PICRAT-Guided Integration of GenAI into a Project-Based Learning Course

Nikola Straková; Jan Válek; Petr Sládek

doi:10.3991/ijim.v20i17.62377

Authors

Nikola Straková Masaryk University, Brno, Czech Republic https://orcid.org/0000-0002-4009-8781
Jan Válek Masaryk University, Brno, Czech Republic https://orcid.org/0000-0002-8122-4211
Petr Sládek Masaryk University, Brno, Czech Republic https://orcid.org/0000-0003-4369-5992

DOI:

https://doi.org/10.3991/ijim.v20i17.62377

Keywords:

PICRAT model, generative artificial intelligence, project-based learning, semantic differential, future teachers, teacher education

Abstract

This study presents a redesign of a university project-based learning (PBL) course in which generative artificial intelligence (GenAI) was integrated using the PICRAT model that guided the incorporation of digital technologies into teaching. The course was intended for future teachers of practical and vocational subjects completing pedagogical qualifications through university study. The redesign introduced two artificial intelligence (AI)-based supports: Project Designer, which scaffolded project planning in line with Gold Standard PBL, and Project Evaluater, which provided formative feedback on drafted project designs. Using the PICRAT model as an interpretive framework, the study shows that the most meaningful uses of generative artificial intelligence (GenAI) were concentrated in the interactive and creative dimensions, particularly in project planning and revision. Initial empirical findings on participants’ attitudes toward PBL are also presented. Quantitative data were collected using a semantic differential and showed that respondents evaluated PBL more positively than traditional teaching, with a statistically significant difference in the evaluation factor. Qualitative findings indicated that participants particularly valued collaboration, practical relevance, active learner involvement, and learner autonomy, while the main perceived drawback of PBL was its time and preparation demands. The study provides an initial example of didactically grounded GenAI integration in teacher education and suggests that AI-supported planning and revision may help reduce practical barriers associated with preparing projectbased instruction.

Author Biographies

Nikola Straková, Masaryk University, Brno, Czech Republic

Nikola Straková is an assistant professor at the Department of Physics, Chemistry and Vocational Education, Faculty of Education, Masaryk University, Czech Republic. Her research and teaching focus on vocational education, project-based learning, AI in education, digital education, financial literacy and the development of entrepreneurial competencies at secondary vocational schools. She is particularly interested in the meaningful integration of generative AI into teaching, instructional design, and innovation in teacher education.

Jan Válek, Masaryk University, Brno, Czech Republic

Jan Válek is an assistant professor at the Department of Physics, Chemistry and Vocational Education, Faculty of Education, Masaryk University, Czech Republic. His research interests include physics education, digital literacy, artificial intelligence in education, STEM tasks, eye-tracking methodology, and the use of digital technologies in teaching and learning.

Petr Sládek, Masaryk University, Brno, Czech Republic

Petr Sládek is head of the Department of Physics, Chemistry and Vocational Education, Faculty of Education, Masaryk University, Czech Republic. His research interests include physics and vocational education, STEM/SCIENCE concept, digital literacy, eye-tracking methodology in education.

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