Wendy Moore (Cal State East Bay)
Abstract
As educators, one of our most critical roles in the learning process is providing meaningful feedback to students. Research has consistently shown that traditional point-based grading systems can negatively impact learning by reducing motivation, increasing anxiety, and hindering material comprehension. Over the past two years, we have explored an alternative approach: ungrading. This grading paradigm has been implemented in both introductory and master’s-level statistics courses to address the challenges associated with numeric scoring. After two semesters of experimentation, we conducted a pseudo-experiment in our introductory statistics courses, randomly assigning two sections to different grading schemes. In Fall 2024, we expanded our exploration of ungrading to two sections of a graduate-level Statistical Methods course—one delivered in person and the other online. In this session, we will share a comparative analysis of ungrading across undergraduate and graduate statistics courses, offer practical recommendations for its implementation, and discuss strategies for scaling ungrading to larger classes.