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Student Performance

✓ Published0🌍 Public
RRuba Khan
Last edited Sep 7, 2024
Created on Sep 2, 2024

This visualization displays a preview of student performance data, showing the first record's attributes such as attendance rate, study hours, previous grade, and final grade. It loads data from a CSV file containing ten students with demographic and academic metrics, converting quantitative fields to numbers. The example uses plain JavaScript to parse the data and render the first entry as formatted JSON text in a container, providing a simple template for inspecting dataset structure before building more complex charts.

AI-generated description

The Student Performance Dataset, loaded and parsed as CSV.

Fork and modify this template to import your data to VizHub and export it for use in other vizzes! To do that:

  • Fork this viz
  • Clear out the README
  • Update the README with details about your dataset (including original source)
  • Replace data.csv with your own data
  • Replace the parsing logic in index.js with your own
  • Set the custom URL so you can import from it easily

Challenge

  • Find 3 datasets on a topic you are interested in
  • For each of those, fork this viz and replace the data
  • Parse the quantitative attributes into numbers
  • Update README.md to indicate the original data source

Analytics Task

  • I want to see if there is a relationship between the attendance rates and final grades. This could tell us how attending classes regularly correlates with high grades
  • I want to analyze study hours per week along with the number of extracurricular activities to determine how students can create a balance between studying and their non-academic interests
  • I want to compare previous and final grades to identify improvements or decline in student performance
  • I want to evaluate the impact of high parental support on final grades compared with students that have low parental support
  • I want to identify patterns in final grades relative to the number of extracurricular activities to help us understand the benefits or even drawbacks or being actively involved outside of academics
MIT Licensed

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