ISSS608 2016-17 T1 Assign2 Ho Li Chin
Contents
- 1 Abstract
- 2 Theme of Interest
- 3 Examine the Survey Questions
- 4 Questions for Investigation
- 5 Analysis of Wiki For Higher Education Dataset through Visualisation
- 6 Tools Used and Visualisation Links
- 7 Tools Used and Visualisation Links
- 8 Conclusion
Abstract
In this assignment, the interactive data exploration and the analysis techniques will be applied to discovery patterns in multivariate data.
Theme of Interest
In this assignment, the dataset that have been chosen for the analysis is “wiki4HE Data Set” (https://archive.ics.uci.edu/ml/datasets/wiki4HE).
The theme of interest is to explore the factors affecting the use of Wikipedia in Higher Education. Wiki technology emerged in higher education teaching and learning experiences as early as 1999 and is integrated into many courses for its ability to provide a collaborative environment for Academic staff and students.
The objective of this assignment is to understand the main factors that influence the teaching uses of Wikipedia among university faculty staff, and any of those factors have significant direct impact on the Behavioral Intention of adopting Wikipedia in higher education, for providing more effective and efficient methods to maximize the teaching and learning experience.
Examine the Survey Questions
In this section, we will first examine the survey questions in the dataset. The survey questions are categorized into respective broader category, and each category is mapped to one construct measure for investigation purpose. These measures will be considered to further derive the investigation questions in next section for the purpose of the analysis.
Survey Question Category | Survey Questions (Variables) | Measures |
---|---|---|
Perceived Usefulness | PU1: The use of Wikipedia makes it easier for students to develop new skills.
PU2: The use of Wikipedia improves students' learning |
User perception of technological innovations using wiki technology |
Perceived Ease of Use | PEU1: Wikipedia is user friendly
PEU2: It is easy to find in Wikipedia the information you seek PEU3: It is easy to add or edit information in Wikipedia |
User perception of technological innovations using wiki technology |
Perceived Enjoyment | ENJ1: The use of Wikipedia stimulates curiosity
ENJ2: The use of Wikipedia is entertaining |
User perception of technological innovations using wiki technology |
Use behaviour | USE1: I use Wikipedia to develop my teaching materials
USE2: I use Wikipedia as a platform to develop educational activities with students USE3: I recommend my students to use Wikipedia USE4: I recommend my colleagues to use Wikipedia USE5: I agree my students use Wikipedia in my courses |
Motivation to use wiki |
Experience | EXP1: I consult Wikipedia for issues related to my field of expertise
EXP2: I consult Wikipedia for other academic related issues EXP3: I consult Wikipedia for personal issues EXP4: I contribute to Wikipedia (editions, revisions, articles improvement...) EXP5: I use wikis to work with my students |
Motivation to use wiki |
Job relevance | JR1: My university promotes the use of open collaborative environments in the Internet
JR2: My university considers the use of open collaborative environments in the Internet as a teaching merit |
Motivation to use wiki |
Sharing attitude | SA1: It is important to share academic content in open platforms
SA2: It is important to publish research results in other media than academic journals or books SA3: It is important that students become familiar with online collaborative environments |
Collaborative Mindset / Attitude |
Profile 2.0 | PF1: I contribute to blogs
PF2: I actively participate in social networks PF3: I publish academic content in open platforms |
Collaborative Mindset / Attitude |
Quality | QU1: Articles in Wikipedia are reliable
QU2: Articles in Wikipedia are updated |
Perceived quality of wiki information |
Social Image | IM1: The use of Wikipedia is well considered among colleagues
IM2: In academia, sharing open educational resources is appreciated IM3: My colleagues use Wikipedia |
Social Influence |
Visibility | VIS1: Wikipedia improves visibility of students' work
VIS2: It is easy to have a record of the contributions made in Wikipedia VIS3: I cite Wikipedia in my academic papers |
Social Influence |
Behavioral intention | BI1: In the future I will recommend the use of Wikipedia to my colleagues and students
BI2: In the future I will use Wikipedia in my teaching activity Incentives |
Intention to use wiki |
Questions for Investigation
From the construct measures as defined in Section 3, following are the evolved list of questions for investigation. Different visualizations will be constructed to present the data and to answer the questions as clearly as possible.
List of questions for investigation:
- a) Relationship between the different factors that could influence the uses of Wikipedia among university faculty.
- What are the positive factors and negative influence factors?
- b) What are the key factors that negatively influence the Behavior Intention to adopt Wikipedia
- Any identification of attributes (e.g. age, academic position, current wiki user etc) that result in the negative Behavior intention to use wiki
- Any skeptical attitudes in university faculty regards using Wikipedia in class
- Any identification of attributes (e.g. age, academic position, current wiki user etc) that result in the negative Behavior intention to use wiki
- b) Understanding of some measures that could influence the behavior intention to use Wikipedia
- User perception of technological innovations using wiki technology
- Motivation factors to use Wikipedia
- Social Influence
- Perceived quality of information using wiki
Analysis of Wiki For Higher Education Dataset through Visualisation
Data Source
The data source for the Wiki dataset can be obtained from
- REDIRECT [[1]]
Data Preparation
The Data preparation is mainly done with JMP, the steps can be summarised as follow:
- Load the wik4HE.csv file into JMP
- Examine the attribute data types
- Convert some attribute data types from Numeric to Categorica
- Recode the values for some categorical attributes. E.g. For Gender, recoded as "Male" and "Female"
- Missing data pattern check
- For categorical variables such as Domain, UOC_Position, the missing values were recoded as "Unknown"
- For Survey Scale values, the missing values were recoded as "Don't Know" response.
Data Cleansing & Transformation
The data transformation was done in JMP in few iterations.
- First, summary and distribution analysis were done for the categorical (univariate) variables.
- Then, for those continuous survey scale response, the multivariate analysis was done to examine the relationship between the variables. Pair-wise correlation, Trenary, Parallel Plot were carried out for this data exploratio
- In order to prepare the dataset for Likert Scale analysis for the survey based questions, all the survey questions variables were stacked using JMP Stacked function to stack all the columns into rows under two columns, namely "Survey Qns" and "Scale".
- One new column was created to recode the Scale to Categorical type with the followings types.
Liker Scale - label each scale as follows: 1-Strongly Disagree 2-Disagree 3-Neutral 4-Agree 5-Strongly Agree
For those missing value, the type is recoded as "Don't Know"
- Lastly, the cleaned data file is imported to Tableau and Qlik Sense for further analysis through Visualisation.
Visualisation to Answer the Questions under investigation
Demographics Profiles of the University Faculty Staff
First, before we analyse on the survey variables that could affect the adoption behavior of Wikipedia among the University staff, let’s take a look on the demographics information of University faculty staff participated in this survey.
Dashboard #1 Demographics Info [[2]] (click here)
Visualisation Design
The above Tableau dashboard provides an interactive way to allow user to use Gender & WikiUser as Filtering options to select the info on University, PhD and Domain details.
Findings
In summary, there are a total of 913 University faculty staff participated in the survey. Some key demographics profile of the staff are:
- More male staff (57.5%) than female staff (42.5%)
- About 85% of the staff are Non-Wiki user
- About 88% of staff were from UOC University.
- Quite high percentage (40%) of the staff’s domain area are unknown (not indicated in the survey responses)
Staff Profile Dashboard
The following Tableau dashboard provides an interactive visualisation to further drill down to more details profile information in terms of Age Group by each Domain, Gender % for each domain, and also the academic position profile for each domain area.
Dashboard #2 Staff Profile Dashboard [[3]]
The Various Factors that Influence the Use of Wikipedia
Now we will analyse at a macro level all the various factors that could influence the adoption of Wikipedia among the University staff.
The following Tableau dashboard provides an interactive visualisation to examine the positive and negative factors that would affect the use of Wikipedia among the University staff in Higher Education .
Dashboard #3 Survey Analysis Dashboard [[4]] (Click here)
Visualisation design
The above Tableau dashboard consists of a Heat Map that visualize the % of survey response scale for each survey category. Note that the % calculation is computed as % of Total across each category, that means the total % for each category should add up to 100%. In this case, we are able to identify the positive and negative factors (variables) that influence the behavior intention to use Wikipedia.
Upon selecting any of the categories in Heat Map, it provides the interactivity to allow user to drill down on the divergent bar chart at the bottom to look at the Likert scales for each survey question.
Findings
- 1) Positive factors (in terms of high response % of Strongly Agree + Agree) are:
- Sharing Attitude (80.6%), Perceived Ease of Use (67%), Perceived Enjoyment (66.2%)
- 2) Poor (negative) factors (in terms of high response % of Disagree + Strongly Disagree) are:
- Use Behavior (51.5%) and Profile 2.0 (51.3%)
- 3) Factors with more than 30% of Neutral responses
- Perceived Usefulness, Quality, Social Image, Visibility, and Behavioral Intention
- It’s observed that non-Wiki users seems to have more Neutral response in most survey categories as compared to Wiki user.
- 4) For Behavior Intention, 29.2% indicated positive response (SA + A), 31.6% indicated negative responses (D + SD), and majority of 35.2% stayed neutral opinion
The Key Factors that Negatively Influence the Behavior Intention to adopt Wikipedia
The two survey questions for BI are:
- BI1: In the future I will recommend the use of Wikipedia to my colleagues and students
- BI2: In the future I will use Wikipedia in my teaching activity
Here, we use JMP to do the Pairwise Correlation for the multivariate analysis. In particular, we are keen to identify the factors (variables) which are highly correlated to Behavioral Intention.
From the above, the variables which are highly correlated to Behavioral Intention are
- Use Behavior, Experience, Visibility, Quality and Social Image
Next, now a Parallel Plot will be used to ascertain the above are the key factors that worth to further investigate in details.
The plot was marked with the color marker on the Behavior Intention as shown below.
From the Parallel Plot above, it's noticeably observed that the bright green markers are cluttered at lower range for Use Behavior, Experience and Visibility. We will therefore further examine into the following measures in next section to further investigate.
- Motivation to use wiki (Use Bahavior, Experience)
- Social Influence (Social Image, Visibility)
- Perceived Quality (Quality)
Investigation on key factors
Now, we will further investigate on the key measures which were identified in the above section.
- Motivation factors to use Wikipedia (Use Behavior, Experience)
- Social Influence (Social Image, Visibility)
- Perceived quality of information using wiki (Quality)
A Qlik Sense App has been created to provide an interactive visualisation to drill down into the relationship between various attributes (age, academic position, domain, current wiki users, survey questions) regards to the positive and negative response in each measure. The types of visualisation objects used in Qlik Sense app include Radar Chart, Dependency Wheel, Bar Charts, Sankey Diagram.
Qlik Sense App [[5]] (click here)
Visualisation design
There are three dashboards in the Qlik Sense App. The purpose of these dashboards are to uncover some of the following insights:
- Any identification of attributes (e.g. age, academic position, current wiki user etc) that could influence the staff behavior intention to use wiki
- Detect any skeptical attitudes among university faculty regards using Wikipedia in class
- Establish any relation to disciplinary factors (e.g. academic position or domain area) or any implicit conflict between the scientific academic culture and Wikipedia culture.
Findings
Over here, we will focus only on discussion based on findings in 3 areas, namely the motivation factors to use wiki, the social influence, and lastly the perceived quality of wiki information.
- .a) Motivation Factors to adopt Wiki (Use Behavior, Experience)
From the Survey Response Dashboard, first we filter only the 2 Survey Categories namely Use Behavior and Experience as shown below. All the chart visualizations are now associated to the filtered data based on the above selection.
Next, we would like to identify some attributes observed from Disagree and Strongly Disagree (D + SD) response group.
The above two visualisations provided some insights to the followings
Note: The % in bracket means the % of all staff indicated A+SA in survey questions regards to Motivation
- For the "Poor in Motivation" response (Disagree + Strongly Disagree)
- Survey questions with high number of (Disagree + Strongly Disagree) responses are:
- EXP4 (17.6%): I contribute to Wikipedia (editions, revisions, articles improvement...)
- USE2 (15.8%): I use Wikipedia as a platform to develop educational activities with students
- USE1 (14.0%): I use Wikipedia to develop my teaching materials
- For the "Good Motivation" was contributed by Experience, followed by Use Behavior
- Survey questions with high number of (Agree + Strongly Agree) responses are:
- EXP3 (20.4%): I consult Wikipedia for personal issues
- EXP2 (18.1%): I consult Wikipedia for other academic related issues
- USE5 (15.0%): I agree my students use Wikipedia in my courses
- Demographics
- The main group was from Adjunct.
- Mostly having years of experience of less than 20 yrs.
- b) Social Influence (Quality)
Using the same interactive techniques as described above, we will now examine the Influence of Social Influence to adopt Wiki.
Observations:-
- By selecting only those with average scale of Behavior Intention less than 2.0, it's observed that most of the response given in Social Image and Visibility cluttered around scale <2.50.
- The biggest contribution to low scale in Avg Scale in Behavior Intention are from Disagree (30.6%), Neutral (26.7%), and Strongly Disagree in Social Image and Visibility survey questions.
- c) Perceived quality of wiki information (Quality)
Lastly, the observations for perceived quality of Wiki Information are as follow:
- QU4 (26.6%): In my area of expertise, Wikipedia has a lower quality than other educational resources
- QU3 (21.9%): Articles in Wikipedia are comprehensive (25%)
- QU5(18.9%): I trust in the editing system of Wikipedia (22.6%)
Tools Used and Visualisation Links
Tools Used and Visualisation Links
Visualisation Toolskit:- 1) Tableau 2) JMP 3) Qlik Sense
The Visualisation links are as follow:- 1) Tableau
2) Qlik Sense
- Qlik Sense App [[9]]
3) JMP
File:Parallel Plot (BI).htm