INTEGRATING AI-POWERED TOOLS IN ONE-ON-ONE MENTORING MODEL IN LANGUAGE EDUCATORS' PROFESSIONAL DEVELOPMENT

Abstract

This paper explores the integration of AI-powered tools into one-on-one mentoring models for language educators' professional development. The strategic use of AI technology can enhance the quality, efficiency, and impact of mentorship, ultimately improving language teaching and learning outcomes. The traditional one-on-one mentoring model for language educators' professional development faces limitations in scalability and personalization. Integrating AI-powered tools can address these challenges, offering a more effective and efficient approach. By leveraging AI-powered tools, mentors and mentees can access data-driven insights, personalized support, and streamlined communication, leading to more effective professional development and improved learners' outcomes. Mentors can improve mentees' teaching skills by offering individualized assistance, instant feedback, and data-driven insights by utilising AI's potentials. This paper argues for AI-powered tools, proposes a framework for implementing AI-infused mentoring, applying Bandura's Social Learning Theory (SLT) and discusses challenges and recommendations.