A Decision Tool for Selecting a Sustainable Learning Technology Intervention

被引:0
|
作者
Raji, Maryam [1 ]
Zualkernan, Imran [2 ]
机构
[1] Amer Univ Sharjah, Engn Syst & Management, Sharjah, U Arab Emirates
[2] Amer Univ Sharjah, Comp Engn, Sharjah, U Arab Emirates
来源
EDUCATIONAL TECHNOLOGY & SOCIETY | 2016年 / 19卷 / 03期
关键词
Education; Learning technology interventions; Sustainability; Multi-criteria decision-making; Analytic network process; ONE LAPTOP; TELEVISION; ANP;
D O I
暂无
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Education is a basic human right. In pursuit of this right, governments in developing countries and their donors often invest scarce resources in educational initiatives that are sometimes not sustainable. This paper addresses the problem of selecting a sustainable learning technology intervention (LTI) for a typical developing country. By solving this problem, more sustainable LTIs can be selected for implementation; this will in turn improve the efficiency with which limited resources are utilised, thereby allowing greater access to education for all. The paper introduces a unique decision framework for project selection by combining "soft" and "hard" decision analysis techniques. The selection problem is modelled as a multi-criteria decision-making (MCDM) problem and a combination of the Future Search Conference technique and the Analytic Network Process (ANP) is used to develop a decision tool for selecting the most sustainable LTI for a developing country. Our analysis revealed that of the nine LTIs considered, school on wheels was the most sustainable LTI in the collective opinion of all the experts involved in this study.
引用
收藏
页码:306 / 320
页数:15
相关论文
共 50 条
  • [1] SELECTING A SUSTAINABLE LEARNING TECHNOLOGY INTERVENTION FOR DEVELOPMENT: AN ANALYTIC NETWORK PROCESS APPROACH
    Raji, Maryam
    Zualkernan, Imran
    [J]. 6TH INTERNATIONAL CONFERENCE OF EDUCATION, RESEARCH AND INNOVATION (ICERI 2013), 2013, : 4976 - 4983
  • [2] An integrated decision making approach for selecting a sustainable waste water treatment technology
    Narayanamoorthy, Samayan
    Brainy, J., V
    Sulaiman, Riza
    Ferrara, Massimiliano
    Ahmadian, Ali
    Kang, Daekook
    [J]. CHEMOSPHERE, 2022, 301
  • [3] DEVELOPMENT OF A DECISION-MAKING CHECKLIST TOOL TO SUPPORT SELECTING TECHNOLOGY IN DIGITAL HEALTH RESEARCH
    Nebeker, Camille
    Ellis, Rebecca Bartlett
    Weibel, Nadir
    Torous, John
    [J]. ANNALS OF BEHAVIORAL MEDICINE, 2019, 53 : S170 - S170
  • [4] MULTI-CRITERIA DECISION MAKING SUPPORT TOOL FOR FREIGHT INTEGRATORS: SELECTING THE MOST SUSTAINABLE ALTERNATIVE
    Simongati, Gyozo
    [J]. TRANSPORT, 2010, 25 (01) : 89 - 97
  • [5] A Network Analysis Model for Selecting Sustainable Technology
    Park, Sangsung
    Lee, Seung-Joo
    Jun, Sunghae
    [J]. Sustainability, 2015, 7 (10): : 13126 - 13141
  • [6] Erratum: Decision support tool for selecting fabrication parameters in stereolithography (International Journal of Advanced Manufacturing Technology)
    Giannatsis, J.
    Dedoussis, V.
    [J]. International Journal of Advanced Manufacturing Technology, 2007, 33 (7-8):
  • [7] Decision support tool for selecting fabrication parameters in stereolithography
    Giannatsis, J.
    Dedoussis, V.
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2007, 33 (7-8): : 706 - 718
  • [8] Decision support tool for selecting fabrication parameters in stereolithography
    J. Giannatsis
    V. Dedoussis
    [J]. The International Journal of Advanced Manufacturing Technology, 2007, 33 (7-8) : 719 - 719
  • [9] Decision support tool for selecting fabrication parameters in stereolithography
    J. Giannatsis
    V. Dedoussis
    [J]. The International Journal of Advanced Manufacturing Technology, 2007, 33 : 706 - 718
  • [10] Decision trees as a tool for selecting sows in commercial herds
    Hilgemberg, Joao Otavio
    Andretta, Ines
    Mariani, Alexandre Bonadiman
    Neimaier, Alisson
    Valk, Marcio
    Bittarello, Fernando
    Hilgemberg, Rafaela
    Lehnen, Cheila Roberta
    [J]. SCIENTIA AGRICOLA, 2024, 81