This study is grounded in constructivist and sociocultural learning theories, viewing knowledge construction as an active, social process shaped by culture and context. It also draws on critical pedagogy and transformative learning theory, emphasizing reflection, agency, and empowerment as central to equitable educational change. These perspectives intersect to frame AI literacy as more than technical proficiency—it is a form of civic and cognitive empowerment that equips learners to engage responsibly and creatively with emerging technologies.
The conceptual framework integrates equity-centered design and AI literacy principles aligned to ISTE Standards and Transformational Learning Principles (Ensure Opportunity, Develop Expertise, Ignite Agency). This alignment supports a continuum of impact: leaders ensure opportunity, educators develop expertise, and students ignite agency through global collaboration. Together, these theoretical foundations position AI literacy as a catalyst for inclusive innovation, reflective teaching practice, and durable skill development in under-resourced educational contexts.
This study employs a mixed-methods design to examine how targeted professional learning on AI literacy influences teacher confidence, instructional design, and student engagement. The research is conducted in a Title I district in collaboration with a regional university, engaging educators, instructional coaches, and students in a semester-long AI literacy initiative funded through a federal STEM grant. Students have the opportunity to design and build AI solutions with support from the local university and their Intelligent Systems Lab.
Participants and Context
Participants include K–12 teachers across multiple grade bands and subject areas, district-level coaches, and students in classrooms implementing AI-integrated lessons. Teachers were recruited voluntarily through district communication and selected to represent diverse schools and teaching contexts.
Data Sources
Pre- and post-surveys measuring changes in teacher confidence, ethical awareness, and perceptions of AI use.
Focus group interviews with teachers and students exploring attitudes toward AI, agency, and collaboration.
Classroom artifacts and lesson plans to evaluate instructional design shifts.
Observation notes and implementation journals documenting changes in practice.
Data Analysis
Quantitative data will be analyzed using descriptive and inferential statistics to identify changes over time. Qualitative data (interviews, reflections, artifacts) will be thematically coded using an iterative process informed by grounded theory and constant comparison methods. Triangulation across data sources will ensure validity and reliability.
Ethical guidelines were followed to protect participant confidentiality and maintain institutional review board (IRB) compliance.
Data collection and analysis are currently underway, with completion expected by January 2026. Preliminary findings indicate measurable increases in teachers’ confidence using AI to design inclusive, student-centered learning experiences and greater awareness of ethical considerations in classroom AI use.
Teachers report shifts in practice—from viewing AI as a replacement tool to recognizing it as a cognitive partner that supports creativity, differentiation, and reflection. Student focus group data suggest enhanced collaboration, curiosity, and engagement when exposed to AI literacy lessons emphasizing human “superpowers” such as critical thinking, empathy, and metacognition.
Expected final results include:
Statistically significant gains in teacher self-efficacy related to AI literacy.
Evidence of more equitable access to AI-integrated instruction across classrooms.
Qualitative themes showing students’ improved agency and ethical understanding.
These results will be presented as a cross-case analysis demonstrating how AI literacy professional development, grounded in equity and transformative learning, can strengthen both teacher and student capacity for ethical and innovative technology use.
This study addresses a pressing need in K–12 education: ensuring equitable access to AI literacy while maintaining human-centered learning through building teacher capacity. It contributes to the field by operationalizing what responsible, developmentally appropriate AI integration looks like in under-resourced schools and by demonstrating how collaborative partnerships between universities and districts can accelerate system-wide capacity building.
The research aligns with ISTE Standards and Transformational Learning Principles, providing empirical evidence for how leaders ensure opportunity, educators develop expertise, and students ignite agency through ethical and creative uses of AI. Findings will inform professional learning models, AI literacy curricula, and policy development across K–12 systems.
For conference audiences, this study offers a replicable model of partnership-driven innovation and actionable frameworks for designing equitable, reflective, and future-ready classrooms. It highlights how intentional AI integration can transform not only teaching and learning but also educators’ and students’ sense of purpose, agency, and global connection.
ISTE. (2021). ISTE Standards for Educators, Coaches, and Students. International Society for Technology in Education.
Equity-Centered Design Framework. (n.d.). National Equity Project.
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