This systematic review synthesises multidisciplinary research to evaluate the determinants of long-term Knowledge, Skills, Values, and Attitudes (KSVA) retention within higher education. By examining the synergy between cognitive learning theories and emerging technologies, the paper identifies evidence-based strategies such as spaced repetition, retrieval practice, and AI-driven adaptive learning as primary catalysts for enhancing knowledge durability and learner motivation. The analysis further investigates the interplay of cognitive load principles and technological mediation, noting that while adaptive instructional designs outperform traditional methods, their efficacy is often moderated by learner characteristics and digital access. Furthermore, the review identifies significant institutional barriers, including curriculum rigidity, resource disparities, and resistance to pedagogical reform, which impede the transition from short-term assessment-focused teaching to durable, retention-based models. The study concludes that optimizing long-term learning outcomes requires a holistic framework that integrates cognitive science, inclusive technological innovation, and supportive institutional policies.

Keywords

Engineering Education, Knowledge Sharing, Learning, Knowledge Retention, Skills Development, Higher Education, Educational Measurement