We report a study where 195 students aged 12 to 15 years were presented with computerbased tasks that require reasoning with multivariate data, together with paper-based tasks from a well established scale of statistical literacy. The computer tasks were cognitively more complex, but were only slightly more difficult than paper tasks. All the tasks fitted well onto a single Rasch scale. Implications for the curriculum, and public presentations of data are discussed.

• Aoyama, K. (2007). Investigating a hierarchy of students’ interpretation of graphs. International Electronic Journal of Mathematics Education, this issue.
• Batanero, C., Godino, J.D., Vallecillos, A., Green, D., & Holmes, P. (1994). Errors and difficulties in understanding elementary statistical concepts. International Journal of Mathematics, Education, Science and Technology, 25(4), 527 – 547.
• Biggs, J. B., & Collis, K. F. (1982). Evaluating the quality of learning: The SOLO Taxonomy. New York Academic Press.
• Bond, T., & Fox, C. (2001) Applying the Rasch model: Fundamental measurement in the human sciences. Mahwah NJ: Erlbaum.
• Callingham, R., & Watson, J. (2005). Measuring statistical literacy. Journal of Applied Measurement, 6(1), 1-29.
• Chance, B.L. (2002). Components of statistical thinking and implications for instruction and assessment. Journal of Statistics Education, 10(3). Online http://www.amstat.org/publications/jse.
• Condorcet, J. (1994). Foundations of social choice and political theory. Aldershot and Brookfield, VT: Elgar (original work published in 1792).
• Cremin, L. (1988). American education: The metropolitan experience 1876-1980. New York: Harper and Row.
• Department for Education and Skills (2005). Harnessing technology transforming learning and children’s services. Online: http://www.becta.org.uk/corporate/publications/.
• Dewey, J. (1999). Democracy and education: an introduction to the philosophy of education. New York : Free Press.
• Gigerenzer, G., Swijtink, Z., Porter, T., Daston, L., Beatt, J., & Kruger, L (1989). The Empire of Chance. New York: Cambridge University Press.
• Grunewald, W., & Mittag, H. J. (2006). The use of advanced visualisation tools for communicating European data on earnings to the citizen. In A. Rossman, & B. Chance (Eds.), Proceedings of the Seventh International Conference on Teaching Statistics, Salvador, Brazil. International Statistical Institute and International Association for Statistical Education. On line: http://www.stat.auckland.ac.nz/~iase.
• Mittag, H. J., & Marty, U. (2005). Gross earnings in Europe 2002. CDROM. Luxembourg: Eurostat.
• Monteiro, C., & Ainley, J. (2007). Investigating the interpretion of media graphs among student teachers. International Electronic Journal of Mathematics Education, this issue.
• Orrill, R. (2001). Preface. In L. Steen (Ed.), Mathematics and democracy; the case for qualitative literacy (pp. xiiixx) Princeton: The National Council on Education and the Disciplines.
• Ridgway, J. (1997). Why measure development? In L. Smith, J. Dockrell, & P. Tomlinson (Eds.). Piaget, Vygotsky, and beyond (pp. 201-210). Routledge: London.
• Ridgway, J., & McCusker, S. (2003). Using computers to assess new educational goals. Assessment in Education, 10(3), 309-328.
• Ridgway, J., Nicholson, J. R., & McCusker, S. (2007d). Engaging citizens in reasoning with evidence. Paper presented at the 56th Session of the International Statistical Institute, Lisbon, Portugal.
• Ridgway, J., Nicholson, J. R., & McCusker, S. (2007a). Teaching statistics – despite its applications. Teaching Statistics, 29(2), 44-48.
• Ridgway, J., Nicholson, J. R., & McCusker, S. (2007b). Using multivariate data as a focus for multiple curriculum perspectives at secondary level. Paper presented at the 56th Session of the International Statistical Institute, Lisbon, Portugal.
• Ridgway, J., Nicholson, J. R., & McCusker, S. (2007c). Embedding statistical assessment within cross-curricular materials. Paper presented to the IASE Satellite Conference on Assessing Student Learning in Statistics, Guimarães, Portugal.
• Ridgway, J., McCusker, S., & Nicholson, J. (2006). Reasoning with evidence – Development of a scale. Paper presented at the 32nd Annual Conference of the International Association for Educational Assessment - Assessment in an Era of Rapid Change, Singapore, May 2006. Online: http://www.iaea2006.seab.gov.sg/conference/programme.html.
• Silva, P. (2006). Statistical education for doing statistics professionally: some challenges and the road ahead. Keynote presentation at the Seventh International Conference on Teaching Statistics. Salvador (Bahia), Brazil.
• Schield, M. (2006). Statistical literacy survey analysis: Reading graphs and tables of rates and percentages. In A. Rossman, & B. Chance (Eds.), Proceedings of the Seventh International Conference on Teaching Statistics, Salvador, Brazil: International Statistical Institute and International Association for Statistical Education. Online: http://www.stat.auckland.ac.nz/~iase.
• Watson, J. M. & Callingham, R. (2003). Statistical literacy: A complex hierarchical construct. Statistics Education Research Journal, 2(2), 3–46.
• Zigure, A. (2005). Focusing on non-professional users. Proceedings of the 91st Conference of the Directors-General of the National Statistics Offices (pp. 93-105). Luxembourg: Eurostat.

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