Abstract: Self-regulated learning is a central skill for students and beyond formal education. Empirical investigations have found that metacognitive prompts can support self-regulated learning and increase learning outcomes. However, the self-regulated learning process itself remains opaque. Educational process mining techniques offer a developing approach to investigate learning processes more deeply. In this study, we investigated the self-regulated learning processes of supported and unsupported learners. Learners with (n = 28) and without (n = 29) metacognitive prompts studied in a hypermedia learning environment while thinking aloud. The think aloud protocols were coded for self-regulation events, constituting the data used for process mining. While the learners with prompts showed more metacognitive events during the learning process, the process models for both conditions were similar. The analysis reveals the insights that process models can provide. However, since process-mining methods are newly applied in educational research, more research is needed to understand their explanatory power.

Engelmann, K., & Bannert, M. (2019). Analyzing temporal data for understanding the learning process induced by metacognitive prompts. Learning and Instruction. https://doi.org/10.1016/j.learninstruc.2019.05.002