Graph-based analytics and visualization

• Main Author: Tiong, Melissa Chia Hui
• Other Authors: Andy Khong Wai Hoong
• Format: Final Year Project
• Language: English
• Published: 2018
• Subjects: DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
• Online Access: http://hdl.handle.net/10356/74626
• Institution: Nanyang Technological University

With the increase in number of e-learning platforms, many educational and training establishments are adopting flipped learning, where instead of using summative assessments, formative assessments are employed. By moving towards formative assessments, students are now assessed by their learning process. This has led to a rise of the need to modify teaching and learning activities during the learning process. Therefore it is critical for online education platforms to become smart learning platforms so as to be able to analyze the process of learning. Data visualization, also known as information visualization can be used to help analyze the learning process and can be vital to make these online platforms smart. By transforming the large amount of e-learning platform data into visualizations, it would aid course administrators in improving the effectiveness and efficiency of their course through modifications based on the feedback received. In this report, we study the fundamentals of data visualization, the tools used and how a smart learning platform, eTube (a joint project with Delta Electronics) is created so as to analyze e-learning courses. Content analysis (teachers) and learning analysis (students) will be the two main parts of this platform, where visuals will be displayed for convenient interpretation. After the development of eTube, a survey will be conducted to evaluate its effectiveness and the results were used to identify areas of improvement. Lastly, future recommendations were discussed to further improve the development of eTube.