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A dashboard for monitoring academic staff teachings & citations

Ng, Brian Yao Sheng (2020) A dashboard for monitoring academic staff teachings & citations. Final Year Project, UTAR.

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    Abstract

    As data visualization is getting more attention, a lot of organization started to invest in it because data visualization is an essential skill as most of the decisions are reliant upon data. With the recent cases in COVID-19, it is made clear that data visualization played a crucial role in fighting against the disease, ensuring the number of cases is below the curve. Similarly, in order to manage a university effectively, the use of dashboard to monitor the staff teaching performance and citation is inevitable, this would eventually affect the ranking of a university. In this report, the university staff data will be collected, analyzed and come up with a dashboard that can view all of the university staff performance in a glance. The first project objective of this report is to collect data, analyze the total publications, citations and teaching performance, then develop a dashboard that monitors on the number of publications, citations and teaching performance and finally assist the university in making decisions in a quick and timely manner to improve the university ranking. The implementation begins from ground zero which starts from data collection through Scopus API and store it as JSON file to be used later for data visualization, along with the sample teaching survey data provided by the supervisor of this project for the data visualization of teaching survey section. The final product of university staff performance dashboard will be developed and ready to use. The output of the dashboard could be filtered based on the faculty of the university, department and the category of the data, some sentiment analysis of the staff performance based on the comments and reviews given by the students will be displayed. For the future work, the dashboard could be made real time in terms of data collection, collecting data from other academic databases, expanding dashboard service to other higher institutions.

    Item Type: Final Year Project / Dissertation / Thesis (Final Year Project)
    Subjects: Q Science > Q Science (General)
    Divisions: Faculty of Information and Communication Technology > Bachelor of Computer Science (Hons)
    Depositing User: ML Main Library
    Date Deposited: 07 Jan 2021 16:17
    Last Modified: 07 Jan 2021 16:17
    URI: http://eprints.utar.edu.my/id/eprint/3943

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