Investigation of Students' Learning, Interest, and Career Aspirations in an Integrated Science and Artificial Intelligence Learning Environment (i-SAIL)

The United States faces the critical need to prepare students and the future workforce for advances in Artificial Intelligence (AI). This project will develop curriculum that will engage middle-school students in learning science and basic AI concepts and in developing related career interests.

Full Description

The United States faces the critical need to prepare students and the future workforce for advances in Artificial Intelligence (AI). This project will develop curriculum that will engage middle-school students in learning science and basic AI concepts and in developing related career interests. The curriculum will first introduce students to the most fundamental approaches in AI-based problem solving. Next, students will learn how to use this knowledge to solve real world problems within an innovative learning environment, adapted to facilitate integrated science and AI problem solving. To contribute to supporting students who are underrepresented and underserved in STEM, the project is designed to foster an inclusive learning environment and provide access to resources and opportunities that promote equitable participation. Project research will investigate the impact of the curriculum in improving students' learning and in cultivating STEM interest and career aspirations. Over 900 middle-grade students from diverse backgrounds will participate in the research.

The project will conduct much-needed research on AI education that facilitates student learning with block-based, visual programming that uses graphical blocks to represent coding concepts instead requiring the writing of complex code. (Users can “drag and drop” these blocks to form sequences that create a program.) Four curriculum units that integrating different science disciplines will be developed. Student learning experiences will be supported by the user-friendly design of a block-based program environment. Teachers will participate in professional learning opportunities introducing AI and block-based programming. A design-based research approach will be employed, proceeding through an iterative process starting with co-design with teachers, followed by field testing, and culminating in a quasi-experimental study in the final year of the project. The research will focus on three areas: 1) How does the curriculum fosters students’ learning of science practices and AI concepts? 2) How do these student learning experiences influence their abilities to create AI solutions to science-focused problems? and 3) How does the curriculum stimulate and sustain student interest in science, AI, and related careers? Qualitative and quantitative data will be collected. The quantitative data will include pre- and post-tests to measure learning and questionnaires on student interest in science and AI. Qualitative data will include video and audio recordings of classroom implementations, peer interactions, student-teacher interactions, and student use of project technologies. The project will disseminate curriculum materials, teacher guides, and research findings to educational researchers and educators through teacher workshops, conference presentations, journal publications, outreach activities, and popular social media outlets.

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