Beyond the Classroom: Utilizing Large Language Models to Propel External Learning

External learning, occurring outside traditional classrooms, emphasizes learner autonomy, flexibility, lifelong learning, critical thinking, and networking. However, it also presents challenges such as limited structure, resource access issues, isolation, distractions, progress assessment difficulties, credibility recognition gaps, and technology barriers exacerbated by the digital divide. With new technologies and innovative methods constantly emerging in the world of education, one such recent development is the use of large language models as a facilitator of learning outside the classroom. To enhance the external learning experience, a workflow incorporating AI tools like Language Model Large (LLM) is proposed. This workflow spans goal setting, curriculum curation, interactive learning sessions, and progress tracking, leveraging LLM capabilities to personalize the learning journey, curate relevant resources, facilitate interactive engagement, and provide real-time feedback. This paper examines the utilization of LLM by presenting the application of LLM in different external learning scenarios.