Generative AI-supported progressive prompting for professional training: Effects on learning achievement, critical thinking, and cognitive load

Abstract

In professional training, developing critical thinking is essential for professionals to analyse problem situations and respond effectively to emergencies. Conventional professional training typically employs multimedia materials combined with progressive prompting (PP) to support trainees in constructing knowledge and solving problems on their own. However, for those trainees who have insufficient knowledge or experience, it could be challenging for them to understand and utilise the prompts for finding solutions to the problems to be dealt with. To provide a personalised advisor during the progressive prompting-based training process, this study proposed a generative artificial intelligence (GenAI)-supported PP (GenAI-PP) learning approach by employing GenAI to facilitate discussions with individual trainees regarding the prompts, thereby encouraging deeper thinking and critical analysis at each stage. This study adopted a quasi-experimental design to compare the effects of GenAI-PP and the conventional PP (C-PP) approach on students' learning outcomes. The participants were 62 newly qualified nurses with less than one year of clinical experience in Taiwan, who needed to learn to interpret electrocardiograms (ECGs) as part of their professional training. Results showed that the GenAI-PP group significantly outperformed the C-PP group on test scores (p < 0.01) and critical thinking (p < 0.01). Moreover, the GenAI-PP group experienced significantly lower extraneous cognitive load compared to the C-PP group (p < 0.001). These findings suggest the potential of GenAI-PP in professional training; that is, GenAI could serve as a learning partner to discuss with trainees the prompts provided by the instructor to help them master core concepts and develop key career competencies, especially for training programs that require in-depth analysis and decision-making.