Darryl Chamberlain

External Links

The views expressed on faculty and external web pages are those of the author and do not necessarily represent those of Embry-Riddle Aeronautical University.

Biography

Dr. Darryl Chamberlain serves as an Assistant Professor and Associate Department Chair for the Department of Mathematics, Science and Technology. With a Ph.D. in Mathematics and Statistics, research background in educational qualitative and quantitative measurement and practical experience writing code in a variety of programming languages (Python, Javascript, C), Darryl serves as an expert in Educational Data Science. His research focuses on applying theoretical learning trajectories and machine learning algorithms to analyze, anticipate and describe student thinking in mathematical sciences. He is commonly called on for his experience surrounding technology in education, serving as chair of the Mathematics Association of America Subcommittee on Technology in Mathematics Education as well as chair of the Embry-Riddle Worldwide Faculty Senate Academic Technology Committee.

See a brief explanation of Dr. Chamberlain's research in Educational Data Science here: https://youtu.be/BA2hrQb-zXY

Education

• Ph.D. - Doctor of Philosophy in Mathematics and Statistics, Georgia State University
• B.S. - Bachelor of Science in Mathematics, University of Florida

Ratings and Certificates

• Applied Data Science with Python - Coursera (University of Michigan)

Currently Teaching

• DSCI 411: Appl Data Sci Capstone
• MATH 502: Boundary Value Problems
• DSCI 201: Intro Data Sci Applications
• STAT 412: Probability and Statistics
• RSCH 395: Publication-Ready STEM Rsch

Publications

Published Peer-Reviewed Articles

1. Chamberlain Jr., D. (Jan 2023). How one instructor can teach a large-scale, mastery-based College Algebra course online. Problems, Resources, and Issues in Mathematics Undergraduate Studies. DOI: TBD.
2. Faulconer, E., Chamberlain Jr., D., & Woods, B. (2022). A Case Study of Community of Inquiry Presences and Cognitive Load in Asynchronous Online STEM Courses. Online Learning Journal. DOI: http://dx.doi.org/10.24059/olj.v26i3.3386.
3. Chamberlain Jr., D. & Vidakovic, D. (2021). Cognitive trajectory of proof by contradiction for Transition-to-Proof students. Journal of Mathematical Behavior. DOI: 10.1016/j.jmathb.2021.100849.
4. Chamberlain Jr., D. & Jeter, R. (2020). Creating diagnostic assessments: Automated distractor generation with integrity. Journal of Assessment in Higher Education. DOI: 10.32473/jahe.v1i1.116892.
5. Chamberlain Jr., D., Grady, A., Keeran, S., Knudson, K., Manly, I., Shabazz, M., Stone, C., & York, A. (2020). Transitioning to an active learning environment for calculus at the University of Florida. Problems, Resources, and Issues in Mathematics Undergraduate Studies. DOI: 10.1080/10511970.2020.1769235
6. Stalvey, H., Burns, A., Chamberlain Jr., D., Kemp, A., Meadows, L., & Vidakovic, D. (2019). Students’ understanding of the concepts involved in hypothesis testing for one population. Journal of Mathematical Behavior. DOI: 10.1016/j.jmathb.2018.03.011.

Under Review Peer-Reviewed Articles

1. Chamberlain Jr., D. and Jeter, R. (Submitted Dec 2022). Utilizing Theoretically-Driven Distractors to Make Diagnostic Multiple-Choice Assessments Possible. International Journal of Research in Undergraduate Mathematics Education (IJRUME).

2. Chamberlain Jr., D., Reed, Z., & Keene, K. (Submitted Dec 2022). Collective Knowledge Progression and Proliferation in Asynchronous Calculus Discussion Boards. International Journal of Research in Undergraduate Mathematics Education (IJRUME).

3. Paolucci, C., Chamberlain Jr., D., Redding, C., Vancini, S., & Reese, A. (first submission Nov 2021, revised and resubmitted Aug 2022). Critical lessons from certification exam preparation materials for mathematics teachers’ content knowledge and professional learning. Journal of Teacher Education.