Aspect-Based Sentiment Analysis of student Sentiment Towards E learning Using VADER Analyzer

Bisan Salem; Hadi Affendy Dahlan

Author(s)

Bisan Salem Faculty of Information Science & Technology,UniversitiKebangsaan Malaysia (UKM), Selangor,Malaysia

Hadi Affendy Dahlan UniversitiKebangsaan Malaysia (UKM), Selangor,Malaysia

Abstract

With the forced shutdown of educational institutions due to the COVID-19 pandemic, eLearning has become a vital tool for continuing education and training for students of all ages and levels. Sentiment analysis (SA) can be a useful tool for evaluating student satisfaction and understanding their perceptions of their learning experiences. However, it seems that there has been limited research on the implementation of this technique in the Malaysian educational sector. Thus, the primary objective of this research is to discover how graduate students at a Malaysian university perceive the eLearning system by the university. Aspect-based sentiment analysis was performed using a rule-based model, VADER, and several Python modules, including the NLTK library, Seaborn, Matplotlib, SpaCy, and TextBlob, were applied on the collected data. Findings showed that the majority of sentiments towards eLearning is positive (84.6%), while 7.7% were negative, and 7.7% as neutral. Moreover, the most frequent aspects used are “system,”“information,”“assignment,”“design,” and “course”. The findings are consistent with earlier research highlighting the importance of excellent communication and feedback for student engagement and satisfaction with the eLearning system. The study also advises that technical concerns and communication obstacles should be addressed in order to improve students' eLearning experiences. The findings imply that universities may improve the eLearning experience by focusing on system clarity, communication, and feedback systems. This can inform policy decisions and improve student learning outcomes in online contexts.

Publication Details

Page(s) 297-317

DOI DOI not available

Published Journal: International Journal of Communication Networks and Information Security, Volume: 16, Issue: 1, Year: 2024

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Keywords

sentiment analysis, Multimedia, Malaysian University, Aspects, eLearning system

References

Adams D.,Sumintono B.,Mohamed A.,Noor N.S.M. .2018 .E-learning readiness among students of diverse backgrounds in a leading Malaysian higher education institution. Malaysian Journal of Learning and Instruction, 15(2) : 227-256.

Allam S. N. S.,Hassan M. S.,Mohideen R. S.,Ramlan A. F.,Kamal R. M.,Abbas H.,Alfayly Z.,A. Z.,Cocea N.,Fallahkhair M.,S. M.,S. M. .2021 .How COVID-19 is reshaping the role and modes of higher education whilst moving towards a knowledge society: the case of the UAE. The Journal of Open, 40(5) : 1-16.

Baragash R. S.,Aldowah H.,Umar I. N.,Laaziri K.,Khoulji M.,Kerkeb S.,El Yamami M. L.,A. M. L. .2018 .Impact of system quality, information quality and service quality on the efficiency of information system. In Proceedings of the 3rd International Conference on Smart City Applications, 21 : 1-6.

Bonta V.,Nandhini K.,Janardhan N. .2019 .A comprehensive study on lexicon based approaches for sentiment analysis. Asian Journal of Computer Science and Technology, 8(S2) : 1-6.

Madan G.,Jaisingh P.,Bhaskar P.,P. P. .2019 .Effectiveness of e-learning portal from students' perspective: A structural equation model (SEM) approach. Interactive Technology and Smart Education, 16(2) : 94-116.

Clark R. C.,Mayer R. E.,Thalheimer W. .2003 .E-learning and the science of instruction: proven guidelines for consumers and designers of multimedia learning. Performance Improvement, 42(5) : 41-43.

McLean W. H.,E. R. W. H. .2003 .The DeLone and McLean model of information systems success: a ten-year update. Journal of management information systems, 19(4) : 9-30.

Kurt Efiloğlu .2019 .Examining an e-learning system through the lens of the information systems success model: Empirical evidence from Italy. Education and Information Technologies, 24(2) : 1173-1184.

.2021 .Factors affecting the quality of e-learning during the COVID-19 pandemic from the perspective of higher education students. COVID-19 and Education: Learning and Teaching in a Pandemic-Constrained Environment. , 189 : .

Forid M.,Hafez M.,Khan W. .2022 .Student satisfaction and retention: impact of service quality and digital transformation. Marketing and Management of Innovations, 13(4) : 152-163.

H. ,Joyner D.,Gobin-Rahimbux B.,Sahib B.,N. B. .2023 .A deep-learning framework for analysing students' review in higher education. Computational Intelligence and Neuroscience, 246(1) : 1-13.

Banihashem O.,Biemans S.,Smits H.,Vervoort M.,Verbaan M.,C. M. .2023 .Design, implementation, and evaluation of an online supported peer feedback module to enhance students' argumentative essay quality. Education and Information Technologies, 28(10) : 12757-12784.

Lee B.,L. B. .2008 .Opinion mining and sentiment analysis. Foundations and Trends® in information retrieval, 2(1-2) : 1-135.

Pang M.,Suh W.,Hong J.,Kim J.,Lee H. .2010 .A new web site quality assessment model for the Web 2.0 Era. IGI Global., (3) : 387-410.

Pradana A. W.,Hayaty M.,Uhrig T.,P. T.,Qaqish E.,Aranki A.,Etaiwi W.,Zukarnain N. A.,Zain Z. A.,Yusof N. A. M.,R. N. A. M.,Lobiyal D. K. .2018 .Automatic construction of generic stop words list for hindi text. Malaysian Journal of Learning and Instruction, 18(2) : .

Respati M. H.,Hidayatullah H.,S. H. .2021 .Conceptual model of user satisfaction as mediator of e-learning services and system quality on students' individual performance. International Journal of Research in Engineering, Science and Management, 4(1) : 60-65.

Rosell C. D. .2022 .Advantages of eLearning for Language Teachers. Retrieved April, 10 : .