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Curriculum Planning for Independent Majors with Large Language Models

  • Hyeon Jin
  • , Chaewon Yoon
  • , Hyun Je Song*
  • *Corresponding author for this work
  • Jeonbuk National University

Research output: Contribution to conferenceConference paperpeer-review

Abstract

The independent major, also known as an individualized studies major or self-designed major, is a program for students whose academic goals cannot be met within standard department-specific curricula. This program enables students to design a customized, interdisciplinary course of study that aligns with their unique learning objectives. However, designing such a curriculum from a wide range of courses while ensuring alignment with these objectives and satisfying prerequisite requirements can be challenging. Additionally, students’ learning objectives may initially be vague, overly broad, or lack coherence across disciplines, making it difficult to design the curriculum. In this paper, we propose a curriculum planning method that leverages prerequisite relationships in traditional department-specific curricula and the capabilities of large language models (LLMs) to support independent majors. The proposed method first refines students’ learning objectives through LLM reasoning, then identifies relevant departments to obtain department-specific curricula and select core courses for each. These selected courses are expanded based on prerequisite relationships, combined into a structured curriculum, and transformed to comply with educational policies and accreditation standards. Experimental results from quantitative evaluations of previously implemented curricula and qualitative analyses by curriculum design experts demonstrate that the proposed method outperforms existing recommendation-based curriculum planning approaches.

Original languageEnglish
Title of host publicationArtificial Intelligence in Education - 26th International Conference, AIED 2025, Proceedings
EditorsAlexandra I. Cristea, Erin Walker, Yu Lu, Olga C. Santos, Seiji Isotani
PublisherSpringer Science and Business Media Deutschland GmbH
Pages463-476
Number of pages14
ISBN (Print)9783031984167
DOIs
StatePublished - 2025
Event26th International Conference on Artificial Intelligence in Education, AIED 2025 - Palermo, Italy
Duration: 2025.07.222025.07.26

Publication series

NameLecture Notes in Computer Science
Volume15878 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference26th International Conference on Artificial Intelligence in Education, AIED 2025
Country/TerritoryItaly
CityPalermo
Period25.07.2225.07.26

Keywords

  • Curriculum planning
  • Independent major
  • Large language model

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