*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.



Peer Reviewed

  1. Dogucu, M. & Hu, J. (In Press) The Current State of Undergraduate Bayesian Education and Recommendations for the Future.The American Statistician.
  2. Rosenberg, J., Kubsch, M, Wegenmakers, E.J. & Dogucu, M. (In Press) Making Sense of Uncertainty in the Science Classroom: A Bayesian Approach. Science & Education.
  3. 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.
  4. 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.
  5. Hu, J. & Dogucu, M. (2022) Content and Computing Outline of Two Undergraduate Bayesian Courses: Tools, Examples, and Recommendations. Stat. 11(1)
  6. Rummerfield, W.**, Ricci, F. Z.** & Dogucu, M. (2021) Training Graduate Students to Teach Statistics and Data Science from a Distance. Refereed conference paper for International Association for Statistical Education (IASE) Satellite Conference.
  7. Dogucu, M. & Çetinkaya-Rundel, M. (2021) Web Scraping in the Statistics and Data Science Curriculum: Challenges and Opportunities. Journal of Statistics Education. 1-11  
  8. 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.
  9. 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.

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. (2021) Contributing to Open Education: Why, How, and What I am Doing. AMS Notices, 68(3), 367-369
  2. Dogucu, M. (2020) Teaching Careers (for Statisticians): What You Should Know. Amstat News (521), 32-34.
  3. Dogucu, M. (July 2020 - present) Data Pedagogy blog.
  4. 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.

Under Preparation

  1. Dogucu, M. Johnson, A.A. & Ott, M. Framework for Accessible and Inclusive Teaching Materials for Statistics and Data Science Courses. Manuscript being revised.
  2. Dogucu, M. & Cetinkaya, M. Tools and Recommendations for Reproducible Teaching Manuscript being revised.
  3. Seo, J. & Dogucu, M. Teaching Visual Accessibility in Introductory Data Science Classes with Multi-Modal Data Representations Manuscript under review.
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