Curriculum Literacy has shifted recent policy discourse with a heightened urgency to adopt High Quality Instructional Materials, or HQIM. Steiner’s (2019) argued Curriculum Literacy is essential to providing rigorous instruction and suggested the need for HQIM. He identified Curriculum Literacy as “the ability to distinguish between high- and low-quality curricula, use curriculum skillfully, and understand why it matters” (p. 1).
In addition to the increased discourse pertaining to HQIM, the public release of GenAI, disrupted thinking related to lesson planning, providing many opportunities to transform instruct and barriers to address. One barrier to address is educator professional development related to AI literacy. Kandlhofer and colleagues (2016) identified AI literacy as the ability to understand the fundamental concepts related to AI application. AI literacy is essential for preservice teachers because they are preparing the next generation of digitally literate students.
This study and session aim to merge Curriculum Literacy and AI Literacy during the lesson preparation process. While preservice teachers participated in this study, there are significant findings for all educators, including implications for policy.
This study employed a mixed methods approach to investigate preservice teachers’ curriculum literacy (CL) and self-efficacy. Quantitative data were gathered using a Likert-scale instrument based on Steiner’s (2019) CL statements. To analyze qualitative responses, Lichtman’s (2023) Three Cs framework, codes, categories, and concepts, was applied.
Participants engaged with either high-quality instructional materials (HQIM) alone or a combination of HQIM and generative AI (GenAI) tools to support CL development. A subset of participants was invited to participate in Phase 2, which involved responding to open-ended prompts focused on CL and lesson preparation. These responses provided insight into how teacher candidates conceptualize and apply curriculum literacy in instructional design.
Lichtman’s Three Cs framework was used to analyze qualitative data across both phases, with Steiner’s CL constructs serving as an interpretive guide for synthesizing findings.
Data collection is ongoing. Two out of four cycles of data are collected. Data collection will conclude March 2026. Findings are shared below based on current data collection.
Current findings suggest that teacher candidates who utilized GenAI to create lesson plans identified a great increase in most criteria related to Curriculum Literacy. For example, students who only utilized HQIM often struggled to identify how to remediate weak instructional materials and explain how to identify resources for students with unique learning needs. Students who utilized GenAI alongside HQIM reported a greater increase in self-efficacy. This was also present in the second phase of data collection, including interviews with students about their process of evaluating and selecting GenAI created materials for the classroom.
While data collection is still underway, the preliminary findings are significant for teacher preparation programs and professional development related to Curriculum Literacy. As Curriculum Literacy has emerged in policy discourse related to HQIM, it is essential that educators understand the benefits and challenges of using GenAI as a technology tool to transform lesson preparation.
Kandlhofer, M., Steinbauer, G., Hirschmugl-Gaisch, S., & Huber, P. (2016). Artificial intelligence and computer science in education: From kindergarten to university. In 2016 IEEE frontiers in education conference (FIE) (pp. 1–9). IEEE. https://doi.org/ 10.1109/FIE.2016.7757570, 2016.
Pei, B., Lu, J., & Jing, X. (2025). Empowering preservice teachers’ AI literacy: Current understanding, influential factors, and strategies for improvement. Computers and Education: Artificial Intelligence, 8, 100406. https://doi.org/10.1016/j.caeai.2025.100406
Steiner, D. (2019). Curriculum literacy for future teachers: A paper prepared for the Schusterman Family. https://education.jhu.edu/edpolicy/policy-research-initiatives/teachers-curriculumliteracy/
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