Clustering digital learning pathway preferences from the perspectives of epistemic justification on self-regulated...

The beliefs about knowledge and knowing have a decisive effect on students' digital learning. Merely using self-reported questionnaire to investigate people's epistemic justifications about digital learning is incomprehension and has its methodological limitations. Therefore, this study used an explanatory sequential design, i.e., clustering followed by content analysis and affective comparisons, to explore people's preference, epistemic justifications, and affective perceptions on digital learning pathways. First, a latent class analysis was conducted to categorise 201 survey participants based on their preferences towards seven types of digital learning pathways. Four clusters were identified. Second, we conducted thematic analysis, relational content analysis and affective analysis on sixteen participants' digital learning experiences. Based on the framework of Internet-based epistemic belief, self-regulated learning, and community of inquiry, three dimensions of digital learning justification were identified, which mutually impact on one another. Furthermore, interviewees' affective perceptions in different clusters were compared, showing different patterns regarding the three dimensions above. These differences informed digital learning designers on instructional designs, teachers' selection of digital learning tools, and policy makers on promoting professional development for digital literacy improving.