Is AI-assisted assessment liable to evaluate young learners? Parents support, teacher support, immunity, and resilience are in focus in testing vocabulary learning

Autor: Mohammad Ahmar Khan, Oysha Kurbonova, Diyorjon Abdullaev, A. Hussien Radie, Nirvana Basim
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Language Testing in Asia, Vol 14, Iss 1, Pp 1-23 (2024)
Druh dokumentu: article
ISSN: 2229-0443
DOI: 10.1186/s40468-024-00324-x
Popis: Abstract This study investigates the impact of artificial intelligence (AI)-assisted assessment on young L2 learners’ vocabulary knowledge, immunity, and resilience, considering parental and teacher support roles. Sixty junior high school students in Afghanistan, aged 13 to 14, participated in the study. They were divided into an experimental group receiving AI-assisted assessment and a control group with traditional instruction. The research employed a pretest–posttest control group design, using teacher-made vocabulary tests validated for reliability and instruments measuring immunity and resilience. The findings revealed that AI-assisted assessment significantly improved vocabulary knowledge and emotional resilience compared to the control group. While parental support showed a positive trend toward vocabulary enhancement, teacher support did not significantly impact the outcomes. The study highlights the potential of AI in language education, emphasizing the need for collaborative efforts among educators, parents, materials developers, syllabus designers, and policymakers to maximize the benefits of AI tools. These findings underscore the importance of integrating advanced technologies into educational frameworks to support cognitive and emotional development in learners.
Databáze: Directory of Open Access Journals