Goal-oriented framework for AI-empowered curriculum design
In adult education, traditional curriculum design faces challenges like limited expertise and time constraints, especially with the need for customized, interdisciplinary content that achieves comprehensive learning outcomes quickly. To overcome these issues, we introduced the Goal-oriented Framewor...
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Nanyang Technological University
2024
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sg-ntu-dr.10356-1815052025-01-02T10:18:25Z Goal-oriented framework for AI-empowered curriculum design Wang, Hang Vun Chan Hua, Nicholas College of Computing and Data Science ASCHVUN@ntu.edu.sg Computer and Information Science In adult education, traditional curriculum design faces challenges like limited expertise and time constraints, especially with the need for customized, interdisciplinary content that achieves comprehensive learning outcomes quickly. To overcome these issues, we introduced the Goal-oriented Framework for AI Empowered Curriculum Design. This framework uses AI to streamline curriculum development, making it efficient and adaptable while ensuring content remains relevant and comprehensive. It incorporates ’learning by argumentation’ to deepen concept understanding. The framework’s effectiveness was evaluated through two methods: firstly, by expert curriculum designers who assessed its readiness and adaptability, practicability, content and curriculum enhancement, and efficiency; and secondly, through feedback from 241 students trained using this framework, focusing on its ability to meet individual learning needs and enhance the overall training experience. This dual evaluation approach provides a thorough assessment of the framework, highlighting its potential to transform curriculum development in adult education and professional training. Doctor of Philosophy 2024-12-09T00:29:06Z 2024-12-09T00:29:06Z 2024 Thesis-Doctor of Philosophy Wang, H. (2024). Goal-oriented framework for AI-empowered curriculum design. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/181505 https://hdl.handle.net/10356/181505 10.32657/10356/181505 en This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). application/pdf Nanyang Technological University |
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Computer and Information Science Wang, Hang Goal-oriented framework for AI-empowered curriculum design |
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In adult education, traditional curriculum design faces challenges like limited expertise and time constraints, especially with the need for customized, interdisciplinary content that achieves comprehensive learning outcomes quickly. To overcome these issues, we introduced the Goal-oriented Framework for AI Empowered Curriculum Design. This framework uses AI to streamline curriculum development, making it efficient and adaptable while ensuring content remains relevant and comprehensive. It incorporates ’learning by argumentation’ to deepen concept understanding.
The framework’s effectiveness was evaluated through two methods: firstly, by expert curriculum designers who assessed its readiness and adaptability, practicability, content and curriculum enhancement, and efficiency; and secondly, through feedback from 241 students trained using this framework, focusing on its ability to meet individual learning needs and enhance the overall training experience. This dual evaluation approach provides a thorough assessment of the framework, highlighting its potential to transform curriculum development in adult education and professional training. |
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Vun Chan Hua, Nicholas |
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Vun Chan Hua, Nicholas Wang, Hang |
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Thesis-Doctor of Philosophy |
author |
Wang, Hang |
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Wang, Hang |
title |
Goal-oriented framework for AI-empowered curriculum design |
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Goal-oriented framework for AI-empowered curriculum design |
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Goal-oriented framework for AI-empowered curriculum design |
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Goal-oriented framework for AI-empowered curriculum design |
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Goal-oriented framework for AI-empowered curriculum design |
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goal-oriented framework for ai-empowered curriculum design |
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Nanyang Technological University |
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2024 |
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https://hdl.handle.net/10356/181505 |
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