Author(s):
Lack of self-efficacy has been identified as a significant barrier for students in introductory computer science courses. Research indicates that enhancing self-efficacy boosts academic performance and can be fostered in the classroom through various strategies. These strategies include verbal persuasion, vicarious experiences, and physiological feedback, many of which can be tailored to encourage productive struggles. The aim of our project is to design, develop, and evaluate an online platform that supports productive struggles and bolsters the self-efficacy of undergraduate students in introductory computer science courses.We have created an online platform named PULSE (Productive Struggle for deveLoping Self Efficacy), which is designed to facilitate skill development via coding activities. PULSE acts as a pedagogical tool, providing instructors with proactive notifications about student challenges, thereby enabling timely interventions that can transform student struggles into productive learning opportunities.PULSE leverages machine learning algorithms to generate class-wide and individual student performance predictions. Alongside these predictive scores, it offers insights into common errors encountered by students during in-class activities or assignments, thereby pinpointing areas of difficulty. This feature allows instructors to engage in early dialogue with students, effectively addressing student struggles.We plan to update the student interface to display information about the challenges faced by their peers. By gaining insight into the class’s collective struggles, students can develop a sense of solidarity, thereby enhancing their confidence to ask questions, ultimately contributing to the development of their self-efficacy.
