Effects on the learning achievement, approaches to learning, and multi-stage reflection quality of students with different levels of digital self-efficacy in a data literacy course: An ARCS-based self-reflective online learning model

Abstract

Data literacy has become a critical core competency for university students. Research has indicated that in digital environments, learners' digital self-efficacy (DSE) not only influences their learning motivation but is also closely linked to their learning outcomes. Additionally, self-reflection could help students evaluate their learning process and deepen their understanding of the content. However, without appropriate instructional scaffolding, self-reflection may become a mere formality, failing to effectively enhance both the depth and quality of their reflection, as well as their learning motivation. Therefore, this study proposed an ARCS (Attention, Relevance, Confidence, and Satisfaction)-based self-reflective online learning model and integrated it into a 12-week data literacy course, with the intervention implemented over a 10-week period (Weeks 2–11). The aim was to explore data literacy achievement and approaches to learning in data literacy (ALDL) among university students with different levels of DSE, and the quality of self-reflection at different stages. Participants were 52 first-year university students, including 27 males and 25 females. Results showed that the proposed model effectively fostered a positive motivation cycle among students. While students with high DSE (HDSE) outperformed those with low DSE (LDSE) in terms of data literacy achievement and ALDL, the majority of students began their reflective process with technical reflection (88.46 %). To further explore the model's influence on self-reflection, Epistemic Network Analysis (ENA) 3D was employed to analyze the coded results of students' reflective diaries. The findings indicated that the model effectively promoted multidimensional self-reflection, broadened and deepened reflective focus across both LDSE and HDSE groups, and reduced the quality gap in self-reflection between the two groups. Additionally, the LDSE group enhanced practical application and critical thinking through conceptual understanding, relying on hands-on experience to construct knowledge. In contrast, the HDSE group focused on deep reflection through logical explanation, self-validation, and critical thinking.