially help to inform teachers to design learning activities to support their students and system developers to create technology assistance to orchestrate those activities In such an authentic natural learning setting, we investigate the following two research questions: 1. In such an authentic natural learning setting, we investigate the following two research questions: 1. What are the reading behaviors of the learners given the critical reading task in terms of interactions within the content and the time spent on that task?

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Conclusion