Potential Abstract:
In today’s rapidly evolving educational landscape, ill-structured problems are becoming increasingly prevalent, requiring students to navigate complex, real-world challenges with no clear-cut solutions. Research has shown that students’ mindsets play a crucial role in their approach to such ill-structured problems, influencing their problem-solving strategies and overall performance. Additionally, the policy environment in which these problems are embedded can significantly impact students’ learning experiences and outcomes.
This study explores the potential of leveraging ChatGPT, a state-of-the-art language model, to support students in developing effective problem-solving mindsets when faced with ill-structured tasks within a semiotic policy environment. By engaging with ChatGPT through interactive dialogues, students can receive personalized feedback, scaffolding, and guidance tailored to their individual needs and learning styles. Through this process, students are encouraged to adopt growth mindsets, embrace challenges, and persist in the face of ambiguity and uncertainty.
Drawing on principles of semiotics, this research investigates how students interpret and construct meaning from the semiotic cues embedded within the policy environment. By analyzing students’ interactions with ChatGPT and the semiotic elements present in the problem scenarios, this study aims to elucidate the underlying cognitive processes involved in navigating ill-structured problems and developing adaptive problem-solving mindsets.
This study contributes to the growing body of literature on the intersection of artificial intelligence, education, and policy, shedding light on innovative approaches to supporting students in tackling ill-structured problems within complex learning environments. By examining the role of ChatGPT in fostering adaptive mindsets and semiotic understanding, this research has the potential to inform educational practices and policies aimed at promoting deeper learning and problem-solving skills among students.
Potential References:
- Expert or machine? Comparing the effect of pairing student teacher with in-service teacher and ChatGPT on their critical thinking, learning performance, and cognitive …
- The Impact of Artificial Intelligence on Materials Engineering Research
- Fluid transformers and creative analogies: Exploring large language models’ capacity for augmenting cross-domain analogical creativity
- Learning by Doing: Educators’ Perspective on an Illustrative Tool for AI-Generated Scaffolding for Students in Conceptualizing Design Science Research Studies
- A Panel Report on Higher Education in the Age of AI from the Perspective of Academic Leaders in the Midwest US
