EVALUATING THE APPROPRIATENESS OF DATA IN TEACHING STATISTICS AT THE LOWER SECONDARY SCHOOL LEVEL: ILLUSTRATIONS USING TWO GEOGEBRA MODELS

Ton That Tu1, , Le Vu Khoa2, Le Bui Quynh Chi1, Le Thanh Nhan1
1 The University of Danang – University of Science and Education, Vietnam
2 Trường Đại học Sư phạm – Đại học Đà Nẵng, Việt Nam

Main Article Content

Abstract

Statistics and Probability is one of the three core areas of knowledge in the 2018 General Education Curriculum for Mathematics, taught from grade 2 to grade 12, with concepts and skills progressing from basic to advanced levels. At the secondary school level, the focus of statistics is primarily on data collection, classification, and representation through tables and charts. Collecting data from various sources may affect the quality of the data, which in turn influences analysis and decision-making. Therefore, evaluating the appropriateness of data has become an important requirement, which is reflected in the curriculum's learning objectives. This paper analyzes the reasons for evaluating data appropriateness and the necessity of using assessment criteria, while also introducing some simple criteria suitable for the lower secondary level. In addition, two dynamic GeoGebra models and two teaching situations are developed to illustrate and support instruction.

Article Details

References

Garfield, J., & Ben-Zvi, D. (2007). How Students Learn Statistics Revisited: A Current Review of Research on Teaching and Learning Statistics. International Statistical Review, 75(3), 372-396. https://doi.org/10.1111/j.1751-5823.2007.00029.x
Jamie, D. M. (2007). Teacher perceptions and attitudes about teaching statistics in P-12 education. Educational Research Quarterly, 30(4).
Khong, I., Yusuf, N. A., Nuriman, A., & Yadila, A. B. (2023). Exploring the impact of data quality on decision-making processes in information intensive organizations. APTISI Transactions on Management (ATM), 7(3), 246–253. https://doi.org/10.33050/atm.v7i3.2138
Kjelvik, M. K., & Schultheis, E. H. (2019). Getting Messy with Authentic Data: Exploring the Potential of Using Data from Scientific Research to Support Student Data Literacy. CBE—Life Sciences Education, 18(2). https://doi.org/10.1187/cbe.18-02-0023
Le, T. B. T. T., Tang, M. D., & Tran, M. M. (2024). Some factors of teacher beliefs and attitudes of middle school mathematics teachers in Bac Lieu province about teaching statistics. Dong Thap University Journal of Science, 13(02S), 52-63. https://doi.org/10.52714/dthu.13.02S.2024.1344
Leighton, J. P., Cui, Y., & Cutumisu, M. (2021). Key Information Processes for Thinking Critically in Data-Rich Environments. Frontiers in Education, 6. https://doi.org/10.3389/feduc.2021.561847
Ministry of Education and Training. (2018). Chuong trinh giao duc pho thong mon Toan [General education program in Mathematics]. Hanoi.
Nguyen, C.T., & Hoang, L.M. (2021). Nhung dinh huong co ban ve day hoc noi dung thong ke cap trung hoc pho thong trong chuong trinh mon toan 2018 [Basic directions on teaching the content of statistics at high school in the mathematics education curriculum 2018]. Vinh University Journal of Science, 50(4B), 67-75.
Nguyen, P. T., & Ho, N. N. L. (2023). Day hoc noi dung “Thong ke” (Toan 7) thong qua hoat dong trai nghiem [Teaching the content "Statistics" (Grade 7 Math) through experiential activities]. Vietnam Journal of Education, 23(21), 1–6.
Nguyen, T. T. T, & Quach, T. S. (2023). Mot so bien phap day hoc chu de Thong ke va Xac suat cho hoc sinh lop 6 voi su ho tro cua cong nghe thong tin [Some methods of teaching statistics and probability topics for 6th grade students with the support of information technology]. The Vietnam Institute of Educational Sciences, 19, 27-34.
Pham, T. Q., & Tran, T. (2023). Ung dung cong nghe thong tin trong mot so tinh huong day hoc mach kien thuc thong ke va xac suat o trung hoc pho thong [Application of information technology in some situations of teaching statistics and probability in high school]. Vietnam Journal of Education, 23(5), 7-11.
Pipino, L. L., Lee, Y. W., & Wang, R. Y. (2002). Data quality assessment. Communications of the ACM, 45(4), 211-218.
Pratt, D., Davies, N., & Connor, D. (2011). The role of technology in teaching and learning statistics. Teaching statistics in school mathematics-challenges for teaching and teacher education: A Joint ICMI/IASE Study: The 18th ICMI Study (pp. 97-107): Springer. http://dx.doi.org/10.1007/978-94-007-1131-0_13
Taş, E. (2024). Data literacy education through university-industry collaboration. Information and Learning Sciences, 125(5-6), 389–405. https://doi.org/10.1108/ILS-06-2023-0077
Ton, T.T., Hoang, T.T.T & Nguyen, D.N. (2024). Mot so mo hinh ho tro day hoc khai niem ngau nhien và y tuong do luong xac suat [Some models support teaching the concept of randomness and measurement of probability]. Ho Chi Minh City University of Education Journal of Science, 21(2), 245-255.
Wang, R. Y., & Strong, D. M. (1996). Beyond Accuracy: What Data Quality Means to Data Consumers. Journal of Management Information Systems, 12(4), 5–33. https://doi.org/10.1080/07421222.1996.11518099
Zrnec, A., Poženel, M., & Lavbič, D. (2022). Users’ ability to perceive misinformation: An information quality assessment approach. Information Processing & Management, 59(1). https://doi.org/10.1016/j.ipm.2021.102739