Aug 2026· e-Jurnal Penyelidikan dan Inovasi· 0 citations· 17 references
TL;DR
It is concluded that AI-powered development tools provide significant advantages in enhancing students’ coding efficiency; however, their application should be supported by well-designed teaching strategies to achieve balanced learning outcomes.
Abstract
Artificial intelligence (AI) has become an integral component of modern software development using AI-powered coding assistants, automated debugging tools, and intelligent programming environments. In higher learning institutions, students increasingly adopt the tools to support programming tasks and enhance coding performance. This study presents a narrative review of existing literature on the effects of AI-powered development tools on students’ coding efficiency in higher learning institutions. The review focuses on studies published between 2022 and 2026 and retrieved from major academic databases, including Scopus, IEEEXplore, and ScienceDirect, using predefined keywords and inclusion criteria. The selected studies were analyzed using thematic analysis to systematically identify and categorize recurring patterns across the literature, focusing on coding efficiency, learning outcomes, and challenges associated with AI-assisted programming tools. The findings indicate that AI-powered development tools significantly improve coding efficiency by increasing development speed, reducing syntax and logical errors, and enhancing debugging processes. In addition, these tools support learning by providing real-time code suggestions and improving students’ problem-solving capabilities. However, certain limitations have been identified, including overdependence on AI-generated code, reduced independent thinking, issues regarding academic integrity, and limited conceptual understanding of programming fundamentals. The study concludes that AI-powered development tools provide significant advantages in enhancing students’ coding efficiency; however, their application should be supported by well-designed teaching strategies to achieve balanced learning outcomes. Future research should examine the long-term impact of AI-assisted programming on students’ technical competence, critical thinking, and professional readiness in software development.
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A systematic literature review synthesized primary empirical studies published between 2019 and 2025 and retrieved from Scopus, Web of Science, ERIC, and Google Scholar, and argues that the value of AI tools depends less on the technology itself than on how it is pedagogically mediated.
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This study maps and synthesises Scopus-indexed research published between 2020 and 2025 and contributes an outcome-centred synthesis that connects bibliometric patterns with the methodological and pedagogical strengths of the available evidence.
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