ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING : UNPACKING HIGH SCHOOL CS TEACHERS' PERSPECTIVES AND PEDAGOGICAL APPROACHES
As the use of artificial intelligence (AI), especially machine learning (ML), has dramatically increased, K-12 schools have begun to deliver AI education; however, little is known about teachers’ views on the field. This qualitative study investigated how U.S. high school computer science (CS) teachers conceptualize AI, the role of AI in their CS instruction, and the instructional curricula and pedagogies these educators use to bring AI into their CS instruction. Data was collected through semi-structured interviews with 23 educators teaching 9-12th grade CS courses in U.S. schools. Data collected from interviews was examined using thematic analysis resulting in seven themes. The findings suggest that teachers see great value in AI education and encourage schools to provide AI literacy instruction for all students while providing AI technical instruction in elective CS courses. Teachers demonstrated high levels of interest in the field but a shallow understanding of AI technology. The study’s findings also showed that CS teachers know of the importance of AI ethics instruction but have a limited view of AI’s impact on society. Additionally, the results point to a general lack of curricula and tools designed to teach K-12 students about AI, especially materials that emphasize critique of AI technology and its societal harms. The study’s results contribute to a deeper understanding of 9-12th grade teachers’ conceptions of AI and the challenges they face when implementing AI instruction. Implications for teachers, school leaders, curriculum developers, policy makers, teacher educators, and professional development (PD) providers are presented.
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- In Collections
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Electronic Theses & Dissertations
- Copyright Status
- In Copyright
- Material Type
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Theses
- Authors
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Opps, Zachary
- Thesis Advisors
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Yadav, Aman
- Committee Members
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Greenhow, Christine
Johnson, Kristen
Leftwich, Anne
- Date Published
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2024
- Degree Level
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Doctoral
- Language
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English
- Pages
- 216 pages
- Permalink
- https://doi.org/doi:10.25335/ng9v-8z37