A Framework of Literacy Development and How AI Can Transform Theory and Practice

Autor/inn/en	Sabatini, John; Graesser, Arthur C.; Hollander, John; O'Reilly, Tenaha
Titel	A Framework of Literacy Development and How AI Can Transform Theory and Practice
Quelle	In: British Journal of Educational Technology, 54 (2023) 5, S.1174-1203 (30 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Sabatini, John) ORCID (Hollander, John)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0007-1013
DOI	10.1111/bjet.13342
Schlagwörter	Literacy Education; Scaffolding (Teaching Technique); Decision Making; Artificial Intelligence; Standards; Learning Trajectories; Secondary School Students; Student Diversity; Intelligent Tutoring Systems; Educational Change + Suchen Sie Ihr Suchwort? Decision-making; Entscheidungsfindung; Künstliche Intelligenz; Standard; Sekundarschüler; Intelligentes Tutorsystem; Bildungsreform
Abstract	We argue in this paper that there is currently no adequate theoretical framework or model that spans the twelve odd year trajectory from non-reader to proficient reader, nor addresses fine-grain skill acquisition, mastery and integration. The target construct itself, reading proficiency, as often operationalized as an endpoint of formal secondary schooling, is defined and measured in imprecise, fragmented terms. Consequently, schools (and empirical research) fall back on heuristics like the Simple View of Reading, or a few stages (learn to read, read to learn, read to do) to describe reading development. Those models, however, are too general to guide instructional decisions for adaptive learning systems. Progress in engineering an adequate learning system has been inhibited by a mismatch with curriculum standards and school organization that impose good-faith but not fully optimized developmental targets on the educational system. We propose the development of a learning and assessment framework to scaffold reading proficiency development while accounting for the diverse learning trajectories of groups or individuals across development. We then identify some key problems, challenges and opportunities that AI technologies are poised to help us address in conceiving individualized, adaptive learning systems for reading proficiency across the developmental spectrum. We close with a selective review of examples of AI-enhanced research or products. (As Provided).
Anmerkungen	Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01