Learnersourcing Modular and Dynamic Multiple Choice Questions

Abstract

Multiple choice questions (MCQs) are widely used for evaluating learning outcomes. In particular, student-generated questions have shown promise in promoting active learning and higher-order thinking. However, the process of generating quality MCQs can be challenging and time-consuming for students. Additionally, the existing crowdsourcing approaches for MCQ generation lack scalability and quality control. To address these issues, we introduce a system concept called Kuiz that implements a modularized and dynamic method for generating MCQs, allowing students to contribute at various levels and personalize their learning experience. The questions are modularized into question stems, answer sets, and distractor sets, enabling students to refine and improve them collaboratively. By dynamically altering question stems and answer sets, we enhance the quality and difficulty of the MCQs, providing personalized learning opportunities. Through Kuiz, we aim to reduce students' burden in question generation tasks, increase engagement, and create scalable learning materials. By combining learnersourcing with dynamic question generation, Kuiz offers a framework for creating engaging and personalized learning experiences.