Abstract
Three different approaches to the concept of probability dominate the teaching of stochastics: the classical, the frequentistic and the subjectivistic approach. Compared with each other they provide considerably different possibilities to interpret situations with randomness. With regard to teaching probability, it is useful to clarify interrelations and differences between these three approaches. Thus, students’ probabilistic reasoning in specific random situations could be characterized, classified and finally, understood in more detail. In this chapter, we propose examples that potentially illustrate both, interrelations and differences of the three approaches to probability mentioned above. Thereby, we strictly focus on an educational perspective.
At first, we briefly outline a proposal for relevant teachers’ content knowledge concerning the construct of probability. In this short overview, we focus on three approaches to probability, namely the classical, the frequentistic and the subjectivistic approach. Afterwards, we briefly discuss existing research concerning teachers’ knowledge and beliefs about probability approaches. Further, we outline our normative focus on teachers’ potential pedagogical content knowledge concerning the construct of probability. For this, we discuss the construct of probability within a modelling perspective, with regard to a theoretical perspective on the one side and with regard to classroom activities on the other side. We further emphasize considerations about situations which are potentially meaningful with regard to different approaches to probability. Finally, we focus on technological pedagogical content knowledge. Within the perspective of teaching probability, this kind of knowledge is about the question of how technology and, especially simulation, supports students understanding of probabilities.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ball, D. L., Thames, M. H., & Phelps, G. (2008). Content knowledge for teaching. Journal of Teacher Education, 59(5), 389–407.
Batanero, C., & Sanchez, E. (2005). What is the nature of high school students’ conceptions and misconceptions about probability. In G. A. Jones (Ed.), Exploring probability in school: challenges for teaching and learning (pp. 241–266). New York: Springer.
Batanero, C., Henry, M., & Parzysz, B. (2005a). The nature of chance and probability. In G. A. Jones (Ed.), Exploring probability in school: challenges for teaching and learning (pp. 15–37). New York: Springer.
Batanero, C., Biehler, R., Maxara, C., Engel, J., & Vogel, M. (2005b). Using simulation to bridge teachers content and pedagogical knowledge in probability. Paper presented at the 15th ICMI study conference: the professional education and development of teachers of mathematics. Aguas de Lindoia, Brazil.
Begg, A., & Edwards, R. (1999). Teachers’ ideas about teaching statistics. In Proceedings of the 1999 combined conference of the Australian association for research in education and the New Zealand association for research in education. Melbourne: AARE & NZARE. Online: www.aare.edu.au/99pap/.
Biehler, R. (1991). Computers in probability education. In R. Kapadia & M. Borovcnik (Eds.), Chance encounters. Probability in education (pp. 169–211). Amsterdam: Kluwer Academic.
Biehler, R. (2003). Simulation als systematischer Strang im Stochastikcurriculum [Simulation as systematic strand in stochastics teaching]. In Beiträge zum Mathematikunterricht (pp. 109–112).
Biehler, R., & Prömmel, A. (2011). Mit Simulationen zum Wahrscheinlichkeitsbegriff [With simulations towards the concept of probability]. PM. Praxis der Mathematik in der Schule, 53(39), 14–18.
Blum, W. (2002). ICMI-study 14: applications and modelling in mathematics education—discussion document. Educational Studies in Mathematics, 51, 149–171.
Borovcnik, M. (1992). Stochastik im Wechselspiel von Intuitionen und Mathematik [Stochastics in the interplay between intuitions and mathematics]. Mannheim: BI-Wissenschaftsverlag.
Borovcnik, M. (2005). Probabilistic and statistical thinking. In Proceedings of the fourth congress of the European society for research in mathematics education, Sant Feliu de Guíxols, Spain (pp. 485–506).
Box, G., & Draper, N. (1987). Empirical model-building and response surfaces. New York: Wiley.
Brown, J. S., Collins, A., & Duguid, P. (1981). Situated cognition and the culture of learning. Educational Researcher, 18(1), 32–42.
Burill, G., & Biehler, R. (2011). Fundamental statistical ideas in the school curriculum and in teacher training. In C. Batanero, G. Burrill, & C. Reading (Eds.), Teaching statistics in school mathematics—challenges for teaching and teacher education (pp. 57–70). New York: Springer.
Broers, N. J. (2006). Learning goals: the primacy of statistical knowledge. In A. Rossman & B. Chance (Eds.), Proceedings of the seventh international conference on teaching statistics, Salvador: International Statistical Institute and International Association for Statistical Education. Online: www.stat.auckland.ac.nz/~iase/publications.
Carnell, L. J. (1997). Characteristics of reasoning about conditional probability (preservice teachers). Unpublished doctoral dissertation, University of North Carolina-Greensboro.
Chaput, B., Girard, J.-C., & Henry, M. (2011). Frequentistic approach: modelling and simulation in statistics and probability teaching. In C. Batanero, G. Burrill, & C. Reading (Eds.), Teaching statistics in school mathematics—challenges for teaching and teacher education (pp. 85–96). New York: Springer.
Chernoff, E. J. (2008). The state of probability measurement in mathematics education: a first approximation. Philosophy of Mathematics Education Journal, 23.
Cognition Technology Group at Vanderbilt (1990). Anchored instruction and its relationship to situated cognition. Educational Researcher, 19(6), 2–10.
Countinho, C. (2001). Introduction aux situations aléatoires dés le Collége: de la modélisation à la simulation d’experiences de Bernoulli dans l’environment informatique Cabri-géomètre-II [Introduction to random situations in high school: from modelling to simulation of Bernoulli experiences with Cabri-géomètre-II]. Unpublished doctoral dissertation, University of Grénoble, France.
De Fineti, B. (1974). Theory of probability. London: Wiley.
Dugdale, S. (2001). Pre-service teachers’ use of computer simulation to explore probability. Computers in the Schools, 17(1/2), 173–182.
Eichler, A. (2008a). Teachers’ classroom practice and students’ learning. In C. Batanero, G. Burrill, C. Reading, & A. Rossman (Eds.), Joint ICMI/IASE study: teaching statistics in school mathematics. Challenges for teaching and teacher education. Proceedings of the ICMI study 18 and 2008 IASE round table conference. Monterrey: ICMI and IASE. Online: www.stat.auckland.ac.nz/~iase/publications.
Eichler, A. (2008b). Statistics teaching in German secondary high schools. In C. Batanero, G. Burrill, C. Reading, & A. Rossman (Eds.), Joint ICMI/IASE study: teaching statistics in school mathematics. Challenges for teaching and teacher education. Proceedings of the ICMI study 18 and 2008 IASE round table conference. Monterrey: ICMI and IASE. Online: www.stat.auckland.ac.nz/~iase/publications.
Eichler, A. (2011). Statistics teachers and classroom practices. In C. Batanero, G. Burrill, & C. Reading (Eds.), Teaching statistics in school mathematics—challenges for teaching and teacher education (pp. 175–186). New York: Springer.
Eichler, A., & Vogel, M. (2009). Leitidee Daten und Zufall [Key idea of data and chance]. Wiesbaden: Vieweg + Teubner.
Eichler, A., & Vogel, M. (2011). Leitifaden Daten und Zufall [Compendium of data and chance]. Wiesbaden: Vieweg + Teubner.
Engel, J. (2002). Activity-based statistics, computer simulation and formal mathematics. In B. Phillips (Ed.), Developing a statistically literate society. Proceedings of the sixth international conference on teaching statistics (ICOTS6, July, 2002), Cape Town, South Africa.
Engel, J., & Vogel, M. (2004). Mathematical problem solving as modeling process. In W. Blum, P. L. Galbraith, H.-W. Henn, & M. Niss (Eds.), ICMI-study 14: application and modeling in mathematics education (pp. 83–88). New York: Springer.
Girard, J. C. (1997). Modélisation, simulation et experience aléatoire [Modeling, simulation and random experience]. In Enseigner les probabilités au lycée (pp. 73–76). Reims: Commission Inter-IREM Statistique et Probabilités.
Greer, B., & Mukhopadhyay, S. (2005). Teaching and learning the mathematization of uncertainty: historical, cultural, social and political contexts. In G. A. Jones (Ed.), Exploring probability in school: challenges for teaching and learning (pp. 297–324). New York: Springer.
Heitele, D. (1975). An epistemological view on fundamental stochastic ideas. Educational Studies in Mathematics, 2, 187–205.
Henry, M. (1997). Notion de modéle et modélization en l’enseignement [Notion of model and modelling in teaching]. In Enseigner les probabilités au lycée (pp. 77–84). Reims: Commission Inter-IREM.
Hoffrage, U. (2003). Risikokommunikation bei Brustkrebsfrüherkennung und Hormonersatztherapie [Risk communication in breast cancer screening and hormone replacement therapy]. Zeitschrift für Gesundheitspsychologie, 11(3), 76–86.
Jones, G. A., Langrall, C. W., & Mooney, E. S. (2007). Research in probability. In F. K. Lester (Ed.), Second handbook of research on mathematics teaching and learning (pp. 909–956). Charlotte: Information Age Publishing.
Kolmogoroff, A. (1933). Grundbegriffe der Wahrscheinlichkeitsrechnung [Fundamental terms of probability]. Berlin: Springer. (Reprint 1973).
Mandl, H., Gruber, H., & Renkl, A. (1997). Situiertes Lernen in multimedialen Lernumgebungen [Situated learning in multimedia learning environments]. In L. J. Issing & P. Klimsa (Eds.), Information und Lernen mit Multimedia (pp. 166–178). Weinheim: Psychologie Verlags Union.
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: a framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054.
Pfannkuch, M. (2005). Probability and statistical inference: how can teachers enable students to make the connection? In G. A. Jones (Ed.), Exploring probability in school: challenges for teaching and learning (pp. 267–294). New York: Springer.
Renyi, A. (1992). Calcul des probabilités [Probability calculus]. Paris: Jacques Gabay. (Trans: L. Félix. Original work published 1966).
Riemer, W. (1991). Stochastische Probleme aus elementarer Sicht [Stochastic problems from an elementary perspective]. Mannheim: BI-Wissenschaftsverlag.
Rossman, A. (1997). Workshop statistics. New York: Springer.
Salomon, G. (1993). Distributed cognitions: psychological and educational considerations. New York: Cambridge University Press.
Scheaffer, R., Gnanadesikan, M., Watkins, A., & Witmer, J. (1997). Activity-based statistics. New York: Springer.
Schneider, I. (1988). Die Entwicklung der Wahrscheinlichkeitstheorie von den Anfängen bis 1933 [Development of probability from beginnings to 1933]. Darmstadt: Wissenschaftliche Buchgesellschaft.
Schnotz, W. (2002). Enabling, facilitating, and inhibiting effects in learning from animated pictures. In R. Ploetzner (Ed.), Online-proceedings of the international workshop on dynamic visualizations and learning (pp. 1–9). Tübingen: Knowledge Media Research Center.
Schupp, H. (1982). Zum Verhältnis statistischer und wahrscheinlichkeitstheoretischer Komponenten im Stochastik-Unterricht der Sekundarstufe I [Concerning the relation between statistical and probabilistic components of middle school stochastics education]. Journal für Mathematik-Didaktik, 3(3/4), 207–226.
Schupp, H. (1988). Anwendungsorientierter Mathematikunterricht in der Sekundarstufe I zwischen Tradition und neuen Impulsen [Application-oriented mathematics lessons in the lower secondary between tradition and new impulses]. Der Mathematikunterricht, 34(6), 5–16.
Shaughnessy, M. (1992). Research in probability and statistics. In D. A. Grouws (Ed.), Handbook of research in mathematics teaching and learning (pp. 465–494). New York: Macmillan.
Sill, H.-D. (1993). Zum Zufallsbegriff in der stochastischen Allgemeinbildung [About the concepts of chance and randomness in statistics education]. ZDM. Zentralblatt für Didaktik der Mathematik, 2, 84–88.
Stachowiak, H. (1973). Allgemeine Modelltheorie [General model theory]. Berlin: Springer.
Steinbring, H. (1991). The theoretical nature of probability in the classroom. In R. Kapadia & M. Borovcnik (Eds.), Chance encounters. Probability in education (pp. 135–168). Amsterdam: Kluwer Academic.
Steinbring, H. & Strässer, R. (Hrsg.) (1981). Rezensionen von Stochastik-Lehrbüchern [Reviews of stochastic textbooks]. ZDM. Zentralblatt für Didaktik der Mathematik, 13, 236–286.
Stohl, H. (2005). Probability in teacher education and development. In G. A. Jones (Ed.), Exploring probability in school: challenges for teaching and learning (pp. 345–366). New York: Springer.
Stohl, H., & Tarr, J. E. (2002). Developing notions of inference using probability simulation tools. The Journal of Mathematical Behavior, 21, 319–337.
Vogel, M. (2006). Mathematisieren funktionaler Zusammenhänge mit multimediabasierter Supplantation [Mathematization of functional relations using multimedia supplantation]. Hildesheim: Franzbecker.
Vogel, M., & Eichler, A. (2011). Das kann doch kein Zufall sein! Wahrscheinlichkeitsmuster in Daten finden [It cannot be chance! Finding patterns of probability in data]. PM. Praxis der Mathematik in der Schule, 53(39), 2–8.
von Mises, R. (1952). Wahrscheinlichkeit, Statistik und Wahrheit [Probability, statistics and truth]. Wien: Springer.
Vosniadou, S. (1994). From cognitive theory to educational technology. In S. Vosniadou, E. D. Corte, & H. Mandl (Eds.), Technology-based learning environments (pp. 11–18). Berlin: Springer.
Wassner, C., & Martignon, L. (2002). Teaching decision making and statistical thinking with natural frequencies. In B. Phillips (Ed.), Developing a statistically literate society. Proceedings of the sixth international conference on teaching statistics (ICOTS6, July, 2002). Cape Town, South Africa.
Wickmann, D. (1990). Bayes-Statistik [Bayesian statistics]. Mannheim: BI-Wissenschaftsverlag.
Wild, C., & Pfannkuch, M. (1999). Statistical thinking in empirical enquiry. International Statistical Review, 67(3), 223–248.
Zhang, J. (1997). The nature of external representations in problem solving. Cognitive Science, 21(2), 179–217.
Zimmermann, G. M. (2002). Students reasoning about probability simulation during instruction. Unpublished doctoral dissertation, Illinois State University, Normal.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Eichler, A., Vogel, M. (2014). Three Approaches for Modelling Situations with Randomness. In: Chernoff, E., Sriraman, B. (eds) Probabilistic Thinking. Advances in Mathematics Education. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7155-0_4
Download citation
DOI: https://doi.org/10.1007/978-94-007-7155-0_4
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-7154-3
Online ISBN: 978-94-007-7155-0
eBook Packages: Humanities, Social Sciences and LawEducation (R0)