Investigating Zoom Continuance Use by Ghanaian University
Students in Blended Learning Arrangements in the Post-Covid
Era
Eli, E, Fianu∗ Zelda, Arku Ernest Affum
University of Mines and Technology University of Mines and Technology University of Mines and Technology
efianu@gmail.com zarku@umat.edu.gh ekaffum@umat.edu.gh
Stephen Boateng Frank Boateng
University of Ghana University of Mines and Technology
stephenboateng.gh@gmail.com fboateng@umat.edu.gh
ABSTRACT ACM Reference Format:
The study sought to determine factors that significantly influence Eli, E, Fianu, Zelda, Arku, Ernest Affum, Stephen Boateng, and Frank
university students’ continuance use of Zoom in blended learning Boateng. 2022. Investigating Zoom Continuance Use by Ghanaian Uni-
arrangements in the post-Covid era. Zoom Cloud Meetings is a versity Students in Blended Learning Arrangements in the Post-Covid Era.In 2022 6th International Conference on Education and E-Learning (ICEEL
proprietary video teleconferencing software program developed by 2022), November 21–23, 2022, Yamanashi, Japan. ACM, New York, NY, USA,
Zoom Video Communications. Zoom became one of the e-learning 6 pages. https://doi.org/10.1145/3578837.3578851
platforms that gained attention in the education sector in Ghana
after the COVID-19 pandemic outbreak and has been widely used
by educational institutions for online lectures. The research model 1 INTRODUCTION
comprises a set of relationships between constructs from the Infor- There has been a paradigm shift in university education from the
mation System (IS) success model (system quality, usage intention, traditional classroom approach to the use of information and com-
and user satisfaction), Expectation Confirmation Model (ECM) of IS munication technologies (ICTs) to support teaching and learning
(perceived usefulness and usage continuance), and two constructs [25]. As a result, the traditional classroom approach, e-learning,
identified from empirical review (instructional quality and com- and blended learning techniques are currently used for teaching in
puter self-efficacy). Three hundred and thirty-five (335) students educational institutes [20].
from selected universities in Ghana who partake in Zoom-based On 11th March 2020, the World Health Organization WHO de-
lectures completed an online survey via Google forms. Survey data clared COVID-19
were analysed using partial least squares structural equation mod- a pandemic and people were advised to prevent close contact
elling (PLS-SEM). Lecturers and management of universities will with others [41]. Universities across the globe, therefore, had to
find the study useful for the improvement of teaching and learning close down [43]. To reduce the impact of closures, several universi-
via Zoom-based lectures. ties made provisions for online classes for their students through
e-learning platforms [6]. Zoom, Skype, Google Meet, etc. are exam-
CCS CONCEPTS ples of e-learning platforms mostly used in the Covid-19 pandemic.
• ; • →World Wide Web; Zoom Cloud Meetings is a proprietary video teleconferencingCCS Description: Information systems
Web applications; Internet communications tools; Web conferenc- software program developed by Zoom Video Communications. The
ing; Zoom software program has been widely used by educational insti-tutions for online lectures after the COVID-19 pandemic outbreak.
Several tertiary educational institutions in Ghana adopted a
KEYWORDS blended mode of lecture delivery to students in the post-COVID
Zoom, Covid-19, blended learning, usage continuance, Ghana era. This blended mode of delivery is a combination of face-to-face
classroom teaching and online teaching (mostly hosted on Zoom).
Several of these institutions continue to adopt this blended mode of
∗Corresponding author. lecture delivery. Some lecturers in these institutions have reported
(during teacher association meetings) unsatisfactory participation
rates in Zoom-based lectures by students. The negative trend is of
Permission to make digital or hard copies of all or part of this work for personal or
classroom use is granted without fee provided that copies are not made or distributed concern because of the importance of lecture attendance to both
for profit or commercial advantage and that copies bear this notice and the full citation students and faculty. The current study seeks to ascertain the factors
on the first page. Copyrights for components of this work owned by others than the that influence Zoom usage continuance by students in blended
author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or
republish, to post on servers or to redistribute to lists, requires prior specific permission learning arrangements in the post-Covid era.
and/or a fee. Request permissions from permissions@acm.org. Arguably, few studies have investigated students’ continuous use
ICEEL 2022, November 21–23, 2022, Yamanashi, Japan of Zoom in blended learning arrangements in the post-COVID-19
© 2022 Copyright held by the owner/author(s). Publication rights licensed to ACM.
ACM ISBN 978-1-4503-9842-8/22/11. . . $15.00 era. The studies on e-learning have focused on the use of virtual
https://doi.org/10.1145/3578837.3578851 learning environments such as Moodle [17, 37], Blackboard [23],
95
ICEEL 2022, November 21–23, 2022, Yamanashi, Japan Eli Fianu et al.
and Sakai [50, 51]. Very few studies have been conducted on Zoom. relevance, understandability, accuracy, conciseness, completeness,
Given the very few studies on Zoom, the current study aims to currency, timeliness, and usability [49]. Use is a success measure
conduct a study on Zoom to fill the gap in the literature. A research and links to the total effective use of a system. User satisfaction is
model is proposed based on Delone and McLean IS success model, the perceived level of amicability toward the entire system [15]. Net
Expectation Confirmation Model (ECM) of IS, and constructs from benefits are the perceived individual and organizational impacts on
empirical review (Instructional Quality and Computer self-efficacy) job performance and efficiency [18].
to examine Ghanaian university students’ continuance participa- The study proposes amodel based on constructs from theDeLone
tion in Zoom-based lectures in the post-COVID era. The proposed and McLean IS Success Model (System Quality, Usage Intention,
model comprises a set of relationships between constructs from the User Satisfaction), ECM (Perceived Usefulness and Usage Continu-
IS success model (system quality, usage intention, and user satisfac- ance), and constructs from empirical review (Instructional Quality
tion) and ECM (perceived usefulness and usage continuance) that and Computer self-efficacy).
are rare in most models used in e-learning studies.
2.2 Empirical Review and Hypotheses
2 LITERATURE REVIEW Table 1 shows a summary of the empirical review as well as the
2.1 Theoretical background hypotheses.
2.1.1 Expectation Confirmation Model. The Expectation Confirma-
tion Theory (ECT) was propounded by Oliver [46] and built on by 3 METHODOLOGY
Bhattacherjee [10] as the Expectation Confirmation Model (ECM). 3.1 Research Design
The difference between ECM and ECT is the change in the varia- The study used a quantitative research design. The quantitative
tions between pre-use expectation and actual performance into a research design was chosen because the researchers wanted to
pure post-acceptance model for continued use of Information Sys- statistically test the influence of independent latent constructs on
tem (IS) or Information Technology /IT [13]. In the fields of IS, ECM mediating latent constructs and dependent latent constructs via
is considered one of the solid theories that explain users’ posta- path analysis.
doption behavior concerning use and intention to use [39]. The
dynamic cognitive processes that people encounter during choices 3.2 Sampling
of IT continuance use are based on four variables as described by
ECM. The variables are the user’s level of satisfaction with the IT; The population comprises students from selected universities in
the extent of the user’s confirmation of expectations; perceived Ghana who partake in blended learning arrangements using Zoom.
usefulness (PU) and continuance intention [10]. In ECM, confirma- The researchers had a challenge calculating the exact population
tion is defined as the users’ level of the appropriateness between size because of the inconsistencies in the implementation of the
their expectation of the IS/IT use and its actual performance [33]. blended learning arrangements across the educational institutions.
Satisfaction represents the user’s post-evaluation of their overall A minimum sample size was calculated, thereafter, a purposive
experience towards a specific IS/IT [10]. PU is the degree to which sampling method was adopted.
a person believes that using a particular system would enhance The minimum sample size was calculated based on the “ten times
his/her job performance [10]. Lastly, continuance intention explains rule of thumb” [9, 30] which recommends a minimum sample size
the user’s intention to continue using IS/IT artefact. of ten times the maximum number of independent variables in theouter model and inner model. This approach is equivalent to using a
2.1.2 DeLone and McLean IS Success Model. The DeLone and sample size of ten times the largest number of formative indicators
McLean IS success model has been used to understand the user used to measure any construct in the outer model or ten times the
acceptance of various IS models (Sharma et al, 2017). The initial IS largest number of structural paths directed at a particular latent
success model developed by DeLone and McLean in included six construct in the inner model [9, 30]. The largest number of forma-
theoretical constructs namely, information quality, system quality, tive indicators used to measure any construct in the outer model
use, user satisfaction, individual and organizational impact as the (of the current research model) is 6, while the largest number of
dependent variable [19]. After a decade, the authors updated the structural paths directed at a particular latent construct in the inner
model by including service quality and combining individual im- model is 6. Based on the “ten times rule of thumb”, the minimum
pacts with organizational impacts, naming it net benefits based on sample size is 60. Generally, a sample size of 300 is regarded as
a review of success measures found in previous empirical works “good” [32] , thus, a sample size of 300 was chosen. This ensured
[35]. DeLone and McLean [18] also proposed usage intention as that the sample size chosen was larger than the minimum sample
a replacement for “use” in their updated IS success model under size.
certain conditions. System quality is the anticipated technical fea-
tures (e.g., ease of use and user-friendliness), while information 3.3 Data Collection
quality takes into consideration the issue of content (e.g., com- An online survey was created via Google forms. Investigations con-
plete, up-to-date, and precise). Service quality refers to the total ducted by the researchers showed that twenty-one (21) universities
service support that the service providers give to users through IS had blended learning arrangements. Lecturers from twenty-one
(e.g., customer support and service) [18]. Again, information qual- (21) selected universities were given a link to the online survey;
ity explains the required features of the system outputs including they subsequently shared the links with their respective students to
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Investigating Zoom Continuance Use by Ghanaian University Students in Blended Learning Arrangements in the
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Table 1: Summary of the empirical review and hypotheses
Hypothesisnumber Hypothesized path Supporting Empirical Studies
H1 Instructional Quality -> Usage Intention [26, 27, 38, 56]
H2 Computer Self-Efficacy -> Usage Intention [52, 55]
H3 Perceived Usefulness -> Usage Intention [4, 36, 40]
H4 Perceived Usefulness -> User Satisfaction [4, 36, 40]
H5 System Quality -> Usage Intention [2, 5, 15]
H6 System Quality -> User Satisfaction [2, 5, 15]
H7 Usage Intention -> Usage Continuance [12, 13, 42]
H8 User Satisfaction -> Usage Continuance [12, 13, 31, 44, 57]
Table 2: Construct Reliability and Validity
Cronbach’sAlpha rho_A CompositeReliability Average Variance Extracted (AVE)
Computer Self-Efficacy 0.897 0.899 0.894 0.585
Instructional Quality 0.910 0.911 0.910 0.717
Perceived Usefulness 0.836 0.856 0.838 0.514
System Quality 0.937 0.938 0.937 0.714
Usage Continuance 0.709 0.840 0.737 0.517
Usage Intention 0.942 0.943 0.942 0.845
User Satisfaction 0.887 0.895 0.889 0.728
complete the survey. Three hundred and thirty-five (335) responses with replacement from the original sample and then estimating the
were received. model parameters for each bootstrap re-sample. The results of the
bootstrapping procedure are shown in Table 4. Constructs with p
4 DATA ANALYSIS AND RESULTS values equal to or less than 0.05 are significant, while constructs
Data analysis was done using the partial least squares-structural with p values greater than 0.05 are not significant. Table 4 shows
equation modelling (PLS-SEM) technique via SmartPLS 3. PLS-SEM that seven of the hypotheses were supported, that is, H1, H3, H4,
is appropriate for the non-parametric modelling of complex cause– H5, H6, H7, and H8, while one hypothesis was not supported, that
effect relationships between latent variables [9]. The two-step ap- is, H2.
proach to PLS-SEM proposed by Chin [14] is used. The measure- The proposed model explained 74.5% of the variance in Zoom
ment model (outer model) was initially assessed, followed by the usage continuance, 67.0% of the variance in Zoom usage intention,
assessment of the structural model (inner model). Data cleaning and 70.3% of the variance in user satisfaction. The R square values
was done before PLS-SEM. The data was checked for missing values are shown in Table 4. The standardized root mean square residual
and outliers; 331 responses were retained after data cleaning. (SRMR) was used to assess model fit in SmartPLS. Hu and Bentler
The measurement model was assessed using reliability, conver- [34] proposed that models that have SRMR values less than 0.08
gent validity, and discriminant validity tests. Reliability was as- have good model fit. Table 4 shows SRMR value of 0.050 which
sessed using Cronbach’s alpha, composite reliability, and Dijkstra– implies the model has good fit.
Henseler’s rho. A construct exhibits reliability if Cronbach’s alpha,
composite reliability, and Dijkstra–Henseler’s rho values are 0.7 5 DISCUSSION OF RESULTS
and above [9]. The results of the study show that instructional quality, perceived
Convergent validity was assessed using the average variance usefulness, and system quality have a significant positive effect
extracted (AVE). A construct exhibits convergent validity if the AVE on usage intention. Perceived usefulness and system quality were
value is 0.5 and above [9]. Table 2 shows that all the constructs found to have a significant positive effect on user satisfaction. Usage
exhibit reliability and convergent validity. intention and user satisfaction were found to have a significant pos-
Discriminant validity was assessed using the heterotrait- itive effect on usage continuance. However, computer self-efficacy
monotrait ratio of correlations (HTMT0.90). If the HTMT value was found not to have a significant influence on usage intention.
is below 0.90, discriminant validity has been established between Seven out of the eight hypotheses stated were supported, which, to
two constructs [29, 30]. Table 3 shows that all the constructs exhibit a large extent supports our research model.
discriminant validity. Our study provides support for studies conducted by Wu and
A bootstrapping procedure was used to assess the structural Wang [56], Fianu et al. [27], Farhan et al. [26], and Larmuseau et
model to determine the significance of each estimated path. Boot- al. [38] which show that instructional quality influences students’
strapping is the process of drawing a large number of re-samples usage of e-learning systems. It points to the fact that lecturers
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ICEEL 2022, November 21–23, 2022, Yamanashi, Japan Eli Fianu et al.
Table 3: Heterotrait-monotrait ratio of correlations (HTMT)
Computer Instructional Perceived System Usage Usage User
Self-Efficacy Quality Usefulness Quality Continuance Intention Satisfaction
Computer
Self-Efficacy
Instructional 0.678
Quality
Perceived 0.557 0.777
Usefulness
System Quality 0.697 0.748 0.652
Usage 0.566 0.741 0.818 0.759
Continuance
Usage 0.529 0.765 0.773 0.648 0.800
Intention
User 0.540 0.677 0.789 0.731 0.776 0.618
Satisfaction
Table 4: Hypothesis testing results
Hypothesisnumber Hypothesized path Pathcoefficient Tstatistics pvalues Results
H1 Instructional Quality -> Usage Intention 0.356 4.534 0.000* Supported
H2 Computer Self-Efficacy -> Usage Intention -0.007 0.144 0.885 Not supported
H3 Perceived Usefulness -> Usage Intention 0.360 7.419 0.000* Supported
H4 Perceived Usefulness -> User Satisfaction 0.459 6.916 0.000* Supported
H5 System Quality -> Usage Intention 0.158 1.975 0.048* Supported
H6 System Quality -> User Satisfaction 0.399 5.506 0.000* Supported
H7 Usage Intention -> Usage Continuance 0.474 8.256 0.000* Supported
H8 User Satisfaction -> Usage Continuance 0.392 6.846 0.000* Supported
R2 (Usage Continuance) = 0.745
R2 (Usage Intention) = 0.670
R2 (User Satisfaction) = 0.703
SRMR = 0.050
* Significant at the 0.05 level
need to have the relevant skills in the use of the Zoom platform to with learning. Zhang and Dang [59] mention that students’ own
effectively teach students. Lecturers need to know how to use all motivation to learn could significantly influence their perceptions
the features of the Zoom platform that can facilitate teaching and of the learning climate and task-technology fit, thus, their level of
learning, especially their configuration settings. The use of features proficiency in using the computer and information technology does
such as screen sharing, the whiteboard, polls, chat, breakout rooms, not seem to matter that much. Turan and Cetintas [53] found that
and apps can be optimized for students to have a very good learning computer self-efficacy did not have any significant influence on
experience. The use of correct audio and video settings are also students’ use of online video lessons; however, they did not attempt
critical for a good learning experience. University management to rationalise this finding but suggested a more detailed enquiry
should organize periodic training of lecturers on the effective use into it. Based on the high mean score of the CSE construct (4.02) in
of the Zoom application. the current study, we argue that it is most likely that the majority
Contrary to expectation, computer self-efficacy was found to of students with high computer self-efficacy perceptions may not
have a slightly negative and insignificant influence on usage inten- view their level of proficiency in using the computer and informa-
tion. This finding is inconsistent with the majority of e-learning tion technology as a significant influencer of the use of e-learning
studies, for instance, Thongsri et al. [52] and Fianu et al. [27]. It is systems. Our argument is supported by Xu et al. [58] who reported
however consistent with studies conducted by Turan and Cetintas a high average CSE score for respondents and proposed that the
[53], Xu et al. [58], and Zhang and Dang [59]. Zhang and Dang negative effect of CSE on students technology adaptation may be
[59] report that students’ computer self-efficacy doesn’t play any due to the confidence they have in the use of mobile devices.
significant role in influencing their perceptions of either the learn- As was the case with studies conducted by Amsal et al. [4], Liaw
ing climate, task-technology fit, or the level of flexibility associated and Huang [40], and Keržič et al. [36]), perceived usefulness (PU)
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Investigating Zoom Continuance Use by Ghanaian University Students in Blended Learning Arrangements in the
Post-Covid Era ICEEL 2022, November 21–23, 2022, Yamanashi, Japan
was found to have a significant influence on usage intention and 8 LIMITATIONS OF THE STUDY
user satisfaction. This points to the fact that generally, when stu- The study employed a non-probability sampling technique which
dents perceive the Zoom application as being useful for lectures, imposes limitations on the generalizability of the findings. Addi-
they will participate. The scale items for PU of Zoom suggest that tionally, the study was conducted in 3 out of the 10 geographical
PU is driven by increased efficiency in the use of the app to discuss and administrative regions of Ghana; this also imposes limitations
more topics (compared to face-to-face lectures), better academic on the generalizability of the findings.
performance, and ease of attending classes/lectures. While lecturers
cannot directly influence the core technology of the Zoom applica-
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