Publikation
Technology Acceptance in University Robot-Supported Quiz-Based Learning: Verbal-Only Versus Multimodal Feedback With Sound Input
Rezaul Tutul; Ilona Buchem; André Jakob; Niels Pinkwart
In: IEEE Access (IEEE), Vol. 14, Pages 956-965, IEEE, 12/2025.
Zusammenfassung
The integration of social robots in higher education is accelerating, yet ensuring fair, engaging, and sustainable adoption remains challenging. This study evaluates a sound-driven, gamified quiz system implemented on the Pepper robot that integrates multimodal interaction, fairness-based first-responder detection, and gamification to enhance students’ motivation and technology acceptance. A betweensubject mixed-method design involving 32 university students was conducted, with participants randomly assigned to a verbal-only or a multimodal sound-feedback condition. Data were collected through a Technology Acceptance Model (TAM) questionnaire assessing Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Attitude Toward Use (ATU), and Behavioral Intention (BI), complemented by openended qualitative feedback. Sessions lasted approximately 25 minutes. Mann–Whitney U tests revealed significant improvements across all TAM constructs for the multimodal group (U= 86.5–264,p<.01), with a strong positive association between PU and BI (Spearman’s ρ =.70,p<.001). Thematic analysis highlighted increased trust, enjoyment, and collaboration resulting from fairness and expressive robot behavior. These findings confirm that equitable multimodal interaction and gamified feedback significantly enhance students’ acceptance, engagement, and trust in educational robots, providing a scalable framework for robot-supported learning environments.