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Insights for academic analytics.

Ya'Acob, Suraya and Abd. Talib, Muhammad Danial (2022) Insights for academic analytics. Open Internationaljournal Ofinformatics(OIJI), 10 (1). pp. 41-50. ISSN 2289-2370

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Official URL: https://oiji.utm.my/index.php/oiji/article/view/18...

Abstract

Education plays a vital role in any civilisation; improving education thus comes priority. With tons of interest shown in analytics, it has become natural for the education world to dive into academic analytics (AA), which two primary methods are educational data mining (EDM) and learning analytics (LA). EDM and LA are used to predict students in academic difficulty, allow faculty and advisers to customise their learning path, or provide guidance tailored to unique learning needs. EDM is a method for extracting useful information that could potentially affect an organisation. LA is a method of collecting, understanding data to optimise the learning experience. This project aims to identify the business requirement specification (BRS) for the Razak Faculty of Technology and Informatics (RFTI). The BRS insight will create a foundation for academic analytics implementation at RFTI. The methodology used in the project is qualitative, with the data collected from the semi- structured interview. This project's end product is the BRS insight that can be used to apply AA at RFTI.

Item Type:Article
Uncontrolled Keywords:Academic analytics, education data mining, learning analytics, education, business requirement specification
Subjects:L Education > LC Special aspects of education
Divisions:Advanced Informatics School
ID Code:104608
Deposited By: Muhamad Idham Sulong
Deposited On:21 Feb 2024 08:27
Last Modified:21 Feb 2024 08:27

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