Digital Smart Citizenship Competence Development with a Cyber-Physical Learning Approach Supported by Internet of Things Technologies

  • Yacine AtifEmail author
  • Stylianos Sergis
  • Demetrios Sampson


The concept of Smart Cities is an emerging social and technology innovation, attracting large public and private investments at a global scale, arguing for the effective exploitation of digital technologies to drive quality of living and sustainable growth. However, these investments mainly focus in smart technical infrastructure, and they have yet to be systematically complemented with efforts to prepare the human capital of future smart cities in terms of core competences anticipated for exploiting their potential. In this context, this chapter introduces “cyber-physical learning” as a generic overarching model to cultivate Digital Smart Citizenship competence. The proposed approach exploits the potential of Internet of Things technologies to create authentic blended and augmented learning experiences. Proof-of-concept case studies of the proposed cyber-physical learning approach, to develop smart household energy management competences, are presented and discussed as a field of application. Finally, the findings of a survey with university students for eliciting their attitudes to engage with cyber-physical learning environments for enhancing their digital smart citizenship competences are reported.


Digital Smart Citizenship competences Smart City learning Syberphysical learning Internet of things 



The first author’s contribution in this work has been partially funded by Västra Götaland Region, as part of the research project on smart grid Kraftsamling Smarta Nät 2015–2016 (dnr MN 39-2015), and partially supported by SP Sveriges Tekniska Forskningsinstitut AB as well as ELIQ AB (energy management company). The second and third authors’ contribution in this work has been partially funded by the Greek General Secretariat for Research and Technology, under the Matching Funds 2014–2016 for the EU project “Inspiring Science: Large Scale Experimentation Scenarios to Mainstream eLearning in Science, Mathematics and Technology in Primary and Secondary Schools” (Project Number: 325123). Finally, the third author’s contribution in this work is part of Curtin’s contribution to the “STORIES—Stories of Tomorrow: Students Visions on the Future of Space Exploration” under the European Commission’s Horizon 2020 Program, H2020-ICT-22-2016–2017 “Information and Communication Technologies: Technologies for Learning and Skills” (Project Number: 731872). This document reflects the views only of the authors and it does not represent the opinion of the Sveriges Tekniska Forskningsinstitut AB, ELIQ AB, Greek General Research Secretariat, the European Commission, or Curtin University. The Sveriges Tekniska Forskningsinstitut AB, ELIQ AB, Greek General Research Secretariat, the European Commission, and Curtin University cannot be held responsible for any use that might be made of its content.


  1. 1.
    Dameri, R. P. (2013). Searching for smart city definition: A comprehensive proposal. International Journal of Computers & Technology, 11(5), 2544–2551.Google Scholar
  2. 2.
    UN. (2014). UN finds world’s population is increasingly urban with more than half living in urban areas today and another 2.5 billion expected by 2050. Retrieved from
  3. 3.
    Clemitshaw, G. (2014). Children, citizenship and environment: Nurturing a democratic imagination in a changing world. By Bronwyn Hayward. British Journal of Educational Studies, 62(1), 85–86.CrossRefGoogle Scholar
  4. 4.
    Hammad, R., & Ludlow, D. (2016). Towards a smart learning environment for smart city governance. In Proceedings of the 9th International Conference on Utility and Cloud Computing (pp. 185–190).Google Scholar
  5. 5.
    Atif, Y., Sergis, S., Sampson, D., & Mathiason, G. (2017). A Cyberphysical learning approach for digital smart citizenship competence development. In Proceedings of the 26th International Conference on World Wide Web (pp. 397–405).Google Scholar
  6. 6.
    Bork, D., Fill, H., Karagiannis, D., Miron, E., Tantouris, N., & Walch, M. (2015). Conceptual Modelling for smart cities: A teaching case. Interaction Design & Architectures Journal, Special Issue on Smart City Learning: Opportunities and Challenges, 27, 10–28.Google Scholar
  7. 7.
    Jin, J., Gubbi, J., Marusic, S., & Palaniswami, M. (2014). An information framework for creating a smart city through internet of things. IEEE Internet of Things Journal, 1(2), 112–121.CrossRefGoogle Scholar
  8. 8.
    Nikolov, R., Shoikova, E., Krumova, M., Kovatcheva, E., Dimitrov, V., & Shikalanov, A. (2016). Learning in a Smart City environment. Journal of Communication and Computer, 13, 338–350.CrossRefGoogle Scholar
  9. 9.
    Cocchia, A. (2014). Smart and digital city: A systematic literature review. In R. P. Dameri & C. Rosenthal-Sabroux (Eds.), Progress in IS (pp. 13–43). New York: Springer.Google Scholar
  10. 10.
    Kyriazopoulou, C. (2015). Smart City technologies and architectures—A literature review. In Proceedings of the International Conference on Smart Cities and Green ICT Systems (pp. 1–12)Google Scholar
  11. 11.
    Anthopoulos, D. L. G. (2015). Understanding the Smart City domain: A literature review. In M. P. Rodríguez-Bolívar (Ed.), Transforming City governments for successful smart cities (pp. 9–21). Cham: Springer.CrossRefGoogle Scholar
  12. 12.
    Gil-Garcia, J. R., Pardo, T. A., & Nam, T. (2015). What makes a city smart? Identifying core components and proposing an integrative and comprehensive conceptualization. Information Polity, 20(1), 61–87.CrossRefGoogle Scholar
  13. 13.
    Cartelli, A. (2012). From smart cities to smart environment: Hints and suggestions for an ecology of the internet. International Journal of Digital Literacy and Digital Competence, 3(4), 65–71.CrossRefGoogle Scholar
  14. 14.
    Liu, D., Huang, R., & Wosinski, M. (2017). Development of smart cities: Educational perspective. In D. Liu, R. Huang, & M. Wosinski (Eds.), Smart learning in smart cities (pp. 3–14). Singapore: Springer.CrossRefGoogle Scholar
  15. 15.
    Giovannella, C., Martens, A., & Zualkernan, I. (2016). Grand challenge problem 1: People centered smart “cities” through Smart City learning. In J. Eberle, K. Lund, P. Tchounikine, & F. Fischer (Eds.), Grand challenge problems in technology-enhanced learning II: MOOCs and beyond (pp. 7–12). New York: Springer.CrossRefGoogle Scholar
  16. 16.
    Andone, D., Holotescu, C., & Grosseck, G. (2014). Learning communities in smart cities. Case studies. In Proceedings of the IEEE International Conference Web and Open Access to Learning (pp. 1–4).Google Scholar
  17. 17.
    European Union. (2016). The European digital competence framework for citizens. Retrieved from Scholar
  18. 18.
    Gianni, F., & Divitini, M. (2015). Technology-enhanced Smart City learning: A systematic mapping of the literature. Interaction Design and Architecture, 27, 28–43.Google Scholar
  19. 19.
    Seitamaa-Hakkarainen, P., Kangas, K., Raunio, A. M., & Viilo, M. (2012). Architecture project: City plan, home and users–children as architects. Procedia-Social and Behavioral Sciences, 45, 21–31.CrossRefGoogle Scholar
  20. 20.
    Wolff, A., Kortuem, G., & Cavero, J. (2015). Towards smart city education. In Proceedings of the 4th IFIP Conference on Sustainable Internet and ICT for Sustainability (pp. 1–3).Google Scholar
  21. 21.
    Rehm, M., Stan, C., Wøldike, N. P., & Vasilarou, D. (2015). Towards Smart City Learning: Contextualizing geometry learning with a Van Hiele inspired location-aware game. In Proceedings of the International Conference on Entertainment Computing (pp. 399–406).Google Scholar
  22. 22.
    Ulrich, C., & Nedelcu, A. (2013). Let’s play as architects in the city! Use of mobile technologies during the pilot phase. In Proceedings of the eLearning and Software for Education Conference (pp. 167–172).Google Scholar
  23. 23.
    Gaved, M., Jones, A., Kukulska-Hulme, A., & Scanlon, E. (2012). A citizen-centred approach to education in the smart city: Incidental language learning for supporting the inclusion of recent migrants. International Journal of Digital Literacy and Digital Competence, 3(4), 50–64.CrossRefGoogle Scholar
  24. 24.
    Hudson, L., Kortuem, G., Wolff, A., & Law, P. (2016). Smart Cities MOOC: Teaching citizens how to co-create smart cities. In Proceedings of the 4th International Conference on ICT for Sustainability (pp. 1–8).Google Scholar
  25. 25.
    Williamson, B. (2015). Educating the smart city: Schooling smart citizens through computational urbanism. Big Data & Society, 2(2).Google Scholar
  26. 26.
    Rudd, J., Davia, C., & Sullivan, P. (2009). Education for a smarter planet: The future of learning. Retrieved from
  27. 27.
    Microsoft Education. (2013). Educated cities. Retrieved from
  28. 28.
    Microsoft (2013). Microsoft CityNext: Technology solutions for smart cities. Retrieved from
  29. 29.
    Kadar, M. (2016). Smart learning environment for the development of Smart City applications. In Proceedings of the 8th International Conference on Intelligent Systems (pp. 59–64).Google Scholar
  30. 30.
    Shelton, T., Zook, M., & Wiig, A. (2015). The actually existing smart city. Cambridge Journal of Regions, Economy and Society, 8(1), 13–25.CrossRefGoogle Scholar
  31. 31.
    Gianni, F., Mora, S., & Divitini, M. (2016). IoT for Smart City learning—towards requirements for an authoring tool. In Proceedings of the First International Workshop on Smart Ecosystems Creation by Visual Design.Google Scholar
  32. 32.
    Mathew, S. S., Atif, Y., & El-Barachi, M. (2016). From the Internet of things to the web of things—Enabling by sensing as-a service. In Proceedings of the 12th IEEE International Conference on Innovations in Information Technology (pp. 1–6).Google Scholar
  33. 33.
    Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18(1), 32–42.CrossRefGoogle Scholar
  34. 34.
    Das, S. (2016). Personalise through the Internet of things. Retrieved from
  35. 35.
    Yang, L., Li, W., Ge, Y., Fu, X., Gravina, R., & Fortino, G. (2014). People-centric service for mHealth of wheelchair users in smart cities. In G. Fortino & P. Trunfio (Eds.), Internet of things based on smart objects (pp. 163–179). New York: Springer.CrossRefGoogle Scholar
  36. 36.
    Skinner, B. F. (1958). Teaching machines. Science, 128(3330), 969–977.CrossRefGoogle Scholar
  37. 37.
    Agarwal, S. (2014). Data mining: Data mining concepts and techniques. In Proceedings of the 2013 IEEE International Conference on Machine Intelligence and Research Advancement (pp. 203–207).Google Scholar
  38. 38.
    Eidenzon, D., & Pilipczuk, O. (2015). Multidimensional data visualization. In M. Khosrow-Pour (Ed.), Encyclopedia of information science and technology (3rd ed., pp. 1600–1610). Hershey PA: IGI Global.CrossRefGoogle Scholar
  39. 39.
    Zhao, H., & Seibert, S. E. (2006). The big five personality dimensions and entrepreneurial status: A meta-analytical review. Journal of Applied Psychology, 91(2), 259–271.CrossRefGoogle Scholar
  40. 40.
    Campillo, J., Wallin, F., & Vassileva, I. (2013). Economic impact of dynamic electricity pricing mechanisms adoption for households in Sweden. In Proceedings of the World Renewable Energy Congress (pp. 1–12).Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Yacine Atif
    • 1
    Email author
  • Stylianos Sergis
    • 2
  • Demetrios Sampson
    • 2
    • 3
  1. 1.Department of Information Technology, School of InformaticsUniversity of SkövdeSkövdeSweden
  2. 2.Department of Digital SystemsUniversity of PiraeusPiraeusGreece
  3. 3.School of Education, Curtin UniversityBentleyAustralia

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