Perceptions of AI-Driven EdTech: Nationwide Survey and Focus Group Insights from Key End Users
Schoolchildren in the United States are increasingly exposed to educational technologies (EdTech), many of which are or will be infused with Artificial Intelligence (AI). Despite this growing integration, there is limited understanding of the current perceptions and attitudes toward EdTech with AI among parents, teachers, and teens. To address this gap, we conducted a mixed-method study involving an A/B experiment through an online survey with 3,051 participants and complemented by focus group discussions with 80 participants. Providing a comprehensive snapshot of AI perception in education in 2024, our findings indicate that participants, particularly teachers, may hold more negative perceptions of our AI-powered EdTech mock-up compared to the one powered by human tutors. Based on these insights, we discuss the future of EdTech regarding the current perceptions. This research contributes to an empirical understanding of the perceptions and attitudes toward AI in K-12 education, providing valuable insights through a comprehensive national survey and in-depth focus group sessions.
Authors
- Aehong Min (ORCID: https://orcid.org/0000-0002-3790-2126)
- Kelli L. Dickerson (ORCID: https://orcid.org/0000-0002-1710-7651)
- Jennifer D. Rubin (ORCID: https://orcid.org/0000-0002-6649-6606)
- Emani Dotch (ORCID: https://orcid.org/0000-0003-1429-7581)
- Riddhi A Divanji (ORCID: https://orcid.org/0009-0005-0978-7385)
- Ariel Han (ORCID: https://orcid.org/0000-0002-0047-0817)
- Katharine Chen (ORCID: https://orcid.org/0000-0002-4405-6052)
- G. Constable Hayes
- Candice L. Odgers
- Ella Lombard
- Sohyeon Park
Institutions
- Utah State University (US)
- University of California, Irvine (US)
- Shenyang Research Institute of Foundry (CN)
- Foundry (United Kingdom) (GB)
Publication Details
- Journal
- ACM Transactions on Computer-Human Interaction
- Published
- 2026-02-25
- DOI
- https://doi.org/10.1145/3798278
- Primary Topic
- Teaching and Learning Programming
- Type
- article
- Field-Weighted Citation Impact
- 0.00