OPTIMIZING LEARNING OUTCOMES THROUGH FLIPPED CLASSROOM STRATEGIES AND GENERATIVE AI TOOLS INTEGRATION

Abstract

This learning innovation is an integration of the flipped learning method with the use of generative AI tools to improve the quality of learning. On the one hand, the flipped learning method provides an opportunity for students to study the material independently before class meetings. On the other hand, generative AI tools such as Claude.ai, Custom GPT Consensus, DeepSeek, and Gamma are used to prepare more interactive and engaging learning materials. The implementation was carried out over five (5) meetings in one of the courses, namely Inferential Statistics, involving one class of 37 students from the Management Study Program. This study used a quantitative approach with a quasi-experimental design in the form of a one-group pre-test – post-test design. The results showed a significant increase in conceptual understanding in the form of an increase in exam scores from 63.73 (mid-term exam) to 80.05 (final exam). The percentage of students who received grades A, A-, B+, B, and B- increased from 21.60% (mid-term exam) to 100% (final exam). Learning satisfaction based on learning evaluation in the Academic Information System was 3.5 / 4 (Very Good). This innovation has proven effective in overcoming the difficulties of learning complex statistics and triggering student involvement in the learning process