2024 ASEE Annual Conference & Exposition

Enrollment in introductory engineering courses, particularly for non-computer science majors, often evokes apprehension, particularly when faced with the prospect of learning programming. The presence of peers with prior coding experience can further compound these concerns. This study, applicable to a broad spectrum of engineering service courses, centers on assignment choice within an undergraduate CS-1 curriculum. Guided by Self Determination Theory, we implement assignment choice as a mechanism for students to chart a tailored path, selecting assignments aligned with course learning objectives. These choices are integrated into Canvas, the Learning Management System, and augmented with a course grade calculator, offering students a personalized course roadmap. This approach leverages students' internal motivation, be it intrinsic or extrinsic, by affording them the agency to customize their path through assignments, fostering a sense of ownership in their learning journey. By incorporating choice, the assignment set becomes more attuned to the diverse interests of the student body.

Building upon preliminary observations, this Work in Progress paper presents results from semesters where assignment choice was integrated, contrasting them with a new study using two-course control groups. One group of 100 students will be taught using the traditional method, while a second group of 100 students will be instructed by the same professor utilizing the Assignment Choice method. We aim to demonstrate that the student populations in both control and experimental groups are statistically similar. Subsequently, we will assess whether there is a statistically significant difference, if any, between the control group and the experimental group. Notably, we have witnessed a notable reduction in the DFQ rate in recent semesters, with a sample size of 200 students in the traditional course delivery compared to 300 students in the Assignment Choice delivery. This study paves the way for future investigations and enhancements. Our Research-to-Practice endeavor strives to develop a framework that enables instructors to ensure comprehensive coverage of course learning objectives, while still affording students a degree of assignment selection.

Anticipated outcomes from this research aim to furnish instructors with a robust framework that supports the dual objectives of student mastery of course content and successful course completion, thereby enabling them to progress in their chosen fields of study with confidence. The findings of this study hold promise in revolutionizing pedagogical approaches, ultimately contributing to enhanced student satisfaction, retention, and academic success in computer science service courses.