Applying Social Network Analysis on Courses relationship in Informatics Mathematics Curriculum

Autor:	Asekha KhantaVchai, Kanyarat Bussaban
Rok vydání:	2019
Předmět:	symbols.namesake Academic year Betweenness centrality Informatics ComputingMilieux_COMPUTERSANDEDUCATION Mathematics education symbols Sample (statistics) Centrality Curriculum Social network analysis Pearson product-moment correlation coefficient
Zdroj:	Proceedings of the 2019 4th International Conference on Information and Education Innovations - ICIEI 2019.
DOI:	10.1145/3345094.3345115
Popis:	This study investigates the relationship the courses achievement of undergraduate students in Informatics Mathematics curriculum. Social Network Analysis and Pearson product Moment Correlation Coefficient are used to determine which courses are significant important and influence predictors. Data collected is from the sample of 91 online report submitted by science graduated students who have graduated during the academic year 2010-2017. The results of the study indicate that Linear Algebra and Discrete Mathematics are the highest score of weighted degree centrality as Mathematics information technology is the highest score of betweenness centrality and English for informatics Mathematics influence over the whole courses.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c31c84751924ec4fdb563e1e8e3723ba https://doi.org/10.1145/3345094.3345115 Zobrazit plný text záznamu