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Title: A Flexible Formative/Summative Grading System for Large Courses
Students in entry level CS courses come from diverse backgrounds and are learning study and time management skills. Our belief for their success is that they must master a growth mindset and that the final grade should represent their final mastery of topics in the course. Traditional grading systems tend to be too restrictive and hinder a growth mindset. They require strict deadlines that fail to easily account for student accommodations and learning differences. Furthermore, they run into averaging and scaling issues with 59% of a score counting as failing, making it difficult for students to redeem grades even if they later demonstrate mastery of topics. We designed a formative/summative grading system in our CS0 and CS1 classes for both on-campus and online students to support a structured growth mindset. Students can redo formative assignments and are provided flexible deadlines. They demonstrate their mastery in summative assignments. While being inspired by other grading systems, our system works seamlessly with auto-grading tools used in large, structured courses. Despite the flexibility, the courses provided a level of rigor before allowing students to continue onto the next course. Overall, 65% of students resubmitted assignments increasing their scores, participated in ungraded assignments, and used formative assignments for additional practice without a distinction between race or gender. These students went to the traditional follow-on CS2 course and 94% passed compared with 71% who took CS1 with a traditional grading system.  more » « less
Award ID(s):
1931363
PAR ID:
10448775
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
SIGCSE 2023: Proceedings of the 54th ACM Technical Symposium on Computer Science Education
Page Range / eLocation ID:
624 to 630
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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