Search for: All records

The increasing use of AI systems opens up opportunities to use learner and teacher-related data for reflection, supporting instruction and professional growth. However, teacher-related data is rarely collected in technology-enhanced learning environments. Understanding teacher preferences can inform the design of AI reflection systems that align with their priorities. The current survey study explores how K-12 teachers' reflection practices and preferences for analytic data types (e.g., learning-related vs. engagement-related) vary by experience, an aspect often overlooked in prior works. Findings from our survey study with N=100 teachers in the U.S. revealed significant differences. Less experienced teachers focus on classroom behavior and prefer analytics on classroom issues, while experienced teachers prefer broader strategies to improve student learning and favor sustained data analysis. Our results reflect the need to consider teachers’ experience level by tuning the complexity and concreteness of analytic recommendations to support ongoing professionalization. 

Teacher reflection is essential for K-12 classrooms, including effective and personalized instruction. Multimodal Learning Analytics (MMLA), integrating data from digital and physical learning environments, could support teacher reflection. Classroom data collected from sensors and TEL environments are needed to produce such analytics. These novel data collection methods pose an open challenge of how MMLA research practices can ensure alignment with teachers’ needs and concerns. This study explores K-12 teachers’ perceptions and preferences regarding MMLA analytics and data sharing. Through a mixed-method survey, we explore teachers’ (N=100) preferences for analytics that help them reflect on their teaching practices, their favored data collection modalities, and data-sharing preferences. Results indicate that teachers were most interested in student learning analytics and their interactions and ways of motivating students. However, they were also significantly less accepting of collecting students’ audio and position data compared to such data about themselves. Finally, teachers were less willing to share data about themselves than their students. Our findings contribute ethical, practical, and pedagogical considerations of MMLA analytics for teacher reflection, informing the research practices and development of MMLA within TEL.