This paper describes the development of a dynamical systems model of motivation and metacognition during learning, which explains some of the practically and theoretically important relationships among three studentengagement constructs and performance metrics during learning. In order to better calibrate and understand the model, the model was also fit with additional fixed factor predictors determined from the factor scores from a factor analysis of the pre-survey given to students. This work mined data from computerized adaptive flashcard learning system to create the dynamical systems model. This flashcard practice included pop-up survey questions on the student's experience of recent easiness, strategy use, and usefulness, in addition to the correctness performance data for the practice. The dynamical systems model of this data was then used to simulate various student profiles to predict how they would experience the flashcard system. These simulations show how strategy use in this task is crucial because of the ways it influences performance and perceived usefulness. In the model, this result is shown by a bifurcation for higher and lower strategy use, where the higher strategy use equilibrium is accompanied by performance predictions suggesting learning that is more efficient. In addition, we examined the implications of our data for the flow theory of optimal experience by testing models of this theory and comparing it to a Vygotskian perspective on the results.
How to Cite
dynamical system model, language learning, motivation, metacognition, efficacy, utility
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