Computational Thinking-Based Metacognitive Learning Assessment: Issues and Challenges
DOI:
https://doi.org/10.20961/ijolii.v3i2.2991Keywords:
computational thinking, learning assessment, learning management system, metacognition, metacognitive scaffoldingAbstract
Metacognition is identified as the awareness and control of thinking for learning, which plays a crucial role in students' problem-solving performance. This urgency is further accentuated in the context of computational thinking, as practicing computational thinking through programming relies on problem-solvers' metacognition. However, the reality is that CT assessment is still in its infancy, particularly for formative assessment, and metacognitive strategies are often not explicitly taught. This study aims to identify critical issues and formulate further research challenges in CT-based metacognitive learning assessment. The method used is a systematic literature review to identify, evaluate, and synthesize all relevant scientific evidence. Four main issues were identified, including the need for rigorous experimental methods to validate CT assessments, Conceptual gaps regarding whether and how CT can support the development of metacognitive strategies, Challenges in implementing more nuanced scaffolding and limited intervention duration, even though improving metacognition requires long-term learning interventions. Furthermore, there are challenges in optimizing learning management systems as metacognitive tools. Metacognitive assessments should explicitly measure cognitive regulation (planning, monitoring, and evaluation) using authentic methods, such as think-aloud. This study's contribution is to provide a structured roadmap for further research, focusing on strengthening validity, clarifying causal relationships, and optimizing digital implementations to foster students' higher-order problem-solving skills.
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