1. Aoyama, K., & Stephens, M. (2003). Graph interpretation aspect of statistical literacy: A Japanese perspective. Mathematics Education Research Journal, 15(3), 207–225. https://doi.org/10.1007/BF03217380.
2. Işıksal-Bostan, M., & Yemen-Karpuzcu, S. (2017). The role of definitions on classification of solids including (non)prototype examples: The case of cylinder and prism. In T. Dooley & G. Gueudet (Eds.), Proceedings of the Tenth Congress of the European Society for Research in Mathematics Education (CERME10, February 1–5, 2017) (pp. 3320–3327). Dublin, Ireland: DCU Institute of Education and ERME.
3. Bright, G. W., & Friel, S. N. (1998). Graphical representations: Helping students interpret data. In S. P. Lajoie (Ed.), Reflections on statistics: Learning, teaching, and assessment in grades K–12 (pp. 63–88). Mahwah, NJ: Lawrence Erlbaum.
4. Cai, J. (2000). Understanding and representing the arithmetic averaging algorithm: An analysis and comparison of US and Chinese students' responses. International Journal of Mathematical Education in Science and Technology, 31(6), 839–855. https://doi.org/10.1080/00207390050203342.
5. Callingham, R., & Watson, J. M. (2017). The development of statistical literacy at school. Statistics Education Research Journal, 16(1), 181–201.