Learning Dynamics in Asynchronous Online Higher Education: Instructional Design, Self‐Regulated Learning Supports, and Academic Performance

Background Online learning has become a defining feature of higher education, expanding access while reshaping how students engage with knowledge, instructors, and peers. Despite its rapid growth, uncertainty persists regarding which instructional design features most effectively support academic achievement and digital competence in asynchronous, skills‐based courses. Prior studies often focus on perceptions or rely on small cross‐sectional samples, leaving limited clarity on how specific design features such as assignments, badges, and feedback influence measurable academic outcomes in asynchronous, skills‐based courses. Objectives This study examines how assignment structures, learning supports, pacing systems, and digital badges are associated with standardized academic performance in an asynchronous pre‐finance computer applications course, drawing on the community of inquiry framework (CoI) and self‐regulated learning (SRL) theory to interpret how instructional design features and regulatory processes interact to shape academic outcomes. Methods Data were collected from 742 undergraduates across six consecutive semesters in a certified asynchronous online course emphasizing Microsoft Excel proficiency. Survey responses on learning materials (e.g., SimuTraining , CapstoneProjects ) and instructional supports (e.g., WeeklyUpdates , QuizFeedback ) were matched with performance records (i.e., Points : total points earned), which were standardized using z ‐scores ( ZTP ) to ensure comparability across semesters while preserving students' relative standing within each term. A pooled regression with semester fixed effects and robust standard errors examined factors associated with performance while controlling cohort and seasonal differences. Results and Conclusions Earning a digital badge, resubmitting capstone projects, and receiving automated feedback were positively linked to performance, while valuing unlimited attempts on low‐stakes assignments and preferring end‐of‐course deadlines were negatively associated. These results reveal a disconnect between student perceptions and actual learning, suggesting that lower‐performing students may rely on repetition without mastering underlying skills. Findings underscore the importance of structured pacing, targeted feedback, and performance‐linked incentives such as badges. Collectively, this study advances technology‐enhanced education by clarifying which practices foster success and offering strategies to strengthen digital competence and learning outcomes in higher education.