A4 Refereed article in a conference publication

International Online Team-Based Learning in Higher Education of Biomedicine - Evaluation by Learning Analytics




AuthorsMairinoja Laura, López-Pernas Sonsoles, Elmoazen Ramy, Niskanen Einari A., Kuningas Tiina, Wärri Anni, Saqr Mohammed, Strauss Leena

EditorsRamy Elmoazen, Sonsoles López-Pernas, Kamila Misiejuk, Mohammad Khalil, Barbara Wasson, Mohammed Saqr

Conference nameTechnology-Enhanced Learning in Laboratories Workshop

PublisherCEUR-WS

Publication year2023

JournalCEUR Workshop Proceedings

Book title Proceedings of the Technology-Enhanced Learning in Laboratories workshop (TELL 2023), April 27, 2023, Online

Journal name in sourceCEUR Workshop Proceedings

Series titleCEUR Workshop Proceedings

Volume3393

First page 49

Last page60

eISSN1613-0073

Web address https://ceur-ws.org/Vol-3393/

Self-archived copy’s web addresshttps://research.utu.fi/converis/portal/detail/Publication/179845309


Abstract

Teamwork skills are important to practice during higher educational studies to prepare students for the future working life. Since online learning has established itself as a relevant part of higher education, we present here an approach to online team-based learning and show the performance of students during the teamwork, proven by learning analysis data. In addition, results from a feedback survey of students´ opinions on teamwork are presented. Online teamwork was implemented for master level biomedicine students from four different Universities in Nordic countries, and student interaction was evaluated. Learning analytics data were collected from Discord, which was the communication platform for students and teachers during the teamwork. The Community of Inquiry (CoI) framework was used as guidance, and indicators of CoI's social, cognitive, and teaching presences were used as a scheme for coding the interaction. To recognize the process of collaboration, the data were first analyzed by using process mining. Further, to understand the multidimensional property of collaboration, we developed a network analysis and visualized the results using Gephi and the Fruchterman-Reingold layout algorithm. The quantitative results of the feedback survey were analyzed by using descriptive statistics and visualized using the R package likert. The learning analytics data included 316 posts divided to 686 annotations, which were categorized to codes. Our results indicate that the most frequent codes were the ones related to the social dimension of CoI, determined with attributes such as ‘interactive’ (173), ‘cohesion’ (119) and ‘affective’ (116). The remaining most frequent codes alternated between ‘facilitation’ and ‘cognition’. Thus, social presence, in the context of CoI was considerable in our online team-based learning approach. However, to enhance students' cognitive presence, and thereby their ability to construct and confirm meaning of what they are learning, students' work should be facilitated by increasing teaching presence through teacher’s contribution online. In line with the learning analytics data, the results of the survey pointed out the need of more in-depth instructions on how to carry out the team exercises, which belongs to the teaching presence category in the frame of CoI. Based on the results of this study and the existing literature, we aim to improve our teambased learning approach and outcomes in the future by increasing students’ contribution through regular feedback assignments during the work and encouraging learners to reflect on their own work, contribution and thinking.


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Last updated on 2024-26-11 at 21:56