Reorienting Teacher and Lecturer Competencies in the Era of Deep Learning and Generative Artificial Intelligence in the Transformation of 21st-Century Learning
Abstract
This study explores the reorientation of teacher and lecturer competencies in the era of deep learning and generative AI as a response to 21st-century learning transformations. Rapid AI advancements are reshaping educational practices, learning environments, and educator roles, requiring competency frameworks beyond traditional pedagogy. Using a Systematic Literature Review (SLR) of 32 Q1-Q4 international journal articles (2019-2024), the study examines AI-based learning trends, digital pedagogy, learning analytics, and ethical challenges. Findings indicate that educator competencies must be reoriented across four dimensions: pedagogical, professional, social, and ethical. Pedagogical competence focuses on higher-order thinking, adaptive digital teaching, and authentic assessment. Professional competence emphasizes AI literacy, data-driven instruction, and continuous development. Social competence highlights digital communication, collaboration, and emotional engagement. Ethical competence ensures academic integrity, data privacy, and responsible AI use. The study proposes a conceptual model for AI-oriented educator competency and offers policy recommendations for sustainable professional development. It contributes theoretically by advancing discourse on AI-driven educational transformation and practically by guiding policymakers, institutions, and teacher education programs in adapting to the digital learning era.
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