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Data and Analytics (Sec 2)

INSTRUCTOR: JAEHWUEN JUNG

Data and Analytics

MIS 2502.002 ■ Spring 2025 ■ Jaehwuen Jung
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Introducing a new learning tool: MasteryGrids (Extra Credit)

January 30, 2025 Leave a Comment

MasteryGrids system is an interactive learning tool that helps you improve and track your understanding of course concepts. The system visualizes your progress through different course topics using a color-coded grid, where darker shades indicate higher mastery levels. As you work through the exercises and questions, you’ll not only strengthen your knowledge, but you can also earn extra credit. Specifically, you will receive a checkmark for a topic when you complete at least two Independent problems in it, and you can earn up to two extra points toward your final grade if you get checkmarks for all the topics presented in MasteryGrids. However, beyond the extra points, active engagement with MasteryGrids is an excellent way to reinforce learning. You can access the system anytime to practice and improve at your own pace. (Please note that your activity in MasteryGrids will be evaluated based on progress made up until the final exam on April 23.)

To get started, simply follow the http://adapt2.sis.pitt.edu/kt/ and log in using your existing MySQL data server username with “tu” added at the beginning. For example, if your data server username is m123, your MasteryGrids username will be tum123. The password is the same as the one you use for the MySQL server. If you would have any questions, please reach out to Prof. Bauman at kbauman@temple.edu.

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QUICK INFO

  • Time and Locations: 12:30 pm – 1:50 pm, Tuesday and Thursday, Alter 234
  • Instructor: Jaehwuen Jung (jaejung@temple.edu)
    Office hours: 2:30 pm – 3:30 pm, Tuesday and Thursday (Speakman 201D)
  • ITA: Matthew Thomas
    (matt.thomas@temple.edu)
  • TA: Shuhua Wu
    (shuhua.wu@temple.edu)
    Office hours: 4 pm – 5 pm on the day of the assignment due (208 F or Zoom)

LINKS

  • Temple Canvas
  • MasteryGrids (Extra Points)
  • MySQL Workbench Instruction
  • Jupyter and Anaconda Instruction

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