Working Paper: A Statistical Approach to Likert Survey Data for a Competency-Based Grading Schema

• In Event: AERA Graduate Student Research in Progress Roundtable Session One
  In Roundtable Session: Competency-Based Grading, Intelligent Tutoring, and Utility Value Intervention as Tools for Postsecondary Education (Table 3)

Abstract

Competency-based grading (CBG) is a system that emphasizes mastery of outcomes and aims to promote a sense of autonomy and competence in students. The Self-Determination Theory (SDT) suggests that students will be more intrinsically motivated if their autonomy, competence, and relatedness are valued. This study investigates the impact of a CBG schema on student effort, performance, retention, and perceived value in an undergraduate computer science course. A mixed-method design-based research study was conducted with 46 consenting students, who completed an Intrinsic Motivation Inventory survey at the end of the course. The Likert survey data was analyzed using descriptive and inferential parametric statistics. Results indicated that the CBG schema had a positive impact on student effort, performance, and retention, and was perceived as more valuable than a traditional grading system. These findings support the use of CBG in computer science education.

Author

• Kelli Adam, Texas A&M University
  Presenting Author