Key points are not available for this paper at this time.
Purpose The present study synthesizes the variable-centered and person-centered approaches to examine the mediating role of flow experience in the relationship between SRL and AI-mediated IDLE learning engagement, identify latent profiles of AI-mediated IDLE SRL, and compare flow experience and learning engagement across different SRL profiles.Methodology Questionnaires were collected online among 1956 college students in China to measure self-regulated learning, flow experience, and learning engagement. Mediation analysis, latent profile analysis, as well as BCH method were adopted for data analysis.Findings Mediation analysis results demonstrate that flow experience mediated in the relationship between SRL and AI-mediated IDLE learning engagement. Latent Profile Analysis results reveal four AI-mediated IDLE SRL profiles. In addition, BCH results demonstrate that all four profiles differed significantly in learners’ flow experience and AI-mediated IDLE learning engagement, with the ‘all-high SRL profile’ and ‘all-low SRL profile’ displaying the highest and lowest level of engagement, respectively.Originality The study provides empirical proof for an extended SRL model with multidimensional engagement (emotional, behavioral, cognitive) as the outcome of SRL and with flow experience as a mediator in the relationship between SRL and engagement. At last, it adds literature on the distribution and nature of SRL profiles in an AI-mediated IDLE environment. In addition, the study synthesizes variable-centered and person-centered approaches to compensate for the shortcoming of over-reliance on one single approach.
Yang et al. (Wed,) studied this question.