Evidence-based teaching practices
I have taught eight different undergraduate courses with over 7200 students, from freshman to senior level. Throughout my teaching I observed and improved how: (a) students learn better when they construct their knowledge through active learning, (b) students are more engaged when applying class concepts to solve real-world problems, and (c) the learning process and knowledge retention are improved with the use of frequent assessments and immediate feedback.
Teaching practices adopted in my Numerical Methods course
Teaching experience
| Course name | Term taught |
|---|---|
| Numerical Methods 1 | Spring 2018, Fall 2018, Spring 2019, Fall 2019, Spring 2020, Fall 2020, Spring 2021, Fall 2021, Spring 2022, Fall 2022, Spring 2023, Fall 2023, Spring 2024, Fall 2024 |
| Intro to Computing: Eng & Sci | Fall 2024 (co-instructor) |
| Current Topics in Computing Education Research | Fall 2024 (co-instructor) |
| Applied Linear Algebra | Fall 2020 |
| Computational Tools for Linear Algebra | Spring 2020 |
| Brushing up Linear Algebra and Programming Fundamentals using Python | Fall 2019 |
| Python for Data | Fall 2019, Spring 2020 - Pot A, Spring 2020 - Pot B |
| Real World Cases in Scientific Computing | Fall 2018 |
| Introduction to Online Learning Systems | Fall 2017 |
| Finite Element Analysis | Spring 2016, Spring 2017 |
| Introductory Solid Mechanics | Spring 2012, Fall 2012, Spring 2013, Fall 2013, Spring 2014, Fall 2015, Fall 2016, Fall 2017 |
| Statics | Fall 2014, Spring 2015, Spring 2017 |
Teaching awards
-
Rose Award for Teaching Excellence, 2022, Grainger College of Engineering, University of Illinois at Urbana-Champaign
-
Scott H. Fisher Computer Science Teaching Award, 2022, Computer Science, University of Illinois at Urbana-Champaign
Past Highlights
Over the years, I have explored various teaching innovations and course development projects that have shaped my approach to education. Below is a collection of key resources and activities that reflect these efforts.