Research article | Open Access
International Journal on New Trends in Education and Their Implications 2026, Vol. 17(1) 37-57
pp. 37 - 57
Publish Date: June 28, 2026 | Single/Total View: 0/0 | Single/Total Download: 0/0
Abstract
The purpose of this study is to determine the statistical reasoning levels of gifted middle school students, and to examine these levels in terms of variables such as grade level and parental education status. The research was conducted with 150 students attending Science and Art Centres (BİLSEM) in İzmir, and the students' statistical reasoning skills were measured using LOCUS Assessment Questions. A correlational survey model was used in the study. The data were analysed using quantitative methods. The study found that gifted students had low levels of statistical reasoning skills. Furthermore, analysis of grade levels revealed that 7th and 8th grade students performed better than 6th grade students, but there was no significant difference between 7th and 8th grades. No significant difference was observed between parents' educational status and students' reasoning levels. The results reveal that, despite gifted students' high analytical thinking abilities, they struggle to understand complex statistical concepts, and that their education in this area needs to be strengthened in greater depth.
Keywords: gifted students, statistical reasoning levels, grade level, parents' educational status
APA 7th edition
TUNALI, C., Emir, S., & Karabey, B. (2026). Determining The Statistical Reasoning Levels Of Gifted Students. International Journal on New Trends in Education and Their Implications, 17(1), 37-57.
Harvard
TUNALI, C., Emir, S. and Karabey, B. (2026). Determining The Statistical Reasoning Levels Of Gifted Students. International Journal on New Trends in Education and Their Implications, 17(1), pp. 37-57.
Chicago 16th edition
TUNALI, Ceren, Serap Emir and Burak Karabey (2026). "Determining The Statistical Reasoning Levels Of Gifted Students". International Journal on New Trends in Education and Their Implications 17 (1):37-57.
Aoyama, K., & Stephens, M. (2003). Graph interpretation aspects of statistical literacy: A Japanese perspective. Mathematics Education Research Journal, 15(3), 207-225. DOI:10.1007/BF03217380
Aydın, Ş. (2020). An examination of eighth-grade students' statistical thinking regarding measures of central tendency (Master's thesis, Hacettepe University). YÖK Thesis Center.
Bargagliotti, A., Franklin, C., Arnold, P., Gould, R., Johnson, S., Perez, L., & Spangler, D. A. (2020). Pre-K–12 guidelines for assessment and instruction in statistics education II (GAISE II) (Second edition). American Statistical Association. https://www.amstat.org/education/guidelines-for-assessment-and-instruction-in-statistics-education-(gaise)-reports
Batur, A., & Baki, A. (2022). Examining the relationship between high school students' statistical literacy levels and their perceptions of statistical literacy self-efficacy. TED Education and Science, 47(209), 171–205. https://doi.org/10.15390/EB.2022.9970
Bayrak, B. U. (2024). An examination of eighth-grade students' statistical reasoning in the context of model-building activities (Master's thesis, Ordu University). YÖK Thesis Center.
Ben-Zvi, D. (2004). Reasoning about variability in comparing distributions. Statistics Education Research Journal, 3(2), 42–63. https://doi.org/10.52041/serj.v3i2.547
Ben-Zvi, D., & Garfield, J. B. (2004). Statistical literacy, reasoning, and thinking: Goals, definitions, and challenges. In D. Ben-Zvi & J. Garfield (Eds.), The challenge of developing statistical literacy, reasoning and thinking (pp. 3-15). Kluwer Academic Publishers. https://doi.org/10.1007/1-4020-2278-6
Clark, B. (2015). The development of giftedness (S. Talas, Trans.). In Growing up gifted: Developing children's potential at home and at school (8th ed., pp. 35-90). Nobel Akademi Publishing. (Original work published in 2013).
Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. https://doi.org/10.1037/0033-2909.112.1.155
Çanakçı, O., & Özdemir, A. Ş. (2015). Mathematics achievement and parental education level. Istanbul Aydın University Journal, 25, 19-36. https://doi.org/10.17932/IAU.IAUD.m.13091352.2015.7/25.19-36
Del Mas, R. C. (2005). A comparison of mathematical and statistical reasoning. In D. Ben-Zvi & J. Garfield (Eds.), The challenge of developing statistical literacy, reasoning and thinking (pp.79- 95). Kluwer Academic Publishers.
Durak, T., & Tutak, F. A. (2019). Comparison of gifted and mainstream 9th grade students' statistical reasoning types. Proceedings of the 11th International Conference on Mathematical Creativity and Giftedness, 136-141. https://wtmverlag.de/OA_Download/Nolte_Ed_Including_the_Highly_Gifted_ISBN9783959871327-CC-BY-NC-ND.pdf
Franklin, C., Kader, G., Mewborn, D. S., Moreno, J., Peck, R., Perry, M., & Scheaffer, R. (2007). Guidelines for assessment and instruction in statistics education (GAISE) report: A pre-K–12 curriculum framework. American Statistical Association. https://www.amstat.org/education/gaise/
Garfield, J., delMas, R., & Chance, B. (2003). The challenge of developing statistical reasoning. In G. Burrill & M. Camden (Eds.), Developing reasoning about samples and sampling (pp. 1–11). International Statistical Institute.
Gil, E., & Ben-Zvi, D. (2010). Emergence of reasoning about sampling among young students in the context of informal inferential reasoning. In C. Reading (Ed.), Data and context in statistics education: Towards an evidence-based society. Proceedings of the Eighth International Conference on Teaching Statistics (ICOTS8, July, 2010), Ljubljana, Slovenia. International Statistical Institute. https://www.stat.auckland.ac.nz/~iase/publications/icots8/ICOTS8_8A3_GIL.pdf
Güray, U. Ş., Gök, M., & Bilgin, E. A. (2019). An investigation of the statistical reasoning skills of 8th grade primary school students [Paper presentation]. 3rd International Congress of Social and Human Sciences Congress, Turkey.
Güven, B., Öztürk, T., & Özmen, Z. M. (2015). Examining the statistical process experiences of 8th grade students. TED Education and Science, 40(177), 343-363. https://doi.org/10.15390/EB.2015.3313
Jacobbe, T., Case, C., Whitaker, D., & Foti, S. (2014). Establishing the validity of the LOCUS assessments through an evidence-centered design approach [Paper presentation]. 9th International Conference on Teaching Statistics (ICOTS-9), Arizona, USA. https://icots.info/icots/9/proceedings/pdfs/ICOTS9_7C2_JACOBBE.pdf
Kale, F. (2024). Examining middle school students' informal statistical reasoning using real-life situations (Master's thesis, Mersin University). YÖK Thesis Center.
Karaca, Ş. A., & Ay, Z. S. (2025). Investigation of eighth grade students’ performance on tasks involving statistical thinking about measures of central tendency. Participatory Educational Research, 12(1), 18-42. https://doi.org/10.17275/per.25.2.12.1
Karasar, N. (2020). Scientific research method: Concepts, principles, techniques (38th ed.). Nobel Academic Publishing.
Ko, E.-S. (2012). A comparison of mathematically talented students and non-talented students’ level of statistical thinking: Statistical modeling and sampling distribution understanding. Journal of Gifted/Talented Education, 22(3), 503-525. https://doi.org/10.9722/JGTE.2012.22.3.503
Ko, E.-S. (2013). A comparison of mathematically talented students and non-talented students’ level of statistical thinking: The noticing of statistical variability. Journal of Gifted/Talented Education, 23(3), 387-406. https://doi.org/10.9722/JGTE.2012.22.3.503
Koparan, T., & Güven, B. (2013). A study on the differentiation levels of middle school students' statistical thinking. Elementary Education Online, 12(1), 158-178. https://dergipark.org.tr/tr/pub/ilkonline/issue/8586/106677
Koparan, T., Güven, B., & Karataş, İ. (2014). High school students' use of contextual knowledge in data analysis and mathematical/statistical knowledge in data analysis. Journal of Computer and Education Research Journal, 2(4), 1-22. https://dergipark.org.tr/tr/pub/jcer/issue/18616/196507
Koparan, T., & Güven, B. (2014). Examining the statistical thinking levels of 6th-7th-8th grade middle school students according to the M3ST model. Education and Science, 39(171), 37-51. https://doi.org/10.15390/ES.2014.1217
Levent, F. (2011). A study of the view and policies on gifted education (Doctoral Thesis, Marmara University). YÖK Thesis Center.
McClain, K., Cobb, P., & Gravemeijer, K. (2000). Supporting students’ ways of reasoning about data. In M. J. Burke & F. R. Curcio (Eds.), Learning mathematics for a new century (pp. 174–187). National Council of Teachers of Mathematics.
Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook (2nd ed.). Sage Publications.
Ministry of National Education. (2019). https://dhgm.meb.gov.tr/tebligler-dergisi/2019/2747_Aralik_2019.pdf
Mooney, E. S. (2002). A framework for characterizing middle school students’ statistical thinking. Mathematical Thinking and Learning, 4(1), 23-63. https://doi.org/10.1207/S15327833MTL0401_2
Öz, Ö. (2019). An examination of seventh-grade students' understanding of the statistical research process (Master's thesis, Middle East Technical University). YÖK Thesis Center.
Özdemir, S. (2014). The effect of collaborative learning in statistics courses on students' academic achievement and attitudes and an examination of their levels of statistical thinking (Master's thesis, Çukurova University). YÖK Thesis Center.
Öztürk Zora, L., & Anapa Saban, P. (2023). Examination of eighth grade students’ statistical reasoning skills regarding pie charts. Osmangazi Journal of Educational Research, 10(1), 1–10. https://doi.org/10.59409/ojer.1257451
Pfannkuch, M. (2006). Informal inferential reasoning. In A. Rossman & B. Chance (Eds.), Working cooperatively in statistics education: Proceedings of the Seventh International Conference on Teaching Statistics (ICOTS7). International Statistical Institute. https://iase-web.org/documents/papers/icots7/6A2_PFAN.pdf?1402524965
Renzulli, J. S. (2003). The three-ring conception of giftedness: Its implications for understanding the nature of innovation. In L. V. Shavinina (Ed.), The international handbook on innovation (pp. 79–95). Elsevier.
Sak, U. (2017). Characteristics of gifted individuals and their education (7th ed.). Vize Yayıncılık.
Sternberg, R. J., & Grigorenko, E. L. (2002). The theory of successful intelligence as a basis for gifted education. Gifted Child Quarterly, 47. 265–277. https://doi.org/10.1177/001698620204600403
Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Pearson.
Watson, J. M., & Kelly, B. A. (2008). The vocabulary of statistical literacy. International Journal of Science and Mathematics Education, 6(4), 741-767. https://doi.org/10.1007/s10763-007-9083-x
Watson, J., Chick, H., & Callingham, R. (2014). Average: The juxtaposition of procedure and context. Mathematics Education Research Journal, 26(3), 477–502. https://doi.org/10.1007/s13394-013-0113-4
Watson, J. M., & English, L. D. (2017). Statistical problem posing, problem refining, and further reflection in grade 6. Canadian Journal of Science, Mathematics and Technology Education, 17(4), 347–365. https://doi.org/10.1080/14926156.2017.1380867
Yolcu, A. (2012). An investigation of eighth-grade students' statistical literacy, their attitudes toward statistics, and the relationship between them (Master's thesis, Middle East Technical University). YÖK Thesis Center.
Yolcu, A. (2014). Middle school students’ statistical literacy: Role of grade level and gender. Statistics Education Research Journal, 13(2), Article 2. https://doi.org/10.52041/serj.v13i2.285