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All Journal IJORER : International Journal of Recent Educational Research Foreign Language Instruction Probe
Sadji Evenddy, Sutrisno
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Education Languange, Linguistic, Communication & Media Mathematics Other

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Journal : Foreign Language Instruction Probe

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Adapting Assessment for Diverse ELT Learners Sadji Evenddy, Sutrisno
Foreign Language Instruction Probe Vol 2 No 2 (2023): Technology Enhanced Language Learning
Publisher : STIT Buntet Pesantren Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54213/flip.v2i2.322

Abstract

This article comprehensively addresses the significance and complexities of adapting assessment for diverse ELT learners. The research design employs a literature review approach, systematically analyzing academic articles, reports, and case studies.The study identifies key concepts and patterns related to adapting assessment for diverse ELT learners. Diverse learners in ELT encompass individuals with varying identities, motivations, and language proficiency levels. Strategies to adapt assessment include incorporating culturally diverse materials, providing multiple assessment formats, considering individual language proficiency levels, and accommodating learners with disabilities. Clear assessment instructions and rubrics are also crucial for effective evaluation. Implementing adapted assessment faces challenges such as diverse academic abilities, linguistic backgrounds, and the need for collaboration with families and communities. Strategies to overcome these challenges include building trust, employing communication strategies, integrating digital storytelling, adapting assessments to online environments, and framing language learning as critical engagement. recognizing and accommodating diverse learners in ELT assessment is vital for creating equitable and inclusive educational experiences. This article provides educators with valuable insights and strategies to meet the diverse needs of their students
Investigating AI's Automated Feedback in English Language Learning Sadji Evenddy, Sutrisno
Foreign Language Instruction Probe Vol 3 No 1 (2024): Technology and AI in ELT
Publisher : STIT Buntet Pesantren Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54213/flip.v3i1.401

Abstract

This literature review examines the role of artificial intelligence (AI) in enhancing feedback mechanisms within English language learning, emphasizing the integration of AI technologies such as Natural Language Processing (NLP), Machine Learning (ML), and speech recognition to provide real-time, personalized feedback. The purpose of this review is to synthesize existing research findings on the effectiveness of AI-driven feedback in improving language skills such as grammar, vocabulary, and pronunciation, while also assessing learner engagement and retention rates. A thorough methodology involving a selection of recent peer-reviewed articles, academic databases, and a mixed-methods approach for data synthesis and analysis was employed to ensure comprehensive coverage of the topic. The review highlights that AI feedback often surpasses traditional methods in terms of speed, availability, and personalization. However, it also identifies significant challenges, including issues with accuracy, dependency on extensive datasets, and institutional resistance, which could hinder the broader adoption of AI in educational settings. Also, the paper discusses potential technological improvements, the need for integrative feedback approaches combining human and AI elements, and highlights gaps in current research that offer directions for future inquiry. This comprehensive analysis aims to provide educators, technologists, and policymakers with insights into leveraging AI to foster more effective and engaging language learning experiences.
Co-Authors Gailea, Nurhaeda Syafrizal Syafrizal