Writing PrairieLearn Questions and Computer-Based Test Practices

Computer-based assessment can change how students practice, test, and learn. Craig Zilles, Ph.D., University of Illinois Urbana-Champaign, explains how PrairieLearn supports mastery-oriented teaching through immediate feedback, auto-grading, randomized question generators, and repeat practice. Zilles examines asynchronous exams, frequent small tests, retake opportunities, and question banks designed around specific learning objectives, helping clarify how assessment systems can reduce administrative overhead while giving students more chances to demonstrate learning. He also discusses fairness in randomized exams, the balance between auto-grading and manual grading, and the emerging role of AI in formative feedback. This work helps explain how digital testing tools can support flexible assessment without forcing instructors to simplify what they teach. Series: "Computer Science Channel" [Science] [Education] [Show ID: 41409]