Abstract
Traditional grading practices in STEM courses often emphasize point accumulation, correctness, and performance under pressure, which can unintentionally undermine curiosity, risk-taking, and deeper learning. In an era where generative AI can produce polished answers instantly, the limitations of product-focused grading become even more visible. This workshop explores how ungrading and growth-based assessment can shift the focus from outcomes to learning processes, supporting student motivation, equity, and mastery in university STEM contexts. The session introduces participants to core principles of ungrading, including clear standards, formative feedback, and opportunities for reassessment without penalty. Through a combination of mini-lectures, guided reflection, and small-group activities, attendees will analyze one assignment from their own course to identify what it is meant to assess, how current grading shapes student behavior, and where it may conflict with their learning goals. Guided by a simple planning table, participants will then begin to rethink that assignment by naming problems with the existing grading approach and outlining an alternative, more growth-focused feedback and grading plan. The workshop’s collaborative and practical structure allows faculty to engage with ungrading as learners while developing concrete ideas they can adapt to their own teaching. By centering feedback, reflection, and opportunities for students to take an active role in understanding their progress, the session encourages approaches to assessment that promote resilience, clearer understanding, and students’ thinking about their own learning. These practices are especially important in AI-supported learning environments, where process-oriented assessment helps maintain academic integrity and supports the development of future-ready skills.
Presenters
Karno NgProfessor, Chemistry & Biochemistry, California State University San Marcos, California, United States
Details
Presentation Type
Theme
KEYWORDS
Ungrading, Growth-Based Assessment, STEM Education, Feedback for Learning, Alternative Assessment, Higher Education, Generative AI
