 Tutorial experience during online learning: a topic modelling approachChioma Okoro, Peter Baur and Oliver Takawira International Journal of Innovation and Learning, 2023, vol. 33, issue 4, 458-488 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. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijilea:v:33:y:2023:i:4:p:458-488 Access Statistics for this article More articles in International Journal of Innovation and Learning from Inderscience Enterprises Ltd |
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