A VR-Based Multimodal System for Assessing Presentation Integrity and Character Formation in Higher Education
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Background. Artificial intelligence (AI) integration in online presentation assessment has expanded rapidly; however, existing facial emotion recognition systems in education remain largely focused on surveillance and behavioral monitoring, with limited validation against human judgment and insufficient attention to ethical and character-development dimensions.
Purpose. This study aimed to develop and validate a virtual reality (VR)-based multimodal assessment framework for evaluating presentation integrity among higher education students.
Method. A design science research approach was employed involving 64 students from two parallel classes (A1, n = 33; A2, n = 31) at a university in South Sulawesi, Indonesia. Data from expert validation, technical performance evaluation, NASA-TLX, System Usability Scale, and lecturer assessments were analyzed using content validity analysis with modified kappa, classification metrics, Bland-Altman agreement analysis, and descriptive statistics.
Novelty. This study introduces a human-centered AI-VR assessment approach that integrates facial emotion recognition, gaze detection, and cognitive load measurement into a reflective Presentation Integrity Index. Unlike conventional AI-based monitoring systems that generate binary judgments, the proposed framework emphasizes ethical interpretation by combining affective, behavioral, and cognitive indicators to support formative character-based assessment.
Results. The framework demonstrated satisfactory content validity (S-CVI/Ave = 0.83), although refinement of several indicators was required. Emotion and gaze modules achieved accuracy levels of 85.3% and 89.0%, respectively. The Presentation Integrity Index showed 93.8% agreement with lecturer assessments, moderate cognitive load (NASA-TLX = 46.7), and good usability (SUS = 76.4).
Conclusion. The proposed AI-VR framework provides an ethical and reflective approach for character-based presentation assessment while requiring broader validation involving multiple evaluators and diverse educational contexts.
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