R is a free and powerful statistical computing language. Most courses that teach R start with an esoteric computer science lecture and sample data about cars. THIS course will provide busy faculty and graduate students with tools to analyze actual classroom data to start you on the path to using quantitative methodologies to conduct education research. It will relate concepts in Excel with programs in R. The workshop series includes an introduction to R through the lens of classroom teaching, R for analysis of classroom data for education researchers, and graphing in R. Attendees are expected to be novices to R.

The workshop is designed to be hands-on. Participants are required to bring laptops and be ready to start learning R, writing code, analyzing data, and writing results. Each participant will choose a course that they taught in the past at UCI and bring the gradebook data for that course. Institutional data related to that course will be provided to participants. By the end of the workshop series, participants will be comfortable with R Commander (a point and click alternative to coding in R), basic coding, graphing in R, and basic statistical analyses (t-tests, ANOVA, and regression).   

To register for the course, please complete the following form

 Cost 

  • $200

 Location 

  • Anteater Instruction and Research Building (AIRB) 1030

 Time 

  • 12:00-2:00pm

Workshop Schedule

  • Friday, October 11, 2019
  • Friday, October 25, 2019
  • Friday, November 8, 2019
  • Friday, December 6, 2019
  • Friday, December 13, 2019

Materials Needed 

Participants are asked to bring the following to the workshop: 

  • Laptop with R installed (will send instructions)
  • Gradebook data in csv format 
    • Columns: StudentID, CourseCode, Homework, MidtermExam1, MidtermExam2, FinalExam 
  • Please feel free to bring your lunch to the workshop.

Learning Outcomes 

  • Summarize and carry out exploratory and descriptive analysis of data. 
  • Conduct appropriate statistical modeling techniques for continuous, categorical, and dichotomous responses
  • Use R competently to model and interpret the results for the analysis of data. 
  • Present and communicate, both orally and in written-form, the results of statistical analyses of data. 

Instructor:

Dr. Kameryn Denaro is the computational statistician at the Teaching and Learning Research Center, UCI. She taught math and statistics for 14 years at community colleges, SDSU and UCI. In her current role, she collaborates with UCI faculty on education research projects and provides institutional data for education research on campus.

Comments are closed.