Abstract:

Adaptive learning as an instructional method differs from traditional teaching methods through utilization of technology to enhance the learning process, especially for the younger generation. In science education, adaptive learning technologies are noteworthy as they enable flexible, personalized and conceptually rich learning experiences. One of the core advantages is its ability to deliver personalized learning paths that adapt in real-time to each student’s performance, needs, and pace. This is particularly helpful in science, where learners often have varying levels of prior knowledge in subjects like chemistry, biology, and physics. As such, to examine the key design principles and implementation strategies for adaptive learning environments in science education, we conducted a systematic literature review spanning from 2010 to 2024. Using 29 search terms, three databases (EBSCOhost, Web of Science and Scopus) were searched for empirical, peer-reviewed studies. The PRISMA framework was adapted, and 14 studies which met our inclusion criteria were identified. The adaptive teaching model provided the foundation for our analysis, emphasizing a clear three-step continuous adaptive cycle that includes: noticing student cues, reflecting on their needs, and responding with instructional adjustments. Findings of this study revealed that the different adaptive systems such as the intelligent tutoring systems, adaptive simulations, and rule-based platforms enable personalized and data-driven learning by adjusting instruction to individual learner needs. By offering real-time feedback, ongoing assessment, and instructional scaffolding, these technologies enhance learners’ conceptual understanding in science. However, their successful implementation is shaped by various contextual conditions. In this regard, most adaptive platforms are designed for Western contexts, highlighting the need for locally developed tools aligned with African contexts and curricula. In the African context where there are large and diverse classrooms, these systems can help teachers track learner progress and identify learning gaps in real-time.

Keywords:

Adaptive Learning Environments, Science Education, Instructional Design.