2025 ASEE Annual Conference & Exposition

Technology plays a critical role to support problem-solving tasks for students in engineering education through computer-supported learning interventions. There is also a growing interest in using computer-supported learning to enhance the development of creativity, critical thinking, and problem-solving abilities among learners. In this space, design and design thinking are a significant focus for researchers looking to engage students in the design process to develop their expertise. Design thinking is a set of activities including empathizing, defining and ideating carried out by learners when designing a solution, product, or service. Many research approaches have been used to study how design thinking can be developed among learners through different pedagogical interventions yet, there is a continued need to investigate the diverse pedagogical approaches to develop design thinking. The aforementioned is even more important when computer-supported approaches are studied for enhancing design thinking abilities for open-ended problems that have multiple viable solutions. Literature has focused extensively on the design and implementation of Intelligent tutoring systems for close-ended problem solutions in STEM education. However, there remain primarily scattered efforts to build systems for open-ended problems. This work has often been done in isolation and little work has sought to synthesize them.

To draw this work together our research will employ a systematic review of this scholarship to identify approaches and strategies for conceptualizing an agent system to support learning in open-ended problems. Further, this work may also shed some light on how an Agent system should understand the student's existing knowledge and the nature of open-ended problems. Our initial review focuses on intelligent tutoring systems and Artificial Intelligence to support students’ learning in STEM, between the period of 1992 to 2024 in several databases. We focus on STEM topical areas and open-ended problems as the work that focuses explicitly on agents supporting design thinking is limited, however, we believe we may gain valuable insights from analyzing the broader area that will be transferable to supporting design thinking. An initial search procedure guided us to identify the scholarly work on Intelligent tutoring systems for STEM problem solving, Artificial Intelligence for Design thinking, and open-ended problem solving with virtual agents. We have restricted our scope by removing any scholarly work presenting an Intelligent tutoring system for the close-ended problems. We have considered articles that have K-12 or undergraduate participants. In analyzing past work as part of this review, this investigation seeks to address the following areas of interest i) Identifying interactions within learners and Agent within the learning environment and how those interactions evolve during the learning process, ii) how Agent Systems facilitate a structured learning approach (rules-based learning ) without nullifying the complexities and ambiguities of real-world learning, iii) How do Agent Systems facilitate discovery learning over instructional learning, and iv) What strategies are to be incorporated in Agent System to enhance the collaboration learning for open-ended problem-solving process. We will use inductive qualitative content analysis ,starting with open coding by two independent coders who will meet, reconcile codes and later develop categories to address the research prompts above. Our results will catalog the ways researchers have operationalized agents, student interactions, and the problem or knowledge space and the commonalities and differences between approaches. From these results we will discuss new avenues of structuring agent systems for open-ended design thinking problems reflecting on the innovations and limitations in existing scholarships and how interactive learning environment should be created to support this learning. The resulting outcomes provide a foundation for future researchers and system developers with a comprehensive strategy to adopt in the design and development of Artificial Intelligence (Agent Systems) to support the design thinking.