AI Enhanced Assessment and Feedback in English Language and Literature

Abstract

Abstract AI significantly enhances English language and literature teaching by providing instant, personalized feedback on writing (grammar, style, clarity via tools like Grammar), pronunciation and comprehension, freeing teachers for higher-level instruction. Tools like ChatGPT generate varied materials, while AI tutors offer 24/7 support, adapting difficulty and providing detailed analysis, fostering self-regulated learning, cultural sensitivity, and improved outcomes through data-driven insights, though teacher verification of AI outputs remains crucial. English literature and linguistics have long served as foundational disciplines in humanities education, cultivating critical analysis, linguistic proficiency, and cultural interpretation. This study conducts a comprehensive content analysis focusing on the landscape of assessment and feedback types in education, with a particular emphasis on the advantages and limitations of AI tools in this domain. The study meticulously categorizes and analyses the diverse array of assessment and feedback types prevalent in educational settings, examining traditional methods alongside emerging AI-driven approaches. By synthesizing existing literature and empirical studies, the paper identifies and evaluates the advantages that AI tools offer in assessing and providing feedback to learners, shedding light on their potential to enhance educational practices. Furthermore, the content analysis delves into a detailed examination of the AI tools that have predominantly been utilized in educational fields, mapping out their functionalities, features, and impact on teaching and learning processes. Through a systematic coding process, the research identifies common themes and trends in the use of AI tools for assessment and feedback within educational contexts, offering insights into their effectiveness and usability. In addition to highlighting the benefits of AI tools, the paper critically assesses the limitations and challenges associated with their implementation in educational settings. By conducting a comparative content analysis between human assessment practices and AI-based assessment methods, the study aims to provide a nuanced understanding of the strengths and weaknesses of each approach. Moreover, the research explores the perceptions of teachers regarding AI assessment and feedback tools, analyzing their attitudes, concerns, and expectations towards the integration of AI technology in educational assessment practices.

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