International Journal of Education and Management Engineering (IJEME)
IJEME Vol. 13, No. 3, 8 Jun. 2023
Cover page and Table of Contents: PDF (size: 342KB)
Exploring the Factors and Dimensions of Information Quality for E-learning Systems: A case of Tanzanian Higher Learning Institution
Full Text (PDF, 342KB), PP.33-38
Views: 0 Downloads: 0
Author(s)
Index Terms
E-learning system E-learning models, Information Quality, Tanzania, Factors, Dimensions, Systematic Review
Abstract
The role played by the E-learning system is crucial, especially in the urgent need for working away from the universities and colleges such as on holidays, weekends, and during pandemic situations like COVID-19. Researchers have constantly been producing more sophisticated alternatives for effective usage of E-learning systems and among them include models which explain how users accept, use, and evaluate such systems as they use them on daily basis. Due to the low ICT readiness in developing nations like Tanzania, there is a lack of grounds for the inclusion of various factors and dimensions to the conceptual models which in turn results in testing incomplete, intuitive, and ad hoc sets or irrelevant dimensions. This study closes this gap by conducting a systematic documentary review of studies from 2007 to 2020 on E-learning systems to identify the key factors and their associated dimensions. The findings provide foundations that further research on e-learning acceptance in the contexts of developing countries including Tanzania can adopt on formulating hypotheses and generating information on their research contexts.
Cite This Paper
Renatus Mushi, Deogratius Mathew Lashayo, "Exploring the Factors and Dimensions of Information Quality for E-learning Systems: A case of Tanzanian Higher Learning Institution", International Journal of Education and Management Engineering (IJEME), Vol.13, No.3, pp. 33-38, 2023. DOI:10.5815/ijeme.2023.03.04
Reference
[1]Lashayo, D. M., & Md Johar, M. G. (2017). A Review of E-Learning Systems’ Adoption in Tanzania Universities.
[2]Adkins, S. S. (2013). The Africa market for self-paced eLearning products and services: 2011-2016 forecast and analysis. Monroe, WA: Ambient Insight.
[3]DeLone, W. H., & McLean, E. R. (2016). Information systems success measurement. Foundations and Trends® in Information Systems, 2(1), 1-116.
[4]Alkhattabi, M., Neagu, D., & Cullen, A. (2010). Information quality framework for e-learning systems. Knowledge Management & E-Learning: An International Journal, 2(4), 340-362.
[5]Wang R.Y., and Strong D.M. (1996). Beyond accuracy what data quality means to data consumers, Journal of Management Information Systems Vol. 12, No 4, (1996).
[6]Alexander, J. E., & Tate, M. A. (1999). Web wisdom: how to evaluate andcreate information quality on the web (4th ed.). New Jersey Lawrence ErlbaumAssociates
[7]Besiki, S., Gasser, L., Twidale, M. B., & Smith, L. C. (2007). A framework forinformation quality assessment. Journal of the American Society for InformationScience and Technology, 58(12), 1720-1733.
[8]Chen, Y., Zhu, Q., & Wang, N. (1998). Query processing with quality control inthe World Wide Web. World Wide Web Journal, 1(4), 241–255.
[9]Howard, G. R., Lubbe, S., & Klopper, R. (2011). The impact of information quality on information research.
[10]Wang, R. Y. (1998). A product perspective on total data quality management. Communications of the ACM, 41(2), 58-65.
[11]Ndou, V. (dardha. (2004). E–government for developing countries: Opportunities and challenges. Ejisdc, 1–24.
[12]Farid, S., Ahmad, R., Alam, M., Akbar, A., & Chang, V. (2018). A sustainable quality assessment model for the information delivery in E-learning systems. Information Discovery and Delivery.
[13]Abdellatief, M., Sultan, A. B. M., Jabar, M. A., & Abdullah, R. (2011). A technique for quality evaluation of e-learning from developers perspective. American Journal of Economics and Business Administration, 3(1), 157-164.
[14]Olsina L. (2001) , Web-site Quantitative Evaluation and Comparison: a Case Study on Museums, Workshop on Software Engineering over the Internet, Web Engineering pp 266–278
[15]Hassan M. Selim (2007). Critical success factors for e-learning acceptance: Confirmatory factor models. Computers & Education Volume 49, Issue 2, September 2007, Pages 396-413
[16]Shankar, S., Watts, S (2003). A Relevant, Believable Approach For Data Quality Assessment. Proceedings of the Eighth International Conference on Information Quality (ICIQ-03)
[17]Alkhattabi, M., Neagu, D., & Cullen, A. (2010). Information quality framework for e-learning systems. Knowledge Management & E-Learning: An International Journal, 2(4), 340-362.
[18]Wang, R. Y. (1998). A product perspective on total data quality management. Communications of the ACM, 41(2), 58-65.
[19]Howard, G. R., Lubbe, S., & Klopper, R. (2011). The impact of information quality on information research.
[20]Wang, Y.S., Wang, H.Y. and Shee, D.Y. (2007) Measuring e-Learning Systems Success in an Organizational Context Scale Development and Validation. Computers in Human Behavior 23(4):1792-1808
[21]Lashayo, D. M. (2020). Measuring E-Learning System Adoption in Universities in Tanzania: An Integration of Trust, Environmental Factors, and University Readiness Into an IS Success Model. International Journal of ICT Research in Africa and the Middle East (IJICTRAME), 9(2), 1-18.
[22]Mtebe. J, Raphael, C (2018). Key factors in learners’ satisfaction with the e-learning system at the University of Dar es Salaam, Tanzania, Australasian Journal of Educational Technology (AJET), Vol. 34 No. 4 (2018)
[23]Lwoga, E. (2014). Critical success factors for adoption of web-based learning management systems in Tanzania. International Journal of Education and Development using ICT, 10(1)
[24]Dudek, M (2000). Architecture of Schools: The New Learning Environments, 1st Edition. London, Routledge
[25]Leung, H. K. N. (2001). Quality metrics for intranet applications. Information &Management, 38(3), 137 – 152
[26]Klein, B. D. (2002). When do users detect information quality problems on theWorld Wide Web? American Conference in Information Systems.
[27]Liu, X. W., & Han, S. L. (2005). Ranking fuzzy numbers with preference weighting function exp
[28]Kandari, J., Jones, E. C., Nah, F. F. H., & Bishu, R. R. (2011). Information quality on the world wide web: development of a framework. International Journal of Information Quality, 2(4), 324-343.
[29]Jarke, M., & Vassiliou, Y. (1997). Data Warehouse Quality: A Review of theDWQ Project. 2nd Intl. Conf. on Information Quality Cambridge, Mass
[30]Tao, D., LeRouge, C., Smith, K. J., & De Leo, G. (2017). Defining information quality into health websites: a conceptual framework of health website information quality for educated young adults. JMIR human factors, 4(4), 6455.
[31]Riesener, M., Dölle, C., Schuh, G., & Tönnes, C. (2019). Framework for defining information quality based on data attributes within the digital shadow using LDA. Procedia CIRP, 83, 304-310.