Abstract:

Many students' understanding of probability is based on misconceptions that are not aligned with established disciplinary meanings. This leads to problems in decision making later in life, where almost everyone, even professional statisticians, suffers from systematic biases in judgments of probability while maintaining strong misconceptions. Artificial Intelligence (AI) offers a setting for probabilistic problem solving that is relevant and meaningful to students, as probability is one of the mathematical concepts that are foundational to AI. For students, AI provides a modern context for connecting probability concepts to real-life situations and provides unique opportunities for transdisciplinary learning that can advance student understanding of both AI systems and probabilistic reasoning. One approach to bring AI to the K-12 classroom that has shown promise in other STEM disciplines is digital game-based learning. Designing game-based environments with AI problem-solving offers a great opportunity to both build on and contribute to the existing knowledge of how to integrate math and AI education in K-12 classrooms through technological innovations. In prior work, we described the design and implementation of our educational game, ``The 7th Patient'', aimed at teaching probability concepts within an environment that supports the reciprocal development of math and AI skills. We conducted a study where more than 1200 high-school students played the game, and we previously presented coarse statistical analyses on the games' impact on their knowledge of (and interest in) probability and AI. In this paper, we apply machine learning to dig deeper into the more fine-grained impacts of different game design elements on subpopulations of students. The resulting student model helps illuminate what content was effectively conveyed by the game, and where improvements are needed. The overall results demonstrate the value of this game-based platform and others like it as a methodology for experimenting with and evaluating alternate methods for teaching probability and AI concepts.

Keywords:

Education, game-based learning, math education, probability education, AI education.