基于混合软计算技术和DEMATEL方法的AI在高等教育中应用的关键决定因素探究
An Exploration of the Key Determinants of AI Adoption in Higher Education Based on Hybrid Soft Computing and DEMATEL
杨平乐 1赵来军 1李惠永 1周立欣 1张勤阁2
作者信息
- 1. 上海理工大学,上海 200093
- 2. 江苏科技大学,江苏张家港 215600
- 折叠
摘要
当前,采用适合的人工智能技术发展高等教育领域的教与学是一项必要的任务.高等教育人工智能技术的开发和实施涉及许多因素,这些纷繁的因素会使高等教育决策者感到困惑,并可能导致错误判断.为了澄清相关问题并说明各因素之间的因果关系,本研究提出一种混合软计算技术(即模糊粗糙集理论与蚁群优化算法)和 DEMATEL方法(决策实验室分析法),帮助高等教育决策者在管理战略中捕捉实现理想高等教育人工智能应用水平所需的最佳模型.
Abstract
It is a necessary task to develop teaching and learning in the field of higher education by adopting suitable AI technologies at present.There are many factors involved in the development and implementation of AI technologies in higher education,and thesevaried factors can confuse higher education decision makers and may lead to misjudgments.In order to clarify the relevant issues and illustrate the causal relationships among the factors,this study proposes a hybrid soft computing technique(i.e.,Fuzzy Rough Set Theory and Ant Colony Optimization Algorithm)and the DEMATEL method(Decision Laboratory Analysis Methodology).The proposed technique can help higher education decision makers to capture the optimal model needed to achieve the desired level of higher education AI application in their management strategies.
关键词
人工智能/高等教育/模糊粗糙集理论/DEMATEL方法Key words
artificial intelligence/higher education/fuzzy rough set theory/DEMATEL method引用本文复制引用
出版年
2024
NETL
NSTL
万方数据