Enhancing Early Literacy Instruction with Artificial Intelligence Tools in the Context of Science of Reading

• In Event: Roundtable Session 13
  In Refereed Roundtable Session: Expanding Early Literacy: From Heritage Language Policies to AI and Robotic Tools

Proposal

Early literacy is a foundational skill that underpins lifelong learning and academic success, yet persistent gaps remain across populations and contexts (Delfi et al., 2025; Lee et al., 2025). These disparities, shaped by socioeconomic status, disabilities, and limited home literacy environments, are further compounded by the growing digital and “AI divide” (Chen, 2025; Yeter et al., 2025). Addressing such challenges requires adaptive approaches that provide individualized, early interventions (Yigitalieva et al., 2024). This paper examines how artificial intelligence (AI) tools can enhance early literacy instruction when aligned with the Science of Reading (SOR), an evidence-based framework emphasizing phonemic awareness, phonics, fluency, vocabulary, and comprehension (National Reading Panel, 2000; NYSED, 2025). Drawing on SOR, Vygotsky’s sociocultural theory, and frameworks such as TPACK and SAMR, the paper advances the AI-SOR Integration Framework as a conceptual model for guiding practice and research. AI tools can function as adaptive scaffolds by monitoring progress, adjusting instruction in real time, and providing feedback within learners’ zones of proximal development (Tolentino, 2023; Vygotsky, 1978). These tools support key SOR pillars by enhancing phonemic awareness and phonics (Chen, 2025), improving fluency (Daweli & Mahyoub, 2024), strengthening vocabulary (Wu, 2024), and fostering comprehension (Han et al., 2024; Oakley, 2024). They also provide opportunities for differentiation, inclusive support for students with special needs, and reduction of teacher workload through automation (Kosmas et al., 2025; Yim & Wegerif, 2024). However, the paper underscores that AI’s impact depends on teacher roles and AI literacy. Teachers act as mediators who design, implement, and critically evaluate AI-enhanced instruction to ensure that tools are used ethically and pedagogically to complement, rather than replace, human teaching (Yim & Su, 2024). Professional development that equips educators with technical, pedagogical, and ethical competencies is essential (Ding et al., 2024; Biagini, 2024). Persistent barriers—including insufficient training, privacy concerns, limited infrastructure, and inequitable access—pose risks of deepening educational divides (Han et al., 2024).
The conceptual framework advances four propositions: (1) AI can act as adaptive scaffolds aligned with SOR by personalizing practice (Tolentino, 2023; Yigitalieva et al., 2024); (2) teacher AI literacy mediates effective AI integration (Yim & Su, 2024; Karatas & Atac, 2024); (3) equity, ethics, and cultural responsiveness determine whether AI narrows or widens literacy gaps (Chen, 2025; Yeter et al., 2024); and (4) AI should complement, not replace, human teaching (Kohnke, 2025; Su & Yang, 2022). The paper concludes with implications for policy, practice, and research. Policies should promote age-appropriate AI literacy frameworks (Su, 2023a; Wu, 2024). In practice, sustained professional development and equitable implementation strategies are needed to empower teachers and ensure access (Ding et al., 2024; Yim & Wegerif, 2024). Future research should include classroom design studies to test AI-SOR integration, longitudinal studies of reading outcomes, and comparisons with traditional instruction (Oakley, 2024; Sun et al., 2025). In conclusion, this theoretical paper contributes a framework positioning AI as a promising but contingent tool for early literacy. By aligning AI use with SOR and centering teacher expertise, it highlights pathways to leverage AI for narrowing literacy gaps while safeguarding equity and educational integrity.

Authors

• Mujibat Atinuke Akorede, Old Dominion University

• Guang-Lea Lee, Old Dominion Univsersity