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Direct linkChanMin Kim; Rebecca J. Passonneau; Eunseo Lee; Mahsa Sheikhi Karizaki; Dana Gnesdilow; Sadhana Puntambekar – British Journal of Educational Technology, 2026
As use of artificial intelligence (AI) has increased, concerns about AI bias and discrimination have been growing. This paper discusses an application called PyrEval in which natural language processing (NLP) was used to automate assessment and provide feedback on middle school science writing without linguistic discrimination. Linguistic…
Descriptors: Natural Language Processing, Automation, Artificial Intelligence, Bias
Jing Zhang; Qiaoyun Liao; Lipei Li; Jingyi Luo – Journal of Educational Computing Research, 2026
Natural Language Processing (NLP) has emerged as a transformative tool for EFL speaking instruction. However, prior research lacks robust empirical investigations into how distinct NLP tools independently enhance adaptability, accuracy, and fluency--particularly through controlled, large-scale interventions. Most studies focus on short-term…
Descriptors: Artificial Intelligence, Natural Language Processing, English (Second Language), Second Language Instruction
Michael Suhan; Mikyung Kim Wolf – Language Testing, 2026
Large language models, such as OpenAI's GPT-4, have the potential to revolutionize automated writing evaluation (AWE). The present study examines the performance of the GPT-4 model in evaluating the writing of young English as a foreign language learners. Responses to three constructed response tasks (n = 1908) on Educational Testing Service's…
Descriptors: Language Tests, Automation, Computer Assisted Testing, Scoring
