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| Published: June 21, 2025
Digital Assessment Techniques and AI-Powered Feedback Systems in English Language Learning
Research Scholar (Department of Education), Babasaheb Bhimrao Ambedkar University (A Central University), Lucknow
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Professor (Department of Education), Babasaheb Bhimrao Ambedkar University (A Central University), Lucknow
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DIP: 18.01.349.20251302
DOI: 10.25215/1302.349
ABSTRACT
The integration of digital assessment techniques and AI-powered feedback systems has significantly transformed the landscape of English language learning. This paper explores the efficacy, challenges, and pedagogical implications of using technology-enhanced assessments and artificial intelligence (AI) in evaluating and enhancing learners’ proficiency in English. Digital assessments, ranging from online quizzes to adaptive learning platforms, offer immediacy, flexibility, and scalability, especially in diverse and remote learning environments. AI-powered feedback systems, including Natural Language Processing (NLP)-driven tools like Grammarly and AI tutors, provide real-time, personalized, and data-informed feedback that supports continuous language development. Drawing from recent empirical studies and theoretical frameworks, this research examines how these technologies influence student motivation, engagement, self-regulation, and academic achievement in English. Additionally, the paper discusses the role of AI in formative and summative assessments, highlighting opportunities for differentiated instruction and inclusive education. Challenges such as data privacy, algorithmic bias, overreliance on automated systems, and the digital divide are critically analyzed. The paper concludes with recommendations for educators, policymakers, and developers to ensure ethical implementation, teacher training, and the alignment of AI tools with pedagogical goals. The findings underscore the potential of digital and AI-powered assessment systems in revolutionizing English language education by promoting learner autonomy, equity, and academic excellence.
This is an Open Access Research distributed under the terms of the Creative Commons Attribution License (www.creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any Medium, provided the original work is properly cited.
© 2025, Singh, S. & Singh, H.
Received: May 20, 2025; Revision Received: June 17, 2025; Accepted: June 21, 2025
Article Overview
ISSN 2348-5396
ISSN 2349-3429
18.01.349.20251302
10.25215/1302.349
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Published in Volume 13, Issue 2, April-June, 2025
