Design MMLA deployments with fair data representation, multilevel data access, cultivated transparency, and continuous measurable informed consent¶

Strategy · All strategies
Evidence · no claims cited

Description¶

Based on their findings, the authors recommend that future MMLA systems ensure "accurate and comprehensive data representation to ensure visualization fairness", provide "different levels of data access to foster accountability", measure and cultivate transparency with students, and transform informed consent "from dichotomous to continuous and measurable scales". The strategy treats FATE as design requirements to be addressed during deployment, not afterthoughts.

Design Implications¶

Context¶

Requirements¶

• Co-creation of visualizations with teachers and iterative piloting, as the authors did over nine months before classroom use
• Clear communication to students of data collection, processing, and their options to withdraw

Constraints¶

• Recommendations arise from a single qualitative study of 14 students in one nursing program; the authors frame them as issues for future MMLA studies and practices to address

Target Learners¶

• students in physical, collaborative learning environments instrumented with MMLA

Target Learning Goals¶

• post-activity reflection on collaboration and communication
• trustworthy engagement with learning analytics

Affordances¶

• Fate Framework Mmla Student Centred

Related Strategies¶

• Prioritize transparency, ethical guidelines, and researcher-educator collaboration when conducting K–8 MMLA research

Examples¶

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Key Sources¶

• Jin, Y., Echeverria, V., Yan, L., Zhao, L., Alfredo, R., Tsai, Y.-S., Gašević, D., & Martinez-Maldonado, R. (2024). FATE in MMLA: A Student-Centred Exploration of Fairness, Accountability, Transparency, and Ethics in Multimodal Learning Analytics. Journal of Learning Analytics, 11(3), 6–23. https://doi.org/10.18608/jla.2024.8351