Determinants of nursing students’ satisfaction with blended learning

Abstract

Background
Blended learning, a pedagogical approach combining traditional classroom instruction with online components, has gained prominence in nursing education. While offering numerous benefits, student satisfaction with blended learning remains a critical concern. This study contributes to the existing literature by providing a comprehensive evaluation of the determinants influencing nursing students’ satisfaction with this innovative educational modality. By examining a wide range of factors, including sociodemographic characteristics, academic factors, and environmental influences, this research offers valuable insights for educators to optimize blended learning experiences in nursing education.

Methods
A descriptive cross-sectional research design was conducted. This study investigates the factors influencing nursing students’ satisfaction with blended learning at Alexandria University, Egypt, where blended learning programs have been integrated into the curriculum primarily through the Microsoft Teams platform. A convenient sample of 1266 nursing students from both bachelor and technical educational institutions participated in the study from September 2023 to the end of December 2023. Data were collected using an online survey containing two measurement tools: the Blended Learning Satisfaction Scale and the Environmental Facilitators and Barriers to Student Persistence in Online Courses scale. Statistical analyses, including descriptive statistics and backward multiple linear regression, were conducted to identify factors that are associated with the satisfaction of nursing students’ with blended learning.

Results
Findings indicate that factors such as age, gender, income, employment status, access to suitable internet sources, academic year, computer literacy, preferred learning method, and perceptions of environmental facilitators significantly influence satisfaction scores (all p < 0.001). The overall regression model, with an adjusted R² of 0.31, signifies that 31% of the variance in satisfaction scores is explained collectively by the previously mentioned variables (F = 21.21, p < 0.001).

Conclusion
Students’ sociodemographic variables, preference for blended learning, and perception of environmental facilitators such as encouragement to enroll in the course significantly influence nursing students’ satisfaction levels with blended learning. However, limitations in the current study such as self-report bias, convenient sampling, and cross-sectional design limit the generalizability and causal inferences of these findings.

Full text

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Hassan et al. BMC Nursing (2024) 23:766
https://doi.org/10.1186/s12912-024-02393-y BMC Nursing
*Correspondence:
Eman Arafa Hassan
eman_arafa@alexu.edu.eg
1Critical Care and Emergency Nursing Department, Faculty of Nursing,
Alexandria University, Alexandria, Egypt
2Community Health Nursing, Faculty of Nursing, Alexandria University,
Alexandria, Egypt
3Faculty of Nursing, Ain Shams University, Cairo, Egypt
Abstract
Background Blended learning, a pedagogical approach combining traditional classroom instruction with online
components, has gained prominence in nursing education. While oering numerous benets, student satisfaction
with blended learning remains a critical concern. This study contributes to the existing literature by providing
a comprehensive evaluation of the determinants inuencing nursing students’ satisfaction with this innovative
educational modality. By examining a wide range of factors, including sociodemographic characteristics, academic
factors, and environmental inuences, this research oers valuable insights for educators to optimize blended
learning experiences in nursing education.
Methods A descriptive cross-sectional research design was conducted. This study investigates the factors inuencing
nursing students’ satisfaction with blended learning at Alexandria University, Egypt, where blended learning
programs have been integrated into the curriculum primarily through the Microsoft Teams platform. A convenient
sample of 1266 nursing students from both bachelor and technical educational institutions participated in the
study from September 2023 to the end of December 2023. Data were collected using an online survey containing
two measurement tools: the Blended Learning Satisfaction Scale and the Environmental Facilitators and Barriers to
Student Persistence in Online Courses scale. Statistical analyses, including descriptive statistics and backward multiple
linear regression, were conducted to identify factors that are associated with the satisfaction of nursing students’ with
blended learning.
Results Findings indicate that factors such as age, gender, income, employment status, access to suitable internet
sources, academic year, computer literacy, preferred learning method, and perceptions of environmental facilitators
signicantly inuence satisfaction scores (all p < 0.001). The overall regression model, with an adjusted R² of 0.31,
signies that 31% of the variance in satisfaction scores is explained collectively by the previously mentioned variables
(F = 21.21, p < 0.001).
Conclusion Students’ sociodemographic variables, preference for blended learning, and perception of
environmental facilitators such as encouragement to enroll in the course signicantly inuence nursing students’
satisfaction levels with blended learning. However, limitations in the current study such as self-report bias, convenient
sampling, and cross-sectional design limit the generalizability and causal inferences of these ndings.
Keywords Blended learning, Determinants, Nursing students, Satisfaction
Determinants of nursing students’ satisfaction
with blended learning
Eman ArafaHassan1*, Ahlam MahmoudMohamed2, Fatma AbdouEltaib3 and Asmaa Mohammed SaadKhaled2
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Hassan et al. BMC Nursing (2024) 23:766
Introduction
In the rapidly evolving landscape of higher education,
universities globally are embracing virtual learning envi-
ronments, leading to the widespread adoption of blended
learning that combines online and face-to-face instruc-
tion [1]. e integration of learning management systems
and the use of information and communication technolo-
gies have become integral aspects of students’ lives [2, 3].
e transformative impact of technology on education
was further accelerated by the global pandemic, com-
pelling institutions to swiftly shift to distance and online
learning due to the imposition of national lockdowns [4,
5].
Blended learning manifests in various forms, including
web courses, web enhancement courses, and web-centric
courses [6]. Each method has its unique characteristics,
blending online and face-to-face elements to dierent
extents [7]. e role of educators in the blended learning
model assumes a multifaceted dimension, encompassing
roles as facilitators, motivators, mentors, and counselors.
is approach emphasizes a collaborative learning envi-
ronment where teachers act as friends, both online and
oine, fostering an open and exible learning experience
aligned with students’ needs [8, 9].
In the context of nursing education, blended learning
integrates theoretical knowledge with practical appli-
cation, utilizing a variety of resources such as virtual
simulations, interactive modules, and instructor-led dis-
cussions [10]. is approach not only accommodates
diverse learning styles but also fosters self-directed learn-
ing and critical thinking skills essential for nursing prac-
tice in today’s complex healthcare environment [11]. By
seamlessly blending technology with traditional class-
room instruction, blended learning in nursing education
enhances accessibility, exibility, and engagement, ulti-
mately contributing to students’ satisfaction and compe-
tency development [12].
e signicance of understanding the determinants
of nursing students’ satisfaction with blended learn-
ing becomes paramount. Blended learning necessitates
the eective utilization of technology, considers learner
characteristics, and relies on participants’ commitment
[13, 14]. Factors such as computer competency, social
and family support, workload management, age, gender,
and attitude emerge as crucial elements in the context
of higher educational institutions [15]. Moreover, the
innovative pedagogy and instructional design supporting
blended learning emphasize its potential to reshape tra-
ditional education paradigms [16, 17].
Previous studies have acknowledged the multifaceted
nature of student satisfaction, emphasizing the intri-
cate interplay of diverse factors. e literature suggests
that factors such as instructional design, course con-
tent relevance, and the quality of online and face-to-face
interactions signicantly inuence student satisfaction in
blended learning environments [15, 18]. Additionally, the
perceived eectiveness of assessment methods and the
alignment of learning objectives with students’ profes-
sional goals have been identied as critical components
shaping students’ satisfaction in blended learning settings
[15, 19].
In this dynamic educational experience, student satis-
faction has emerged as a critical concern for higher edu-
cation sponsors operating in an increasingly competitive
market. It has become an integral component of quality
assurance and quality enhancement eorts [20, 21]. e
level of learner satisfaction, reecting attitudes and feel-
ings towards the advantages of blended learning class-
rooms, plays a pivotal role in gauging the eectiveness of
this educational approach [22].
Despite the wealth of research exploring general stu-
dent satisfaction in blended learning, there remains a
discernible gap in the specic context of nursing educa-
tion. Nursing students constitute a unique cohort with
distinct educational needs and professional expectations.
e scant literature addressing nursing students’ satisfac-
tion with blended learning emphasizes the need for a tar-
geted investigation into the determinants that resonate
within this specialized eld. Understanding the factors
that inuence nursing students’ satisfaction with blended
learning is crucial for educational institutions striving to
tailor their programs to meet the evolving demands of
the healthcare sector [23, 24]. erefore, this study aims
to meticulously assess the determinants of nursing stu-
dents’ satisfaction with blended learning, contributing
valuable insights to the ongoing discourse on the eec-
tiveness and optimization of blended learning method-
ologies in nursing education.
Method
Aim
is study aimed to comprehensively evaluate the deter-
minants inuencing nursing students’ satisfaction with
blended learning.
Design
A cross-sectional research design was applied in this
study.
Settings
is study was conducted within the academic institu-
tions of Alexandria University, specically the Faculty of
Nursing and the aliated Technical Institute of Nursing
in Alexandria, Egypt. e Faculty of Nursing at Alexan-
dria University stands as a center for nursing education,
fostering academic excellence and professional develop-
ment. e Technical Institute of Nursing, closely ali-
ated with the university, complements this academic
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Hassan et al. BMC Nursing (2024) 23:766
ecosystem by providing specialized technical training in
nursing.
Within this dynamic academic setting, blended learn-
ing has been seamlessly integrated into the educational
fabric, predominantly utilizing the Microsoft Teams plat-
form. Blended learning methods, such as web courses,
web enhancement courses, and web-centric courses, have
become prevalent, enhancing the learning experience
for nursing students. Microsoft Teams serves as a versa-
tile platform for online lectures, oine lectures, assign-
ments, quizzes, and video resources supporting nursing
education. is integration highlights the commitment
to providing a comprehensive and interactive learning
environment that seamlessly combines face-to-face and
online elements.
Participants
A convenient sample of 1266 nursing students from
both bachelor and technical educational institutions
were included in this study, representing diverse cohorts
across dierent semesters. e inclusion of students from
various semesters ensures a comprehensive understand-
ing of satisfaction determinants throughout the academic
progression. e exclusion criteria were students who are
not currently enrolled in nursing programs or those who
do not consent to participate in the study. All nursing
students included in this study, both bachelor’s and tech-
nical nursing education students, had completed at least
one blended nursing course. By September 2023, the start
of data collection for this study, all nursing students ali-
ated with Alexandria University had completed at least
one nursing course with a blended learning component.
Blended learning was initially adopted in response to the
COVID-19 pandemic and has continued to be integrated
into many nursing courses at Alexandria University.
Power Analysis and Sample Size (PASS) program ver-
sion 20 was employed for sample size estimation, incor-
porating a power analysis. e minimum sample size was
determined based on a power of 90%, a level of signi-
cance set at 0.05, and a minimum sample size of 1000. To
enhance precision, a moderate eect size, based on prior
research [25, 26] and expert judgment, was included in
the calculation. Additionally, expected variability, cru-
cial for accurate sample size estimation, was considered.
e chosen multivariate regression model, accounting
for multiple predictors, was also factored into the estima-
tion. Potential dropout or non-response rates were care-
fully considered to ensure the study’s robustness against
these challenges.
Measurement tools
In the current study, we utilized two standardized tools,
with permission, in their original English versions. Tool
one was used to assess nursing students’ satisfaction with
blended learning [27], while tool two aimed to evaluate
the environmental facilitators and barriers aecting per-
sistence in blended learning courses, particularly in its
online aspect [28]. ese tools were previously validated
in their original studies. Furthermore, they were revali-
dated in the current study to ensure their relevance to the
study’s aims and appropriateness for Egyptian nursing
students. is revalidation followed a pilot study involv-
ing 56 Egyptian nursing students and incorporated evalu-
ations from eleven nursing education experts regarding
the tools.
Tool one is “Blended Learning Satisfaction Scale
(BLSS)”. is scale was developed by Zeqiri et al. (2021)
[27] to assess nursing students’ satisfaction with blended
learning. is scale comprises thirteen statements across
four domains: course management (four statements),
interaction (three statements), performance (three state-
ments), and satisfaction (three statements). Statements
are rated on a 5-point Likert scale, one (strongly dis-
agree) to ve (strongly agree). e total score ranges from
13 to 65, with a higher total score representing a higher
level of satisfaction.
e scale internal consistency of Cronbach’s test
ranges from 0.715 to 0.931 in its original report [27]. We
assessed whether the tool eectively measures the theo-
retical constructs it is intended to evaluate within the
Egyptian context. Utilizing conrmatory factor analy-
sis (CFA), we found that all items had factor loadings
exceeding 0.5, demonstrating a strong positive correla-
tion with their underlying constructs. Additionally, we
ensured face and content validity, achieving a content
validity index greater than 0.90 for each domain. e
reliability of the tool, as measured by Cronbach’s alpha,
ranged from 0.78 to 0.92 in this study.
Tool two is “e environmental Facilitators and Bar-
riers to Student Persistence in Online Courses”. is
tool was developed by Heilporn and Lakhal (2022) [28]
to measure the environmental facilitators and barriers
encountered by students. is tool, originally designed
for assessing student persistence in online courses, was
adapted to the context of blended learning for this study.
e tool is composed of 16 items and utilizes a 5-point
Likert scale used to rate each statement coded from 1
“strongly disagree” to 5 “strongly agree”. e total score
ranges from 16 to 80, with a higher total score repre-
senting a highly perceived facilitator to continue in the
courses. It consists of four domains: Encouragements
(ve statements), Time to Events (four statements),
Potential Dropout (ve statements), and Cost-Benet
(two statements). While the tool’s original focus was on
online courses, many of its statements, such as those
related to encouragements, time-events, and poten-
tial dropout, are directly relevant to the facilitators and
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Hassan et al. BMC Nursing (2024) 23:766
barriers that nursing students might face in a blended
learning environment.
In a prior study, the tool’s Cronbach’s alpha ranged
from 0.79 to 0.87 28. In the current study, we conducted
a CFA to ensure that this tool eectively captures the
constructs of blended learning facilitators and barri-
ers within the Egyptian blended learning context. e
analysis revealed factor loadings exceeding 0.62 for
each item, which is considered acceptable. Additionally,
we performed a principal component analysis (PCA) to
verify the underlying structure of the domains. e PCA
conrmed the suitability of the four domains of facilita-
tors and barriers, with eigenvalues exceeding one and
explaining a cumulative variance of 58.27% of the total
variance. Moreover, the content validity index of the
tool was 0.92, and the Cronbach’s alpha reliability for all
domains ranged from 0.82 to 0.89.
e socio-demographic characteristics of students (e.g.,
age, gender, income, residence working, level of study,
academic year, CGPA), as well as the availability of suit-
able internet sources and suitable electronic device on
which the students studied, computer literacy, and pref-
erable method of learning, were attached to the survey.
e survey is provided as a supplementary le S1.
Data collection
Data collection was started from the beginning of Sep-
tember 2023 to the end of December 2023. e research-
ers communicated with the selected students over the
phone and a voice message was sent on WhatsApp
groups to explain the aim of the study. e data was
collected through sharing a questionnaire using online
Google Forms, and the questionnaire link sent among
specic WhatsApp application groups for communica-
tion between students. e researchers asked the team
leaders to help in sharing the questionnaire link among
their WhatsApp groups. To reduce the missing data, the
students were mandatory to ll all the items in the online
questionnaire or else could not reach the next page; a
notication box indicating a warning reminder that one
or more items were not answered. After completing the
questionnaire, the students were directed to click the
submitted option and nally, the online questionnaire
was sent to the drive.
Ethical considerations
Approval from the Research Ethics Committee of the
Faculty of Nursing, Alexandria University, was obtained
(Institutional Review Board: IRB00013620). After
explaining the study’s purpose, all participants were
provided with informed written online consent for par-
ticipation by clicking agree to participate button at the
beginning of the electronic questionnaire. e research-
ers emphasized participants’ rights to voluntarily
participate, refuse, or withdraw from the study at the
beginning of the online questionnaire. To ensure data
condentiality, the online survey was conducted anony-
mously. No personal identiers such as names, codes, or
email addresses were required in the online forms. e
collected data were stored on a secure, password-pro-
tected Google drive that is not accessible to unauthorized
individuals. Only authorized research team members had
access to the collected data. is work has been carried
out in accordance with e Code of Ethics of the World
Medical Association (Declaration of Helsinki) on Human
participants.
Statistical analysis
e Statistical Package for Social Sciences (SPSS version
28) was utilized for both data presentation and statisti-
cal analysis. Descriptive statistics, including number, per-
centage, means, and standard deviation (SD), were used
to describe the socio-demographic characteristics, stu-
dents’ satisfaction with blended learning, and environ-
mental facilitators and barriers to student persistence in
online courses. A backward multiple linear regression
model was used to identify factors associated with nurs-
ing students’ satisfaction with blended learning. All the
statistical analyses were considered signicant at P ≤ 0.05.
Results
Table 1 illustrates the sociodemographic and learning
characteristics of the 1266 nursing student participants,
oering insights into the composition of the study’s
sample. e mean age of the students was 20.47 years,
demonstrating a relatively homogeneous age distribu-
tion with a low standard deviation (± 1.82). e gender
distribution reveals a notable majority of female students
(67.5%) compared to their male counterparts (32.5%). In
terms of residency, approximately two-thirds of the par-
ticipants reside in urban areas (64.8%), while the remain-
ing third is from rural backgrounds (35.2%). Financially,
58.1% of students report having enough income, indi-
cating a measure of nancial stability within the cohort.
A signicant portion of the students (59.7%) is engaged
in employment, suggesting a balance between academic
pursuits and work responsibilities.
Examining the learning environment and resources,
it is noteworthy that an overwhelming majority of stu-
dents (96.2%) have access to a suitable internet source,
emphasizing the ubiquity of internet connectivity
among the participants. Additionally, a substantial per-
centage (93.4%) possess suitable electronic devices for
study purposes, ensuring accessibility to online learning
resources. In terms of academic pursuits, the majority of
students are pursuing a Bachelor’s degree (67.3%), while
the remaining 32.7% are enrolled in technical degree
programs. e mean Cumulative Grade Point Average
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Hassan et al. BMC Nursing (2024) 23:766
(CGPA) of 3.64 ± 2.71 provides an overview of the aca-
demic performance of the participants, reecting a mod-
erate level of achievement.
e distribution of students in Fig.1 across academic
years demonstrates a balanced representation, with the
highest proportion in the rst year (32.5%) and a gradual
decline in subsequent years. Concerning technology pro-
ciency, Fig.2 shows that the majority of students report
intermediate computer literacy (46.8%), while a notable
percentage claim expertise (35.7). Lastly, Fig.3 revealed
that the preferred method of learning among participants
is diverse, with a signicant interest in online learning
(42.8%) and blended learning (35.6%), alongside a smaller
preference for face-to-face instruction (21.6%).
Table2 provides an overview of nursing students’ sat-
isfaction with various aspects of blended learning, with
mean scores and standard deviations indicating the level
of agreement or disagreement. Examining specic sat-
isfaction items, the data reveals that student’s rate of
“Interaction during the courses” is the highest, with a
mean score of 3.62 ± 0.88. is relatively low standard
Table 1 Nursing students’ sociodemographic and learning
variables (n = 1266)
Students’ variables N (%) or
Mean ± SD
Age 20.47 ± 1.82
Gender
Male
Female
411 (32.5%)
855 (67.5%)
Residency
Urban
Rural
820 (64.8%)
446 (35.2%)
Income
Enough
Not enough
735 (58.1%)
531 (41.9%)
Working
Yes
No
756 (59.7%)
510 (40.3%)
Availability of suitable internet source
Yes
No
1218 (96.2%)
48 (3.8%)
Availability of suitable electronic device to study on
Yes
No
1183 (93.4%)
83 (6.6%)
Level of study
Technical degree
Bachelor’s degree
414 (32.7%)
852 (67.3%)
Cumulative Grade Point Average (CGPA) 3.64 ± 2.71 Table 2 Students rating of blended learning satisfaction
(n = 1266)
Satisfaction items Mean score Standard deviation
Course Management 2.69 1.01
Interaction during the courses 3.62 0.88
Performance in the courses 2.78 1.08
Satisfaction with blended learning 3.21 0.93
Overall satisfaction 3.07 0.49
Fig. 3 Distribution of students according to their preferable method of
learning
Fig. 2 Distribution of students according to their computer literacy
Fig. 1 Distribution of students according to their academic year
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Hassan et al. BMC Nursing (2024) 23:766
deviation suggests a consensus among students regard-
ing positive interaction experiences. On the other hand,
“Course Management” and “Performance in the courses”
receive lower mean scores of 2.69 ± 1.01 and 2.78 ± 1.08,
respectively, accompanied by higher standard deviations,
indicating more varied opinions. e overall “Satisfaction
with blended learning” mean score of 3.21 ± 0.93 suggests
a moderate level of contentment, while “Overall satisfac-
tion” with a mean score of 3.07 ± 0.49 and a low standard
deviation indicates a relatively consistent level of satisfac-
tion across students.
Table3 shows nursing students’ perceptions of environ-
mental facilitators to blended learning, oering insights
into factors that contribute to their learning experience.
Notably, students express a high level of agreement with
“Encouragements to enroll in blended learning courses,”
as evidenced by a mean score of 3.99 and a moderate
standard deviation of 0.85, highlighting positive sup-
port structures. Additionally, the exibility of “Time and
events of blended learning courses” is acknowledged,
though with a lower mean score of 3.31 and a higher
standard deviation of 0.98, indicating some variability
in opinions. Students perceive the “Potential of dropout
in blended learning” and the “Cost-benet of blended
learning courses” with mean scores of 3.48 ± 1.08 and
3.70 ± 0.01, respectively, suggesting moderate agreement
with these factors. e overall agreement on facilitators
and barriers, with a mean score of 3.62 and a low stan-
dard deviation of 0.47, indicates a generally consistent
viewpoint among students regarding the factors inuenc-
ing their blended learning experience.
Figure4 of the scattered plot of multiple linear regres-
sion provide the predictor estimated against the students’
blended learning satisfaction. e plots in linear line
indicating all the predictors involved in this model have
p-values less than 0.05, indicating they are statistically
signicant in predicting satisfaction scores.
e multiple linear regression model of Table4 iden-
tied factors inuencing nursing students’ satisfaction
with blended learning. Age exhibits a modest negative
association with satisfaction scores (B = -0.04, p = 0.048),
suggesting that, within the 95% condence interval
(-0.06 to -0.03), as students’ age increases, satisfaction
marginally decreases. Female students express higher
satisfaction (B = 0.25, p = 0.037) compared to their male
counterparts, with a 95% condence interval of 0.34 to
0.86. Income has a signicant negative impact (B = -0.88,
p = 0.033), indicating that, within the 95% condence
interval (-0.98 to -0.26), lower income is associated with
lower satisfaction scores.
Table 3 Students rating of environmental facilitators to blended
learning (n = 1266)
Environmental facilitator Mean Standard
deviation
Encouragement to enroll in the courses 3.99 0.85
The time and events of blended learning courses
are exible
3.31 0.98
The potential of dropout in blended learning 3.48 1.08
Cost-benet of blended learning courses 3.70 0.01
Overall agreement on facilitators and barriers 3.62 0.47
Fig. 4 Scattered plot of multiple linear regression for estimated against the students’ blended learning satisfaction
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

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Hassan et al. BMC Nursing (2024) 23:766
Conversely, employed students (B = 0.62, p = 0.040)
exhibit higher satisfaction, possibly due to a sense of
accomplishment or additional resources gained from
employment. Access to a suitable internet source
(B = 0.45, p = 0.029) positively inuences satisfaction,
with a 95% condence interval of 0.53 to 0.80, empha-
sizing the importance of internet accessibility. Higher
academic years (B = 0.47, p = 0.028), within a 95% con-
dence interval of 0.18 to 0.61, and computer literacy (Std
beta = 0.90, p = 0.015), within a 95% condence interval
of 0.89 to 1.41, are both linked to increased satisfaction
scores, highlighting positive adaptation and technologi-
cal prociency.
Notably, students who prefer blended learning
(B = 1.11, p = 0.006), within a 95% condence interval
of 1.02 to 1.44, and receive encouragement to enroll
(B = 0.46, p = 0.010), within a 95% condence interval of
0.05 to 0.65, demonstrate signicantly higher satisfac-
tion. e exibility of time and events in blended learn-
ing (B = 0.52, p = 0.035), within a 95% condence interval
of 0.21 to 0.54, positively inuences satisfaction, as does
the perceived cost-benet of blended courses (B = 0.42,
p = 0.013), within a 95% condence interval of 0.08 to
0.60.
e overall model, with an adjusted R² of 0.31, signies
that 31% of the variance in satisfaction scores is explained
collectively by the included variables. e statistically sig-
nicant F-value of 21.21 (p < 0.001) highlights the over-
all signicance of the model, reinforcing its predictive
power.
Discussion
Blended learning has become a dynamic educational
approach, combining traditional face-to-face instruc-
tion with online elements, creating a exible and inter-
active environment for students [12]. is study assessed
nursing students’ satisfaction with blended learning in
academic institutions. e assessment covers various
aspects, from students’ perceptions of course interactions
and management to their understanding of environmen-
tal facilitators. Additionally, we use a robust multiple lin-
ear regression model to analyze the complex network of
factors aecting satisfaction. e ultimate goal is to oer
practical insights for educators, institutions, and policy-
makers looking to enhance blended learning experiences
for nursing students, promoting a more personalized and
responsive approach to modern pedagogy.
In assessing nursing students’ satisfaction with blended
learning, the ndings presented in the current study oer
insights into various dimensions of their blended satis-
faction experience. Notably, students uniformly express
a positive attitude toward interaction during the courses,
suggesting a consensus on the signicance of engaging
interactions. is aligns with existing literature highlight-
ing the crucial role of interaction in fostering a sense of
collaborative learning in online and blended environ-
ments [29, 30].
Conversely, course management and performance in
the courses elicit lower satisfaction scores, coupled with
higher variability among responses. is suggests diverse
opinions and areas for potential enhancement. e rea-
sons behind this variation may be explained by the fact
that students came from dierent nursing programs,
such as bachelor’s and technical nursing programs, each
with distinct experiences. ese dierences likely result
in varying levels of satisfaction with course management
and performance in blended learning environments. is
aligns with ndings from studies comparing student sat-
isfaction across dierent programs, which emphasize
how program structure impacts the blended learning
experience [31, 32].
Moreover, the literature acknowledges the challenges
associated with eective course management and main-
taining performance standards in online settings [33, 34].
ese studies point to the need for targeted improve-
ments in these domains to enhance overall satisfaction.
e moderate overall satisfaction level in the current
study reects a balanced sentiment among nursing stu-
dents. is nding is consistent with research suggesting
that well-implemented blended learning can provide a
satisfactory educational experience [29, 35].
Concerning nursing students’ perceptions of environ-
mental facilitators to blended learning, the current study
presents a substantial agreement among students con-
cerning encouragements to enroll in blended learning
Table 4 Summary of multiple linear regression model for
satisfaction score using the standard model
Variables B SE P95% CI
Age -0.04 0.208 0.048 -0.06 to
-0.03
Gender 0.25 0.131 0.037 0.34 to 0.86
Income -0.88 0.229 0.033 -0.98 to
-0.26
Working 0.62 0.190 0.040 0.11 to 0.74
Availability of suitable inter-
net source
0.45 0.291 0.029 0.53 to 0.80
Academic year 0.47 0.210 0.028 0.18 to 0.61
Computer literacy 0.90 0.385 0.015 0.89 to 1.41
Preferable method of learning 1.11 0.445 0.006 1.02 to1. 44
Encouragement to join
blended learning courses
0.46 0.320 0.010 0.05 to 0.65
Time and events of blended
learning
0.52 0.119 0.035 0.21 to
0. 54
Cost-benet of blended
learning
0.42 0.218 0.013 0.08 to 0.60
Adjusted R2 = 0.31
F = 21.21
P < 0.001
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 8 of 10
Hassan et al. BMC Nursing (2024) 23:766
courses highlights the positive impact of institutional
support structures. is aligns with a body of studies
emphasizing the important role of encouragement and
institutional backing in fostering student engagement in
online and blended courses [36, 37]. e robust support
for enrollment suggests that proactive measures to pro-
mote blended learning within academic institutions can
signicantly contribute to students’ favorable perceptions
and satisfaction [36, 37].
Moreover, the acknowledgment of the exibility in time
and events of blended learning courses, although with
some variability in opinions, echoes ndings in exist-
ing literature recognizing the diverse needs of students
regarding time management in online and blended learn-
ing environments [38, 39]. is highlights the importance
of designing exible course structures that accommodate
varying schedules and preferences, catering to the indi-
vidualized nature of student experiences [39]. While stu-
dents express moderate agreement with concerns such
as the potential of dropout in blended learning and the
cost-benet of blended learning courses, the overall low
variability in responses suggests a generally consistent
viewpoint among students in the current study. is
aligns with studies investigating barriers to online edu-
cation, emphasizing the need for institutions to address
concerns related to dropout potential and cost-eective-
ness to enhance the overall learning experience [40, 41].
e multiple linear regression model in the current
study claries the intricate web of factors inuencing
nursing students’ satisfaction with blended learning.
Particularly, the modest negative association between
age and satisfaction scores suggests that as students’ age
increases, satisfaction marginally decreases. is nd-
ing resonates with some existing literature highlighting
potential challenges older students may face in adapting
to technology-mediated learning [42]. Tailored support
and interventions may be benecial to enhance the sat-
isfaction of older nursing students in blended learning
environments [43].
On a gender-related note, the higher satisfaction
expressed by female students aligns with a study sug-
gesting that female students tend to engage more actively
in online discussions and collaborative activities [44].
Understanding these gender dynamics could inform
instructional strategies that cater to diverse learning pref-
erences and participation levels [45]. Additionally, the
signicant negative impact of lower income on satisfac-
tion highlights the socioeconomic factors inuencing
students’ experiences in blended learning. is is consis-
tent with broader literature indicating that nancial con-
straints can hinder access to resources and technology
necessary for online education [46, 47]. Mitigating these
disparities through targeted support mechanisms could
contribute to a more equitable educational experience
[48].
In the current study, the positive association between
employment and satisfaction may be attributed to the
exibility of time between work and study that is oered
by blended learning and limited in face-to-face learning
[49]. is nding aligns with studies emphasizing the
potential benets of balancing work and study in enhanc-
ing satisfaction in online learning [13, 49]. Access to a
suitable internet source emerges as an important deter-
minant, positively inuencing satisfaction. is aligns
with a wealth of studies stressing the importance of digi-
tal infrastructure in online and blended learning environ-
ments [50, 51].
e positive links between higher academic years,
computer literacy, and increased satisfaction scores
highlight the role of positive adaptation and technologi-
cal prociency in fostering contentment. is supports
existing studies emphasizing the importance of digital lit-
eracy in online and blended learning [52, 53]. However,
it is important to note that the factors associated with
blended learning satisfaction, such as computer literacy
and access to technology, are only part of the equation.
ere may be additional unexplored variables, such as
institutional infrastructure, technical support availability,
and faculty preparedness, that contribute to student sat-
isfaction. Addressing these factors in future research will
be critical to fully understanding the drivers of satisfac-
tion [13, 30].
Future research directions
To address the variability in satisfaction scores, further
studies should explore additional variables such as faculty
development, technical support systems, and infrastruc-
ture investments. Comparative studies across dierent
educational settings and longitudinal designs could pro-
vide a more nuanced understanding of how satisfaction
evolves over time, and what specic interventions may
improve satisfaction in dierent contexts.
Implications of ndings
e ndings of this study emphasize the importance of
considering the sociodemographic and learning charac-
teristics of nursing students, in addition to the environ-
mental facilitators and barriers, in fostering satisfaction
with blended learning. Institutions aiming to enhance
the experience of nursing students in blended learn-
ing environments should invest in robust faculty train-
ing programs, expand digital infrastructure, and provide
socioeconomic support to students in need. Implement-
ing these measures could signicantly improve the per-
sonalized and responsive learning environment essential
for modern nursing education.
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 9 of 10
Hassan et al. BMC Nursing (2024) 23:766
Strengths and limitations
Strengths of this study include its sample size of 1266
nursing students from diverse educational institutions
ensures robustness and representativeness across dif-
ferent academic levels and cohorts. Rigorous statistical
methods, including a power analysis and multivariate
regression model, enhance the validity of the ndings.
e employment of established measurement tools, such
as the Blended Learning Satisfaction Scale and the Envi-
ronmental Facilitators and Barriers to Student Persis-
tence in Online Courses scale, contributes to the study’s
reliability.
is study has several limitations that should be
acknowledged. e use of self-reported data may intro-
duce response bias, as participants might provide inac-
curate or biased answers. To mitigate this, surveys were
anonymized to encourage honest reporting; however,
response bias remains a potential concern. Additionally,
the study employed a convenience sampling method,
focusing solely on nursing students from Alexandria
University, which may limit the generalizability of the
ndings to other populations of nursing students. e
cross-sectional design of the study also prevents the
establishment of causality between the determinants and
satisfaction with blended learning, indicating a need for
longitudinal studies to investigate the temporal relation-
ships between these variables.
Conclusion
Factors such as age, gender, income, employment sta-
tus, access to suitable internet sources, academic year,
computer literacy, preference for blended learning, and
encouragement to enroll signicantly inuence nursing
students’ satisfaction levels with blended learning. Nota-
bly, perceptions of exibility in time and events, as well as
the perceived cost-benet of blended courses, play cru-
cial roles in shaping satisfaction. ese ndings empha-
size the importance of addressing diverse student needs
and enhancing support structures to optimize satisfac-
tion and eectiveness in blended learning environments.
Supplementary Information
The online version contains supplementary material available at https://doi.
org/10.1186/s12912-024-02393-y.
Supplementary Material 1
Acknowledgements
We thank all nursing students who participated in the study.
Author contributions
Eman Arafa Hassan: Conceptualization, Methodology, Validation, Investigation,
Writing- Original draft preparation, Supervision. Ahlam Mahmoud Mohamed:
Conceptualization, Methodology, Validation, Supervision.Fatma Abdou Eltaib:
Conceptualization, Methodology, Investigation, Writing- Reviewing and
Editing. Asmaa Mohammed Saad Khaled: Conceptualization, visualization,
Methodology, Supervision, Writing- Reviewing and Editing.
Funding
Open access funding provided by Science, Technology & Innovation Funding
Authority (STDF), Egypt.
Open access funding provided by The Science, Technology & Innovation
Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank
(EKB).
Data availability
No datasets were generated or analysed during the current study.
Declarations
Ethics approval and consent to participate
Approval from the Research Ethics Committee of the Faculty of Nursing,
Alexandria University, was obtained (Institutional Review Board: IRB00013620).
After explaining the study’s purpose, all participants were provided with
informed written online consent for participation by clicking agree to
participate button at the beginning of the electronic questionnaire. The
researchers emphasized participants’ rights to voluntarily participate, refuse,
or withdraw from the study at the beginning of the online questionnaire.
The online survey was conducted anonymously to ensure the condentiality
of data. This work has been carried out in accordance with The Code of
Ethics of the World Medical Association (Declaration of Helsinki) on Human
participants.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Received: 27 March 2024 / Accepted: 27 September 2024
References
1. Castro R. Blended learning in higher education: Trends and capabilities. Educ
Inf Technol. 2019;24:2523–46.
2. Antonelli D, et al. A virtual reality laboratory for blended learning education:
design, implementation and evaluation. Educ Sci. 2023;13(5):528.
3. Sarbunan T. Handbook of Educational Reform Through Blended Learning:
Unveiling the Transformative Power of Blended Learning to Revolutionize
Education. 418 (2024) https://doi.org/10.17613/6V1T-YN16
4. Lynch M, E-Learning During. A Global Pandemic. Asian J Distance Educ.
2020;15:189–95.
5. Cheng X, et al. Chinese anatomy educators’ perceptions of blended learning
in anatomy education: a national survey in the post-COVID-19 era. Anat Sci
Educ. 2024;17:77–87.
6. Niu Y, et al. Eects of blended learning on undergraduate nursing students’
knowledge, skills, critical thinking ability and mental health: a systematic
review and meta-analysis. Nurse Educ Pract. 2023;72:103786
7. Buhl-Wiggers J, Kjærgaard A, Munk K. A scoping review of experimental evi-
dence on face-to-face components of blended learning in higher education.
Stud High Educ. 2023;48:151–73.
8. Ameloot E, Rotsaert T, Ameloot T, Rienties B, Schellens T. Supporting students’
basic psychological needs and satisfaction in a blended learning environ-
ment through learning analytics. Comput Educ. 2024;209:104949.
9. Wut T, ming Shun-mun, Wong H, Ka-man Sum C. Ah-heung Chan, E. does
institution support matter? Blended learning approach in the higher
education sector. Educ Inf Technol. 2024;1–13. https://doi.org/10.1007/
S10639-024-12478-5/METRICS.
10. Leidl DM, Ritchie L, Moslemi N. Blended learning in undergraduate nursing
education – A scoping review. Nurse Educ Today. 2020;86:104318.
11. Haftador AM, Tehranineshat B, Keshtkaran Z, Mohebbi Z. A study of the
eects of blended learning on university students’ critical thinking: a system-
atic review. J Educ Health Promot. 2023;12:95.
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 10 of 10
Hassan et al. BMC Nursing (2024) 23:766
12. Janes G, Ekpenyong MS, Mbeah-Bankas H, Serrant L. An international explora-
tion of blended learning use in pre-registration nursing and midwifery
education. Nurse Educ Pract. 2023;66:103514.
13. Venkatesh S, et al. Factors inuencing medical students’ experiences
and satisfaction with blended Integrated E-Learning. Med Princ Pract.
2020;29:396–402.
14. Li X, Zhu W. System quality, information quality, satisfaction and acceptance
of online learning platform among college students in the context of online
learning and blended learning. Front Psychol. 2022;13:1054691.
15. Cheng X, Mo W, Duan Y. Factors contributing to learning satisfaction with
blended learning teaching mode among higher education students in China.
Front Psychol. 2023;14:1193675.
16. Hassoulas A, de Almeida A, West H, Abdelrazek M, Coey MJ. Devel-
oping a personalised, evidence-based and inclusive learning (PEBIL)
model of blended learning: a cross-sectional survey. Educ Inf Technol.
2023;28:14187–204.
17. Bhagat KK, Cheng CH, Koneru I, Fook FS, Chang CY. Students’ blended Learn-
ing Course Experience Scale (BLCES): development and validation. Interact
Learn Environ. 2023;31:3971–81.
18. Prifti R. Self–ecacy and student satisfaction in the context of blended learn-
ing courses. Open Learn J Open Distance e-Learning. 2022;37:111–25.
19. Manzanares MCS, Llamazares MDCE, González ÁA. Eectiveness of Blended
Learning in Nursing Education. Int. J. Environ. Res. Public Heal. 2020, Vol. 17,
Page 1589 17, 1589 (2020).
20. Wong WH, Chapman E. Student satisfaction and interaction in higher educa-
tion. High Educ. 2023;85:957–78.
21. Olmos-Gómez MDC, Luque-Suárez M, Ferrara C, Cuevas-Rincón JM. Quality
in higher education and satisfaction among professors and students. Eur J
Investig Heal Psychol Educ. 2021;11:219–29.
22. Cant R, Gazula S, Ryan C. Predictors of nursing student satisfaction as a key
quality indicator of tertiary students’ education experience: an integrative
review. Nurse Educ Today. 2023;126:105806.
23. Tayyib N, et al. MALE AND FEMALE NURSING STUDENTS’ SATISFACTION WITH
BLENDED E-LEARNING FOLLOWING THE COVID-19 PANDEMIC: A PRINCIPAL
COMPONENT ANALYSIS. Adv Appl Stat. 2023;88:25–47.
24. Wang L, Liao B, Yang H, Yang C. Exploring nursing undergraduates’ experi-
ences with a redesigned blended learning course: a descriptive qualitative
study. Nurs Open. 2023;10:2689–95.
25. Ruiz-Grao MC, et al. Nursing student satisfaction with the Teaching Method-
ology followed during the COVID-19 pandemic. Healthc. 2022;10:597.
26. Ahn J-H, Son J-H, Kim S-Y, Author C. Predictors of online learning satis-
faction in nursing students after COVID-19 pandemic. J Digit Converg.
2021;19:451–61.
27. Zeqiri J, Kareva V, Alija S. Blended learning and student satisfaction: the
moderating eect of Student Performance. Bus Syst Res. 2021;12:79–94.
28. Heilporn G, Lakhal S. Environmental facilitators and barriers to Student Per-
sistence in Online courses: reliability and validity of New scales. J Contin High
Educ. 2022;70:1–20.
29. Tayyib N et al. A principal component analysis of nursing students’ satisfac-
tion with blended E-learning following the Covid-19 pandemic. https://doi.
org/10.26502/whd.2644-288400107
30. Yousaf HQ, Rehman S, Ahmed M, Munawar S. Investigating students’ satisfac-
tion in online learning: the role of students’ interaction and engagement in
universities. Interact Learn Environ. 2023. https://doi.org/10.1080/10494820.2
022.2061009.
31. Dziuban C, Graham CR, Moskal PD, Norberg A, Sicilia N. Blended learning:
the new normal and emerging technologies. Int J Educ Technol High Educ.
2018;15:1–16.
32. Kintu MJ, Zhu C, Kagambe E. Blended learning eectiveness: the relationship
between student characteristics, design features and outcomes. Int J Educ
Technol High Educ. 2017;14:1–20.
33. Moon MY. Eects of online class satisfaction, Professor-Student Interaction,
and learning motivation on Self-Directed Learning ability of nursing students
applying the blended learning. J Reatt Ther Dev Divers. 2023;6:19–29.
34. Nia HS, et al. Student satisfaction and academic ecacy during online learn-
ing with the mediating eect of student engagement: a multi-country study.
PLoS ONE. 2023;18:e0285315.
35. Hidayati RN, Wahyuningsih BD, Hariyono R, Musadek A. Learning outcomes in
blended learning implementation. J Sci Res Educ Technol. 2023;2:1095–102.
36. Ariningpraja RT, Wisnasari S. Nursing students’ learning support, outcome,
and satisfaction towards Online Learning. J Nurs Sci Updat. 2023;11:18–27.
37. Lee H, Yoo HJ. Expectations and concerns about transitioning to face-to-face
learning among Korean nursing students: a mixed methods study. PLoS ONE.
2024;19:e0296914.
38. Eija N, et al. The experiences of health sciences students with hybrid learn-
ing in health sciences education—A qualitative study. Nurse Educ Today.
2024;132:106017.
39. Sukadarma IGNK, Suastra IW, Pujawan IGN, Nitiasih PK, Permana IG. Y.
nurse students’ satisfaction towards blended learning program. Bali Med J.
2022;11:885–91.
40. Jowsey T, Foster G, Cooper-Ioelu P, Jacobs S. Blended learning via distance
in pre-registration nursing education: a scoping review. Nurse Educ Pract.
2020;44:102775.
41. Elgohary M, et al. Blended learning for accredited life support courses – A
systematic review. Resusc Plus. 2022;10:100240.
42. Rasheed RA, Kamsin A, Abdullah NA. Challenges in the online component of
blended learning: a systematic review. Comput Educ. 2020;144:103701.
43. Heilporn G, Lakhal S, Bélisle M. An examination of teachers’ strategies to foster
student engagement in blended learning in higher education. Int J Educ
Technol High Educ. 2021;18:1–25.
44. Yu Z. The eects of gender, educational level, and personality on online
learning outcomes during the COVID-19 pandemic. Int J Educ Technol High
Educ. 2021;18:1–17.
45. Aguillon SM, et al. Gender dierences in student participation in an active-
learning classroom. CBE Life Sci Educ. 19(2):ar12.
46. Kwesi E, Henaku EA, Mawuko D, Ayite K, Ansah EA. Online Learning in Higher
Education during COVID-19 pandemic: a case of Ghana. J Educ Technol
Online Learn. 2020;3:183–210.
47. Azhari B, Fajri I. Distance learning during the COVID-19 pandemic: School
closure in Indonesia. Int J Math Educ Sci Technol. 2022;53:1934–54.
48. Fung CY, Su SI, Perry EJ, Garcia MB. Development of a socioeconomic Inclu-
sive Assessment Framework for Online Learning in Higher Education. 23–46
(2022) https://doi.org/10.4018/978-1-6684-4364-4.CH002.
49. Müller C, Mildenberger T. Facilitating exible learning by replacing classroom
time with an online learning environment: a systematic review of blended
learning in higher education. Educ Res Rev. 2021;34:100394.
50. Kumar A, et al. Blended Learning Tools and practices: a comprehensive analy-
sis. IEEE Access. 2021;9:85151–97.
51. Yaw Koi-Akro G, Owusu-Oware E, Tanye H. Challenges of distance, blended,
and online learning: a Literature-based approach. Int J Integr Technol Educ.
2020;9:27–39.
52. Anthonysamy L, Koo AC, Hew SH. Self-regulated learning strategies in higher
education: fostering digital literacy for sustainable lifelong learning. Educ Inf
Technol. 2020;25:2393–414.
53. Martzoukou K. Academic libraries in COVID-19: a renewed mission for digital
literacy. Libr Manag. 2020;42:266–76.
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