Learning Analytics (LA) holds significant potential to enhance self-regulated learning in higher education. However, its effectiveness depends not only on technical infrastructure but also on pedagogical integration and learner acceptance. This study investigates changes in students’ acceptance of LA dashboards over the course of a semester and explores whether individual motivational and self-regulatory characteristics influence these changes. The study was conducted in hybrid STEM courses using the Excalibur plugin within Moodle. Survey data were collected at the beginning and end of the semester, drawing on constructs from the Technology Acceptance Model (TAM) and the Motivated Strategies for Learning Questionnaire (MSLQ). Contrary to expectations, no significant increase in acceptance was observed; perceived usefulness and Intention to Use even declined slightly over time. Moreover, none of the hypothesized correlations between learner characteristics and post-semester acceptance or acceptance change reached statistical significance. These findings highlight the limitations of LA interventions that are not meaningfully embedded into course structures or aligned with instructional goals. The study underscores the need for learner-centered implementation strategies that foster motivation, reflection, and self-regulation, and offers critical insights for future LA design and integration in higher education contexts.