Difference between revisions of "ISSS608 2016-17 T1 Assign2 XU Qiuhui"
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==User behaviors and external environments== | ==User behaviors and external environments== | ||
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External environments tend to have huge influences on behavioral intention. Form the parallel set we can clearly get that almost all people whose colleagues don’t use wiki and are not consider well on wiki are not intended to use wiki in teaching in the future. | External environments tend to have huge influences on behavioral intention. Form the parallel set we can clearly get that almost all people whose colleagues don’t use wiki and are not consider well on wiki are not intended to use wiki in teaching in the future. | ||
Revision as of 14:13, 26 September 2016
Contents
Data Sources
Dataset from UCI, Survey of faculty members from two Spanish universities on teaching uses of Wikipedia
Source: E. Aibar, J. Lladós, A. Meseguer, J. Minguillón (jminguillona[at]uoc[dot]edu), M. Lerga. Universitat Oberta de Catalunya, Barcelona, Spain.
Theme of Interest and Motivation
This Analysis aims to find out overall impressions of different user segments on Wikipedia and their use behavior according to high dimensional survey question answers. Then propose recommendations for Wikipedia's future development. In this analysis, we'll mainly answer the following questions：
- Relationships between user impressions and user behaviors.
- Relationships user behaviors and external environments.
Data Preparation
Transfer Data Type
| Variables | Original Data Type | Transferred Data Type | Reason |
|---|---|---|---|
| Gender | Numeric | Categorical | According to dataset dictionary, gender is meaningless while using numeric value to do analysis. |
| PhD | Numeric | Categorical | According to dataset dictionary, PhD is meaningless while using numeric value to do analysis. |
| University | Numeric | Categorical | According to dataset dictionary, University is meaningless while using numeric value to do analysis. |
| YearsExp | Categorical | Numeric | Years of experience should be continuous data, so that we can firstly bin them into several groups, then use groups to classify them. |
Bin Numeric Data
| Variables | Original | Transferred Variables | Formula |
|---|---|---|---|
| Age |  |
Age(bin) | If(:AGE <= 30,"20~30",If(:AGE <= 40,"30~40",If(:AGE <= 50,"40~50",If(:AGE <= 60,"50~60","60~70")))) |
| YearsExp |  |
YearsExp(bin) | If( :YEARSEXP <= 10,"0~10",If( :YEARSEXP <= 20,"10~20",If( :YEARSEXP <= 30,"20~30","more than 30"))) |
Group Categorical Data
Transform all survey question answers with 1-5 scores to “High, Mid, Low” degree.
| Scores | Degree |
|---|---|
| 1 | Low |
| 2 | Low |
| 3 | Mid |
| 4 | High |
| 5 | High |
Inset New Column
Insert a new column, User ID to uniquely represent one user in the dataset.
| Variable | Data Type | Example | Description |
|---|---|---|---|
| UserID | Categorical | “U1”, “U2” …” U913” | Each User ID uniquely identifies a user in the dataset. |
Visualization
Analysis
User impressions and behaviors
There’s a large proportion user who don’t use to teach have very good impression on wiki, they’re potential users.
Information on wiki are considered updated and relatively reliable, but still considered with lower quality than other educational resources.
Even though wiki is considered with lower quality, users still trust in it's editing system.
User behaviors and external environments
External environments tend to have huge influences on behavioral intention. Form the parallel set we can clearly get that almost all people whose colleagues don’t use wiki and are not consider well on wiki are not intended to use wiki in teaching in the future.
Relationships beneath the surface
Conclusions and Recommendations
Key Findings
Recommendations
Tools Utilized
- High-D - For initial data exploration and analysis
- JMP 12, MS Excel – For data preparation
- d3.js - For data visualization
