• Aneta Hybšová Charles University in Prague
  • Jimmie Leppink Maastricht University



Statistics education, cognitive load theory., course analysis, curriculum development, cognitive load theory


Statistics is considered to be an indispensable part of a wide range of curricula across the globe, natural science curricula included. Teachers and curriculum developers are typically confronted with four questions with regard to the role and position of statistics in a curriculum: (1) how to integrate statistics in the curriculum; (2) which topics to cover and in what detail; (3) how much time to allocate to statistics in a curriculum; and (4) how to organize a course and which study materials to select. This paper addresses these four questions through a case study: four curricula at Charles University, Prague, Czech Republic, are compared in terms of how they address these four questions. Placing this comparison in a framework of cognitive load theory and two decades of research inspired by this theory, this paper concludes with a number of guidelines for addressing the aforementioned four questions when designing a curriculum.


Ayres, P. (2001) ‘Systematic mathematical errors and cognitive load’, Contemporary Educational Psychology, vol. 26, no. 2, pp. 227-248.

Chráska, M. (2010) Metody pedagogického výzkumu: základy kvantitativního výzkumu, Prague: Grada.

Fidler, F., Cumming, G. (2010) ‘The new stats: attitudes for the 21st century’, in Osborne, J. W. (Ed.) Best Practices in Quantitative Methods, London: Sage Publications, pp. 1-12.

Gavora, P. (2010) Úvod do pedagogického výzkumu, Brno: Paido.

Havránek, T. (1993) Statistika pro biologické a lékařské vědy, Prague: Academia.

Hybšová, A. (2013) Biostatistika,

Kalyuga, S., Ayres, P., Chandler, P., Sweller, J. (2003) ‘The expertise reversal effect’, Educational Psychologist, vol. 38, no. 1, pp. 23-31.

Kalyuga, S., Chandler, P., Tuovinen, J., Sweller, J. (2001) ‘When problem-solving is superior to studying worked examples’, Journal of Educational Psychology, vol. 93, no. 3, pp. 579-588.

Kvasz, L. (1997) ‘Why don’t they understand us?’, Science and Education, vol. 6, no. 3, pp. 263-272.

Lafleur, A., Côté, L., Leppink, J. (2015) ‘Influences of OSCE design on students’ diagnostic reasoning. Medical Education, vol. 49, no. 2, pp. 203-214.

Leppink, J. (2012) Propositional knowledge for conceptual understanding of statistics, PhD Dissertation, Maastricht University. Maastricht: Boekenplan.

Leppink, J., Broers, N.J., Imbos, Tj., Van der Vleuten, C.P.M., Berger, M.P.F. (2012a) ‘Prior knowledge moderates instructional effects on conceptual understanding of statistics’, Educational Research and Evaluation, vol. 18, no. 1, pp. 37-51.

Leppink, J., Broers, N.J., Imbos, Tj., Van der Vleuten, C.P.M., Berger, M.P.F. (2012b) ‘Self-explanation in the domain of statistics: an expertise reversal effect’, Higher Education, vol. 63, no. 6, pp. 771-785.

Leppink, J., Broers, N.J., Imbos, Tj., Van der Vleuten, C.P.M., Berger, M.P.F. (2014) ‘The effect of guidance in problem-based learning of statistics’, Journal of Experimental Education, vol. 82, no. 2, pp. 391-407.

Leppink, J., Paas, F., Van der Vleuten, C.P.M., Van Gog, T., Van Merriënboer, J.J.G. (2013) ‘Development of an instrument for measuring different types of cognitive load’, Behavior Research Methods, vol. 45, no. 4, pp. 1058-1072.

Leppink. J., Paas, F., Van Gog, T., Van der Vleuten, C.P.M., Van Merriënboer, J.J.G. (2014) ‘Effects of pairs of problems and examples on task performance and different types of cognitive load’, Learning and Instruction, vol. 30, pp. 32-43.

Pagano, M., Gauvreau, K. (2000) Principles of biostatistics.  CA: Duxbury: Pacific Grove.

Švaříček, R., Šeďová, K. (2007) Kvalitativní výzkum v pedagogických vědách, Prague: Portál.

Sweller, J. (2010) ‘Element interactivity and intrinsic, extraneous, and germane cognitive load’, Educational Psychology Review, vol. 22, no. 2, pp. 123-138.

Sweller, J., Ayres, P., Kalyuga, S. (2011) Cognitive load theory, New York: Springer.

Vltavská, K., Vondra, Z. (2014) ‘An Analysis of the Study Plan of the Professionally Oriented Bachelor Study Field of Multimedia in Economic Practise‘, Journal on Efficiency and Responsibility in Education and Science, vol. 7, no. 3-4, pp. 74-79.

Young, M.S., Stanton, N.A. (2002) ‘Attention and automation: new perspectives on mental underload and performance’, Theoretical Issues in Ergonomics Science, vol. 3, no. 2, pp. 178-194.

Zvára, K. (2001) Biostatistika (ON2302052), Prague: Karolinum.

Zvára, K. (2013) Základy statistiky v prostředí R, Prague: Karolinum.

Zvára, K. (2014) Základy biostatistiky,

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How to Cite

Hybšová, A. and Leppink, J. (2015) ’THE SUBJECT OF STATISTICS IN NATURAL SCIENCE CURRICULA: A CASE STUDY’, Journal on Efficiency and Responsibility in Education and Science, vol. 8, no. 1, pp. 8-14



Research Paper