I believe that the performance of a professor should be open and transparent, giving students (the ultimate customers) information on their teacher. As a data scientist, I love the numbers and analysis aspect and as an educator I love the student feedback as it helps me to identify what is working and what isn’t so that I can constantly improve my teaching. The following tables and charts show my most up-to-date teaching evaluations and performance data from students to allow you, the future student, to make an informed decision regarding your education.
The data encompasses Fall 2000 – Spring 2025 with an average teacher rating of 4.26 and a standard deviation of 0.51 over 178 classes to date. The average uses the scale of Excellent (5.0), Above Average (4.0), Average (3.0), Below Average (2.0) and Failing (1.0). The standard deviation represents the amount of variation around the average. A low standard deviation represents uniformity among student raters whereas high standard deviation represents a disparity or a wide dispersion of ratings, e.g.; some loved the class where others did not. Assuming a normal distribution of ratings (e.g.; a bell-shaped curve) we would expect 67% of values to be within one unit of standard deviation around the average (4.26 ± 0.51) for a range of 3.75 to 4.77 and 95% of values to be within two units of standard deviation around the average (4.26 ± 2*0.51).
From the data, my teaching evaluations have remained fairly consistent throughout my career and have shown steady improvement since joining UT Tyler for the 2015-2016 academic year (AcadYear=2016). For comparison purposes, here is a link to the UT Tyler faculty evaluations that are required by Texas 81(R) HB 2504.
The table below contains all of the courses I have taught at UT Tyler, the number of times I have taught the course, average teacher evaluation, standard deviation and average grade (GPA) of students in the course. Research has shown that teaching evaluations are positively correlated to course grades and class attendance [1]. You will notice that my math-oriented or mentally challenging courses will have lower teacher ratings (e.g.; Capstone, Data Analytics and Database), consistent with educational research. Courses that are more conceptual with topics already familiar to students will have higher ratings.
| Coursename | Num times taught | Avg Rating | Std Deviation | Avg GPA |
| Business Information Systems | 12 | 4.46 | 0.25 | 2.56 |
| Business Intelligence | 19 | 3.96 | 0.75 | 3.00 |
| Capstone | 8 | 3.78 | 0.55 | 3.42 |
| Database | 4 | 3.85 | 0.40 | 2.68 |
| Design of MIS | 3 | 4.49 | 0.08 | 3.32 |
| eCommerce | 6 | 4.39 | 0.27 | 3.01 |
| ERP Architecture | 8 | 4.51 | 0.07 | 3.20 |
| Machine Learning | 3 | 4.65 | 0.13 | 3.69 |
| Microsoft Office | 2 | 4.08 | 0.02 | 2.94 |
| Networking | 1 | 4.50 | 0.00 | 3.00 |
| Quantitative Investing | 5 | 4.87 | 0.11 | 3.69 |
| Research Methods | 1 | 4.70 | 0.00 | 3.50 |
| Sports Data Analytics | 10 | 4.66 | 0.41 | 3.27 |
| Systems Analysis and Design | 3 | 4.43 | 0.34 | 2.48 |
| Text Analytics | 2 | 3.77 | 0.00 | 3.45 |
As you can see from the data, my goal of maintaining high teacher ratings aligns with your goals to succeed. However, I won’t make it easy because I genuinely want you to learn from my field in order to be a successful and productive member of industry. The main takeaway is if you work hard, immerse yourself in the material, do every extracurricular opportunity offered and try your best, you will have a good experience in my class.