1. What are the best classes to take? A DATA MINING APPROACH TO FINDING THE BEST CLASSES AND TEACHERS BY JOSEPH BRODERICK

2. Project Goals  What are the best classes to take at CWRU?  What makes a class good?  Who are the best teachers at Case Western?  What can a teacher do to improve their teaching style?  Is there that big of a difference between a class at CWRU?  Same class different teacher?  Different class same teacher?

3. Data Collection  How to format the data  Give every Data point a star rating  Use the ratings to determine conclusions about the data  How many people in a class?  How about more current data rather than just 1997-2006.

4. Data Preprocessing  Dr. Oc did not put in 0 for his reports.  Isn’t all of the data normally distrusted anyways? (Turn to Z values, so scale from (-1 to 1) (need to do)  Multiple teachers with the same last name  Different Departments switch name (EECS came as a department in 2000)  No nursing evaluations

5. Implementation  Run all the text data into a string reader from python  Get all the numbers  Turn those numbers into ratings  Use the Scikit for clustering analysis  IPython Notebook for more precise results of teachers and courses to determine who belong to what group.

6. How do we decide the results  K means  Already know different group of teachers want to find those groups  “Percentile” of teacher  Which department average  Average by class or by students  Standard deviation away

7. Question what Departments have courses with lighter workloads  https://plot.ly/~jase.broderick/1/overall-work-load-of-different- departments/ https://plot.ly/~jase.broderick/1/overall-work-load-of-different- departments/  https://plot.ly/~jase.broderick/2/average-workload-of-different- departments/ https://plot.ly/~jase.broderick/2/average-workload-of-different- departments/

8. More Interesting Results

9. Clustering some of the Data

10. Good Teachers? YearWinners 2005 Robert E. Dunn (Music) Robert E. Harris (Chemical Engineering) 2004 Chris Butler (Mathematics) Hillel Chiel (Biology) 2003 Jutta Ittner (Modern Languages & Literatures) Eric Youngstrom (Psychology) 2002 Ronald Cechner, Biomedical Engineering John Orlock, Theatre 2001 Ken Ledford, History Mano Singham, Physics 2000 Thomas S. Ellis, English Carol D. Epstein, Nursing 1999 Gary M. Ciepluch, Music David A. Smith, Physics 1998 Miram R. Levin, History Joe H. Payer, Materials Science and Engineering Past Recipients of the Carl F. Wittke Award Group They Belong To: 2,3,4,1 2,2 2,3 6,0,0 7,6,5 2,6 0 1,2,3 5,0 6,5,5,2 6,0,5 3,5 3 2,0 1,3

11. Future Implementations  Biclustering  Look at the different attributes of the instructor (Questions 5-16) and see which groups of teachers will show up  Which of those groups of teachers are the best at teaching  Good teaching?  Compartmentalize Classes and Teachers into their own categories.  All reviews of one teacher go into one data point  All reviews of one class go into one data point  Normalize all the data for better results  Figure out best teacher for different classes.

12. Results so far from Teaching Styles Question 15 seems to be irrelevant for some teachers

13. Questions?  End of Presentation