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

Strategy · All strategies
Evidence · no claims cited

Description¶

Based on the identified gaps, the review recommends that "researchers must prioritize ethical guidelines and ensure transparency in their data handling practices, including how the data is managed, stored, and accessed." It also proposes that making sense of multimodal data requires "a collaboration between researchers with strong computational experience and learning and cognition, as well as educators." Journals should encourage open science practices, and future work should integrate theory more comprehensively and conduct studies in authentic classroom settings.

Design Implications¶

Context¶

Requirements¶

• Intentional design in selecting and integrating modes of interaction that capture student learning processes
• Shared understanding of the data fusion process and reporting guidelines

Constraints¶

• Transitioning MMLA from laboratory to real classrooms introduces data quality and technological challenges, including noise, hardware malfunctions, ethics, and transparency

Target Learners¶

• K–8 students

Target Learning Goals¶

• improving learning outcomes and learning experience design through multimodal analytics

Affordances¶

Related Strategies¶

• Design MMLA deployments with fair data representation, multilevel data access, cultivated transparency, and continuous measurable informed consent
• Ground AI integration in higher education on core principles of human agency, academic freedom, transparency, ethics, inclusivity, and critical thinking

Examples¶

-

Key Sources¶

• Caskurlu, S., Ocak, C., & Dai, C.-P. (2025). The Scope of Multimodal Learning Analytics in K–8: A Systematic Review. Journal of Learning Analytics, 12(2), 224–236. https://doi.org/10.18608/jla.2025.8505