<![CDATA[Advances in artificial intelligence (AI) have opened up new opportunities for transforming higher education assessment systems, particularly in supporting the measurement of Higher Order Thinking Skills (HOTS), which are a key requirement of Outcome-Based Education (OBE). However, assessment practices in higher education are still dominated by conventional methods that tend to focus on lower-order thinking skills, thus failing to optimally measure HOTS achievements. This study aims to develop an AI-Assisted Assessment model suitable for measuring students’ HOTS in OBE-based learning, to test the validity and feasibility of the developed model, and to analyze its effectiveness compared to conventional assessment. The study employed a Research and Development (R&D) approach using the ADDIE model, which includes the analysis, design, development, implementation, and evaluation stages. Data were collected through interviews, expert validation questionnaires, observations, documentation, and HOTS tests involving faculty members, learning assessment experts, educational technology experts, and students. The results of the study indicate that the AI-Assisted Assessment model has three main characteristics: it is integrated with OBE learning outcomes, it is capable of comprehensively measuring HOTS indicators, and it provides automatic and real-time feedback. The validation results indicate that the model falls into the category of highly feasible for implementation. Additionally, im.]]>
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