TriQuest:An AI Copilot-Powered Platform for Interdisciplinary Curriculum Design

2025-10-03

AI Summary

Interdisciplinary instruction faces practical bottlenecks, including difficulties in knowledge integration and time-intensive lesson planning, while existing tools lack disciplinary depth and pedagogical alignment. This study proposes an AI-driven interdisciplinary lesson plan generation platform that innovatively integrates large language models with domain-specific knowledge graphs to establish an intelligent knowledge fusion mechanism and a human-AI collaborative review process—enabling semantic linking of cross-disciplinary concepts and creative lesson plan generation. The platform features a visual interactive interface supporting automated lesson plan generation and iterative optimization. In an empirical study involving 43 in-service teachers, course design efficiency improved by 75% on average, lesson plan quality scores increased by 41%, and both cognitive load and subject-matter expertise requirements were significantly reduced. The work delivers a reusable technical pathway and practical paradigm for deploying AI in education.

Technology Category

• Humans and AI: Planning and Decision Support for Human-Machine Teams
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Application Domains: Humanities & Computational Social Science

Application Category

• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

Interdisciplinary teaching is a cornerstone of modern curriculum reform, but its implementation is hindered by challenges in knowledge integration and time-consuming lesson planning. Existing tools often lack the required pedagogical and domain-specific depth.We introduce TriQuest, an AI-copilot platform designed to solve these problems. TriQuest uses large language models and knowledge graphs via an intuitive GUI to help teachers efficiently generate high-quality interdisciplinary lesson plans. Its core features include intelligent knowledge integration from various disciplines and a human-computer collaborative review process to ensure quality and innovation.In a study with 43 teachers, TriQuest increased curriculum design efficiency by an average of 75% and improved lesson plan quality scores by 41%. It also significantly lowered design barriers and cognitive load. Our work presents a new paradigm for empowering teacher professional development with intelligent technologies.

Problem

• Addressing knowledge integration challenges in interdisciplinary teaching
• Reducing time-consuming lesson planning for curriculum design
• Overcoming lack of pedagogical depth in existing tools

Innovation

• Uses large language models for knowledge integration
• Employs knowledge graphs via intuitive GUI interface
• Implements human-computer collaborative review process