About the Project
This study investigates how generative AI tools like ChatGPT influence two critical cognitive processes in adult professional development: (a) metacognition—the ability to monitor and regulate learning—and (b) learning transfer—the capacity to apply knowledge in new contexts. While AI offers instant access to information and problem-solving support, unguided use may encourage cognitive offloading, reducing metacognitive awareness and independent application of skills. Guided AI use, incorporating structured prompts for goal setting, comprehension monitoring, and evaluation, is hypothesized to enhance active learning and strengthen both metacognition and transfer. The research draws on Cognitive Load Theory, Self-Regulated Learning Theory, and the Desirable Difficulty framework to clarify when AI acts as a scaffold rather than a substitute for effortful thinking.
To test these hypotheses, the project employs a randomized controlled design involving 300 adult learners assigned to one of three conditions: unguided AI use, guided AI use, or a non-AI control. Participants will complete workplace-relevant problem-solving tasks, performance-based transfer assessments, and validated metacognitive measures across three sessions, followed by a one-week practice period. Quantitative outcomes will be complemented by qualitative data from interviews and think-aloud protocols to elucidate the cognitive and metacognitive mechanisms underlying AI-supported learning. Together, the findings will advance theoretical models of self-regulated learning in technology-mediated environments and inform evidence-based strategies for designing AI-supported training that fosters adaptability, sustained cognitive engagement, and transferable expertise in professional contexts.
Research Impact: The findings will inform the development of AI-enabled training frameworks that promote durable learning, reflective thinking, and transferable skills among working adults.
Theme: Adult Learning Transfer
Principal Investigator(s)
ResWORK Fellow, YANG Hwajin @ SOSS
Co-Principal Investigator(s)
Sarah Wong @ SOSS
Gary Pan @SOA
Andree Hartanto @ SOSS
Collaborator(s)
Wong Zi Yang, Research Fellow, SMU