<![CDATA[In modern education, enhancing interactivity and learning effectiveness is a crucial aspect. This study aims to develop and evaluate a web-based quiz system that integrates hand gesture recognition technology using OpenCV to increase student engagement and participation. To ensure that the system is developed adaptively and responsively to user needs, this research implements the Extreme Programming (XP) methodology, known for its fast and iterative development cycle. A quantitative approach is used in this study by conducting trials with students from class A ITG, where pre-tests and post-tests are conducted to evaluate interactivity levels, responsiveness to hand gestures, and overall user satisfaction. Usability measurement is performed using the System Usability Scale (SUS), with evaluation results showing an increase in SUS scores from pre-test to post-test. These results indicate that the developed system is capable of significantly improving the student learning experience. However, this study has several limitations, such as the need for optimization of gesture recognition algorithms to improve the system's accuracy and responsiveness. Additionally, the study was only conducted on one group of students, limiting the generalizability of the results. Therefore, future research is expected to include a broader population and explore the integration of additional technologies to enhance system effectiveness in various learning contexts. This study demonstrates that the use of hand gesture recognition technology in a web-based quiz system can create a more dynamic and interactive learning environment. These findings open opportunities for the development of more innovative, adaptive, and responsive educational applications to meet the needs of today’s digital generation.]]>
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