Integrating ICT and AI-driven Reflective Practice to Enhance EFL Teachers’ Language Assessment Literacy: A Comparative Study of Young and Adult-Learner Contexts

Document Type : Research Paper

Authors

Department of English Language Teaching, Faculty of Literature and Humanities, Imam Khomeini International University, Qazvin, Iran

10.22034/elt.2026.70601.2839

Abstract

Language Assessment Literacy (LAL) is vital for effective instruction, but its development is often limited by institutional policies and a lack of contextualized professional development. Although information and communication technology (ICT) and Artificial Intelligence (AI) provide new avenues for nurturing reflective practice and fostering LAL, their influence across various instructional contexts remains underexplored. This qualitative, multiple case study explores how incorporating ICT and AI-driven reflective practices impacts the LAL of EFL teachers, comparing experiences in young-learner (YL) and adult-learner (AL) contexts in Iran. Data from post-observation discussions, classroom observations, semi-structured interviews, and narrative frames from 12 teachers revealed that both groups faced similar limitations from institutional policies, which restricted their assessment agency and reflective practice. Nevertheless, key differences emerged: YL teachers mainly required material and technological affordances to support multimodal, age-appropriate assessment, whereas AL teachers highlighted the need for conceptual tools and professional development to leverage data-informed, reflective practices. The study concludes that targeted teacher education, integrating AI-driven reflective systems and digital assessment tools, can allow teachers to explore institutional limitations and develop their LAL in ways that are responsive to the particular sociocultural and developmental needs of their learners.

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