The effect of generative learning in augmented reality-supported case-based learning on achievement, retention, self-regulation, and self-efficacy

In this study, it was aimed to investigate the effect of students' use of self-explanation or focused self-explanation strategies as generative learning on achievement, retention, self-regulation, and self-efficacy in augmented reality-supported case-based learning. In addition, students' opinions on the effectiveness of the learning strategy they used as generative learning were examined. The participants in the study were 76 undergraduate students in the Nursing Department of a state university during the fall semester of the 2023–2024 academic year. According to the convergent design of mixed methods research, the quantitative part of the study was conducted as a pretest-posttest control group design, while the qualitative part was conducted as a case study. Data were collected using the "Personal Information Form", "Achievement Test", "Self-Regulation Scale", "Self-Efficacy Scale" and "Semi-Structured Interview Form". As part of the study, cases in a course using the case-based learning method were supported by augmented reality, and students in the experimental groups were asked to write self-explanation or focused self-explanation as generative learning after each case study. According to the quantitative results of the study, there was a significant difference in achievement, retention, and self-regulation scores between students in the experimental groups, who used self-explanation or focused self-explanation strategies as generative learning, and those in the control group. There was a significant difference in students' self-efficacy scores only in the experimental group using a focused self-explanation strategy, compared to the other groups. The qualitative results of the study indicated that the learning strategies used as generative learning supported students' learning.