Understanding Peer Feedback Contributions Using Natural Language Processing
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Dokumenter
- Understanding Peer Feedback
Forlagets udgivne version, 272 KB, PDF-dokument
Peer feedback has been widely used in computer-supported collaborative learning (CSCL) setting to improve students’ engagement with massive courses. Although the peer feedback process increases students’ self-regulatory practice, metacognition, and academic achievement, instructors need to go through large amounts of feedback text data which is much more time-consuming. To address this challenge, the present study proposes an automated content analysis approach to identify relevant categories in peer feedback based on traditional and sequence-based classifiers using TF-IDF and content-independent features. We use a data set from an extensive course (N = 231 students) in the setting of engineering higher education. In particular, a total of 2,444 peer feedback messages were analyzed. The CRF classification model based on the TF-IDF features achieved the best performance. The results illustrate that the ability to scale up the automatic analysis of peer feedback provides new opportunities for student-improved learning and improved teacher support in higher education at scale.
Originalsprog | Engelsk |
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Titel | Responsive and Sustainable Educational Futures - 18th European Conference on Technology Enhanced Learning, EC-TEL 2023, Proceedings |
Redaktører | Olga Viberg, Ioana Jivet, Pedro J. Muñoz-Merino, Maria Perifanou, Tina Papathoma |
Antal sider | 16 |
Forlag | Springer |
Publikationsdato | 2023 |
Sider | 399-414 |
ISBN (Trykt) | 9783031426810 |
DOI | |
Status | Udgivet - 2023 |
Begivenhed | Proceedings of the 18th European Conference on Technology Enhanced Learning, ECTEL 2023 - Aveiro, Portugal Varighed: 4 sep. 2023 → 8 sep. 2023 |
Konference
Konference | Proceedings of the 18th European Conference on Technology Enhanced Learning, ECTEL 2023 |
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Land | Portugal |
By | Aveiro |
Periode | 04/09/2023 → 08/09/2023 |
Navn | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Vol/bind | 14200 LNCS |
ISSN | 0302-9743 |
Bibliografisk note
Publisher Copyright:
© 2023, The Author(s).
ID: 390400320