Bridging Theory and Practice:: The Impact of Computer-Assisted Learning and Metacognitive Skills on Algorithm Design Performance in African Students

This study investigates the effectiveness of Computer-Assisted Learning and the development of metacognitive skills in improving the performance of senior secondary school students in algorithm design across Africa. As technology becomes increasingly integrated into education, CAL provides new ways of learning that can significantly enhance the ability of students to understand and apply complex concepts such as algorithms. This study uses a mixed-methods design, where student performance is quantitatively measured and complemented by educator and student insights qualitatively. The findings reveal that CAL not only enables deeper understanding of the algorithmic principles but also provides metacognitive awareness for self-regulation of the learning process. The implications are that the integration of CAL with metacognitive strategies will have better learning outcomes and eventually equip students for future challenges in the disciplines of computer science and related areas.