Using data science for sustainable development in higher education

Author:

Leal Filho Walter12ORCID,Eustachio João Henrique Paulino Pires2ORCID,Nita (Danila) Andreea Corina3ORCID,Dinis Maria Alzira Pimenta45ORCID,Salvia Amanda Lange6ORCID,Cotton Debby R. E.7ORCID,Frizzo Kamila8ORCID,Trevisan Laís Viera9ORCID,Dibbern Thais10ORCID

Affiliation:

1. Department of Natural Sciences Manchester Metropolitan University Manchester UK

2. European School of Sustainability Science and Research (ESSSR) Hamburg University of Applied Sciences Hamburg Germany

3. Department of Economics, Economic Informatics, and Business Management, Faculty of Economics Administration and Business Administration, Stefan cel Mare University of Suceava Suceava Romania

4. UFP Energy, Environment and Health Research Unit (FP‐ENAS) University Fernando Pessoa (UFP) Porto Portugal

5. Fernando Pessoa Research, Innovation and Development Institute (FP‐I3ID) University Fernando Pessoa (UFP) Porto Portugal

6. Graduate Program in Civil and Environmental Engineering University of Passo Fundo Passo Fundo Brazil

7. SCION Research Group Plymouth Marjon University Plymouth UK

8. School of Administration Federal University of Santa Maria Santa Maria Brazil

9. School of Administration Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil

10. Department of Science and Technology Policy University of Campinas Campinas Brazil

Abstract

AbstractDespite the abundance of studies focused on how higher education institutions (HEIs) are implementing sustainable development (SD) in their educational programmes, there is a paucity of interdisciplinary studies exploring the role of technology, such as data science, in an SD context. Further research is thus needed to identify how SD is being deployed in higher education (HE), generating positive externalities for society and the environment. This study aims to address this research gap by exploring various ways in which data science may support university efforts towards SD. The methodology relied on a bibliometric analysis to understand and visualise the connections between data science and SD in HE, as well as reporting on selected case studies showing how data science may be deployed for creating SD impact in HE and in the community. The results from the bibliometric analysis unveil five research strands driving this field, and the case studies exemplify them. This study can be considered innovative since it follows previous research on artificial intelligence and SD. Moreover, the combination of bibliometric analysis and case studies provides an overview of trends, which may be useful to researchers and decision‐makers who wish to explore the use of data science for SD in HEIs. Finally, the findings highlight how data science can be used in HEIs, combined with a framework developed to support further research into SD in HE.

Publisher

Wiley

Subject

Development,Renewable Energy, Sustainability and the Environment

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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