*indicates a co-author who was an undergraduate student mentored by Dogucu at the preparation stage of the publication.

**indicates a co-author who was a graduate student mentored by Dogucu at the preparation stage of the publication.



Under Preparation / Pre-Prints

  1. Dogucu, M., Demirci, S., Bendekgey, H.**, Ricci F. Z.**,& Medina, C. M.** Undergraduate data science education: Who has the microphone and what are they saying?

Peer Reviewed

  1. Dogucu, M., Kazak, S. & Rosenberg, J. (In Press) The Design and Implementation of a Bayesian Data Analysis Lesson for Pre-Service Mathematics and Science Teachers. Journal of Statistics and Data Science Education.
  2. Ricci, F. Z.**, Medina, C.** & Dogucu, M. (2024) Automated grading workflows for providing personalized feedback to open-ended data science assignments. Technology Innovations in Statistics Education. 15(1).
  3. Demirci, S., Dogucu, M., Zieffler, A. & Rosenberg, J. (2023) The Learning Difficulties of Introductory Data Science Students In E. Jones (Ed) Proceedings of the International Association for Statistical Education Satellite Conference. Online.
  4. Dogucu, M. Johnson, A.A. & Ott, M. (2023) Framework for Accessible and Inclusive Teaching Materials for Statistics and Data Science Courses. Journal of Statistics and Data Science Education. 31(2), 144-150.
  5. Seo, J. & Dogucu, M. (2023) Teaching Visual Accessibility in Introductory Data Science Classes with Multi-Modal Data Representations Journal of Data Science. 21(2), 428-441.  
  6. Dogucu, M. & Johnson A. (2022) Supporting Bayesian Modeling with Visualizations. In S. Peters (Ed) Proceedings of the 11th International Conference on Teaching Statistics. Rosario, Argentina.
  7. Dogucu, M. & Cetinkaya, M. (2022) Tools and Recommendations for Reproducible Teaching. Journal of Statistics and Data Science Education. 30(3), 251-260.
  8. Dogucu, M. & Hu, J. (2022) The Current State of Undergraduate Bayesian Education and Recommendations for the Future.The American Statistician, 74(2), 405-413.
  9. Rosenberg, J., Kubsch, M, Wegenmakers, E.J. & Dogucu, M. (2022) Making Sense of Uncertainty in the Science Classroom: A Bayesian Approach. Science & Education, 31, 1239–1262.
  10. Çetinkaya-Rundel, M., Dogucu, M. & Rummerfield, W.** (2022) The 5Ws and 1H of Final Projects in the Introductory Data Science Classroom. Statistics Education Research Journal, 21(2), 4-4.
  11. Shindler, M., Pinpin N., Markovic M., Reiber F., Kim, J.H., Nunez Carlos, G.P.*, Dogucu, M., Hong, M., Luu, M., Anderson, B., Cote, A., Ferland M., Jain P., LaBonte, T., Mathur, L., Moreno R. & Sakuma, R. (2022) Student Misconceptions of Dymanic Programming: A Replication Study. Computer Science Education, 32(3), 288-312.
  12. Hu, J. & Dogucu, M. (2022) Content and Computing Outline of Two Undergraduate Bayesian Courses: Tools, Examples, and Recommendations. Stat. 11(1)
  13. Rummerfield, W.**, Ricci, F. Z.** & Dogucu, M. (2021) Training Graduate Students to Teach Statistics and Data Science from a Distance. In R. Helenius (Ed) Proceedings of the International Association for Statistical Education Satellite Conference. Online.
  14. Dogucu, M. & Çetinkaya-Rundel, M. (2021) Web Scraping in the Statistics and Data Science Curriculum: Challenges and Opportunities. Journal of Statistics Education. 29(sup1), S112 - S122.  
  15. Piasta, S.B., Sawyer, B., Justice, L.M., O’Connell, A.A., Jiang, H., Dogucu, M., & Khan, K. (2020). Effects of Read It Again! in Early Childhood Special Education Classrooms. Journal of Early Intervention, 42(3), 224-243.
  16. Farley, K.S., Piasta, S. B., Dogucu, M. & O’Connell, A. (2017) Assessing and Predicting Small-Group Literacy Instruction in Early Childhood Classrooms. Early Education and Development, 28(4), 488-505.

Book

  1. Johnson, A. A., Otts, M. & Dogucu, M. (2022), Bayes Rules! An Introduction to Applied Bayesian Modeling. CRC Press. 1st edition.

Book Chapter

  1. Seo, J. & Dogucu, M. Data Science + Accessibility. In A. Oleson, A. J. Ko, R. Ladner (Eds) Teaching Accessible Computing. 2024.

Software

  1. Ricci, F. Z.**, Medina, C.** & Dogucu, M. R package gradetools: Tools to Assist with Providing Grades and Personalized Feedback to Students. GitHub, March 2022.
  2. Dogucu, M., Johnson, A.A. & Otts, M. , R package bayesrules: Datasets and Supplemental Functions from Bayes Rules! Book. CRAN, June 2021.

Other Publications

  1. Dogucu, M. (In Press) Reproducibility in the Classroom Annual Review of Statistics and Its Application
  2. Dogucu, M. (2024) Recommendations for Undergraduate Students Interested in Statistics and Data Science. Amstat News (564), 30-32.
  3. Bellini Saibene, Y., Dogucu, M., Palopoli, N., Campitelli, E., Acion, L. Corrales, P., & Loto, P.A. (2022) MetaDocencia: Enseñando a Enseñar Estadística y Ciencia de Datos Online [MetaDocencia: Teaching How to Teach Statistics and Data Science Online]. In S. Peters (Ed) Proceedings of the 11th International Conference on Teaching Statistics. Rosario, Argentina.
  4. Dogucu, M. (2021) Contributing to Open Education: Why, How, and What I am Doing. AMS Notices, 68(3), 367-369
  5. Dogucu, M. (2020) Teaching Careers (for Statisticians): What You Should Know. Amstat News (521), 32-34.
  6. Haylock D. & Cockburn A. (2014). Ölçmeyi Anlama [Understanding Measurement] (M. Dogucu Trans.). In Küçük Çocuklar İçin Matematiği Anlama [Understanding Mathematics for Young Children]. Ankara, Turkey: Nobel.
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