Proceedings of the Annual Meeting of the Cognitive Science Society

Assessing the levels of motivation in the learning process are pivotal in the daily life of college students, for the learning motivation profoundly impacts their overall academic performance. Yet, the prevailing methods to measure learning motivation levels still predominantly depend on expert evaluation and self-report, advancements in passive smartphone sensing have not been fully utilized in measuring motivation levels in learning process. In this study, we investigate and analyze behaviors and behavioral changes associated with their levels of learning motivation of N=118 undergraduate college students integrating passive smartphone sensing with self-report survey. We collect a dataset regarding the students' daily behaviors and self-report responses using a mobile application and questionnaire. Subsequently, we identify a variety of behaviors based on behavioral features captured from passive sensing data, followed by an exploration of the correlations between levels of learning motivation and the identified behaviors. Moreover, we analyze differences in behavioral changes among groups characterized by varying levels of learning motivation. Our study contributes to enhancing psychological assessment approaches by introducing a novel integrated method for more quantified and multidimensional measurement of learning motivation, providing valuable perspectives for assessing and intervening learning motivation in future research endeavors.