In this work, we used log files gathered from an online queueing system and combined those logs with the scores students earned on graded assessments. With data from four sections across two semesters of a large sophomore-level computer science course, this work is the largest known observational analysis of the impact of office hour attendance on graded assessments. This work in progress begins this analysis by exploring the relationship between office hour attendance and graded assessments over a full academic year in a large Data Structures course (n=1,238 students).
Our initial findings suggest that there are several relationships that warrant further exploration. The first major finding is that office hour attendance provides a significant increase to a student’s score on upcoming graded homework; however, it does not provide a significant boost to a student’s score on upcoming exams. The second major finding is that the overall impact on a student’s course grade by attending office hours decreases the closer that student attended office hours relative to an assignment due date or exam date.
Our work outlines the statistical techniques used in our analysis, explores differences between various sections of a course across two semesters, and provides an outline of recommended changes for how office hours are run based on lessons learned from this analysis. In the future, we hope that this will lead to improved learning, which will improve students’ mastery of the material and problem-solving abilities.
Natalia Ozymko is a rising senior majoring in Computer Science with a minor in Spanish at the University of Illinois at Urbana-Champaign (UIUC). She is interested in helping students master advanced topics in Computer Science and building new technologies to improve people’s lives. She was awarded the Scott Fisher Outstanding Course Assistant award, and has worked under the direction of multiple faculty members assisting in teaching both Data Structures and Systems Programming.
Matthew McCarthy is a Junior in Mathematics at The University of Illinois at Urbana-Champaign. He likes to do programming projects and data analysis in his free time. For this past year he has been working under different faculty members in both research and software development. He hopes to make the world amazing with his work.
Wade Fagen-Ulmschneider is a Teaching Associate Professor of Computer Science at the University of Illinois at Urbana-Champaign (UIUC). With a passion for data, he teaches thousands of students each year in his courses on Data Structures, Data Visualization, and Data Science. He was selected as one of the National Academy of Engineering’s Frontiers of Engineering Education scholars, awarded the Collins Award for Innovation Teaching, and has been consistently ranked as an excellent instructor by his students for the past ten years. His work on data visualizations has been used by governors of multiple states, featured by websites including Popular Mechanics and The Verge, and has been viewed by millions of readers.
Karin Jensen, Ph.D. (she/her) is an assistant professor in biomedical engineering and engineering education research at the University of Michigan. Her research interests include mental health and wellness, engineering student career pathways, and engagement of engineering faculty in engineering education research.
Karle Flanagan is a Senior Instructor of Statistics at the University of Illinois at Urbana-Champaign. She has taught introductory statistics to thousands of students at UIUC since Spring of 2014. She also serves as the MS advisor for the statistics dep
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