CODAP Publications

Researchers

Research publications featuring CODAP

Read a diverse selection of researcher and practitioner publications featuring CODAP.

Hudson, R. A., Mojica, G. F., Lee, H. S., & Casey, S. (2024). Data moves as a focusing lens for learning to teach with CODAP. Computers in the Schools, 1–26. https://doi.org/10.1080/07380569.2024.2411705

Nicholson, J., & Ridgway, J. (2024). New viruses are inevitable; pandemics are optional—Lessons for and from statistics. Teaching Statistics, 46(3), 132–140. http://doi.org/10.1111/test.12379 

Engel, J., & Erickson, T. (2023). What goes before the CART? Introducing classification trees with Arbor and CODAP. Teaching Statistics, 45(S1). Wiley Online Library. https://doi.org/10.1111/test.12347

Higgins, T., Mokros, J., Rubin, A., & Sagrans, J. (2023). Students’ approaches to exploring relationships between categorical variables. Teaching Statistics, 45(S1), S52-S66. https://doi.org/10.1111/test.12331  

Mokros, J., Rubin, A., Sagrans, J., & Higgins, T. (2023). Curating datasets to support middle school student inquiry. In E. M. Jones (Ed.), Fostering Learning of Statistics and Data Science: Proceedings of the Satellite Conference of the International Association for Statistical Education (IASE). https://iase-web.org/Webinars.php?p=230711_2000  

Louie, J., Stiles, J. Fagan, E., Chance, B., & Roy, S. (2022). Building toward critical data literacy with investigations of income inequality. Educational Technology and Society, 25(4), 142–163. https://par.nsf.gov/servlets/purl/10474020

Martignon, L., Erickson, T., & Viale, R. (2022). Transparent, simple and robust fast-and-frugal trees and their construction. Frontiers in Human Dynamics, 4. https://doi.org/10.3389/fhumd.2022.790033

Noyce, P., Mokros, J., Martin, L., & Sagrans, J. (2022). Integrating technology and narrative to engage young adolescents with COVID data. In S. A. Peters, L. Zapata-Cardona, F. Bonafini, & A. Fan (Eds.), Bridging the Gap: Empowering & Educating Today’s Learners in Statistics. Proceedings of the 11th International Conference on Teaching Statistics (ICOTS11 2022). Rosario, Argentina. International Association for Statistical Education. https://www.doi.org/10.52041/iase.icots11.T2I3 

Sagrans, J., Mokros, J., Voyer, C., Sagrans, J., & Harvey, M. (2022, Jan/Feb). Data science meets science teaching. The Science Teacher. https://doi.org/10.1080/00368555.2022.12293671

Biehler, R., & Fleisher, Y. (2021). Introducing students to machine learning with decision trees using CODAP and Jupyter Notebooks. Teaching Statistics, 43(S1), S133-S142. https://doi.org/10.1111/test.12279 

Erickson, T., & Chen, E. (2021). Introducing data science with data moves and CODAP. Teaching Statistics, 43, S124-S132. https://doi.org/10.1111/test.12240

Frischemeier, D., Biehler, R., Podworny, S., & Budde, L. (2021). A first introduction to data science education in secondary schools: Teaching and learning about data exploration with CODAP using survey data. Teaching Statistics, 43, S182-S189. https://doi.org/10.1111/test.12283

Biehler, R., Fleischer, Y., Budde, L., Frischemeier, D., Gerstenberger, D., Podworny, S., & Schulte, C. (2020). Data science education in secondary schools: Teaching and learning decision trees with CODAP and Jupyter Notebooks as an example of integrating machine learning into statistics education. In New Skills in the Changing World of Statistics Education Proceedings of the Roundtable Conference of the International Association for Statistical Education (IASE). ISI/IASE, Voorborg, The Netherlands. https://doi.org/10.52041/srap.20304

Budde, L., Frischemeier, D., Biehler, R., Fleischer, Y., Gerstenberger, D., Podworny, S., & Schulte, C. (2020). Data science education in secondary school: how to develop statistical reasoning when exploring data using CODAP. In New Skills in the Changing World of Statistics Education Proceedings of the Roundtable Conference of the International Association for Statistical Education (IASE). ISI/IASE, Voorborg, The Netherlands. https://doi.org/10.52041/srap.20305

Harvey, M., Mokros, J., Sagrans, J., & Voyer, C. (2020). What makes them tick? Middle school data science explorations of ticks and Lyme disease. Connected Science Learning, 2(3). https://doi.org/10.1080/24758779.2020.12318738

Erickson, T., Wilkerson, M., Finzer, W., & Reichsman, F. (2019). Data moves. Technology Innovations in Statistics Education, 12(1). http://dx.doi.org/10.5070/T5121038001 

Mojica, G. F., Barker, H., & Azmy, C. N. (2019). Instrumented learning in a CODAP-enabled learning environment. In J. M. Contreras, M. M. Gea, M. M. López-Martín, & E. Molina-Portillo (Eds.), Proceedings of the III International Virtual Congress on Statistical Education. https://www.ugr.es/~fqm126/civeest/mojica.pdf 

Engel, J. (2018). Exploring civic statistics with CODAP. In P. Kovács (Ed.), Proceedings of Challenges and Innovations in Statistics Education Multiplier Conference of ProCivicStat. https://eco.u-szeged.hu/download.php?docID=73891 

Haldar, L. C., Wong, N., Heller, J. I., & Konold, C. (2018). Students making sense of multi-level data. Technology Innovations in Statistics Education, 11(1). http://dx.doi.org/10.5070/T5111031358