Journal of Computing in Higher Education

, Volume 28, Issue 3, pp 389–405 | Cite as

A study on the use of a metadata schema for characterizing school education STEM lessons plans by STEM teachers

  • Panagiotis ZervasEmail author
  • Eleftheria Tsourlidaki
  • Yiwei Cao
  • Sofoklis Sotiriou
  • Demetrios G. Sampson
  • Nils Faltin


Online labs (OLs) constitute digital educational tools which can have a significant role in supporting science, technology, engineering and mathematics (STEM) teachers in their daily teaching practice. Designing STEM lessons supported by specific OLs is a challenging task and thus, it is useful for STEM teachers to be able to share their lesson plans in a way that these can be effectively searched by others. The most common way to facilitate this process is (a) to characterize the lesson plans with appropriately selected educational metadata and (b) to build a web repository that collects the metadata records of the lesson plans (following a common metadata schema) and offers search and retrieval functionalities. In our previous work, a metadata schema that can be used for characterizing STEM lesson plans supported by OLs has been proposed. The scope of this paper is to complement the findings of our previous work and present the technical implementation of the proposed metadata schema via a web-based repository, namely the Go-Lab repository and a study on the real usage of the metadata schema’s elements through the analysis of the lesson plans’ metadata records that have been published to this repository by STEM teachers.


School STEM education Inquiry-based learning Online lab Web-based repository Metadata schema Lesson plan 



The work presented in this paper has been partially funded by the European Commission in the context of the Go-Lab project (Grant Agreement No. 317601) under the Information and Communication Technologies (ICT) theme of the 7th Framework Programme for R&D (FP7). This document does not represent the opinion of the European Commission, and the European Commission is not responsible for any use that might be made of its content.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


  1. Anderson, L. W. (Ed.), Krathwohl, D. R. (Ed.), Airasian, P.W., Cruikshank, K. A., Mayer, R. E., Pintrich, P. R., Raths, J., & Wittrock, M. C. (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom’s taxonomy of educational objectives. New York: Longma.Google Scholar
  2. Balamuralithara, B., & Woods, P. C. (2009). Virtual laboratories in engineering education: The simulation lab and remote lab. Computer Applications in Engineering Education, 17(1), 108–118.CrossRefGoogle Scholar
  3. Battigelli, S., & Sugliano, A. M. (2009). Lesson plan archiviation: Metadata and Web 2.0 applications. Journal of e-Learning and Knowledge Society, 5(3), 59–67.Google Scholar
  4. Cao, Y., Govaerts, S., Dikke, D., Faltin, N., & Gillet, D. (2014). Helping each other teach: Design and realisation of a social tutoring platform. In Journal of Immersive Education (JiED)proceedings of 4th European immersive education summit, immersive education initiative, Austria.Google Scholar
  5. Creswell, J. W. (2008). Research design: Qualitative, quantitative, and mixed methods approaches (3rd ed.). Thousand Oaks, CA: Sage.Google Scholar
  6. Dagienė, V., & Kubilinskienė, S. (2010). Technology-based lesson plans: Preparation and description. Informatics in Education-An International Journal, 9(2), 217–228.Google Scholar
  7. De Jong, T., Linn, M. C., & Zacharia, Z. C. (2013). Physical and virtual laboratories in science and engineering education. Science, 340(6130), 305–308.CrossRefGoogle Scholar
  8. De Jong, T., Sotiriou, S., & Gillet, D. (2014). Innovations in STEM education: The Go-Lab federation of online labs. Smart Learning Environments, 1(1), 1–16.CrossRefGoogle Scholar
  9. Dikke, D., Tsourlidaki, E., Zervas, P., Cao, Y., Faltin, N., Sotiriou, S., & Sampson, D (2014). GoLabz: Towards a federation of online labs for inquiry-based science education at school. In Proceedings of the international conference on education and learning (EDULEARN14), pp. 3238–3248.Google Scholar
  10. Dong, L., Marshall, J., & Wang, J. (2009). A web-based collaboration environment for k-12 math and science teachers. In Proceedings of the 39th IEEE conference on frontiers in education (FIE’09), pp. 1–6.Google Scholar
  11. Geelan, D. R., & Fan, X. (2014). Teachers using interactive simulations to scaffold inquiry instruction in physical science education. In J. Gilbert & B. Eilam (Eds.), Science Teachers’ use of visual representations (pp. 249–270). Dordrecht: Springer.Google Scholar
  12. Gomes, L., & Bogosyan, S. (2009). Current trends in remote laboratories. IEEE Transactions on Industrial Electronics, 56(12), 4744–4756.CrossRefGoogle Scholar
  13. Govaerts, S., Cao, Y., Vozniuk, A., Holzer, A., Zutin, D. G., Ruiz, E. S. C., Bollen, L., Manske, S., Faltin, N., Salzmann, C., Tsourlidaki, E., & Gillet., D. (2013). Towards an online lab portal for inquiry-based stem learning at school. In Proceedings of the international conference on web-based learningICWL 2013, (pp. 244–253). Springer, Berlin.Google Scholar
  14. Harlen, W. (Ed.). (2010). Principles and big ideas of science education. Herts: Association for Science Education.Google Scholar
  15. Heintz, M., Law, E. L.-C., Govaerts, S., Holzer, A., & Gillet, D (2014). Pdot: Participatory design online tool. In CHI ‘14 extended abstracts on human factors in computing systems (CHI EA ‘14). ACM, New York, NY, pp. 2581–2586.Google Scholar
  16. Heintz, M., Law, E. L. C., Manoli, C., Zacharia, Z., & van Riesen, S. A. (2015). A survey on the usage of online labs in science education: Challenges and implications.Google Scholar
  17. IEEE Learning Technology Standards Committee (LTSC). (2005). Final standard for learning object metadata. IEEE Learning Technology Standards Committee. Accessed 21 December 2015.
  18. Ochoa, X., & Duval, E. (2009). Automatic evaluation of metadata quality in digital repositories. International Journal on Digital Libraries, 10(2–3), 67–91.CrossRefGoogle Scholar
  19. Pedaste, M., Mäeots, M., Siiman, L. A., de Jong, T., van Riesen, S. A., Kamp, E. T., et al. (2015). Phases of inquiry-based learning: Definitions and the inquiry cycle. Educational research review, 14, 47–61.CrossRefGoogle Scholar
  20. Renear, A. H., Sacchi, S., & Wickett, K. M. (2010). Definitions of dataset in the scientific and technical literature. Proceedings of the American Society for Information Science and Technology, 47(1), 1–4.CrossRefGoogle Scholar
  21. Sayary, A. M. A., Forawi, S. A., & Mansour, N. (2015). STEM education and problem-based learning. In R. Wegerif, L. Li, & J. Kaufman (Eds.), The Routledge international handbook of research on teaching thinking (pp. 357–368). NY: Routledge.Google Scholar
  22. Tsourlidaki, E., Zervas, P., Sotiriou S., & Sampson, D. (2015). An investigation with European school teachers on how to characterize virtual and remote labs. In Proceedings of the 6th IEEE international conference on engineering education towards excellence and innovation 2015 (EDUCON2015). Google Scholar
  23. Van Es, R., & Koper, R. (2006). Testing the pedagogical expressiveness of IMS LD. Educational Technology & Society, 9(1), 229–249.Google Scholar
  24. Wang, C.-Y., Wu, H.-K., Lee, S. W.-Y., Hwang, F.-K., Chang, H.-Y., Wu, Y.-T., et al. (2014). A review of research on technology-assisted school science laboratories. Educational Technology & Society, 17(2), 307–320.Google Scholar
  25. Wiggins, G., & McTighe, J. (1999). Understanding by design. Alexandria, VA: Association for Supervision and Curriculum Development.Google Scholar
  26. Zervas, P., Kalamatianos, A., Tsourlidaki, E., Sotiriou, S., & Sampson, D. (2014). A methodology for organizing virtual and remote laboratories. In D. G. Sampson, D. Ifenthaler, J. M. Spector, & P. Isaias (Eds.), Digital systems for open access to formal and informal learning (pp. 235–255). Berlin: Springer.Google Scholar
  27. Zervas, P., Sergis, S., Sampson, D., & Fyskilis, S. (2015a). Towards competence-based learning design driven remote and virtual labs recommendations for science teachers. Technology, Knowledge and Learning, 20(2), 185–199.CrossRefGoogle Scholar
  28. Zervas, P., Tsourlidaki, E., Sotiriou, S., & Sampson, D. (2015a). Towards a metadata schema for characterizing lesson plans supported by virtual and remote labs in school education. In Proceedings of the IADIS 12th international conference on cognition and exploratory learning in digital age (CELDA2015). Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Panagiotis Zervas
    • 1
    Email author
  • Eleftheria Tsourlidaki
    • 2
  • Yiwei Cao
    • 3
  • Sofoklis Sotiriou
    • 2
  • Demetrios G. Sampson
    • 1
    • 4
  • Nils Faltin
    • 3
  1. 1.Information Technologies InstituteCentre for Research and Technology HellasThessalonikiGreece
  2. 2.Ellinogermaniki AgogiPallini AttikisGreece
  3. 3.IMC Information Multimedia Communication AGSaarbrückenGermany
  4. 4.School of EducationCurtin UniversityPerthAustralia

Personalised recommendations