Revista Sextante

Generative and Agentive AI Integration and Pedagogical Competence among ESL Teachers in Public and Private Colleges: A Comparative Survey

Muhammad Tasleem Alam

PhD Scholar NCBA&E Alhamra University, Multan

Dr. Muhammad Mahmood Ahmad Shaheen

Associate Professor Department of English Govt. Sadiq Egerton Graduate College Bahawalpur

Irum Altaf

M.Phil Scholar Department of English NCBA&E (Alhamra University), Bahawalpur

Maria Fareed

Visiting Lecturer Department of English Govt Sadiq College Women University, Bahawalpur

Dr. Muhammad Arfan Lodhi

Higher Education Department, Punjab

Keywords: Generative AI, agentive AI, ESL teachers, pedagogical competence, institutional support

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Abstract

The growing use of generative and agentive artificial intelligence (AI) in education necessitates a closer examination of teachers’ AI literacy, instructional practices, pedagogical competence, and institutional preparedness. This study investigates the integration of generative and agentive AI among English as Second Language (ESL) teachers in public and private colleges of Punjab, Pakistan, with particular attention to differences in reported competencies, professional attitudes, and institutional support. A quantitative, cross-sectional comparative survey design was employed. Data were collected from 80 randomly selected college teachers, comprising 40 public-sector and 40 private-sector teachers, from colleges in Bahawalpur, Rahim Yar Khan, Lodhran, and Multan. A researcher-developed questionnaire administered through Google Forms measured six domains: AI knowledge and literacy, generative AI integration, agentive AI integration, AI-supported pedagogical competence, motivation and professional attitudes, and institutional resources and support. The analytical procedure comprised frequencies, percentages, means, and standard deviations, alongside independent-samples comparisons to examine sectoral differences in teachers’ responses. The comparative analysis indicates higher reported scores among private-sector teachers in AI literacy, generative and agentive AI integration, pedagogical competence, and institutional support. The most pronounced differences concern generative AI use and institutional resources, whereas professional attitudes are comparatively similar across the two groups. Agentive AI integration receives lower scores than generative AI integration in both public and private sectors, suggesting that teachers’ familiarity with content-generating applications does not necessarily extend to delegated, multistep instructional workflows. These patterns highlight the need to distinguish technological access and willingness to adopt AI from the pedagogical knowledge required for its responsible application. The study recommends sustained, practice-oriented teacher development, equitable access to digital resources, clear institutional guidance, and human oversight of AI-supported instruction. Because the cross-sectional design relies on self-reported data, the findings do not establish causal relationships or independently verify classroom performance. Further research using classroom observations and performance-based assessments could provide a more comprehensive understanding of teachers’ demonstrated AI competence.