Is Prompting All You Need?

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Authors: Myint Swe Khine, László Bognár, Liu Yang
Cited by: 0
References: 31

Abstract

This chapter explores how large language models (LLMs) and AI can transform education, emphasizing the need to move beyond basic prompting. While prompting is an important entry point, it can limit users with less technical expertise or complex tasks. The focus is on the advanced capabilities of LLMs, such as independent reasoning, adaptive learning, and dynamic interactions, which extend far beyond prompting. It integrates these capabilities with educational theories like the Socratic method, dialogic inquiry, and argumentation, grounding them in sound pedagogy. Additionally, it offers strategies for effectively integrating LLMs into education to empower educators and learners, fostering critical thinking, collaboration, and deeper understanding. The chapter bridges theoretical and practical perspectives, creating a robust framework for LLMs' application in educational contexts.

Fields of Study & Subjects

Artificial Intelligence in Education Artificial Intelligence in Healthcare and Education Intelligent Tutoring Systems and Adaptive Learning

Publication details

Journal / source
Advances in computational intelligence and robotics book series
Pages
243–260
Publication date
15 January 2026
Document type
Book chapter