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Essays in Education

Abstract

This article proposes AI-Supported Reflective Practice, a design framework that positions generative AI as a secondary evaluator and reflective partner in a graduate-level online ELL assessment course. Drawing on two redesigned assignments, an ELL writing evaluation and an assessment critique, the framework asks teacher candidates first to conduct independent analyses, then to elicit, compare, and critically interrogate AI-generated evaluations. These designs aim to cultivate critical AI literacy, professional judgment, and equity-centered interpretation, particularly for multilingual learners. The article discusses emerging benefits, challenges, and program-level implications, arguing that embedding AI within authentic disciplinary tasks can deepen, rather than erode, candidates’ ethical and pedagogical decision-making.

Primary Author Bio Sketch

Nabat Erdogan, Ph.D., is an Associate Professor and coordinator of the MSE in ELL program in the Department of Educational Foundations and Literacy at the University of Central Missouri. She has twenty-seven years of experience in Teaching English to Speakers of Other Languages (TESOL) and Linguistics in the United States and abroad. She earned her first Ph.D. in Linguistics from Azerbaijan University of Languages in 2008 and her second Ph.D. in Teaching English to Speakers of Other Languages (TESOL) and English from the University of Missouri–Kansas City in 2018. With a background in Linguistics, TESOL, and English, Dr. Erdogan’s research and publications focus on comparative and applied linguistics, syntax, phonetics, pragmatics, second language literacy, and the use of generative artificial intelligence (GenAI) in language teaching and learning. Her award-winning book, “Applied Linguistics for Teachers of Culturally and Linguistically Diverse Learners”, combines linguistic theory and practice and offers practical approaches and techniques for teaching English to English language learners.

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