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STEM Education with a Better Understanding

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Ján Gunčaga, Faculty of Education, Comenius University in Bratislava, Slovakia


According Breiner et al. (2012) acronym STEM (Science, Technology, Engineering, and Mathematics) has become very frequently word among many stakeholders in the school policy. According El Nagdi et al. (2018) real-world problems are complex and inherently multidisciplinary. Tackling such problems requires not just the ability to use design thinking or inquiry, but also the ability to choose the best approach or combination of approaches that capitalizes on the strengths of each way of thinking. From this perspective, STEM encompasses the content, skills, and ways of thinking of each of the disciplines, but it also includes an understanding of the interactions between the disciplines and the ways they support and complement each other.
It is important for each STEM discipline in education to build notions with better understanding by each learner. For example in the case of mathematics Wittmann (1998) states, that like the education of other subjects, mathematics education requires the crossing of boundaries between disciplines and depends on results and methods of considerably diverse fields, including mathematics, pedagogy, sociology, psychology, history of science and others. The core of mathematics education also covers following activities:

  • analysis of mathematical activities and of mathematical ways of thinking,
  • development of local theories (for example, on mathematizing, problem solving, proving and practising skills),
  • exploration of possible contents that focusses on making them accessible to learners,
  • critical examination and justification of contents in view of the general goals of mathematics teaching,
  • research into the pre-requisites of learning and into the teaching/learning processes,
  • development and evaluation of substantial teaching units, classes of teaching units and curricula,
  • development of methods for planning, teaching, observing and  analysing lessons, and
  • inclusion of the history of mathematics education.

Similar situation takes place in education of other subjects related to STEM school subjects (physics, biology or chemistry education).

If we like to arrange that learners better understand the notions during the STEM education, we will have to find the ways how to work with understanding barriers by learners and different kind of obstacles (see Mayer, 2005 and Sierpinska, 1987, 1990). It is forced to respect the process of gaining knowledge in education (see Hejný et al., 2006).

Visualisation through educational software can play an important role in this context (see Fuchs, Plangg, 2018 and Bender, Schreiber, 1985). Opens source software such as GeoGebra (see Hohenwarter, Lavicza, 2007) is a good tool for preparing different applets for STEM education (Micheuz et al., 2007).


This special issue looks for contributions that exemplify the different approaches to STEM education (to build notions with respect to the process of gaining knowledge).Therefore modern ICT technologies for visualisation and simulations are used (Eckerdal et al., 2006). Case studies that analyse educational and methodological approaches to STEM content are of particular interest (students and pupils difficulties – possible boards in the understanding in STEM education). Research using quantitative and qualitative empirical methods such as field notes, surveys, mixed methods or students’ projects in STEM education is welcomed equally.

Topics include but are not limited to:

    • Understanding of notions in STEM Education from curricular and organizational point of view,
    • STEM Education with better understanding in primary and secondary level,
    • Teacher Training in STEM Education,
    • Content education („Stoffdidaktik“) in STEM school subjects (Wittmann, 2014 and Vollrath, 1989),
    • Inquiry-based learning, using ICT in STEM education to support motivation and activities of learners (Weigand, Weth, 2002).


This special issue will publish original research papers (approx. 4,000-8,000 words). Papers submitted must not have been published previously or under consideration for publication, though they may represent significant extensions of prior work. All submitted papers will go through a rigorous single-blind peer-review process (with at least two reviewers).
Before completing their manuscript, authors should carefully read over the journal’s Author Guidelines, which are located at https://www.degruyter.com/view/supplement/s25447831_Instruction_for_Authors.pdf.
Prospective authors should submit an electronic copy of their complete manuscript using the journal’s submission system: http://www.editorialmanager.com/openedu/.


Deadline for article submission: March 1, 2019 (via journal submission system http://www.editorialmanager.com/openedu).
Planned publication: September 2019 (articles will be published upon being accepted on an ongoing basis).


Bender; P.  & Schreiber, A. (1985). Operatrive Genese der Geometrie. HPT, B.G. Wien, Stuttgart: Teubner.

Breiner, J. M., Harkness, S. S., Johnson, C. C. &  Koehler, C. M. (2012). What Is STEM? A Discussion About Conceptions of STEM in Education and Partnerships. School Science and Mathematics, 112, 3-11. doi: 10.1111/j.1949-8594.2011.00109.x

Eckerdal, A., McCartney, R., Moström, J. E., Ratcliff, M., Sanders, K., Zander, C. (2006). Putting Treshold Concepts into Context in Computer Science Education. In: Proceedings of the 11th  Annual Conference on Innovation and Technology in Computer Science Education, Bologna, Italy, 103-107

El Nagdi, M. , Leammukda, F.  & Roehrig G.  (2018).  Developing identities of STEM teachers at
emerging STEM schools. International Journal of STEM Education, 5:36 doi: 10.1186/s40594-018-0136-1

Fuchs, KJ.& Plangg, S. (2018), Computer Algebra Systeme in der Lehrer(inen)bildung. Münster: WTM Verlag.

Hejný, M et al. (2006). Creative Teaching in Mathematics. Prague: Charles University.

Hohenwarter, M., & Lavicza, Z. (2007). Mathematics teacher development with ICT: towards an International GeoGebra Institute. In: D. Küchemann (Ed.), Proceedings of the British Society for Research into Learning Mathematics. 27(3), 49-54. University of Northampton, UK: BSRLM.

Meyer, J.H.F. & Land, R. (2005).  Threshold Concepts and Troublesome Knowledge (2): linkages to ways of thinking and practising within the disciplines  Higher Education,  49, 373-388. doi: 10.1007/s10734-004-6779-5

Micheuz, P., Fuchs, KJ. & Landerer, C. (2007). Mission Possible - Computers in “Anyschool”.  Informatics, Mathematics and ICT: a 'golden triangle'. Boston: International Federationfor Information Processing, 10 . ISBN 13:978-0-615-14623-2.

Sierpinska, A. (1990). Some remarks on understanding in mathematics. For the Learning of Mathematics, Nr. 3, 24-41.

Sierpinska A. (1987).Humanities students and epistemological obstacles related to limits. Educational Studies in Mathematics, ·Nr. 18, 371-397.

Vollrath, H.-J. (1989). Funktionales Denken. Journal für Mathematikdidaktik 10(19), 3-37.

Weigand, H-G. & Weth,  (2002). Computer im Mathematikunterricht. Heidelberg: Springer Spektrum.

Wittmann E.C. (1998), Mathematics Education as a ‘Design Science’. In: Sierpinska A., Kilpatrick J. (eds). Mathematics Education as a Research Domain: A Search for Identity. New ICMI Studies Series, vol 4. Dordrecht: Springer.

Wittmann, E.C. (2014), Die Ideologie der Selbstbeschränkung in der Mathematikdidaktik. GDM-Mitteilungen, 96, 15-18.