About this paper

Appears in:
Pages: 7691-7700
Publication year: 2017
ISBN: 978-84-617-8491-2
ISSN: 2340-1079
doi: 10.21125/inted.2017.1783

Conference name: 11th International Technology, Education and Development Conference
Dates: 6-8 March, 2017
Location: Valencia, Spain

A COMPREHENSIVE DATA MINING FRAMEWORK USED TO EXTRACT ACADEMIC ADVISING KNOWLEDGE FROM SOCIAL MEDIA DATA

H. Brdesee1, A. Madbouly2, A.Y. Noaman3, A.H. Ragab3

1Jeddah community College, King Abdulaziz University, Jeddah (SAUDI ARABIA)
2Vice Presidency for development, King Abdulaziz University, Jeddah (SAUDI ARABIA)
3Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah (SAUDI ARABIA)
In higher education institutions, students' academic advising is an essential activity for improving the students’ academic performance. However, academic advising tasks demand a considerable amount of effort and time by the advisors, especially in case of universities with a large number of enrolled students. This practice also entails a variety of means to deliver academic advising services. Passionate use of social media by students urges the universities to make use of social media network for delivering the massive educational and academic advising services. Hence, there is a vast amount of unstructured data available that can generate themes of students' academic needs. This paper proposes a comprehensive framework of social media academic advising service that uses this amount of unstructured data and converts it into a structured data. Data mining techniques could be used to extract knowledge, features, and patterns that help to enhance the students' learning. This approach is expected to facilitate in developing an e-academic advising system, which will be beneficial especially for universities with a large number of students. Discovered knowledge will support the academic advising systems to intervene if needed and take actions to enhance the students’ academic performance.
@InProceedings{BRDESEE2017ACO,
author = {Brdesee, H. and Madbouly, A. and Noaman, A.Y. and Ragab, A.H.},
title = {A COMPREHENSIVE DATA MINING FRAMEWORK USED TO EXTRACT ACADEMIC ADVISING KNOWLEDGE FROM SOCIAL MEDIA DATA},
series = {11th International Technology, Education and Development Conference},
booktitle = {INTED2017 Proceedings},
isbn = {978-84-617-8491-2},
issn = {2340-1079},
doi = {10.21125/inted.2017.1783},
url = {http://dx.doi.org/10.21125/inted.2017.1783},
publisher = {IATED},
location = {Valencia, Spain},
month = {6-8 March, 2017},
year = {2017},
pages = {7691-7700}}
TY - CONF
AU - H. Brdesee AU - A. Madbouly AU - A.Y. Noaman AU - A.H. Ragab
TI - A COMPREHENSIVE DATA MINING FRAMEWORK USED TO EXTRACT ACADEMIC ADVISING KNOWLEDGE FROM SOCIAL MEDIA DATA
SN - 978-84-617-8491-2/2340-1079
DO - 10.21125/inted.2017.1783
PY - 2017
Y1 - 6-8 March, 2017
CI - Valencia, Spain
JO - 11th International Technology, Education and Development Conference
JA - INTED2017 Proceedings
SP - 7691
EP - 7700
ER -
H. Brdesee, A. Madbouly, A.Y. Noaman, A.H. Ragab (2017) A COMPREHENSIVE DATA MINING FRAMEWORK USED TO EXTRACT ACADEMIC ADVISING KNOWLEDGE FROM SOCIAL MEDIA DATA, INTED2017 Proceedings, pp. 7691-7700.
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