SYNERGIES OF DATA-DRIVEN LEARNING ANALYTICS AND THE TRANSFORMATION OF STUDENT LEARNING: THE MISSING PIECE OF THE PUZZLE IN A CASE STUDY
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Chrispen Chiome
This mixed-methods study examined the missing piece of the puzzle in transforming student learning through data-driven learning analytics. It is a case study of an open, distance, and e-learning institution in Zimbabwe. The research was a mixed methods study that used open, distance, and e-learning institution as a case study. Data was collected from the analytics generated by the learning management platform, and this was supplemented by interviews with the teaching Faculty. The results show that while learning analytics provide data visualizations on engagement and performance in this institution, there are still many missing pieces of the puzzle that prevent this institution from fully utilizing learning analytics. The results show that this institution is a long way off in building on how data intersects with human decisions, optimal use of resources to achieve learning outcomes, improvement in data infrastructure, recommendations arising from data analytics, using data analysis to adjust or enhance student learning, use of predictive and prescriptive analytics, monitoring student course activity in real-time, using personal data tracking to support learning, among others. The research concludes that learning analytics improve teaching and learning through the quality of teaching, quality of monitoring, quality of feedback, and quality of data-driven decision-making among others. The institution under study is still grappling with the missing piece of the puzzle to tap into the extensive learning data to transform student learning. These areas are discussed in this paper.
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