Transforming Grading Practices in the Computing Education Community

This project aims to serve the national interest by transforming grading practices in the computing education community. Most computing instructors grade assignments by deducting points for each mistake made by a student from the maximum possible score on an assignment. Grading practices that rely on deducting points often discourage student achievement. The use of equitable and inclusive grading practices has been shown to promote self-regulation of student learning and can be easily incorporated by instructors when they are given the proper training and support. This Level 3 Engaged Student Learning project seeks to transform grading practices across the community of computing educators by developing and implementing a unified theory of fair grading for computing education. Implementation of this theory will result in the adoption of fair practices, and promote self-regulation of student learning, leading to improved learning and retention throughout the computing education community. This project leverages support in automated grading systems and grading by hand to transform grading practices. To produce this transformation, this project will pursue four objectives. First is to develop grading resources to facilitate and promote adoption, including recommended practices for learning management system features and support for commonly used automated grading tools. Second is to deploy a full-scale professional development campaign to institute and nurture a community of practice (CoP) focused upon these grading strategies. Third is to measure the impact on computing educators, including the extent of adoption. Fourth is to measure the impact of this approach on students, considering achievement, motivation, stress, and anxiety. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.