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@article{191400,
        author = {Mr. Mehulkumar Agrawal},
        title = {Faculty 2.0: Developing English Teachers to an AI-Based Higher Education System},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {12},
        number = {no},
        pages = {1373-1377},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=191400},
        abstract = {The sphere of higher education is entering the period when AI influences nearly all teaching and learning dimensions. The process of content delivery, grading, analytics, and even student advising are becoming mediated by AI systems that adjust to the needs of a person and monitor learning patterns in real-time. In the case of English language teachers, it is not just a change of technology, but it is a change of the essence of their job. They can no longer do the work of primary content transmitters but must design, select, and manage learning spaces in which AI will play a supporting role and human knowledge lead to interpretation, engagement and ethical judgment.
This paper presents a Faculty 2.0 model which reinvents teacher development in this type of ecosystem. The model is constructed on three strands, which are interrelated. The first one is technical fluency: educators should get used to writing support and automatic feedback tools based on AI, generative content creation, assessment analytics, and adaptive platforms. The second one is to redesign pedagogy that enables learning to be more individualized and iterative because adaptive systems can exploit learning when intentionally implemented into teaching. The third is concerned with ethical and data-literate judgment, which is required in classrooms when the use of algorithmic systems impacts the feedback, performance, and learning opportunities. According to the research on professional learning, the teachers develop best when the development is long-term, practice-based, and mentorship or coaching supported (Darling-Hammond, Hyler, and Gardner, 2017). Simultaneously, the research of AI in education shows that the properly designed systems may offer personalized learning sequences and constant formative feedback in cases when educators are aware of how to combine them (Holmes, Bialik, and Fadel, 2019).
In the English language teaching, previous research in the field of computer-assisted language learning presents an advantageous background. Digital technology can enhance the volume of the learner, more complicated language production and provision of space in which meaningful interaction can occur-when the teachers appropriately form tasks and understand when intervention is necessary (Warschauer, 2000). Based on this knowledge, the Faculty 2.0 model focuses on the co-design labs in which instructors collaborate with instructional designers to test AI-enhanced activities. It also encompasses micro-credentials, which are stackable to confirm a certain set of competencies in regard to AI pedagogy, and alignment of policy with internationally accepted standards of ethics of AI in education (UNESCO, 2021).
The study is a mixed-method research design. It starts with a Delphi study among teacher-educators and EdTech experts in order to test the competency framework. It is then followed by a multi-sited quasi-experimental pilot which monitors the differences in the teaching practices and student learning in institutions. The data is collected using observations of the classroom, AI-powered analytics, and semi-structured interviews, which trace the advantages and limitations that a teacher faces.
The project will provide an approved competency framework on the English faculty in AI-supported settings, experience of practical implications of model of professional growth that actually change classroom practice, and guidance on policies to be adopted by institutions in ethical and scalable implementation. Fundamentally, the paper states that Faculty 2.0 is not about the implementation of new tools to the current workflow. It concerns the professional identity of English teachers being changed to become able to guide, shape, and humanize the future of the AI-based higher education.},
        keywords = {.},
        month = {},
        }