Proceedings of the Annual Meeting of the Cognitive Science Society

LLMs can interact as though they understand language, yet they remain algorithms and can be used as such. This study explores a novel guided interaction design for modeling users' information foraging behavior when navigating GPT-generated content and the role of Computational Thinking skills in shaping such behavior. Conducted with nine educational researchers in a doctoral-level AIEd course, our research used editable prompt templates and keywords to structure the prompt crafting process. We modeled and analyzed participants' behaviors in terms of \textit{exploration} (to generate and explore various information landscapes) and \textit{exploitation} (to delve deeper in a specific landscape). Our data, including responses from the Computational Thinking Scale, suggests that Algorithmic Thinking and Creativity might encourage exploitation behavior, leaning more on AI-generated information rather than pre-defined design elements.