Role of Artificial Intelligence in Transforming Faculty Members Practices and Engagement in ELT

Description

This research provides a critical examination of the technological frontier within Sudanese higher education. While AI integration in English Language Teaching (ELT) is well-documented in the Global North, this study addresses the empirical gap regarding the pedagogical, infrastructural, and ethical landscapes of Sudanese universities. By centering on faculty at Nile Valley and Dongola Universities, the study moves beyond theoretical abstraction to illustrate how educators in developing contexts navigate the "double-edged sword" of AI to enhance learner autonomy and instructional efficiency. Research Framework and Hypotheses The study is built upon the hypothesis that AI tools catalyze a paradigm shift in the educator's role, moving from traditional content delivery toward technology-mediated mentorship. Key assumptions include: Transformational Impact: AI significantly mitigates administrative burdens while improving the precision of assessment.Learner Engagement: AI-driven tools provide individualized, dynamic learning paths that surpass traditional classroom capabilities. Contextual Barriers: Success depends on institutional readiness and is inversely related to infrastructural limitations. Methodology Dr. Adlan employed a mixed-methods design to ensure statistical breadth and qualitative depth. The Quantitative Phase utilized a 25-item questionnaire with 50 ELT instructors to identify correlations between AI use and teaching efficiency. The Qualitative Phase involved phenomenological, semi-structured interviews with 10–15 participants, capturing "lived experiences" regarding data privacy, cultural appropriateness, and the risks of technological over-reliance. Findings and Insights The results reveal a state of "optimistic caution." While 47% of instructors view AI as transformative and 85% recognize efficiency gains—including a 65% reduction in administrative tasks—the "digital divide" remains a formidable barrier. Fifty-five percent of participants cited hardware and internet issues as primary obstacles, and only 45% felt their institutions were prepared for full implementation. This highlights a gap between high "human capital" readiness (80% desire training) and lagging physical infrastructure. Academic and Policy Contribution The study provides a strategic roadmap for ELT in resource-constrained environments by:Redefining TPACK: Evidence shows how the Technological Pedagogical Content Knowledge framework must adapt to developing contexts.Informing Policy: It urges policymakers to prioritize ethical, inclusive frameworks to prevent increased educational inequality.Empowering Faculty: By identifying a 60% shift toward fostering learner autonomy, it validates the academic’s evolving role as a facilitator of digital literacy.Ultimately, this research serves as a clarion call for contextually relevant AI integration, ensuring the future of Sudanese English education remains both technologically advanced and human-centered.

Steps to reproduce

The methodology of this study is rooted in a mixed-methods research design that purposefully blends a quasi-experimental quantitative component with a phenomenological qualitative approach to capture a comprehensive view of AI integration in Sudanese ELT. The primary instrument for data collection was a dual-layered system: first, a structured questionnaire consisting of 25 closed-ended items administered to 50 ELT instructors at Nile Valley and Dongola Universities to quantify perceptions of efficiency and engagement; and second, a semi-structured interview protocol featuring 20 open-ended questions conducted with a subset of 10–15 participants to explore the "lived experiences" and ethical anxieties of the faculty. The research protocol followed a rigorous sequence of stratified random sampling for the surveys and purposive sampling for the interviews, ensuring a representative cross-section of teaching experience (2–15 years) and academic disciplines (General English to Literature). All qualitative data underwent a strict transcription and thematic analysis protocol, while quantitative responses were analyzed to identify the 47% positive attitude toward AI, ensuring that the final findings were grounded in both statistical significance and authentic human narrative.

Institutions

• Nile Valley University

  Khartoum, Khartoum

Categories

Licence