Fostering Computer Science and AI Learning through Youth-Led Conversational App Development Experiences
Computing skills are essential for 21st-century workforce development, and artificial intelligence (AI) is increasingly at the center of computationally rich careers. To remain at the forefront of global technology, the US needs a diverse workforce prepared with these skills. There is a tremendous pool of talented learners who are currently not given access to computer science and AI learning opportunities during the critical ages when they develop educational interests and career identities. Experiences during K-12 have a significant impact on those identities and resulting career path choices. This project will engage historically marginalized middle school students in Alachua County, Florida in a summer program that teaches them computer science and AI concepts. Through an authentic inquiry process centered on developing conversational AI, spoken technologies that engage users in conversation, students will investigate and create innovative computational applications. Young learners will have the opportunity to develop skills in the design and implementation of a variety of personally relevant projects including speech assistants, question-answering systems, and games. These projects can offer meaningful engagement that has the potential to transform the way middle school students view computing and AI careers. This project is funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers. In this project, 210 students from diverse, underserved schools with limited access to AI and computer science will engage in two-week summer experiences to learn computer science and conversational AI development. The curriculum design is guided by the theoretical framework of a four-phase process model of interest development from initial situational interest to the eventual well-developed individual interest. Researchers in computer science and educational technology from the University of Florida will investigate the following overarching research question: In what ways can a summer development experience around spoken conversational apps foster middle school students' cognitive outcomes around computing and social-emotional outcomes of interest and identity formation related to STEM careers? The project will use a mixed-method research design to test the hypothesis that students will achieve significant knowledge gain as measured on a pre/post-test for computer science concepts, and that students will show a progression in the use of user-centered design practices as evidenced by source code analysis and mapping both the prototyping and user testing processes they undertake. The project will also test the hypothesis that students will display a significantly increased sense of identity and interest formation toward STEM careers. The research team will analyze patterns of collaboration and participation to explain why the learning experience supports these outcomes. The project will answer important research questions on how to engage middle school students in learning AI and what type of learning outcomes are achievable. This research has the potential to shed light on the emerging field of AI education within the context of computer science and conversational applications for the K-12 population. 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.