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Imagining Futures for Early Literacy and Responsible AI: Results from CELaRAI’s Year 1 Exploratory Study

Fri, April 10, 3:45 to 5:15pm PDT (3:45 to 5:15pm PDT), Los Angeles Convention Center, Floor: Level Two, Room 515A

Abstract

Objectives/Purposes: The Center for Early Literacy and Responsible AI (CELaRAI), a national AI research center funded by the Institute for Education Sciences, will present the results of the Year 1 Exploratory Study. The purpose of the study was to identify teachers’ current practices, interests, and needs in early literacy, digital reading, and AI and to inform the development of the AI Reading Enhancer (AIRE), a new AI platform to generate decodable, culturally relevant texts for reading practice for beginning readers.

Perspectives/Theoretical Framework: Teachers worldwide are in the process of developing their Technological Pedagogical and Content Knowledge (TPACK; Koehler et al., 2013) for early literacy instruction with digital texts and AI. This study examines how teachers are adopting and integrating AI into early literacy instruction to inform future tool development and identify professional learning needs in a rapidly changing technological-pedagogical space.

Methods: The CELaRAI Year 1 Exploratory Study included the development of quantitative and qualitative data collection instruments including surveys, observations, interview, and focus groups on K-2 teachers’ early literacy practices, explicit literacy instruction, and use of digital texts and generative AI in teaching.

Data Sources: The CELaRAI Year 1 exploratory study included a survey of a nationally representative sample of teachers (n = 1200 K-2 teachers in the U.S.) and 12 teacher interviews and seven teacher focus groups across three states (South, Midwest, and Northeast).

Results: Teachers identified 30 digital and AI-powered literacy tools used in their classrooms, including digital libraries (EPIC, myON), curriculum-based platforms (Benchmark, Lalio by Renaissance), instructional support products (iReady, Lexia), and teacher-focused programs (ChatGPT and Magic School). Students used these programs to read text, listen to text, engage in research, review vocabulary, play games, and complete lessons. They used digital features including phonics instruction, games, text highlighting, videos, read aloud mode, songs, graphics, voice recording, zooming in on text, making words activities, and digital dictionaries. Teachers valued programs that personalized students’ learning and that supported their own planning and instruction, including assessments, recommendations for differentiation, lesson plans, and text generation. Challenges with digital texts and AI included student difficulties using the technology, monotone voice features, attentional difficulties, lack of tactile support, inappropriate differentiation based on difficulty, reliance on read aloud functionality, and concerns about too much screen time.

Scientific/Scholarly Significance: CELaRAI’s comprehensive Year 1 Exploratory Study provides researchers and developers with an in-depth look at K-2 teachers’ development of TPACK for AI use in early literacy instruction. Teachers in the U.S. are actively incorporating digital technology and AI into their early literacy instruction and imagining futures in which these tools can support their students in robust reading practice. Unforgetting the lessons of previous technological adoption, however, teachers also recognize the limitations of currently available options and provide new directions for innovation and research on AI in early literacy instruction. Taken together, researchers, developers, and teachers can work together to construct a new vision of AI in education through improved AI text generation, evidence-based digital supports for reading, assessment, and progress monitoring.

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