Exploring the potential of student-facing learning analytics for formative assessment and feedback in engineering education
Dr. Dai Yun, Department of Curriculum and Instruction, Chinese University of Hong Kong
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Student-facing learning analytics (SFLA) is the learning analytics tools specifically designed for and used by students. SFLA usually tracks and analyzes students’ online behaviors, and reports the analytics outcomes back to students via dashboards, notifications, and/or recommendations. Considering its direct and interactive contact with students, SFLA has shown great potential as a formative assessment tool. That is, it can facilitate teachers’ in-process evaluation of student comprehension and academic progress and provide students with personalized feedback to inform their further improvement. In this seminar, I will present preliminary research on developing an SFLA-enhanced instructional approach to facilitating the formative assessment and feedback. Through a systematic review, I have evaluated the cutting-edge SFLA tools against the criteria of good formative assessment practices and identify the gaps in practice. Guided by the socio-cultural and socio-cognitive perspectives, I have developed a design framework with a set of principles for future design and development of SFLA tools.
Dr. DAI Yun is an assistant professor from the Department of Curriculum and Instruction at the Chinese University of Hong Kong (CUHK). Before joining the CUHK, she served as Postdoc Fellow on engineering education and the manager of the Viterbi iPodia Educational Program, at the University of Southern California, USA. She earned her Ph.D. degree in education at the University of California, Santa Barbara. Her research broadly examines how to use digital technologies and resources to enhance the teaching and learning practices and processes in engineering education and other subject-specific settings. Her work has been published in top-tier journals in learning sciences and technology.