Scaffold Ill-Structured Problem Solving Processes through Fostering Self-Regulation — A Web-Based Cognitive Support System

Ge, Xun (The University of Oklahoma)

AAAI Conferences 

This paper provides an overview of a web-based, database-driven cognitive support system for scaffolding ill-structured problem solving processes through fostering self-regulation. Self-regulation learning and ill-structured problem-solving theories guided the design framework of this cognitive tool. Of particular interest are the roles of question prompts, expert view, and peer review mechanisms in supporting self-monitoring, self-regulation, and self-reflection in the processes of ill-structured problem solving, which have been tested through empirical studies in various content domains and contexts. Based on findings, suggestions are made to improve the cognitive support system for future research, including mapping self-regulation learning processes more closely with ill-structured problem-solving processes, and focusing on the system’s capability to automatically adapt scaffolding based on individual needs and prior knowledge.