Automated evaluation system improves student feedback and teaching effectiveness, suggesting shifts from final exams.
Traditional exam-oriented evaluation systems often fail to provide continuous insight into student learning. This paper presents an Automated Evaluation System (AES) that generates topic-aligned quizzes based on teacher schedules, collects student feedback, and analyzes it to evaluate both student progress and teaching effectiveness. Using AI-based quiz generation, flashcards, and feedback analysis, the system enables a holistic assessment approach, reducing reliance on final exams. The paper outlines the system’s architecture, technologies used, design methodology, and results of preliminary testing
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