Mendoza professor provides STEM training to local teachers with center support

December 1, 2022

As data-driven technologies have become increasingly embedded in our lives, interest in understanding and creating them has become similarly widespread. Principles of data science and data literacy have started to become part of the educational curricula in some communities, helping prepare students to engage with the tools of today and the jobs of tomorrow. Such programs recognize that effective training around data science requires instructors that are equipped with the knowledge and tools to lead students on these subjects. Yet many teacher training programs and K–12 curricula around the country have not kept pace with these trends. This is especially true for younger students and students of color. While changes are occurring, many elementary and middle school teachers have not been trained in key data science principles. Crucially, this means that teachers are often unprepared to teach data science in a culturally-relevant way that is grounded in real-world applications. Fred Nwanganga, an associate teaching professor in the Mendoza College of Business, is working to change that in South Bend.

Computer technologies and artificial intelligence (AI) today shape an increasing amount of our personal and professional lives. Whether identifying the best route for us to drive to work or suggesting a book for us to read, digital tools are frequently at hand, suggesting behaviors that we may adopt with little scrutiny. The World Economic Forum estimates that by 2030 up to 30% of future jobs will be fundamentally altered by AI and scholars expect AI to be a central part of most other jobs not long after. Rather than replacing employees, AI is likely to become the core of a wide range of tools used by most workers. Yet these benefits are unlikely to be evenly realized across the economy or society, especially in the short term. 

AI-based shifts will happen at different rates across different industries. Nevertheless, widespread changes are occurring and the need to equip students with appropriate skills will only grow. Data-centric technologies require relevant training to effectively leverage, and individuals without the necessary knowledge may miss some of the attendant benefits. As a result, according to Nwanganga, “there is growing recognition that today’s young adults and students must develop a fundamental understanding of data science to become more data-literate citizens in preparation not only for a growing job sector, but also to be able to read, understand, and communicate relevant insight from data.”

Yet existing training opportunities for K–12 students are inaccessible for many students. Youth from lower-income families, girls, and students of color are consistently underrepresented in most STEM programs. Nwanganga argues that besides the glaring socio-economic imbalance, one of the other contributing factors to this disparity is a shortage of teachers trained in the relevant disciplines. Using funds provided by the Institute for Social Concerns, he has partnered with three local middle schools to provide focused data science training and content creation coaching to current math and science teachers. 
Over the summer, as part of the Early Bridges to Data Science program at the Lucy Family Institute for Data and Society, teachers were invited by their principal to participate in a three-day workshop organized by Nwanganga and taught by Notre Dame faculty. During their time together, participants were introduced to, discussed, and modeled core data science principles such as statistical thinking, data visualization, and data management. Together, they considered inclusive, accessible ways to teach each principle. They also considered together inclusive, accessible ways to teach each principle. The teachers identified strategies that would invite students of color, girls, and other historically underrepresented groups to engage with data science in new ways. Participants were enthusiastic about the workshop and looked forward to applying their newly acquired skills in the classroom. Speaking about the three-day immersion, one teacher said “I can’t believe statistics doesn’t have to make me cry!”