Predicting students’ intention to continue business courses on online platforms during the Covid-19: An extended expectation confirmation theory
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The document presents a study on predicting students' intention to continue business courses on e-learning platforms during the COVID-19 pandemic, utilizing the expectation confirmation model (ECM) and structural equation modeling techniques. The analysis involving 285 respondents indicated that student satisfaction and psychological safety significantly influenced their continuance intention on online learning platforms. The research underscores the importance of task enjoyment and psychological safety, recommending improvements in e-learning systems to enhance student engagement and satisfaction.
![The International Journal of Management Education 20 (2022) 100706
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Predicting students’ intention to continue business courses on online platforms during the Covid-19: An extended expectation confirmation theory
- 1. See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/363792408 Predicting students’ intention to continue business courses on online platforms during the Covid-19: An extended expectation confirmation theory Article in The International Journal of Management Education · September 2022 DOI: 10.1016/j.ijme.2022.100706 CITATIONS 0 READS 69 5 authors, including: Some of the authors of this publication are also working on these related projects: Understanding Attitude towards Green IT among Professionals in IT Service SMEs in Bangladesh View project 4G service quality in Dhaka City View project Samsul Alam Begum Rokeya University, Rangpur 27 PUBLICATIONS 28 CITATIONS SEE PROFILE Imran Mahmud Daffodil International University 78 PUBLICATIONS 657 CITATIONS SEE PROFILE Saiful Hoque Daffodil International University 1 PUBLICATION 0 CITATIONS SEE PROFILE Rana S M Sohel Independent University, Bangladesh 26 PUBLICATIONS 123 CITATIONS SEE PROFILE All content following this page was uploaded by Samsul Alam on 15 October 2022. The user has requested enhancement of the downloaded file.
- 2. The International Journal of Management Education 20 (2022) 100706 Available online 22 September 2022 1472-8117/© 2022 Elsevier Ltd. All rights reserved. Predicting students’ intention to continue business courses on online platforms during the Covid-19: An extended expectation confirmation theory Samsul Alam a , Imran Mahmud b,c,* , S.M. Saiful Hoque b , Rozina Akter b , S.M. Sohel Rana d a Begum Rokeya University, Rangpur, Bangladesh b Daffodil International University, Dhaka, Bangladesh c Universiti Sains Malaysia, Malaysia d Independent University Bangladesh, Dhaka, Bangladesh A B S T R A C T The objective of this study was to analyze the intention of a University’s business department students to continue their studies on e-learning platforms during the ongoing COVID-19 pandemic. To this end, a questionnaire was developed to collect primary data from students in business fields. The study took into account more than 285 respondents from two different universities and relied on the expectation confirmation model (ECM) theory and the structural equation model. The partial least squares (SEM-PLS) method was used to analyze the data. The results of the study showed that task skills (TS) and task challenges (TC) were significant for the enjoyment (EN) of the students which in turn had a positive effect on the satisfaction levels. Confirmation (CON) had an impact on the post adoption perceived usefulness (PAPU), which was deemed positive for student satisfaction (SAT). The SAT and psychological safety (PS) of online learning platforms were found to positively influence the continuance intention (CI) on e-learning platforms. Finally, both SAT and PS of online learning platforms were observed to positively influence CI on e-learning platforms. Further research in this area could be useful in making decisions about promoting educational programs based on e-learning. The researchers recommend that academicians and policymakers must ensure appropriate arrangements for teaching on e-learning platforms. 1. Introduction Blended learning systems have gained a lot of attention from education providers, as many universities have already integrated such programs with face-to-face (F-T-F) learning systems. Recent studies have shown that introducing technology in higher education is the key to enhancing students’ personal development during and after graduation by helping them actively learn to achieve their long-term goals (Zhu et al., 2020). Past EDUCAUSE reports by Becker et al. (2017, 2018) and Alexander et al. (2019) observed that adoption of technology in higher education was influenced by blended learning design acting as one of the short-term forces (Zhu et al., 2020). Trends in learning have shifted from “know-how” and “know-what” to “know-where”, as mentioned by Siemens (2005). Formal learning in a physical environment is therefore not the only way forward, and Massive Open Online Courses (MOOCs) first introduced by University of Manitoba in 2008 are a result of this trend. This new system initially received little attention but gained popularity when elite universities joined forces with their offerings * Corresponding author. Daffodil International University, Dhaka, Bangladesh. E-mail addresses: alam@mis.brur.ac.bd (S. Alam), imranmahmud@daffodilvarsity.edu.bd (I. Mahmud), shyful@daffodilvarsity.edu.bd (S.M.S. Hoque), rozina@daffodilvarsity.edu.bd (R. Akter), sohelrana@iub.edu.bd (S.M. Sohel Rana). Contents lists available at ScienceDirect The International Journal of Management Education journal homepage: www.elsevier.com/locate/ijme https://doi.org/10.1016/j.ijme.2022.100706 Received 5 November 2021; Received in revised form 15 August 2022; Accepted 1 September 2022
- 3. The International Journal of Management Education 20 (2022) 100706 12 Evaluation of the proposed research model revealed that the continuance intention was strongly affected by the satisfaction and psychological safety of the students. Therefore, this approach has several implications for both research and practice, and is discussed in the following sections. 10.1. Theoretical contribution: validation of ECM and integration of task and psychological safety The findings of this research validate the modified ECM theory in the context of e-learning platforms being used in private uni versities in Bangladesh. Certain prior studies have mainly focused on the e-learning acceptance, m-learning acceptance, e-learning adoption, digital readiness for e-learning, digital transformation, and the continuance learning intention in the MOOC setting. Other studies have focused on new technologies in e-learning, outcomes of e-learning, continuance intention to use online library or digital text books, evaluation of video lecturers, factors of LMS, acceptance of LMS, trans-formative teaching and learning. Nevertheless, there have been studies highlighting the continuance intention of learners in using e-learning systems as evidenced by the findings of Xu and Wang (2018), Zhang et al. (2012), and Zhu et al. (2020). However, these studies primarily concentrated on a different domain for e.g., they were conducted in countries with varying learning environments and different domains e.g., online short courses. Contrary to the aforementioned studies, this study targets the formal educational settings (tertiary level) in a developing country like Bangladesh where e-learning is still nascent. The main contribution is to combine the pleasure of the task (skill of the task, challenge, and pleasure) to examine how users rate it in terms of business students’ satisfaction of online platforms especially in the region of South-Asian country like Bangladesh. Using past studies on ECM to integrate and complement the relevant conceptual theories hitherto unused in this context (task enjoyment), this study provides a better understanding into the continuation intention of using e-learning platforms. The study also makes it potentially possible to operationalize psychological safety and test the model developed through the survey methodology. This po tential has largely been ignored in past studies focusing on e-learning. The empirical validation of the newly developed model in this study showed how psychological safety can be used in IS research to explain the continuation intentions of users in using online platforms, which can be best described as the extension of previous research studies. Based on the results of this study, modified ECM theory can best be applied in other settings as well, thereby adding new knowledge to existing literature. Therefore, this research has significant impact to enhance theoretical knowledge. 10.2. Practical implication: task based usage of e-learning and psychological safety With regards to LMS management in educational institutes of developed countries, the results of this study reveal that the manifestation of workarounds are specifically related to psychological safety. Teachers should avoid criticizing participants in the event of mistakes occurring. This suggestion would be applicable not only within the domain of knowledge sharing between students, but also for knowledge-based collaborations within a project team. This study offers suggestions to the management department of universities on how to maintain the intention to continue using an e-learning system. First, the administration must purchase or develop various features such as interactive content in order to increase student enjoyment in the task. Analytical tools can also be employed to monitor student engagement. Second, the e-learning platform must be made more user-friendly and teachers must be adequately trained so that the content provided by them translates into perceived utility and satisfaction after adoption by students. Finally, the managers of e-learning platforms should aim to improve the psychological safety of the students and create an encouraging atmosphere for students in order to promote student feedback and knowledge sharing. 11. Limitations and scope for future work The present study is the result of the reaction of students to e-learning platforms used in universities in DIU. However, limitations of the study include being limited to the scope of universities in Bangladesh and not global in nature. Moreover, only private universities were considered for this study while public and international universities based in Bangladesh were left out. Apart from the aforementioned implications, another scope for future research may be focused on technology induced research. Since the current study considered the impact of positive variable, future research might not only focus on the perspective of satis faction but also consider the impact of exhaustion caused by technostress on the continuance intention. Furthermore, the present study did not use machine learning algorithms for predicting the influence of these variables over a time period. The authors propose to use the PLS-SM and artificial neural network (ANN) based hybrid model to predict the most important variable impacting the continuance intention. This may help stakeholders to take necessary steps for boosting the intention of students. 12. Concluding oberservations This research is part of the limited studies - which explain students’ intention to pursue academic studies on e-learning platforms - that integrate task-related enjoyment and psychological safety from a theoretical perspective with empirical validation. As we suffered in pandemic, our ability to understand information technology for learning is key to extended successful sustainable education. This research project was undertaken to provide a proof of concept for this individual level framework, finding support and more insightful results than what prior research and theory offer. Beyond previous research, this study develops a theoretical model using ECM theory and emphasizes psychological safety during the period of Covid-19. S. Alam et al.
- 4. The International Journal of Management Education 20 (2022) 100706 18 Appendix 3. Process of the survey Appendix 4. Common Method Bias Using Marker Variable Without Marker variable With Marker variable Path Coefficient Result Path Coefficient Result H1 TS - > EN 0.404 Supported 0.404 Supported H2 TC - > EN 0.398 Supported 0.398 Supported H3 EN - > SAT 0.227 Supported 0.225 Supported H4 CON - > PAPU 0.745 Supported 0.745 Supported H5 CON - > SAT 0.172 Not Supported 0.172 Not Supported H6 PAPU - > SAT 0.383 Supported 0.384 Supported H7 SAT - > CI 0.412 Supported 0.411 Supported H8 PS - > CI 0.338 Supported 0.338 Supported S. Alam et al.
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