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.

In this project, I will first practice and show some simple example of interactive visualizations, and then I will build one to show how students master different skills as tested.

Random Histogram Generator

Now we will build another Shiny App one piece at a time (Only the code starting at line 97 will run). This app will generate a histogram based on random values drawn from a normal distribution, the user will be able to select the number of draws that generate the histogram by using a slider.

Skill Mastery Check

Build an interactive visualization using the data sets quiz-categories.csv and midterm-results.csv. These data represent midterm results from an open book test. The categories represent the skills required to answer each question:

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

Here is what the app looks like:

In this visualization, questions are clustered within skill categories. Some skill categories are more specific (such as wrangling, nlp, sna, d.trees), some are more general (such as coding, goolgeableable, non-googleable). We can see how many students get the questions related to specific skills right.

Relevant Materials

Shiny Apps Documentation

Shiny Gallery

Verbert, K., Duval, E., Klerkx, J., Govaerts, S., & Santos, J. L. (2013). Learning Analytics Dashboard Applications. American Behavioral Scientist, 57(10), 1500–1509.