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Prior research has found that teacher reflection is important for both teachers’ professional development and students’ learning, but frequent, effective reflection faces many obstacles. Could an analytics-based reflection tool help address these barriers? Reflecto is a novel teacher-facing tool designed to support teachers in reflecting (after-the-fact) on their classroom practices during sessions when students are engaged with intelligent tutoring systems. Whereas many teacher analytics tools support real-time decision-making in class, Reflecto aims to promote teacher agency through out-of-class teacher-initiated, data-driven exploration of possible trends in their classroom practice. Unlike many other analytics tools, it combines learning analytics and teaching analytics. 

Snow Water Equivalent dataset contains information about snow water equivalent (SWE), temperature, precipitation, wind speed, relative humidity, and related climate variables across different locations and time periods. It includes daily observations and derived variables for hydrological and climate analysis. An additional column, source, specifies the origin of each data column. 

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.