An 871 Response Survey Dataset on Public Perceptions of Education for Sustainable Development, Digital Competencies, and Industry 4.0
DOI:
https://doi.org/10.13052/srm2795-0514.015Keywords:
Fourth Industrial Revolution, Education for Sustainable Development, digital technologies, public perceptions, sustainable developmentAbstract
The progressive integration of digital technologies into education, together with the rising policy salience of sustainable development, has intensified the demand for datasets capable of sustaining interdisciplinary educational research. This paper presents a structured survey dataset documenting public perceptions of the relationships among Education for Sustainable Development (ESD), digital competencies, and the Fourth Industrial Revolution (Industry 4.0). Data were collected through an online questionnaire administered over seven consecutive days, yielding 871 valid responses and a curated dataset of 34 variables. These variables cover demographic characteristics, educational background, digital competencies, sustainability awareness, and perceptions of technology supported learning and sustainable development. The dataset combines categorical, binary, ordinal, and Likert scale measures, accommodating descriptive, correlational, multivariate, and predictive analyses. Its interdisciplinary scope and standardized coding make it a reusable resource for researchers, educators, and policymakers concerned with digital transformation, sustainability education, and educational innovation. The dataset further supports secondary analysis, cross national comparison, and the empirical validation of theoretical models linking ESD to Industry 4.0.
Downloads
References
Beiske, B. (2007). Research Methods. Uses and Limitations of Questionnaires, Interviews, and Case Studies. Economy.
Boynton, P. M., & Greenhalgh, T. (2004). Selecting, designing, and developing your questionnaire. BMJ, 328(7451), 1312–1315. https://doi.org/10.1136/bmj.328.7451.1312
Chawla, D., & Sondhi, N. (2011). Research Methodology. New Delhi.
Daniel, S. J. (2020). Education and the COVID-19 pandemic. Prospects, 49(1–2), 91–96. https://doi.org/10.1007/s11125-020-09464-3
Drennan, J. (2003). Cognitive interviewing: Verbal data in the design and pretesting of questionnaires. Journal of Advanced Nursing, 42(1), 57–63. https://doi.org/10.1046/j.1365-2648.2003.02579.x
Henry, G. T. (1990). Practical Sampling. Sage Publications.
Lambropoulos, I. (2019). Business Plan of a Company for the Expansion of the Activity of Selling Goods through Electronic Orders in a Branch of a Supermarket Company. Open University of Cyprus.
Li, G., Hou, Y., & Wu, A. (2017). Fourth Industrial Revolution: Technological drivers, impacts and coping methods. Chinese Geographical Science, 27(4), 626–637. https://doi.org/10.1007/s11769-017-0890-x
Paraskevopoulos, I. (1999). Interpersonal and Intrapersonal Adjustment Questionnaire. Athens.
Popović, A. (2020). Implications of the Fourth Industrial Revolution on sustainable development. Economics of Sustainable Development, 4(1), 45–60. https://doi.org/10.5937/ESD2001045P
Schwab, K. (2016). The Fourth Industrial Revolution. World Economic Forum.
Stathakopoulos, V. (2005). Market Research Methods. Athens.
Tsakanikas, A., & Athanassoulis, N. T. (2019). Greece 4.0 towards sustainable development goals. In Proceedings of the 12th Panhellenic Scientific Conference of Chemical Engineering. Athens.
Vardopoulos, I., & Salvati, L. (2026). Statistica multidimensionale: applicazioni per l’economia, l’architettura e le scienze. ISBN 9798195675202.
Wan, J., Cai, H., & Zhou, K. (2015). Industrie 4.0: Enabling technologies. In 2014 International Conference on Intelligent Computing and Internet of Things (ICIT). IEEE.
