ISSS608 2016-17 T1 Assign2 Franky Eddy

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Abstract

Nowadays, internet has been one of the most popularly used technology to explore and find useful information. Wikipedia is one of the most commonly used source for studying as well as teaching resource.From the survey data of faculty members from two Spanish universities on teaching uses of Wikipedia, there are some insights and findings that wanted to be explored:

  • How do respondents with different age groups rate their experience on using Wikipedia?
  • What is the rating (Likert Value) of each question or statement used in the survey?
  • How do respondents with different gender from different universities, domains, and age group rate?
  • How do universities, domain, or Wikiuser rate ?

To answer these questions, data visualization is used to get insights:


Overview of Data

The dataset used is the survey of faculty members from two Spanish universities on teaching uses of Wikipedia.

Approaches

Step 1: Identify a theme of interest

The wiki dataset consists of answers from survey for research on university faculty perceptions and practices of using Wikipedia as a teaching resource. Theme of interest that can be explored from the dataset is the relationship between different attributes of the respondents and how they assess based on the survey. Another thing that also wanted to be observed from the data is analysing the survey results on teaching uses of Wikipedia to see whether there are insights that can be obtained.

Step 2: Define questions for investigation

There are 4 questions that will be investigated based on the theme of interests defined:

  • How do respondents with different age groups rate their experience on using Wikipedia?
  • What is the rating (Likert Value) of each question or statement used in the survey?
  • How do respondents with different gender from different universities, domains, and age group rate?
  • How do universities, domain, or Wikiuser rate ?

Step 3: Find appropriate data attributes

After defining the questions, the next step is finding the appropriate data attributes. The data attributes that will be used are University, Domain, Gender, and UserWiki. These attributes will be used to analyse the survey results and see whether there are some insights that can be obtained.


Data Preparation

Before using the data to do analysis, firstly data preparation needs to be done. The first thing to be done is recoding all "?" values to blank values. After that, other variables such as Gender, Domain, PhD, YearsExp, University, UOC_Position, Other Position, OtherStatus, and UserWiki are also recoded as can be seen in the figure below.

Recode Franky.png

After recoding the variable values, next, the dataset needs to be reshaped so that . The reshaped data can be seen in the figure below. Reshape Franky.png
After reshaping the data, the data is now ready to be used for analysis.

Analysis

After preparing the data, next step is to do the analysis. The analysis is done to answer the questions that have been defined.

Results

There are 3 results from the analysis: Age Group Response Franky.png

Likert Franky.png

Treemap Franky.png

Trellis Franky.png

Link to Tableau Public :
Dashboard 1[1]
Dashboard 2[2]


Tools Utilized

The tools used for this analysis are Tableau 10.0, JMP Pro12, and Microsoft Excel, Tableau Public.
Charts used: Bar Chart, Stacked bar Chart, Treemap, Trellis Chart


References

http://www.datarevelations.com/using-tableau-to-visualize-survey-data-part-1.html
http://www.datarevelations.com/using-tableau-to-visualize-survey-data-part-2.html


Comments

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