2025 ASEE Annual Conference & Exposition

In this complete evidence-based practice paper, we will present our analysis of student use of office hours in a large introductory computer programming course and how we have used this data to best staff office hours for this large course in a way that is accessible and beneficial to our students.

For students beginning their foray into the wider world of engineering, hands-on programming experience is invaluable to developing an intuition for technical problem solving. As such, ensuring that resources like office hours are as accessible to the student population of a first-year programming course as possible is imperative, especially in larger courses where instructor-student interaction becomes limited.

We teach a large required introductory programming class at a large, midwestern research university. This course has approximately 500-800 students depending on the semester. With log files from our departmental office hours queue system, we were able to determine that there were surges of attendance in office hours at points during the semester that aligned with project due dates and checkpoints. Using this information, we formed an office hours schedule that prioritized the times that students were more likely to attend by adding extra shifts in the three days leading up to a project deadline. The purpose of this paper is to document these data-driven changes that were made to shift scheduling and report on the impact that these changes had on graded assignment performance.

In a course with projects as the primary assessment of progress, there are a number of metrics that define project performance. These include the number of submissions to our autograder, the time taken to complete an assignment, and the overall final score. We aim to analyze these metrics as compared to those from the previous semester where the office hours schedule was unchanging week-to-week. Further, we plan to investigate the relationship between consistent office hour attendance and project performance using attendance data from the past two semesters. We hope to better understand the impact that good office hour attendance habits have on improving project performance and encouraging students to engage more with the programming assignments.

We hope to validate the changes to our shift structure through the overall performance results from the Fall 2024 semester. Based on our results regarding project performance as a function of office hour attendance, we will discuss recommendations for office hours shift staffing.