A DATA-DRIVEN APPROACH TO FLIPPED LEARNING FOR DIFFERENTIATED INSTRUCTION IN ELECTRONIC ENGINEERING

This paper documents an evaluation of a project that aimed to use a technology platform in a flipped learning format that generates student performance data to provide a differentiated learning environment. This project was focused on enhancing key aspects of the student learning experience, especially in relation to CDIO Standards 8: Active Learning and 11: Learning Assessment. The technology employed the Brightspace Learning Management System, especially the learning analytics features, to extract, collate, and present key performance data on online assessment in preparation for focused feedback and differentiated instructional activities in the face-to-face sessions. The scope of the implementation at the School of Electrical & Electronic Engineering (EEE) at Singapore Polytechnic (SP) involved 36 classes, 20 lecturers and 648 students. The methodology followed a broad Action Research approach that sought to understand how the initiative impacted the students learning experience, as well as how teaching faculty dealt with the challenges of the instructional approaches employed. The evaluation findings showed positive results on the use of the selected active learning methods (e.g., challenging questions, peer instruction, and differentiated learning activities). The design and use of the active learning methods reflected the integration of subject content with key critical thinking skills (e.g., analysis, evaluation) about the concepts the students were learning and their application in real work contexts. The importance of providing focused and timely feedback for enhancing student understanding was also supported in the data obtained. Future research will seek to incorporate emerging generative Artificial Intelligence (AI) tools that can further enhance SP’s goal towards providing a holistic education underpinned by the CDIO framework.