From user needs to AI solutions: a human-centered design approach for AI-powered virtual teamwork competency training

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Dades bibliogràfiques
Publicat a:	International Journal of Educational Technology in Higher Education vol. 22, no. 1 (Dec 2025), p. 52
Autor principal:	Hu, Wenjie
Altres autors:	Chan, Cecilia Ka Yuk
Publicat:	Springer Nature B.V.
Matèries:	Principles Students Usability Collaboration Curricula Communication Feedback Instructional design Teamwork Task analysis Training User needs Learning analytics Stakeholders Designers Real time Pedagogy Higher education Generative artificial intelligence Skills Learning Rapid prototyping Core competencies Engineering education Needs Technological change Classroom communication Simulation Engineering Innovations Competence Customization Conceptual knowledge Task completion Artificial intelligence Instructional Improvement Direct Instruction Cooperative Learning Educational Theories Competency Based Education Educational Objectives Language Processing Learning Objectives Brainstorming Educational Resources Influence of Technology Curriculum Design Learning Experience Educational Technology Engineering Technology Computer Mediated Communication Conflict Resolution Instructional Material Evaluation Educational Needs
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Descripció
Resum:	This study develops a human-centered design (HCD) approach to create a GenAI trainer that addresses critical gaps in virtual teamwork training for engineering students. While virtual teamwork competency is increasingly essential, current programs often prioritize task completion over competency development. Leveraging generative AI's capabilities for personalized interaction, scenario simulation, and tailored feedback, we employ a three-phase HCD approach: (1) identifying unmet user needs through stakeholder interviews, revealing key challenges in instructional support, training formats, feedback mechanisms, and teamwork awareness; (2) co-designing solutions with instructors and students to create an AI trainer that combines Socratic questioning and scenario-based learning; and (3) testing the system and obtaining feedback from engineering students. Results demonstrate significant improvements across multiple dimensions: transforming passive learning into active experiences, delivering real-time actionable feedback, enhancing conceptual understanding and awareness of virtual teamwork, and developing practical virtual teamwork skills through authentic scenarios. Participant feedback also identified future improvements for enhanced personalization and immersion. This study contributes both theoretically and practically by illustrating how HCD can effectively integrate AI capabilities with pedagogical needs, while providing a replicable model for developing competency-based training tools that balance technological innovation with educational effectiveness.
ISSN:	2365-9440 1698-580X
DOI:	10.1186/s41239-025-00551-z
Font:	Political Science Database