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Data Analysis and Visualization: Creating Plots, Modified Metrics of Accuracy, and User Dashboards

Illustrating Information from Tables using Plots

  1. Who are the users? To answer this question, you will need to compile a user profile table (Table 1) with information about users including
    1. Overall practice volume and performance ( of questions answered, % of questions answered correctly)
    2. Learning activity (e.g. # lectures watched, # explanation read)
    3. Add three additional metrics you would like to compute to describe users

Create a few plots to illustrate the information in the tables. Feel free to choose the appropriate type of plots you think is appropriate. 

What are the questions/items? To answer this question, you will need to compile a question profile table (Table 2)  with information including Create a few plots to illustrate the information in the tables. Feel free to choose the appropriate type of plots you think is appropriate. 

Design a modified metric of “accuracy” to fairly describe users’ ability by taking into account the difficulty level as derived from Table 2. Describe the procedure to compute the metrics.  Be sure to be specific so that interns can use your pseudo code to implement the metrics without much trouble. implement the proposed metrics and plot a histogram of the metrics across all users (or subset of users of your choices). 

Pick a user with a reasonable amount of activity (you will define the “reasonableness” and specify the selection criteria) and create a dashboard that consists of a series of plots to tell a story of this user’s activity patterns. For inspiration, you may look at the user dashboard for fitness tracker such as Fitbit. 

Propose two tasks for your interns to work on. The first task is of unsupervised/descriptive type and a second one is of supervised/predictive task. Please provide clear specification of the tasks so that your interns can start to work right away. You should try to propose tasks that are not attempted in the existing work with this dataset. 

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