Knowledge and Skill Sets for Big Data Profession: Assessing Student's Quality using Exploratory Factor Analysis

Recently, several higher education institutions in Malaysia announced discontinuing some courses to ensure employability post-graduation. Finding a job that fits their qualifications is a hurdle that graduates frequently face. The International Labor Organization states that when the education and t...

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Published in:IVIT 2022 - Proceedings of 1st International Visualization, Informatics and Technology Conference
Main Author: Yusoff S.; Md Noh N.H.; Isa N.; Nor-Al-Din S.M.
Format: Conference paper
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2022
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148578221&doi=10.1109%2fIVIT55443.2022.10033399&partnerID=40&md5=87da982523ed03bb208953843095eb2a
id 2-s2.0-85148578221
spelling 2-s2.0-85148578221
Yusoff S.; Md Noh N.H.; Isa N.; Nor-Al-Din S.M.
Knowledge and Skill Sets for Big Data Profession: Assessing Student's Quality using Exploratory Factor Analysis
2022
IVIT 2022 - Proceedings of 1st International Visualization, Informatics and Technology Conference


10.1109/IVIT55443.2022.10033399
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148578221&doi=10.1109%2fIVIT55443.2022.10033399&partnerID=40&md5=87da982523ed03bb208953843095eb2a
Recently, several higher education institutions in Malaysia announced discontinuing some courses to ensure employability post-graduation. Finding a job that fits their qualifications is a hurdle that graduates frequently face. The International Labor Organization states that when the education and training system does not deliver the skills the labour market needs, there is a mismatch between skills and jobs. This paper presents research on big data analytics knowledge and skills acquired by students throughout their studies. A sample of 185 UiTM students from various campuses participated. These students were among those who had formally taken big data courses during their studies. Data analysis was done using exploratory factor analysis (EFA) to identify the knowledge and skills obtained. Those are important to UiTM students' preparedness for the big data profession. From the exploratory factor analysis, 26 of the 40 items are included in the six constructs with factor loadings above 0.60: teamwork, student awareness and university readiness, programming language, student's effort, data storytelling and visualization, and data organization. These factors align with the finding made by [26], which identified the key competencies the employer needs for big data professions. In conclusion, higher education institutions need to focus on these skills in improving the existing program to meet better market demand and satisfy employer expectations since the score of factor loadings obtained are just satisfactory. © 2022 IEEE.
Institute of Electrical and Electronics Engineers Inc.

English
Conference paper

author Yusoff S.; Md Noh N.H.; Isa N.; Nor-Al-Din S.M.
spellingShingle Yusoff S.; Md Noh N.H.; Isa N.; Nor-Al-Din S.M.
Knowledge and Skill Sets for Big Data Profession: Assessing Student's Quality using Exploratory Factor Analysis
author_facet Yusoff S.; Md Noh N.H.; Isa N.; Nor-Al-Din S.M.
author_sort Yusoff S.; Md Noh N.H.; Isa N.; Nor-Al-Din S.M.
title Knowledge and Skill Sets for Big Data Profession: Assessing Student's Quality using Exploratory Factor Analysis
title_short Knowledge and Skill Sets for Big Data Profession: Assessing Student's Quality using Exploratory Factor Analysis
title_full Knowledge and Skill Sets for Big Data Profession: Assessing Student's Quality using Exploratory Factor Analysis
title_fullStr Knowledge and Skill Sets for Big Data Profession: Assessing Student's Quality using Exploratory Factor Analysis
title_full_unstemmed Knowledge and Skill Sets for Big Data Profession: Assessing Student's Quality using Exploratory Factor Analysis
title_sort Knowledge and Skill Sets for Big Data Profession: Assessing Student's Quality using Exploratory Factor Analysis
publishDate 2022
container_title IVIT 2022 - Proceedings of 1st International Visualization, Informatics and Technology Conference
container_volume
container_issue
doi_str_mv 10.1109/IVIT55443.2022.10033399
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148578221&doi=10.1109%2fIVIT55443.2022.10033399&partnerID=40&md5=87da982523ed03bb208953843095eb2a
description Recently, several higher education institutions in Malaysia announced discontinuing some courses to ensure employability post-graduation. Finding a job that fits their qualifications is a hurdle that graduates frequently face. The International Labor Organization states that when the education and training system does not deliver the skills the labour market needs, there is a mismatch between skills and jobs. This paper presents research on big data analytics knowledge and skills acquired by students throughout their studies. A sample of 185 UiTM students from various campuses participated. These students were among those who had formally taken big data courses during their studies. Data analysis was done using exploratory factor analysis (EFA) to identify the knowledge and skills obtained. Those are important to UiTM students' preparedness for the big data profession. From the exploratory factor analysis, 26 of the 40 items are included in the six constructs with factor loadings above 0.60: teamwork, student awareness and university readiness, programming language, student's effort, data storytelling and visualization, and data organization. These factors align with the finding made by [26], which identified the key competencies the employer needs for big data professions. In conclusion, higher education institutions need to focus on these skills in improving the existing program to meet better market demand and satisfy employer expectations since the score of factor loadings obtained are just satisfactory. © 2022 IEEE.
publisher Institute of Electrical and Electronics Engineers Inc.
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language English
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