Project Description

The project is developed from scratch as a team with anonymised live student data from the Academic year 2018-2019. The aim of this project is to design and develop web-based interactive data visualisation using Javascript, HTML, CSS and d3js. This is a lightweight web-based application that focuses on enabling the end-user to read the information from hugely available data more easily with help of interactive graphics.

Data Pre-Processing

Technical Implementation: The raw data was provided in a JSON file, which had lots of missing, duplicate and corrupt data as it was captured from the live environment. Power BI, We have used Power BI to understand and do the basic data processing. This data cleaning process was centralised with all members of the team. Python, we have implemented python code to convert the CSV files to JSON and vice versa, and also to analyse the data (as live data was huge). Exploratory Data Analysis, Understand and visualise the different aspects of the real-time data. Identify the research questions and how can the data be presented. Identify the appropriate visuals/graphs. Research Question, to investigate and identify the student performance depending on attendance and gender. Each member of the team developed visualisations to answer the same research question from different aspects with different interactive visuals of their interest.

Research Analysis

Visual 1: Organisation Overview by Departments’ Student Strength

Purpose: This visual is developed to show the organisational hierarchy and the respective student strength drill down from Organisational level to Module level and further by gender.

Functionality: This is an interactive sunburst chart showing the number of students present in each department and module. The tooltip highlights the number of students present in the focused department/module. Also, there is an option available for the user to choose between the size and the count of the department/module. On selecting this user desired option the visual changes appropriately by the student strength or by the department/module count.





Visual 2: Present and Absent Statistics By Gender/By Week

Purpose: This is an interactive visual to understand the present and absent trends and stats of female and male students by week.

Functionality: The bar chart is a simple yet effective way to present the attendance trends in both female and male students for each week. From the visual, it can be observed that students attending the session gradually decrease reaching the end of the semester which implies that absentees increase while reaching the end of the course. 





Visual 3: Statistics of Attendance Category  By Percentage / By Week

Purpose:  The stacked bar chart graphically shows the students status for each week for different attendance codes ( lab sessions, present, absent, present in a different group, project etc). 

Functionality: End-user is provided with a check box that shows the percentage for both female and male students in two different adjacent plots. These charts could be merged with an option to select students by gender, but this may not be helpful to visually understand and compare the attendance trends in male and female groups.





Skip to content
%d bloggers like this: