Developing Learning Trajectories Supporting Middle School Student Understanding of Artificial Intelligence Concepts

With recent advances in artificial intelligence (AI), the United States needs to develop a diverse workforce with strong computational skills and the knowledge and capability to work with AI. Recent studies have raised questions about the extent to which youth are aware of AI and its application in industries of the future that may limit their interest in pursuing learning that lead toward careers in these industries.

To address this challenge, Learning Trajectories (LTs) will be developed and researched for AI concepts that are challenging for middle and high school students. (LTs outline the learning goals, pathways, and learning experiences which would support related learning at grade levels.) The project will design and pilot test learning activities and assessments targeting these concepts based on the LTs, offer teacher professional development (PD) on the LTs and related activities, and research the effectiveness of the LT-based activities when implemented by teachers during the regular school day. The LTs and other educational resources have have the potential to benefit society at large by preparing diverse groups of students for life and work in computationally intensive industries of the future and to have a significant impact on developing the workforce for AI-related industries.

Project research and resources will be disseminated through an awareness campaign aimed at researchers, practitioners, school administrators, and teachers; a project website including lessons, activities, assessment tools, press releases, project reports, and journal articles; and presentations and journal articles reaching both educators and researchers.

Research questions will focus on: (1) investigating the competencies and difficulties students demonstrate when making sense of AI concepts and processes, (2) how students’ understanding of AI corresponds to the hypothetical LTs, and (3) to what extent the LT-based activities support student understanding of AI topics when taught in school. Teachers and researchers will be engaged co-designing, testing, and refining LT-based lessons in their classrooms.

Initially, the research will engage 96 middle and high school students in cognitive interviews to build the LTs, 16 middle and high school teachers in PD and co-design, and 640 of their classroom students in the pilot testing. Additionally, 16 teachers and 640 students will participate in an effectiveness study of the curriculum with the LT-based learning activities inserted.

Students involved in the project will be recruited from schools that have diverse students from urban, rural, and suburban school districts. The research will offer invaluable insights on student competencies and difficulties when learning AI and yield AI LTs for grades 7 - 10. The co-design team will include learning scientists and curriculum developers who have successfully developed AI literacy curricula and assessments; experts in AI and AI education including AI teacher PD; experts in cognitive science; and researchers who have developed LTs for Math and Computer science.

The teacher-refined activities will reveal where and how teachers feel the AI topics can be connected to and fit within their existing curricula.

The project is supported by the Discovery Research preK-12 program (DRK-12), which seeks to significantly enhance the learning and teaching of science, technology, engineering, and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models, and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects.

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.