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A Framework for Developing Deeper Self-Directed Learning in Computer Science Education
Abstract
To prepare students for the challenges of the Fifth Industrial Revolution, it is essential to cultivate deeper self-directed learning (DSDL) in computer science education. The process of DSDL empowers students to take ownership of their learning, enabling them to transfer their knowledge and skills to unfamiliar contexts. The proposed DSDL framework is anchored in cognitive load theory and social constructivism and draws upon three core concepts: the organization of course content; teaching and learning methods rooted in cooperative learning; and the characteristics of tasks. The importance of structuring course content to offer an initial holistic overview of key concepts, followed by deeper cycles of revisiting and reinforcing these concepts is underscored. Teaching and learning methods, such as cooperative pair programming and cooperative pair problem solving, are recommended. Moreover, the framework advocates for the adoption of a whole-task approach, involving authentic, complex tasks that encourage students to grapple with challenges and to learn from their failures.
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