Title: Tutorial experience during online learning: a topic modelling approach

Authors: Chioma Okoro; Peter Baur; Oliver Takawira

Addresses: Department of Finance and Investment Management, College of Business and Economics, University of Johannesburg, South Africa ' School of Economics, College of Business and Economics, University of Johannesburg, South Africa ' Department of Finance and Investment Management, College of Business and Economics, University of Johannesburg, South Africa

Abstract: The role of tutoring in teaching and learning cannot be overemphasised. However, limited studies exist on tutors' strategies, tools, and techniques to assist in their role as teaching assistants. This study aimed to identify the strategies, tools, techniques, and challenges encountered during online tutoring during the lockdown periods necessitated by the COVID-19 pandemic. The study employed a quantitative approach to collect data among tutors within a faculty in a higher education institution. Short-text data were analysed to output themes using topic modelling in supervised machine learning. Findings indicated that technology and tutors were helpful and appreciated during the period under investigation. The challenges were primarily technical and social. Similarities between students' and tutors' perceptions were noted. The study's findings are beneficial to higher education policymakers and authorities to better support tutors going forward. This is especially important as universities gradually reopen contact learning with blended/online approaches.

Keywords: tutoring; students' performance; higher education; topic modelling; sentiment analysis.

DOI: 10.1504/IJIL.2023.131211

International Journal of Innovation and Learning, 2023 Vol.33 No.4, pp.458 - 488

Received: 01 Feb 2022
Accepted: 11 Apr 2022
Published online: 01 Jun 2023 *

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