Date
Publisher
arXiv
Artificial Intelligence (AI) holds transformative potential in education, enabling personalized learning, enhancing inclusivity, and encouraging creativity and curiosity. In this paper, we explore how Large Language Models (LLMs) can act as both patient tutors and collaborative partners to enhance education delivery. As tutors, LLMs personalize learning by offering step-by-step explanations and addressing individual needs, making education more inclusive for students with diverse backgrounds or abilities. As collaborators, they expand students' horizons, supporting them in tackling complex, real-world problems and co-creating innovative projects. However, to fully realize these benefits, LLMs must be leveraged not as tools for providing direct solutions but rather to guide students in developing resolving strategies and finding learning paths together. Therefore, a strong emphasis should be placed on educating students and teachers on the successful use of LLMs to ensure their effective integration into classrooms. Through practical examples and real-world case studies, this paper illustrates how LLMs can make education more inclusive and engaging while empowering students to reach their full potential.
Study at a glance
- Question: How can AI act as a tutor and collaborative partner to support student learning?
- Setting and data: Not stated in the abstract
- Method: Case studies and practical examples
Why it matters
To fully realize AI's transformative potential, large language models cannot be used merely to provide direct solutions. Instead, they must guide students in developing resolving strategies and finding learning paths together.
Key findings
- Large language models can personalize learning and increase inclusivity by providing step-by-step explanations tailored to diverse student backgrounds and abilities.
- As collaborative partners, large language models can help students tackle complex, real-world problems and co-create innovative projects.
- Large language models are most beneficial when guiding students to develop problem-solving strategies rather than providing direct solutions.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
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