The Development of RBL-STEAM Learning Materials to Enhance Undergraduate Students' Computational Thinking Skills in Solving Zakat Distribution Problems Using Local Irregular Labeling

This study aims to develop and validate Research-Based Learning (RBL) instructional materials integrated with the Science, Technology, Engineering, Arts, and Mathematics (STEAM) framework that are valid, practical, and effective in enhancing undergraduate students’ computational thinking skills. The instructional materials address the optimization of zakat distribution through blockchain technology, grounded in the concept of local distance irregular labeling. This research adopted a Research and Development (R&D) methodology using the 4D model. The participants consisted of undergraduate students enrolled in the Mathematics Education program at Nurul Jadid University. Research instruments included expert validation sheets, student response questionnaires, and a computational thinking skills test encompassing the indicators of decomposition, pattern recognition, abstraction, and algorithmic thinking. The findings indicate that the developed instructional materials satisfy the criteria of validity, as evidenced by expert judgment; practicality, based on implementation observations and student responses; and effectiveness, demonstrated by a statistically significant improvement in students’ computational thinking skills following the implementation of the learning intervention. The integration of Islamic philanthropy (zakat) with emerging technologies and graph-theoretical concepts within these instructional materials provides meaningful learning experiences while strengthening students’ capacity to solve complex problems in the digital era.