Belted Learning Model: A Competency-Based Framework for Developing Techno-Pedagogical Skills and Emotional Competence among Prospective Teachers in the Age of Artificial Intelligence

Abstract

The rapid advancement of digital technologies and artificial intelligence (AI) has significantly transformed educational practices across the globe. In contemporary classrooms, teachers are expected not only to possess strong pedagogical knowledge but also to demonstrate technological competence, emotional intelligence, adaptability, and collaborative skills. Traditional teacher education programs often focus on theoretical knowledge and academic achievement, providing limited opportunities for the systematic development of professional competencies required in modern educational settings. In response to these challenges, the Belted Learning Model (BLM) is proposed as an innovative competency-based framework that supports progressive learning through structured levels of mastery. Drawing inspiration from belt-ranking systems commonly used in skill-development disciplines, the model encourages prospective teachers to advance through clearly defined stages based on demonstrated competence rather than time spent in training. This conceptual paper examines the relevance of the Belted Learning Model in teacher education and discusses its potential to enhance techno-pedagogical skills and emotional competence among prospective teachers. The paper argues that the model aligns with current educational reforms, supports lifelong learning, and prepares future educators to meet the demands of AI-supported teaching environments. The study concludes that the Belted Learning Model can serve as a practical and sustainable framework for fostering holistic teacher development in the twenty-first century.

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