WIP: Automated Flexible Extensions for Improving Learning Equity in Large Scale Computing Classrooms
This Work-In-Progress Innovative Practice paper describes a new flexible, at-scale assignment extension policy and its implementation in large undergraduate computing class-rooms. While prior work has studied flexible deadlines and their effect on student learning, such policies are still under-utilized in post-secondary classrooms due to practical constraints on administrative workload, from managing hundreds to thousands of requests to reducing excessive grading overhead, especially in large post-secondary classrooms. The Flextensions tool-an automated flexible extension assignment software-promotes equitable learning opportunities in higher education by providing sufficient accommodations to each student's unique learning needs and life circumstances. Part of Flextensions is a scalable software tool implementation that facilitates instructor management of extension requests across thousands of students and a variety of course policies. We present Flextensions and describe initial experiences with adapting the tool to computer science and data science undergraduate courses at an R1 institution in the United States. This work shares the open-source software that enables and streamlines the management of extension requests across different course policies. Additionally, we provide an initial analysis of flexible extensions in three specific large-scale (500–1500 students) undergraduate computing courses. Overall, students tended not to take advantage of the policy but rather used it only when needed, with many citing extenuating circumstances-personal or otherwise. By analzing survey results, the policy was well-received, with positive impressions on well-being, learning outcomes, and overall academic experience. One student-reported benefit was that many felt valued as individuals in the classroom. Despite some students still reporting stigma towards requesting an extension, Flextensions has the promising ability to improve the quality and responsiveness of creating accommodations in large-scale classrooms.
Authors
- Lisa Yan (ORCID: https://orcid.org/0009-0007-2310-3060)
- Jordan Schwartz (ORCID: https://orcid.org/0009-0002-0691-3815)
- Narges Norouzi (ORCID: https://orcid.org/0000-0001-9861-7540)
- Dana Benedicto (ORCID: https://orcid.org/0009-0000-9812-6127)
Institutions
- University of California, Berkeley (US)
Publication Details
- Published
- 2024-10-13
- DOI
- https://doi.org/10.1109/fie61694.2024.10892976
- Citations
- 1
- Primary Topic
- Online Learning and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 0.41