LAUSR

Multiple-choice questions (MCQs) have been considerably used for assessing the individual’s performance in various contexts. The optimal number of options in MCQs is a debatable issue, followed by contradictions and discussions, and is needed for a firm conclusion from empirical and hypothetical findings. This study aims to link theoretical concepts, including challenge-based gamification, zone of proximal development, and prospect theory, and generate insight into educational assessment using motion-in-mind measures. Classical test theory was used to determine reliability and validity. Variations of MCQs experimented: the number of options, settings, and scoring methods. The experimental data was gathered from human and AI simulations and measured using motion-in-mind. It was found that increasing the number of options in the MCQ makes the test more challenging, explaining an increase of mass in mind $m$ . The findings also revealed that time pressure provides competitiveness while scaffolding provides support. In addition, the hybrid system demonstrates the balance of education and entertainment. Finally, the results addressed the general discussion and analogical interpretation in the education context based on physics-in-mind values. These findings can be promising for analyzing the balance between competitiveness and entertainment while enabling the learning process in the practical assessment.