Skip to content

About

Creating an interactive visualization consists of skill mastery for each student based on the midterm results

Resources

Stars

0 stars

Watchers

0 watching

Forks

Repository files navigation

Interactive Visualization

Interactive visualization is becoming a more prominent feature of reporting. Business analytics packages tend to stress the ease eith which data can be played with by non-experts. Allowing students to explore aspects of complex data rather than simply telling them what you see can be a powerful tool for learning as explored in the readings. Within the RStudio universe this functionality is accomplished through the Shiny ecosystem. A web-app designing interface that allows web-apps to be built from within R with limited knowledge of javascript or html.

midterm

Project Objective:

The purpose of this project is to build a couple of basic Shiny Apps and then create an interactive visualization of some midterm test data that can aid student learning. This dashboard consists of skill mastery for each student based on the midterm results, which can be seen below. The skills are as follows: coding, decision trees, just-in-time-learning (JITL), neural networks, natural language processing (NLP), social network analysis (SNA), substantive meaning from the analysis (Substantive), data visualizations (Viz), and data wrangling. It also includes scatterplot which displays the relationship between the student's grades, total time spent on the midterm and total click count where the user chooses the variables for the x-axis and y-axis and what variable to color by. Each data point on the scatterplot represents student's data.

Datasets:

  • midterm-results.csv
  • quiz-categories.csv
    • wrangling - Question required data manipulations skills
    • coding - Question required coding skills
    • d.trees - Question invoilved decision trees
    • sna - Question involved social network analysis
    • nlp - Question involved natural language processing
    • viz - Question involved visualization of data
    • n.nets - Question involved neural nets
    • googleable - Question could be answered by searching the internet
    • non-googleable - Question could not be answered through simple searching of the internet
    • jitl - Question involved learning somethimg new (just in time learning)
    • substantive - Question involved wrestling with a complex idea that does not have a definitive answer

Dashboard Links:

Interactive Visualizations Histogram Link
Midterm Results Dashboard Link

About

Creating an interactive visualization consists of skill mastery for each student based on the midterm results

Resources

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages