Proceedings of the Annual Meeting of the Cognitive Science Society

Self-adapted testing is designed to allow examinees to choose the level of difficulty of the items they receive. Thisresults in different levels of overall difficulty across exams, but examinees ability can be estimated regardless of theitems chosen using Item Response Theory. Here we also evaluated whether an examinees selection process could beinformative in assessing ability, engagement, and mindset. Two groups of examinees completed a self-adaptive generalknowledge test under different instructions, one emphasizing performance (fixed mindset) and one emphasizing learning(growth mindset). We modeled examinees choices of item difficulty using a Hidden Markov Model to predict whetherthey transition between difficulty levels based on their goal condition, the correctness of their last answer, the level ofconfidence in their last answer, and the interactions therein. Preliminary results suggest higher likelihood of examineeschoosing more difficult items following correct responses, high confidence, and learning (growth) instructions.