Educational Practices and Algorithmic Framework for Promoting Sustainable Development in Education by Identifying Real-World Learning Paths

Author:

Liu Tian-Yi1ORCID,Jiang Yuan-Hao234ORCID,Wei Yuang234ORCID,Wang Xun1,Huang Shucheng1,Dai Ling5ORCID

Affiliation:

1. School of Computer, Jiangsu University of Science and Technology, Zhenjiang 212100, China

2. Lab of Artificial Intelligence for Education, East China Normal University, Shanghai 200062, China

3. Shanghai Institute of Artificial Intelligence for Education, East China Normal University, Shanghai 200062, China

4. School of Computer Science and Technology, East China Normal University, Shanghai 200062, China

5. Department of Education, East China Normal University, Shanghai 200062, China

Abstract

Utilizing big data and artificial intelligence technologies, we developed the Collaborative Structure Search Framework (CSSF) algorithm to analyze students’ learning paths from real-world data to determine the optimal sequence of learning knowledge components. This study enhances sustainability and balance in education by identifying students’ learning paths. This allows teachers and intelligent systems to understand students’ strengths and weaknesses, thereby providing personalized teaching plans and improving educational outcomes. Identifying causal relationships within knowledge structures helps teachers pinpoint and address learning issues, forming the basis for adaptive learning systems. Using real educational datasets, the research introduces a multi-sub-population collaborative search mechanism to enhance search efficiency by maintaining individual-level superiority, population-level diversity, and solution-set simplicity across sub-populations. A bidirectional feedback mechanism is implemented to discern high-quality and low-quality edges within the knowledge graph. Oversampling high-quality edges and undersampling low-quality edges address optimization challenges in Learning Path Recognition (LPR) due to edge sparsity. The proposed Collaborative Structural Search Framework (CSSF) effectively uncovers relationships within knowledge structures. Experimental validations on real-world datasets show CSSF’s effectiveness, with a 14.41% improvement in F1-score over benchmark algorithms on a dataset of 116 knowledge structures. The algorithm helps teachers identify the root causes of students’ errors, enabling more effective educational strategies, thus enhancing educational quality and learning outcomes. Intelligent education systems can better adapt to individual student needs, providing personalized learning resources, facilitating a positive learning cycle, and promoting sustainable education development.

Funder

Postgraduate Research & Practice Innovation Program of Jiangsu Province

Special Foundation for Interdisciplinary Talent Training in “AI Empowered Psychology/Education”

Doctoral Research and Innovation Foundation of the School of Computer Science and Technology, East China Normal University

Publisher

MDPI AG

Reference68 articles.

1. UNESCO (2021). Reimagining Our Futures Together: A New Social Contract for Education, Educational and Cultural Organization of the United Nations.

2. Intelligent Tutoring Systems in Education: A Systematic Review of Usage, Tools, Effects and Evaluation;Alrakhawi;J. Theor. Appl. Inf. Technol.,2023

3. Gligorea, I., Cioca, M., Oancea, R., Gorski, A.-T., Gorski, H., and Tudorache, P. (2023). Adaptive Learning Using Artificial Intelligence in E-Learning: A Literature Review. Educ. Sci., 13.

4. Knowledge Discovery: Methods from Data Mining and Machine Learning;Shu;Soc. Sci. Res.,2023

5. Zhou, Z., Liu, G., and Tang, Y. (2023). Multi-Agent Reinforcement Learning: Methods, Applications, Visionary Prospects, and Challenges. arXiv.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3