@article{tian_wiggins_fahid_emerson_bounajim_smith_boyer_wiebe_mott_lester_2021, title={Modeling Frustration Trajectories and Problem-Solving Behaviors in Adaptive Learning Environments for Introductory Computer Science}, volume={12749}, ISBN={["978-3-030-78269-6"]}, ISSN={["1611-3349"]}, DOI={10.1007/978-3-030-78270-2_63}, abstractNote={Modeling a learner’s frustration in adaptive environments can inform scaffolding. While much work has explored momentary frustration, there is limited research investigating the dynamics of frustration over time and its relationship with problem-solving behaviors. In this paper, we clustered 86 undergraduate students into four frustration trajectories as they worked with an adaptive learning environment for introductory computer science. The results indicate that students who initially report high levels of frustration but then reported lower levels later in their problem solving were more likely to have sought help. These findings provide insight into how frustration trajectory models can guide adaptivity during extended problem-solving episodes.}, journal={ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2021), PT II}, author={Tian, Xiaoyi and Wiggins, Joseph B. and Fahid, Fahmid Morshed and Emerson, Andrew and Bounajim, Dolly and Smith, Andy and Boyer, Kristy Elizabeth and Wiebe, Eric and Mott, Bradford and Lester, James}, year={2021}, pages={355–360} }