Facilitating students' critical thinking, metacognition and problem-solving tendencies in geriatric nursing class: A mixed-method study.

Abstract

Aim: The aim of this study was to explore the use of generative artificial intelligence (GenAI) in geriatric nursing classes for the design of older adult activities to educate students on how to pose clear questions, provide and identify potentially suitable daily activities for older adults.

Background: Researchers in various educational fields are increasingly employing GenAI tools such as ChatGPT for curriculum development and research. Question generation is an essential skill for all students to learn to acquire knowledge. However, there is limited experimental evidence on teaching students to correctly use GenAI for assisting with question generation ability and empirical data related to improving students' capacity for solving complex problems remains scarce.

Design: A mixed-method study design with both quantitative and qualitative analysis.

Methods: This study investigated the effectiveness of a GenAI-guided prompt-based learning approach implemented in a geriatric nursing class for first-year undergraduate students, involving a cohort of 56 participants.

Results: Experimental results indicated that the GenAI-guided prompt-based learning approach significantly enhanced students' critical thinking, metacognition and problem-solving tendencies and their question generation via prompts performance. Moreover, participants who engaged in the GenAI-guided prompt-based learning approach found the tasks easier to complete and required less cognitive effort.

Conclusions: Nursing students using the GenAI-guided prompt-based learning approach outperformed the control group in cognitive network analysis dimensions of clarity, relevance, complexity, precision and engagement. Thus, integrating GenAI prompts into course activities can effectively improve student learning outcomes, reduce metacognitive load and assist in solving learning problems.