决策科学进化趋势 教育研究 从模拟和游戏到大数据分析和生成人工智能
Ikpe Justice Akpan1, Rouzbeh Razavi1, Asuama A Akpan2
1Department of Information Systems and Business Analytics, Kent State University, Kent, OH, USA.
Big data
|February 28, 2025
概括
决策科学 (DSC) 已经显著发展,人工智能和数据分析成为关键技能. 未来的教育必须整合生成性AI (GenAI),同时应对道德挑战.
科学领域:
- 决策科学 (DSC) 是一种决定科学.
- 多学科的研究和教育.
背景情况:
- 在复杂,不确定的系统中,DSC有助于做出明智的选择.
- 它整合了各种不同的决策工程和改进方法.
- 这项研究考察了25年的DSC教育和研究演变.
研究的目的:
- 分析决策科学教育和研究中的进化趋势和创新.
- 绘制和评估25年来DSC研究的主题,智力和社会结构.
主要方法:
- 文献学元数据分析.
- 科学绘图技术. 科学绘图技术.
- 用于评估研究结构的文本分析.
主要成果:
- 确定了关键技能:知识管理,决策支持系统,数据包裹分析,模拟和人工智能 (AI).
- 新兴的关键领域:数据分析框架 (大数据,机器学习,商业智能,数据挖掘,可视化).
- 教育中的趋势:虚拟/在线学习,计算机模拟和游戏;采用AI代理和生成AI (GenAI).
结论:
- DSC教育和研究反映了实际进展,强调数字化转型.
- 将GenAI整合到DSC教育中即将到来,这既带来了机遇,也带来了挑战 (学术诚信,道德,法律问题).
- 未来的DSC教育必须主动整合GenAI并应对相关挑战.
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