Group06 proposal

Growth Signal

Proposal

Poster

Application

Research Paper

Problem & Motivation

Problem

In Singapore, education is one of the sectors that is heavily invested by the state besides defence and health. As years progress, more data are accumulated and made available to the public by various government institutions such as Singapore Department of Statistics and data.gov. Despite the abundance of data, it is often not easy for someone fresh out of post-secondary education to plan for further studies in an efficient and thorough manner due to decentralisation and lack of visualisation (data are in raw/unstructured/tabular form).

Motivation

Enrolling in higher education such as polytechnics, especially universities is becoming a commonplace in Singapore. Not only does it prepare the next generation for the future (individual level), the country as a whole can significantly benefit as a result of a highly-educated population. This interactive visualisation will serve as a platform for post-secondary individuals to analyse the changing landscape and trends of higher education where they can uncover interesting insights and make well-informed decisions to ensure a sustainable future.

Objectives

Target Group: Post-Secondary individuals

Many of the available data such as Graduate Employment Survey, Enrolment of students in institutions of higher education and government expenditure are located either on various institutions’ website, government generated reports or on data sites. The general reader is unable to get the full information on higher learning institutions in Singapore.

As such, our Dashboard will fulfil the following objectives:

1. Visualise Singapore’s ranking in various metrics of GCI’s 5th pillar (higher Education and Training) over time
2. Identify enrolment demographic across different institutions and courses and how they changed over time.
3. Comparison of Governments’ efforts in developing Polytechnics and Universities with different sectors and other levels of education
4. Identify the courses which churns out the most successful graduates by employment rates and starting income.

Dataset

Dataset/Source	Variables & Description	Rationale of Usage
Dataset: GCI_Dataset_2007-2017 Source: World Economic Forum	Users New Users Sessions Number of Sessions Per User Page Views	abc

Background Survey

Research	Learning points	Improvement
Source: https://www.tapclicks.com/resources/blog/6-steps-marketing-dashboard/	Example of sales funnel (top right) on the to show conversion of Users to Leads and Trial. Can be broken down into timeline as well. The sales funnel would give an accurate idea of how many percentage of users are really interested in the advertisement or those that actually manage to secure leads. However, diagrams in 3D can be misleading due to overlaps and is not very neat. How many leads in the last 90 days or this month can be combined.	Can add Interaction for across a time period. Funnel can be broken down into more categories such as number of potential leads, marketing leads, sales leads, deals etc. Can give top 5 sources of traffic
Source:https://www.klipfolio.com/resources/dashboard-examples/marketing/digital-marketing-dashboard	Another dashboard example provided by kilpfolio. Useful example to show metrics such as quality of leads and conversion metrics, leads by region and top few social media channels. It can be animated or add a scale to show changes across timing However, leads by region is too small. Google web analytics Web traffic targets is not labeled and just shows the bar. Can change to label with highlight of red and green (based on whether the progress is negative or positive)	Perhaps can show the top 5 areas instead and table can be replaced by a bar graph. Key conversion metrics and quality of leads can be replaced with line graph to show changes over time.

References

• 6 Steps to Creating a Better Marketing Dashboard
• Klipfolio - Digital Marketing Dashboard
• 100 Tasks
• Web Analytics 2.0 by Avinash Kaushik

Technical Challenges

Challenge	Description	Mitigation Plan
Unfamiliarity with Tools	Most of the team members are not too familiar with R and R Shiny.	Make use of external sources for information and troubleshooting Utilise DataCamp to learn, practice and brush up skills on R and R Shiny
Lack of policy knowledge	There may be gaps in knowledge of policy jargons.	Research online for the latest educational policy details Cross-reference and state assumptions if there are conflicting information
Data Quality & Integrity	Difficult to consolidate data as they are from different government agencies. Some of the data are in an unstructured format.	Conduct proper EDA and data cleaning methods to minimise quality problems Apply filters and follow best practices from the industry to reduce data abnormalities

Storyboard

Dashboards	Description
Dashboard 1: Higher Education Ranking	The GCI assesses the ability of countries to provide high levels of prosperity of citizens. There are 12 pillars of competitiveness. Here, we analyse the 5th pillar, namely Higher Education and Training, and its subcategories. The chart displays the ranking among the top 10 countries for the selected category. Singapore is denoted by the red line. If Singapore is not among the top 10, each country will be represented by a different colour. Select an option from the filter to view the ranking by category (5th pillar - the overall, or its subcategories).
Dashboard 2: Enrollment	The line charts show the number of enrollment for both polytechnic and university institutes over the years. Breakdown by course types are displayed on the second graph. Dropdown bar and year range slider are available on both graph and this allows for further segmentation.
Dashboard 3: Government Expenditure	The 100% stacked bar chart shows the proportion of government expenditure by sector. The education sector is shown at the top of each bar for ease of comparison over the years. The line chart shows the breakdown of education expenditure by level across year.
Dashboard 4: Graduate's Prospects	The GES is an annual survey conducted by the Ministry of Education (MoE) and the 6 universities on the employment conditions after graduation. The bar chart shows the gross monthly mean salary of different degrees offered under a university and school/faculty in 2018. The line chart shows the 25th, 50th (median) and 75th percentile of the salary of one of the degrees across year. Click on any bar of a degree to see its salary percentiles. Use the filters to compare the gross monthly mean salary of the degrees offered by other universities and their schools/faculties.

Project Timeline & Milestones

Detailed Project Timeline from Asana (team's task tracker)

Comments

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