Department of English

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    Evaluating AI’s Effectiveness in Content Analysis: A Linguistic Comparison of Automated and Human Text Interpretation in the Aurat March Discourse on Social Media
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Esha Shakoor; CIIT/SP24-MEL-003/LHR; Dr. Javaria Farooqui; LHR TP 10048
    This study evaluates the effectiveness of AI in analyzing the emotional, cultural, and ideological aspects of feminist discourse in Pakistan. It compares human and AI interpretations of online discussions related to the Aurat March on Facebook, Instagram, and YouTube. Using qualitative methodology supported by relational content analysis (RCA) and Technofeminism (Wajcman, 2004) as a theoretical framework, the research examines how human and the ChatGPT-5 model interpret emotional tone, sarcasm and moral framing in multilingual comments written in English, Urdu and Roman Urdu. The results shows that while the AI efficiently detects explicit emotions in English, it fails in understanding sarcasm, irony and moral expressions embedded in Urdu and Roman Urdu. AI misinterpreted phrases with cultural and religious connotations, such as “khuda ka wasta hai” or “drama karna,” while human interpreters recognized their emotional and contextual depth. This shows the limitations of AI's ability to deal with culturally specific discourse. The study supports Technofeminist arguments that technology reflects the social and gender biases of its developers. The gap in AI highlights the persistence of algorithmic bias and the dominance of Western linguistic frameworks in language models. This research contributes to studies of feminist discourse and AI ethics by proposing a hybrid model that integrates human interpretation with AI-assisted sentiment analysis. This approach combines the efficiency of AI with the sensitivity of human understanding of context. The study concludes that although AI can quickly process large data sets, it cannot yet replace human understanding when analyzing emotionally and culturally complex feminist communication. The study calls for the development of AI systems that take into account cultural, gender and context aspects, and are able to interpret various linguistic facts in digital spaces.
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    Lost in AI: Analyzing Students' Linguistic Agency and the Usage of Artificially Generated Writing Tools?
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) IRAM HASSAN; CIIT/SP24-MEL-005/LHR; Dr. Javaria Farooqui; LHR TP 10050
    This study explores the impact of Artificial Intelligence (hitherto referred to as Al) generated writing tools on students' confidence, independence, and linguistic agency in academic writing, and examines how teachers' evaluation strategies of Al-generated content shape students' writing behavior. The increasing prevalence of AI tools (ChatGPT, Grammarly and QuillBot), required an exploration of their impacts on student's learning experiences, perceptions of authorship, and assessment processes. This study employed a mixed-methods design that included quantitative surveys with 200 university students and 50 university professors, as well as qualitative design to analyze the open-ended responses. Linguistic Agency Theory and Formative Assessment Theory is used in this study to illustrate how students employ control over their written work and how teacher's feedback influences student learning outcomes while using Al. The findings of this study shows that frequent use of Al tools improves students' self-confidence, and increase writing fluency, especially grammar as they possessed varying levels of independence and linguistic agency. While some were able to evaluate Al suggestions critically and maintain their voice, others relied on Al too heavily. Educators can support or hinder student agency based on how they provide feedback to students. Ethical issues regarding originality, academic integrity were identified in this study, particularly in Pakistani context, and multilingual higher education. This study extends our understanding of how AI contributes in academic writing, and also provide practical suggestions for ethical usage policies, and evaluation practices with technological support. These findings are helpful for educators, policymakers, and institutions with the goal of supporting the integration of Al tools into the educational environment and to enhance student learning experiences while preserving students' critical thinking skills and authorship.