AI-Aided Podcast Scriptwriting: Prompt Practices and Metacognitive Regulation as Predictors of Distributed Self-Regulated Learning (SLR)
Year: 2026
Type: conference-paper
Study design: Observational Study
Abstract: This study investigates the intersection of metacognition, generative artificial intelligence (AI), and multimedia production through the theory of distributed Self-Regulated Learning (SRL). While existing scholarship highlights the pedagogical potential of AI-mediated environments, there remains a significant empirical gap regarding how AI prompt practices and metacognitive regulation predict SRL outcomes in creative tasks such as podcast scriptwriting. Grounded in a tripartite framework consisting of the forethought, performance, and self-reflection phases, this research empirically examines the regulatory behaviors of learners as they navigate the complexities of AI-supported content creation. The findings reveal that learners demonstrate substantial self-regulatory capacity, with elevated composite mean scores observed across all phases of the SRL cycle. Notably, the Performance Phase yielded the highest mean ($M = 4.17), indicating a pronounced level of "in-action" regulation characterized by robust self-monitoring, adaptive strategy deployment, and iterative prompt refinement. The Forethought Phase (M = 4.09) and Self-Reflection Phase (M = 3.97) also reflected high levels of engagement, though the comparatively lower reflection scores suggest that while AI facilitates active execution, deep evaluative regulation requires more intentional instructional scaffolding. This study underscores the role of generative AI as a strategically regulated cognitive partner rather than a passive utility. The results suggest that by systematically embedding structured goal-setting and post-task reflection mechanisms into AI-supported learning designs, educators can foster greater learner agency and critical appraisal skills. This research contributes to a more comprehensive understanding of regulatory processes in digital environments, offering a process-driven model for cultivating autonomous self-regulation in the age of artificial intelligence.
Authors: Hailey P. Ferrer, Jomel Paulo G. Ebron
Institution: Malayan Colleges Laguna
Language: English
Subfield: Developmental and Educational Psychology
Field: Psychology
Domain: Social Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W7204569252