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The present study examines the impact of Culturally Responsive Pedagogy (CRP) on the language proficiency and classroom engagement of ESL students in a multilingual classroom at NUML Peshawar Campus, Pakistan. A mixed-methods approach was used that integrated quantitative and qualitative analyses to assess the efficacy of CRP in ESL classrooms. The statistical gains in four skills, that is, speaking, writing, reading, and listening skills, were evaluated using standardized tests like pre-test, formative assessments and post-test data. To qualitatively explore students' perceptions, semi-structured interviews were conducted. The findings showed notable improvements in students’ language proficiency. The paired t-tests indicated statistically significant gains across all language skills. Qualitative data further substantiated the transformative role of CRP activities, such as multilingual storytelling, cultural debates, and folk wisdom integration, in promoting classroom engagement and affirming students’ cultural identities. We also came across a few challenges, that is, difficulties in linguistic transitions and institutional constraints. By demonstrating that CRP has pivotal potential, the present study adds to the expanding knowledge of ESL education in Pakistan. It not only acknowledges the linguistic and cultural diversity in ESL classrooms but also offers practical recommendations and insights into how to modify culturally inclusive teaching practices to meet the best interests of ESL students for future research.

This paper examines the experiences of South Asian Muslims in America after the 9/11 attacks, from the perspective of novel The Submission. It also analyzes the effects of American Exceptionalism among Muslim and non-Muslim characters. By using Martin Lipset's idea of a distinct national identity of America, the study contrasts pre-and post-9/11 attitudes towards Muslims in America. Just before the attacks, there had been a rise in implicit prejudice against Muslims, but immediately after them, overt expressions of hatred, discrimination, and violence became prevalent. The protagonist, Mohammad Khan, became a symbol of injustices faced by South Asian Muslims, which ranged from denial of civil rights to being evicted, threatened, and ultimately, to forced self-exile. Asma and others like her, met tragic consequences, creating growing mistrust among Muslims against their fellow Americans. This would allow through analysis of these experiences a reflection of some of the implicit, complex interactions between Islamophobia and American Exceptionalism and the ways in which South Asian Muslims were kept marginalized after the attack on 9/11 in America.

The rapid pace of development and integration of cybernetics and biotechnology into human life renders anthropocentric attempts increasingly absurd. By decentering the human as 'the subject', the cyberpunk genre, with its frequent employment of virtual reality, cybernetics, and artificial intelligence, engages in the construction of a fluid posthuman identity. The current study aims to investigate how Blade Runner 2049 handles the development of posthuman identity. In order to achieve this goal, the data have been analysed qualitatively through textual analysis using insights from Haraway's posthuman theory. The findings indicate that by rejecting the strict anthropocentric distinctions between human and nonhuman/replicant through the exploration of biological, psychological, and spiritual factors, the movie is at ease promoting a posthuman identity. Furthermore, it cautions against human experimentation with biotechnology that could result in the annihilation of humans by their own inventions.

Chatbots are now ubiquitous across fields like education, customer support, and healthcare. Despite significant advances in both artificial intelligence (AI) and natural language processing (NLP), linguistic inaccuracies: somehow termed “slip-ups”, remain present in the answers provided by Chatbots. These errors can be divided into lexical and grammatical, which impair the user experience and the reliability of the Chatbots. The current study analyses the linguistic errors committed by five Chatbots— ChatGPT, Copilot, Google Gemini, Perplexity, and Zapier Central—in eight different categories: adjectives, verbs, articles, and vocabulary range. Whether attributed to limitations in the training data of Chatbots, a lack of lexical embeddings, or a simplistic model of syntactic processing, previous studies have identified these factors as the key causes of linguistic errors. Nonetheless, transformer-based architectures including GPT and BERT have demonstrated improvements but continue to suffer from grammar consistency and contextual correctness issues, highly pronounced in multilingual and culturally rich applications. This study utilised a comparative approach analyzing responses of 200 prompts across eight linguistic categories. Errors were categorised as lexical or grammatical and analyzed according to their frequency, severity, and distribution. We used statistical methods such as ANOVA to find significant differences in chatbot performance in relation to features. The results indicate that the biggest challenges were seen with vocabulary range and adjectives, demonstrating these students' restrictions in lexical range and descriptiveness. However, question words had the lowest number of errors, which suggests strength in forming interrogative structures. Vocabulary range, verbs, and articles showed significant variation depending on the chatbot used, with statistically significant ANOVA results, and most features presented stable results with different Chatbots like orthography and question words. With the growing severity, the differences in the types of errors became more pronounced, we did take note of this difference between Google Gemini, that had a smaller ratio of major errors vs ChatGPT and Perplexity. Overall, this study highlights the importance of language-specific enhancements, particularly in vocabulary variety and grammatical alignment. For improved understanding, utilization of state-of-the-art NLP technologies, varied training data, programming live audit/error correction features may be required.

The study aims to examine the role of metaphors in shaping and conveying poetic iconicity, and to explore how these metaphors reflect or obscure the poet’s perceptions and worldview. The study draws on the theoretical framework of Blending Theory proposed by Tunner and Fauconnier (1995), along with Hiraga’s (2004) analytical model of metaphor and iconicity in poetic texts. Adopting a qualitative approach, the study employs close reading as its primary method of analysis. In particular, metaphors related to war and peace are analyzed to uncover deeper insights into the region’s socio-political realities. The metaphoric and iconic interpretations in this study are extended to the socio-political landscape of Khyber Pakhtunkhwa as depicted in the selected poems. The findings contribute to the growing body of research in cognitive poetics by highlighting the intricate relationship between metaphor and poetic iconicity within socio-political discourse.