Early Experiences with Specifications Grading in Introductory CS Courses
This innovative practice paper describes our experiences with alternative grading practices in introductory computing courses and two large public universities in the United States. Computing classrooms often use traditional grading practices involving allocating points to assignments, deducting points for mistakes and tardiness, and combining assignment scores using a weighted average to determine grades. Recent research suggests that these practices may diminish achievement, discourage students, and suppress effort to such an extent that they are considered by some as detrimental. We approach our work as an exploratory case study, without predefined research questions or hypotheses. Our experiences began with the adoption of specifications grading. We outline the grading scheme applied to traditional programming assignments and exams/quizzes, and discuss the initial integration of these schemes with conventional auto-grading tools. We delve into student perceptions of alternative grading, their utilization of flexible deadlines, and resubmission opportunities. We conclude with a discussion of two challenges encountered during our exploration: student acceptance of a novel grading form, and the adaptation of tools designed for traditional grading to support alternative grading mechanisms. Our early exploration aims to inspire further research on the use of alternative grading in computing. It is clear from our observations that simply implementing the practices does not ensure the equitable and inclusive outcomes that can be achieved with these practices. If students are not prepared to use these practices, they find them difficult to understand and can feel that they are not being treated fairly. Additionally, we wish to foster a community of practice to assist faculty members exploring these changes, with the goal of creating more equitable and inclusive classrooms.
Authors
- Adrienne Decker (ORCID: https://orcid.org/0000-0002-0822-4813)
- Audrey Rorrer (ORCID: https://orcid.org/0000-0003-0600-6545)
- Bob Edmison (ORCID: https://orcid.org/0000-0002-5861-1029)
- Stephen H. Edwards (ORCID: https://orcid.org/0000-0002-5162-9314)
- Manuel A. Pérez-Quiñones (ORCID: https://orcid.org/0000-0003-1786-203X)
- A. Shukla
Institutions
- University of North Carolina at Charlotte (US)
- University at Buffalo, State University of New York (US)
- Virginia Tech (US)
Publication Details
- Published
- 2024-10-13
- DOI
- https://doi.org/10.1109/fie61694.2024.10893554
- Primary Topic
- Teaching and Learning Programming
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation