Development of a Logical Algorithm-Based Game on Roblox for Training Problem Solving Using the ADDIE Model
DOI:
https://doi.org/10.21460/jutei.2026.102.538Keywords:
Educational Game, Logical Algorithm, ADDIE Model, Roblox Studio, Problem SolvingAbstract
Problem-solving ability is an essential skill for university students, yet interactive three-dimensional media for practising it remain limited. This study develops Nalar.exe, an educational puzzle game built with Roblox Studio and the Lua programming language, to train problem solving through three logical algorithm concepts: sequential logic, pattern recognition, and conditional logic. The game was developed using the Research and Development approach with the ADDIE model and consists of 10 levels arranged in three phases. It was evaluated through black-box testing, expert validation, the System Usability Scale (SUS), and a pre-test–post-test design. All 10 levels functioned as designed (100%). The logical algorithm expert and the game design expert gave feasibility scores of 76.67% and 75.00%, respectively. The average SUS score from 15 respondents was 72.17, above the benchmark of 68 and categorised as good. In the pre-test–post-test with 10 students, five participants already obtained the maximum pre-test score, a ceiling effect that prevented measuring their gain. Recalculated following Hake, the class-average N-Gain is 0.33 and the mean individual N-Gain of the five computable respondents is 0.40, both in the medium category. Because the estimate rests on few respondents with room to improve, it is only an initial indication and cannot be taken as proof of effectiveness. A more challenging instrument, a larger sample, and a control group are needed in further research.
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