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Visual Analytics Project

PROPOSAL

POSTER

APPLICATION

RESEARCH PAPER

Problem and Motivation

Problem:
The Graduate Employment Survey (GES) is conducted on a yearly basis to provide insights about the job prospects about a particular course. The Ministry of Education conduct these surveys yearly for Universities in Singapore. However, the results of these surveys are not interactive and do not provide any trends and insights with respect to the Labour Market demands.

Motivation:
As graduates to be who going to enter the job market soon, we felt that it would be interesting to look at the historical salary data to know the gauge of our expected salary, the demand in the job market and as well our position in term of starting salary among our fellow school peers. In addition, we also felt that it would be interesting to find out whether does the starting salary reflect the market demand. Furthermore, we hope that our visualizations would help students from Polytechnic and Junior Colleges decide their courses choices with regards to its career prospects as it would be interesting to find out what are the top paid salary programmes through the year, and the changes to the market demand.

Objectives

In this project, we are interested to create a visualisation application that helps users perform and answer the following:

1. Visualise Ranking of Highest Starting Salary throughout the years
2. To find insight and relationship difference between Starting Salary and Labour Market
3. To find out the trend of the Starting Salary and the employment rate over the years with regards to the courses
4. To find out the popularity of the courses by intake, and what new courses are been introduced or omitted over the years

Dataset Description

DataSet	Description
Ministry of Education (MoE) Graduate Employment Survey - NTU, NUS, SIT, SMU & SUTD Source: https://data.gov.sg/dataset/graduate-employment-survey-ntu-nus-sit-smu-sutd	Graduate Employment Survey of local universities in Singapore for the year 2013 - 2015
SMU Student Statistics Source: https://www.smu.edu.sg/about/university-information/student-statistics/student-statistics	Provides intake data of programmes from Year 2007 - 2016
NUS Student & Graduate Statistics Source: http://www.nus.edu.sg/registrar/statistics.html	Provides intake data of programmes from Year 1994 - 2016
NTU Student Statistics Source: http://www.ntu.edu.sg/AboutNTU/CorporateInfo/FactsFigures/Pages/Undergraduate-Population-by-Gender-AY2016-17.aspx	Provides intake data of programmes from Year 2016 Need to manually extract data from website over the period from 2010 - 2016
NYP Student Statistics Source: https://data.gov.sg/dataset/nanyang-polytechnic-full-time-student-enrolment-annual	Provides intake data of programmes from Year 2016
Temasek Poly Student Statistics Source: https://data.gov.sg/dataset/temasek-polytechnic-full-time-enrolment-figures-breakdown-annual	Provides intake data of programmes from April 25, 2016 to April 23, 2017

Background Research and Survey of Related Work

Visualization	Explanation
Source: http://ideasillustrated.com/blog/2011/11/28/earnings-and-unemployment-by-college-major/	A divergent bar chart provides useful insights with regards to a specific course and is useful in telling the distribution of salary. In addition, it offers a good comparison overview between majors.
Source: http://ideasillustrated.com/blog/2011/11/28/earnings-and-unemployment-by-college-major/	A scatter plot is extremely useful into displaying the employment rate and starting salary. It provides a good visualization to show the trends over the years and more information to be displayed with the size of the circle.
Source: http://pay.sgcharts.com/index.html	This time series bar chart is useful in showing the starting salary of various majors as well the a line graph as the employment rate by major. This graph essentially provides a good summary and comparison of the various degrees and majors

Key Technical Challenges

Key Technical Challenges	Mitigation Plan
D3.js Programming & implementation	Attend Workshop in Week8 Self-learn through online platform for more in-depth content
Data Collections and Clean up	Decide as a team on what data to use and what to do with missing data(if any)
Visualization Tool Usage	Peer Learning Self-learning through online platform

Tools & Libraries

• Tableau
• Microsoft Excel
• Photoshop
• D3.js Library
• HTML, CSS & JavaScript
• Github

Project Timeline

References

• Data Gov : https://data.gov.sg/search?groups=education
• Salary SG : http://www.salary.sg/
• Visualisation of SG Graduate Salary : http://pay.sgcharts.com/
• Digital Senior : http://digitalsenior.sg/graduate-employment-survey-ges-nus-ntu-smu/

Comments

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