Assessment Analytics: Feedback, Feedup, Feedforward on Bayesian Network

Assessments play a crucial role in supporting the learning process by providing learners with formative feedback on their current performance and suggestions for improvement. This chapter focuses on the utilization of assessment analytics to strengthen the dimensions of feedback, feedup, and feedforward. The aim is to complement the value of feedback in practice by integrating learning analytics. In the context of learning analytics, a holistic feedback design is explored, particularly concerning the underdeveloped area of feedforward research. Additionally, using data in assessment processes is emphasized for effective learning analytics. This research endeavours to establish assessment analytics at four levels, mirroring learning analytics: (1) descriptive assessment analytics, (2) predictive assessment analytics, (3) prescriptive assessment analytics, and (4) diagnostic assessment analytics. A dashboard is developed to link each analytics level with three feedback types based on Bayesian network. The study has also bridge assessment analytics and learning analytics at the prescriptive analytics.