University Students' Perceptions of a Multimodal AI System for Real‐World Collaboration Analytics: Lessons Learned From a Case Study.
Background: Many researchers work on the design and development of multimodal collaboration support systems with AI, yet very few of these systems are mature enough to provide actionable feedback to students in real‐world settings. Therefore, a notable gap exists in the literature regarding students...
| Published in: | Journal of Computer Assisted Learning Vol. 41; no. 5; pp. 1 - 16 |
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| Main Authors: | , , |
| Format: | pictorial research tables/charts Journal Article |
| Published: |
Wiley-Blackwell
Oct2025
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=188234201&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 188234201 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02664909 6M1 jtl: Journal of Computer Assisted Learning issn: 02664909 maglogo: Y pubinfo: dt: Oct2025 vid: 41 iid: 5 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 188234201 188234201 188234201 10.1111/jcal.70103 188234201 ppf: 1 ppct: 15 formats: tig: atl: University Students' Perceptions of a Multimodal AI System for Real‐World Collaboration Analytics: Lessons Learned From a Case Study. aug: au: Suraworachet, Wannapon Zhou, Qi Cukurova, Mutlu affil: UCL Knowledge Lab, Institute of Education, University College London, London, UK sug: subj: Student Attitudes Evaluation Students, College Ethical Issues Artificial Intelligence, Generative Data Analytics Collaboration Learning Methods Computer-Assisted Instruction Accountability Human Female Male Qualitative Studies Purposive Sample Interviews Educational Technology Machine Learning Focus Groups Audiorecording Videorecording Feedback Group Processes Communication Task Performance and Analysis Interrater Reliability Thematic Analysis Funding Source Female Male ab: Background: Many researchers work on the design and development of multimodal collaboration support systems with AI, yet very few of these systems are mature enough to provide actionable feedback to students in real‐world settings. Therefore, a notable gap exists in the literature regarding students' perceptions of such systems and the feedback they generate. Objectives: This study designed, built and implemented a set of collaboration analytics to capture, interpret and provide feedback on students' collaborative processes, including their non‐verbal group interactions as well as group challenges and regulation arising from discourse in authentic collocated collaborative settings. Methods: Seven groups of five to six postgraduate students with varying backgrounds participated in face‐to‐face collaborative design tasks (n = 36) for an 11‐week‐long semester. Multimodal data from audio and video recordings of collaborative learning sessions were analysed using various machine learning techniques to model students' group processes and to generate feedback. A post hoc evaluation of the collaboration analytics feedback was conducted using individual student reflections and focus group interviews. Results and Conclusions: The findings suggest that analytics feedback has the potential to promote students' understanding of their collaborative processes (e.g., awareness of individual, peer and group behaviours and alterations at the individual level). However, the study also identified significant limitations and challenges associated with the real‐world application of collaboration analytics (e.g., limited group transactions stemmed from a lack of group interpretative sessions). The paper concludes with a discussion on future design suggestions and principles (e.g., an integration of analytics with the learning design, value alignments among stakeholders and roles of teachers). pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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