Learning Mathematical Concepts and Computational Thinking through Explainable Artificial Intelligence in a Simulation-based Learning Environment

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As a result of the powerful innovation and application of computing in STEM disciplines, the STEM+C program supports research and development of interdisciplinary and transdisciplinary approaches to the integration of computing within STEM teaching and learning for preK-12 students in both formal and informal settings. This project will advance the integration of the education of math within the context of artificial intelligence (AI) and computational thinking skills for high school students. AI has become ubiquitous in our everyday lives. From virtual assistants, to self-driving cars, from diagnosing disease, to building houses, many of today's students will go on to work in fields that involve or are influenced by AI. Being proficient in the language of AI is key to a workforce that will be able to continue to innovate and to support the AI-powered technology infrastructure and eco-system. AI builds on the foundation of mathematics. By illustrating how math concepts can be used in powerful AI tools to solve computational problems, learning math through AI and computation can be a motivational and educational vehicle to illustrate the pathway from K-12 STEM education, to post-secondary STEM education, and later to STEM careers. Most of the AI decision-making process today is a "black box" to non-AI experts, and even to some AI experts. Recent advances in explainable AI, an emerging intelligent human-computer interface that makes the decision-making of AI algorithms transparent to users, creates an opportunity to make AI machine learning concepts accessible to high school students. This proposed project employs explainable AI within a simulation-based learning environment where students follow guided human-robot team explorations to learn how to create abstractions of a problem, utilize AI algorithms to automate the process of solution generation, analyze the outcome, and then improve the performance of their solution. Researchers will iteratively introduce challenge problems and scenarios to encourage students to modify the robot's decision-making where students diagnose, revise, test and analyze, and create new capabilities for the robot. The proposed project partners with three high schools from Virginia and California. The integrated learning content will be developed with high school teachers, focusing on the connections between high school math, AI and computational thinking skills. The proposed project aims to answer the question of to what extent interactive explainable AI design choices and explanations contribute to understanding of math and AI in a use-create-modify framework for high school learners. Research studies will address (1) assessment of the use-create-modify approach and its impact on self-efficacy for computational thinking and use of AI, (2) assessment of understanding of math and AI, and the different uses of explanations to promote learning, and (3) enjoyment and engagement with the human-robot simulation, and to what extent enactment in this human-technology interactive learning environment is able to frame high school level learning of math and its integration with computational thinking.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.