<![CDATA[Accurate profiling of students’ computational thinking (CT) is important, yet conventional assessments provide limited insight into CT as a dynamic problem-solving process. This study examined how stealth assessment embedded within Temple Zone VR, an Ethno-STEM virtual reality game designed around Majapahit cultural heritage, could be used to profile the CT of junior high school students across four pillars: Decomposition, Pattern Recognition, Abstraction, and Algorithmic Design. Each game room was designed using Evidence-Centered Design (ECD) so that students’ puzzle-solving actions generated behavioural log data as evidence of CT processes. The game was developed using the ADDIE model, and a paper-based CT cognitive test was administered as a pretest and posttest to 60 junior high school students. Content validity of the paper-based test was supported by Aiken’s V coefficients ranging from 0.83 to 1.00. Hierarchical cluster analysis identified three CT profiles: High CT (13.3%), Moderate CT (71.7%), and Developing CT (15.0%). Sequential pattern mining identified three problem-solving strategy types: systematic decomposition (46.7%), iterative trial (38.3%), and exploratory (15.0%), with different distributions across the CT profile groups. Overall, the findings suggest that gameplay log data can provide complementary behavioural evidence for profiling CT, while the observed strategy–profile associations should be interpreted cautiously.]]>
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