Influence and Negotiation in Co-Designing an AI-Enhanced Multimodal Learning Analytics Platform for Secondary STEM Classrooms

Hakeoung Hannah Lee, Hyun G. Kwon, Jongheon Kim, JeeHun Sung, Jandi Choi, Hyeri Mel Yang, Chaeyeon Kim, Miguel E. Lujan
Proceedings of the Impactful and Responsible AI Systems for Education Workshop, PMLR 339:70-79, 2026.

Abstract

This study examines how a transdisciplinary team experienced the co-design of an AI-enhanced Multimodal Learning Analytics platform for collaborative secondary Science, Technology, Engineering, and Mathematics classrooms. While artificial intelligence and learning analytics systems are often framed in terms of efficiency and personalization, far less is understood about how such systems are collaboratively designed across stakeholders. Drawing on sociocultural theory and participatory design, this study analyzes in-depth semi-structured interviews with four members of a co-design team engaged in a year-long, online collaboration. Using interpretative phenomenological analysis and theory-informed social network analysis, we examine both participants’ lived experiences and patterns of influence shaping the co-design process. Findings show that co-design unfolded as a negotiated process across personal, interpersonal, and community planes. Educator expertise anchored problem definition and guided development, while roles and authority emerged through interaction. Care and trust sustained collaboration, and participation became a site of adult learning and identity work. Network analysis reveals a dense and reciprocal ecology of influence extending beyond the team. This study reframes co-design not as a procedural step for feedback incorporation, but as a relational process through which educational futures with AI are collectively imagined.

Cite this Paper

BibTeX
@InProceedings{pmlr-v339-lee26a, title = {Influence and Negotiation in Co-Designing an AI-Enhanced Multimodal Learning Analytics Platform for Secondary STEM Classrooms}, author = {Lee, Hakeoung Hannah and Kwon, Hyun G. and Kim, Jongheon and Sung, JeeHun and Choi, Jandi and Yang, Hyeri Mel and Kim, Chaeyeon and Lujan, Miguel E.}, booktitle = {Proceedings of the Impactful and Responsible AI Systems for Education Workshop}, pages = {70--79}, year = {2026}, editor = {Basu Mallick, Debshila and Woodhead, Simon and Wang, Zichao and Ananda, Muktha and Burstein, Jill and Murphy, April}, volume = {339}, series = {Proceedings of Machine Learning Research}, month = {28 Jun}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/v339/main/assets/lee26a/lee26a.pdf}, url = {https://proceedings.mlr.press/v339/lee26a.html}, abstract = {This study examines how a transdisciplinary team experienced the co-design of an AI-enhanced Multimodal Learning Analytics platform for collaborative secondary Science, Technology, Engineering, and Mathematics classrooms. While artificial intelligence and learning analytics systems are often framed in terms of efficiency and personalization, far less is understood about how such systems are collaboratively designed across stakeholders. Drawing on sociocultural theory and participatory design, this study analyzes in-depth semi-structured interviews with four members of a co-design team engaged in a year-long, online collaboration. Using interpretative phenomenological analysis and theory-informed social network analysis, we examine both participants’ lived experiences and patterns of influence shaping the co-design process. Findings show that co-design unfolded as a negotiated process across personal, interpersonal, and community planes. Educator expertise anchored problem definition and guided development, while roles and authority emerged through interaction. Care and trust sustained collaboration, and participation became a site of adult learning and identity work. Network analysis reveals a dense and reciprocal ecology of influence extending beyond the team. This study reframes co-design not as a procedural step for feedback incorporation, but as a relational process through which educational futures with AI are collectively imagined.} }
Endnote
%0 Conference Paper %T Influence and Negotiation in Co-Designing an AI-Enhanced Multimodal Learning Analytics Platform for Secondary STEM Classrooms %A Hakeoung Hannah Lee %A Hyun G. Kwon %A Jongheon Kim %A JeeHun Sung %A Jandi Choi %A Hyeri Mel Yang %A Chaeyeon Kim %A Miguel E. Lujan %B Proceedings of the Impactful and Responsible AI Systems for Education Workshop %C Proceedings of Machine Learning Research %D 2026 %E Debshila Basu Mallick %E Simon Woodhead %E Zichao Wang %E Muktha Ananda %E Jill Burstein %E April Murphy %F pmlr-v339-lee26a %I PMLR %P 70--79 %U https://proceedings.mlr.press/v339/lee26a.html %V 339 %X This study examines how a transdisciplinary team experienced the co-design of an AI-enhanced Multimodal Learning Analytics platform for collaborative secondary Science, Technology, Engineering, and Mathematics classrooms. While artificial intelligence and learning analytics systems are often framed in terms of efficiency and personalization, far less is understood about how such systems are collaboratively designed across stakeholders. Drawing on sociocultural theory and participatory design, this study analyzes in-depth semi-structured interviews with four members of a co-design team engaged in a year-long, online collaboration. Using interpretative phenomenological analysis and theory-informed social network analysis, we examine both participants’ lived experiences and patterns of influence shaping the co-design process. Findings show that co-design unfolded as a negotiated process across personal, interpersonal, and community planes. Educator expertise anchored problem definition and guided development, while roles and authority emerged through interaction. Care and trust sustained collaboration, and participation became a site of adult learning and identity work. Network analysis reveals a dense and reciprocal ecology of influence extending beyond the team. This study reframes co-design not as a procedural step for feedback incorporation, but as a relational process through which educational futures with AI are collectively imagined.
APA
Lee, H.H., Kwon, H.G., Kim, J., Sung, J., Choi, J., Yang, H.M., Kim, C. & Lujan, M.E.. (2026). Influence and Negotiation in Co-Designing an AI-Enhanced Multimodal Learning Analytics Platform for Secondary STEM Classrooms. Proceedings of the Impactful and Responsible AI Systems for Education Workshop, in Proceedings of Machine Learning Research 339:70-79 Available from https://proceedings.mlr.press/v339/lee26a.html.

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