Examining Attitudes and Constructs in AI-Based Digital Knowledge Ensemble for Teaching–Learning in the 4th Industrial Revolution

This mixed-method study examines the integration of Artificial Intelligence-based Digital Knowledge Ensemble (DKE) into education for the 4th Industrial Revolution, employing both systematic literature review and descriptive analysis. The research explores educators’ perspectives on the benefits and challenges of Artificial Intelligence in teaching and learning. While educators anticipate increased efficiency, personalized learning, and improved engagement, concerns about losing the human touch, data privacy, job displacement, and bias in assessments emerge. The results underscore the necessity for an ethical and cautious approach, emphasizing transparency, human oversight, and ongoing evaluation to ensure artificial Intelligence enhances education without compromising student wellbeing and teacher–student connections. The study recommends prioritizing adaptable tools, investing in educator training, implementing robust data security, and fostering collaboration to address ethical concerns and refine its use in education.