Predicting Links from Education Network of Employees

The advances in technology and data science affect many fields positively. One of these fields is education. Learning analytics have the potential to develop new ways of achieving excellence in teaching and learning. The companies try to use learning analytics techniques for their employees' ed...

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Vydané v:Lecture notes in engineering and computer science Ročník 2245; s. 70
Hlavní autori: Kocaman, Ceyda, Orman, Gunce Keziban
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Hong Kong International Association of Engineers 05.07.2023
Predmet:
CAI
Computer assisted instruction
Data science
Datasets
Education
Machine learning
Network analysis
Recommender systems
ISSN:2078-0958, 2078-0966
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Popis
Shrnutí:The advances in technology and data science affect many fields positively. One of these fields is education. Learning analytics have the potential to develop new ways of achieving excellence in teaching and learning. The companies try to use learning analytics techniques for their employees' education and aim to improve employee performance. The education data sets of Softtech employees are used in this study. Softtech is a software company in Turkey, and those data sets include different types of technical, non-technical, online, and offline education. All data sets are combined, and an employee network is created by connecting employees via education. In this study, complex network analysis, link prediction, and machine learning techniques are applied with the aim of creating an education recommendation system.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2078-0958
2078-0966