Teaching and learning in the context of emerging artificial intelligence technologies integrating emotional intelligence and accumulation of cognitive skills

The rapid evolution of artificial intelligence (AI) is reshaping education, transforming how educators teach, how students learn, and how learning itself occurs. This study explores integration of AI with emotional intelligence (EI) and cognitive skill development to foster more personalised and effective learning. While consensus on this synergy is still ongoing, recent research suggests their convergence can improve both academic outcomes and emotional well-being [1]. We propose that reducing reliance on large language models (LLMs) and emphasising direct, in-class cognitive engagement leads to deeper learning. AI tools such as natural language processing and adaptive systems personalise instruction by responding to learner needs, monitoring progress, and dynamically adjusting pathways [3]. However, AI’s role should extend beyond content delivery. Integrating EI enables systems and educators to better interpret and respond to students’ emotional states, enhancing engagement and motivation. EI –defined as the ability to perceive, understand, and manage emotions– is critical for educational success. Its inclusion in AI-assisted learning supports holistic approaches that foster empathy, resilience, and social awareness [4]. This involves learning environments that consider not only what students know but also how they feel. AI-supported educators can personalise interventions to meet both emotional and cognitive needs, improving inclusivity and student-teacher relationships. Yet, challenges persist. Cognitive offloading, algorithmic bias, and reduced human interaction must be addressed [5]. Over-reliance on AI may limit critical thinking. Thus, AI tools should encourage –rather than replace– cognitive effort, promoting creativity, reflection, and collaboration. To support this framework, a preliminary pilot is underway with 17 Master’s students in a Machine Learning course. It combines in-class instruction with AI-assisted learning and emotional scaffolding. Assessment focuses on student engagement, participation quality, emotional self-awareness (via surveys), and metacognitive growth over sessions. In conclusion, this study advocates a balanced educational model where AI complements -rather than replaces- the educator’s role [2]. The convergence of AI, EI, and cognitive development offers a promising path towards adaptive, empathetic, and future-ready education.