A Mixed-Methods Investigation of University-Level Computer Science Education Transformations: Integrating LLMs and ChatGPT-Enhanced Automated Programming Assessments

Introduction: This study reviews how large language models influence curricular design, teaching approaches, and assessment strategies in computer science education while incorporating ChatGPT in automated programming assessments.

Methodology:

• Systematic Literature Review: Compile and analyze articles on curricular adaptations and ethical considerations.
• Comparative Empirical Analysis: Assess student performance metrics before and after ChatGPT integration.
• Integration of Findings: Combine literature insights with empirical data to derive actionable recommendations.

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