Large Language Models for Education: A survey and outlook

Research / Other Relevance: 7/10 255 cited 2024 paper

This is a comprehensive survey paper that systematically reviews the technological applications of large language models (LLMs) in K-12 education across multiple dimensions including student assistance, teacher support, adaptive learning, and commercial tools, while also identifying datasets, benchmarks, risks, and future research opportunities.

The advent of large language models (LLMs) has ushered in a new era of possibilities in the realm of education. This survey article summarizes recent progress in the application of LLMs in educational settings from multiple perspectives, including student and teacher assistance, adaptive learning, and commercial tools. Additionally, it systematically reviews technological advancements in each area, compiles related datasets and benchmarks, and identifies the risks and challenges associated with

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1 General reasoning 2.1 Pedagogical knowledge 2.2 Pedagogy of generated outputs 2.3 Pedagogical interactions 3.1 Content knowledge 4.1 Scoring and grading 4.2 Feedback with reasoning 5 Ethics and bias

Tool Types

AI Tutors 1-to-1 conversational tutoring systems.

Personalised Adaptive Learning Systems that adapt content and difficulty to individual learners.

Teacher Support Tools Tools that assist teachers — lesson planning, content generation, grading, analytics.

Large Language Models for Education: A survey and outlook

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