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

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.本研究对苏丹高等教育领域的技术前沿展开批判性考察。尽管在全球北方地区，人工智能（AI）在英语语言教学（English Language Teaching，ELT）中的整合已有充分文献记载，但本研究填补了苏丹高校在教学法、基础设施与伦理生态维度的经验研究空白。研究以尼罗河谷大学与栋古拉大学的教职员工为研究中心，跳出理论抽象层面，阐明发展中地区的教育工作者如何驾驭AI这把“双刃剑”，以提升学习者自主性与教学效率。 研究框架与假设 本研究基于以下假设展开：AI工具将推动教育者角色发生范式转变，从传统的内容传授者转向技术介导的导师。核心假设包括： 1. 变革性影响：AI可显著减轻行政负担，同时提升评估精度。 2. 学习者参与度：AI驱动的工具可提供个性化、动态的学习路径，优于传统课堂模式。 3. 情境性障碍：AI应用的成功与否取决于院校准备程度，且与基础设施限制呈负相关。 研究方法 阿德兰博士采用混合研究设计，以兼顾统计广度与质性研究深度。量化阶段使用25题项问卷，对50名英语语言教学教师展开调研，以明确AI使用与教学效率间的相关性。质性阶段则开展现象学半结构化访谈，访谈对象为10至15名参与者，旨在捕捉其关于数据隐私、文化适配性以及技术过度依赖风险的亲历体验。 研究发现与洞见 研究结果呈现出“审慎乐观”的态势。47%的教师认为AI具有变革性意义，85%的教师认可其带来的效率提升——包括行政任务减少65%——但“数字鸿沟”仍是难以逾越的障碍。55%的参与者将硬件与网络问题列为主要阻碍，仅45%的教师认为所在院校已为全面落地AI做好准备。这凸显出较高的人力资本准备度（80%的教师希望接受培训）与滞后的实体基础设施之间的差距。 学术与政策贡献 本研究为资源受限环境下的英语语言教学提供了战略路线图，具体体现为： 1. 重塑技术教学法内容知识（Technological Pedagogical Content Knowledge，TPACK）：研究表明，该框架需适配发展中地区的情境。 2. 为政策制定提供参考：研究呼吁政策制定者优先制定伦理化、包容性的框架，以避免加剧教育不平等。 3. 赋能教职员工：研究证实有60%的教师转向培养学习者自主性，验证了教育者作为数字素养培育者的角色演变。 归根结底，本研究发出了契合本土情境的人工智能整合的强烈呼吁，确保苏丹英语教育的未来既能保持技术先进性，又不失人文关怀。