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Teaching

[2019 Fall] Spatial Data and Analysis, in Python (GSPP 275, MPP/MPA/PhD level)

  • Overall teaching evaluation: 4.5 / 5

  • Selected feedback:

    • "Luna clearly knows the material well, is a great resource, and is really supportive. I really appreciated that she was flexible and responsive to students' requests to change the structure of section - going through code and problems similar to our labs was super helpful."
    • "Luna had the difficult task of helping to transition all the Matlab labs into Python -- and helping all the students struggling with Python -- and she managed to do it all seamlessly and with so much positive energy. She was an invaluable resource for those of us that struggled more with Python. She was always helpful and patient with even the most basic questions, and welcomed and responded to feedback on how she was explaining concepts. She was also very responsive on piazza, and encouraged classmates to use it as a forum to help with labs."
    • "Extensive knowledge on the subject and Python. It was really helpful to have Luna's input to go through the Labs. It is not easy to be GSI for this course because of the heterogeneity of the student body. Also, some of the concepts are very hard to explain and that could be an area of improvement (more clarity when explaining materials and complex concepts). Otherwise, her feedback and responsiveness to questions/issues were outstanding."
    • "Luna is always prepared and so helpful considering how difficult this course material can be. She is always very quick to respond to any question I have and has been very effective in being a GSI for this course."

  • See this for the full teaching evaluation report

[2018 Fall] Microeconomics (MBA 201A, MBA level)

[2017 Fall] Microeconomics (EEP 100, undergraduate level)