Mediating effect of e-learning quality on learning outcomes through student satisfaction in nursing education

There has been a steady increase in the prevalence of online programs offered in higher institutions nationwide. In 2020, internet access among the Malaysian population has accelerated to 91.7%.¹ Of these, 98.6% of users were using mobile phones and 77.6% were using computers for online access. These statistics indicate a tremendous increase in utilization and access to the internet by the younger population in Malaysia. Similarly, the demand for online education such as e-learning program in nursing education is increasing as a result of Malaysia’s Ministry of Higher Education (MOHE) initiatives. Many nursing professionals have been motivated by the MOHE’s 2020 strategy to advance their education from a diploma to a bachelor’s degree. Various studies support the advantages of e-learning programs in enhancing nurses’ knowledge, skill, and caring behavior toward quality patient care.^2–4 Pursuing a higher nursing education through e-learning programs is therefore important for nurses to promote their professional development and core values of caring.

The MOHE reported that only 33% (n = 119,873) of students in the undergraduate programs (online and conventional) had completed their studies in Malaysia’s educational institutions.⁵ The local higher education institutions face a considerably greater challenge in keeping the students engaged and completing online learning successfully than they do in conventional learning. Similarly, the attrition rate and delayed graduation for online undergraduate programs remain high in the undergraduate programs and nursing bachelor programs in many countries.^6,7 Only 2% of Malaysia’s nurses possessed a bachelor’s degree, according to reports.⁸ The data are worrying as the percentage of bachelor’s degree holders is much lower than the targeted number set by the MOHE.

E-learning education allows flexibility for adult learners to pursue higher degrees while working full time. E-learning is defined as electronic learning, an education course conducted using information and communication technologies for teaching and learning.⁹ E-learning is also known as online learning, blended learning, hybrid learning, distance-learning, or internet-based learning.¹⁰ In this study, the term e-learning is used to describe 70% of course content facilitated using online-mediated learning and 30% face-to-face classroom learning. Adult learners can benefit from an e-learning platform that leverages web-based technology as an engagement strategy for teaching and learning. It is an integration of teaching methods using both the synchronous (online) and asynchronous (offline) modes for flexible learning in meeting individuals’ learning styles and needs. Varying the flexibility of online learning activities with a blend of synchronous and asynchronous learning modes could be an effective strategy to promote quality learning experiences for students. Such instructional design is not only beneficial in terms of enhancing learning outcomes in e-learning education but also accommodates students’ diverse learning styles.

According to the literature review, the effects of e-learning in nursing are inconsistent. However, there is a great possibility for nursing students to gain lifelong learning through online education, and the positive effect of e-learning remains an important topic for future research in higher education. A systematic review by Rouleau et al.³ revealed several negative factors to e-learning among nurses such as lack of computer and internet efficacy, technical difficulties, preference for face-to-face learning approach, and challenges in time, access, and navigation to e-learning management systems. Out of the 22 reviews, 13 reviews (59%) of past studies reported improved knowledge using e-learning; but 7 reviews (32%) of studies found no effect of e-learning intervention on nurses’ knowledge. Concerning nursing skill performance, 9 reviews (41%) of past studies documented a positive outcome among nurses who participated in e-learning education. The findings are in line with Latif who reported that academic achievement has improved using online learning among student nurses in Malaysia.¹¹ In contrast, Hjorth-Johansen et al.¹² revealed that there was no significant difference in academic achievement between classroom learning and e-learning nursing.

Many past works of literature adopting the DeLone and McLean Information Systems (D&M IS) success model reported that the success of e-learning system is influenced by student satisfaction. Marjanovic et al.¹³ reported a strong significant impact of system quality on student satisfaction; as well as between student satisfaction and e-learning outcome. A study by Cidral et al.¹⁴ revealed that system quality significantly impacted student satisfaction and individual impact. Yet, Yakubu and Dasuki¹⁵ indicated no significant impact of system quality on student satisfaction. It is possible that students from developed countries are well supported with advanced technologies and system interfaces. Whereby, the usability, speed, effectiveness as well as design of the courses are readily available to meet the demands of both teachers and students. Nevertheless, user satisfaction in e-learning environment could be influenced by many contributing factors that need further exploration in various contexts.

In a study, Kunjukunju et al.¹⁶ revealed a positive correlation between information quality and e-learning quality among Malaysian nurses. The study supports a well-designed e-learning Moodle in ensuring positive student experiences and satisfaction in institutions of higher education. The quality of the e-learning information was the most important attribute of an online learning study related to course design and satisfaction.¹⁷ However, Yakubu and Dasuki¹⁵ revealed no statistically significant effect of information quality on student satisfaction. Their findings imply that student satisfaction is not influenced by the quality of the information provided in the e-learning course.

On the other hand, service quality is reported as a significant predictor of satisfaction when nurses found the information system is easy to be used.¹⁸ This finding is supported by Kunjukunju et al.¹⁶ that service quality such as empathy, reliability, assurance, and responsiveness of faculty are associated positively with student satisfaction in e-learning nursing program. The availability, responsiveness, and timely services from information technology personnel are equally important in gaining student confidence in using the e-learning system and thus increasing their satisfaction. In contrast to earlier findings, however, no statistically significant effect of service quality on student satisfaction and the individual impact was found.¹⁴

Another study by Goh et al.¹⁹ on the relationship between learning experience, student satisfaction, and learning outcomes in e-learning found that course design and interaction with faculty and peers are significant predictors of student satisfaction and learning outcomes. Through regression analysis, the study indicated that peer interaction is the most important factor that affects the satisfaction and learning outcomes of students. The study implies that an online virtual environment does not limit interaction, but it allows students and faculty to share information and exchange ideas. These findings have important implications for developing e-learning programs in a way to promote active learning and guide the students for better knowledge acquisition, satisfaction, and learning outcomes.

Despite the inconsistencies of past research findings, many works of literature support the positive impact of student satisfaction on learning outcomes in an e-learning system. Cidral et al.¹⁴ indicate a strong positive effect of user satisfaction on individual impact. In the study, the effect between satisfaction and e-learning outcome is shown to be the highest among all other factors in the information systems success dimensions. Another study on a public university in Malaysia reported a significant association between student satisfaction and academic achievement in undergraduate students.²⁰ These findings are also supported by Shahzad et al.²¹ that student satisfaction has a strong impact on e-learning success among Malaysian university students. The findings of the past studies suggest that student satisfaction can serve as a valid determinant for e-learning outcomes when students’ expectations are met in an online learning environment. Putting together, student satisfaction has been identified as a major contributing factor to the relationship between system quality, information quality, service quality, and learning outcome. Many past studies have hypothesized that linking e-learning quality to student satisfaction is the most effective way to explain students’ learning outcomes in e-learning education.

Demographic data of the participants consist of age, gender, marital status, working experience, working position, current clinical area, past experience in online learning, and current grade point average (CGPA) in Bachelor of Nursing Science (Honors) Post-Registration undergraduate programs. Findings show that majority of the respondents are females (93.4%, n = 225), holding a position as staff nurse (83%, n = 200), assigned at the non-critical care areas (56.8%, n = 137), and experienced in online learning before studies (68.5%, n = 165). More than half of them were single (59.8%, n = 144); within the middle age group (M = 32 years), have fairly long working experience (M = 9 years), and have moderate CGPA scores (M = 3.44) at the point of data collection.

We assessed the indicator reliability, internal consistency reliability, discriminant validity, and convergent validity using Smart PLS 3 analytical software. As illustrated in Table 1, those indicators that have met the loadings of at least 0.70 are retained for further analysis. With that, indicators from the system quality (SQ2, SQ6), service quality (SEQ5), and information quality (IQ3, IQ6) were removed in this stage. In the next analysis, the results show that the indicators for Cronbach’s α were between 0.723 and 0.881, for rho_A was between 0.725 and 0.882, for composite reliability was between 0.878 and 0.941, and for AVE was >0. These findings suggest that all remaining indicators for system quality, information quality, service quality, student satisfaction, and learning outcomes meet internal reliability and convergent validity requirement for the study model. Using the Heterotrait-Monotrait (HTMT) ratio of correlations, discriminant validity was evaluated if a construct is truly distinct from other constructs in a model. The results of the analysis for e-learning quality, student satisfaction, and learning outcomes are between HTMT of 0.699 and 0.764, confirming discriminant validity among the three constructs. Therefore, the reflective model of this study has met the standard requirement of internal consistency, convergent validity, and discriminant validity.

In the next evaluation, structural model evaluation, collinearity assessment (variance inflation factor [VIF]), significance and relevance of path coefficients (Bootstrapping), in-sample predictive power assessment (R²), and out-of-sample predictive power assessment were tested. The VIF values for the constructs e-learning quality, student satisfaction, and learning outcomes were examined for lateral multicollinearity between indicators. A VIF value ranging between 1.0 and 2.4 indicates no correlation problem in the study model.

The direct hypotheses (H1, H2, H3) and indirect hypothesis (H4) were tested using T-statistics with bootstrapping of 10,000 sub-samples for their significant levels. As depicted in Table 2, all of the direct hypotheses are statistically significant with t-value of ≥1.96, P-values of <0.05, and Boot Confidence Interval Bias-Corrected without zero values. Significantly, the predictors of e-learning quality (β = 0.327, P < 0.001) and student satisfaction (β = 0.487, P < 0.001) are positively related to learning outcomes, which explained 58.8% of variances in learning outcome (P < 0.05). The effect of e-learning quality (β = 0.764, P < 0.001) also indicated a positive relationship with student satisfaction with 58.3% of variance explained. As a result, H1, H2, and H3 are supported. To address H4, we evaluated the findings of H1 and H2. The indirect effects (β = 0.764 and β = 0.487) are significant at t-values of 27. 125 and 6. 089 at 95%. Moreover, the indirect effects at 95% Boot Confidence Interval Bias-Corrected level for H1 (LL = 0.482, UL = 0.685) and H2 (LL = 0.224, UL = 0.591) do not contain a zero-value indicating a significant mediation effect of student satisfaction on the relationship between e-learning quality and learning outcomes. Hence, H4 is supported for the study.

We further analyze the mediation effect of the model. The results show that indirect effect (0.764 * 0.487 = 0.372) and direct effect (0.327) are significant (P < 0.05) and the total effect (0.327 + 0.372 = 0.699) is pointing positively towards the same direction. These represent a complementary partial mediation for the study model which implies that 37.2% of e-learning quality is mediated through student satisfaction. The model of the study suggests that a 69.9% total effect is predicted for e-learning quality on learning outcome through the mediator of student satisfaction among nursing students. As a result, the overall impact of the e-learning success is greater when the mediation effect of student satisfaction is added to the relationship between e-learning quality (system quality, information quality, and service quality) and learning outcomes.

A final model of the study based on PLS-SEM is demonstrated in Figure 3. Referring to Cohen’s recommendation for social science research, the R² value of 0.583 for student satisfaction and 0.588 for learning outcomes represent a large effect in producing a substantial model for in-sample for the nursing population of the study.²⁴ In summary, these findings suggest that the relationships among system quality, information quality, service quality, and student satisfaction are accurate predictors of the model. As supported in past studies, students’ satisfaction has a strong influence on academic achievement in online courses.^20,25 The current study concurs that if students have a higher level of perceived success in terms of quality support in e-learning systems/information/service, and with a positive satisfaction level, they will achieve a greater outcome in online programs.

Figure 3.

For a rigorous analysis, an out-of-sample predictive power assessment was conducted to test the prediction error in the model. Findings show that the majority of the values of root mean squared error (RMSE) and mean absolute error (MAE) in the predictive error are higher when compared with the values in the linear regression model (LM). This indicated that the model has lacked predictive power for out-of-sample in the study population.²⁶ Future studies may need to re-examine the model in different disciplines.

The findings of the existing study are consistent with various studies which support the effect of system quality¹⁴, information quality²⁷, and service quality¹⁶ on learning outcomes among undergraduates in e-learning education. Quality of the e-learning system features such as ease of use and stability of the system influences individual impact in learning online. In other words, effectiveness in e-learning system support to improve students’ experience towards e-learning education, and this further impacts students’ perception of the benefits of using the systems and leads to a better learning outcome. Thus, support in e-learning system design and software, grants, and facilities for recording studios are equally crucial to enrich lecturers’ and students’ experience in the e-learning context. Educational institutions should continue to provide a series of e-learning training workshops to improve faculty competence in creating interactive teaching and learning activities.²⁰ With this, support from information technology and information communication technology personnel is vital for sustaining a successful implementation of e-learning programs in higher educational institutions. Integration of instructor-led instruction with technology-driven strategies is believed to benefit both students and lecturers and has a positive impact on students’ academic success.

One possible reason for the significant result is that the sampled study demonstrated no problems with the information delivered through Moodle. When learning materials including course content, reading resources, and online activities are well organized, useful, and presented clearly, students may learn more effectively with the information provided. Providing learning resources that are appropriate to the students, and their levels can also help them to understand the values and meaning of the content, thus enabling them to connect the concepts to real-life practices. These positive contributing factors motivate students to access online content frequently and independently. As a result, the availability of the information and content enhances students’ ability to maximize their use of e-learning resources in an online learning education environment.²⁸ Being innovative, responsible, and accountable to learn new technology is increasingly necessary among faculty in higher educational institutions. Therefore, nursing faculty members involved in e-learning programs play a major role in developing course content, reading materials, learning information, online activities, and assessments.

Although faculty members strive to encourage collaborative interaction among peers, students prefer teacher–student interaction that will benefit their learning. Many students agreed that quality of service in terms of teacher support has a positive influence on individual benefits in achieving academic success. A supportive faculty motivates students to be more independent in planning their learning process, evaluate their learning, identify effective ways to improve, and find useful resources for new learning. It is crucial for faculty to be aware of their online presence in supporting the students during their learning process. Another possible reason is that the demographic background of the students who participated in this study mainly comprises adult learners with work/family commitments. Students may have limited time to participate actively in peer discussions and group activities. Peer learning is, however, an important aspect for nursing students to foster their personal and professional development. Collaborative social learning in peer interactions encourages critical reflection and evaluation of knowledge.²⁹ Motivating and encouraging students to participate actively in online activities creates a positive climate for teamwork, the development of reflective thinking abilities, and communication skills.

The findings of this study show a statistically significant mediation effect on student satisfaction for the relationship between e-learning quality and learning outcomes in e-learning nursing undergraduates. These findings are consistent with Selvaraj³⁰, Shahzad et al.,²¹ and Chang and Maarof³¹ who validated the direct or indirect effect of student satisfaction on the relationship between system quality and e-learning outcome. In their studies, e-learning systems show a positive effect on the depth of learning of students, student productivity, and learning pace when students’ satisfaction increases. User satisfaction such as students’ experience towards their learning environments, course delivery, faculty support, facilities, and resources are the focus of all educational institutions. Likewise, student satisfaction in e-learning programs is paramount for universities to identify the known and unknown factors that could impact the benefits of the students in completing their studies. Other possibilities may be due to students’ positive experiences in the universities that determine their levels of satisfaction. The positive e-learning experiences may positively affect students’ belief in which the well-structured course helps them to achieve their learning outcomes in e-learning success.

The findings of this study have significant implications for learners, educators, and stakeholders in the Malaysian education system, particularly in the nursing field. This study offers insights into what pedagogical and e-learning success strategies are more likely to positively affect student satisfaction and learning outcomes. It will also provide educators with important strategies to ensure the overall success of e-learning education in the nursing context. This study suggests that the quality of e-learning (system quality, information quality, and service quality) is critical in ensuring students’ satisfaction with the learning outcomes in e-learning program. The study reveals that based on the variance-based structural equation modelling (VB-SEM) analysis, factors such as e-learning quality and student satisfaction are significant predictors of e-learning outcomes.

The findings of this study will also be useful to policymakers, administrators, and e-learning designers for program development. The universities need to maintain the quality features of the e-learning systems: easy-to-use, user-friendly, stable, secure, fast, and interactive. This is to ensure the system quality is meeting the needs of students in online teaching and learning activities, wherever they may be. Also, there must be appropriate pedagogical methods and technologies to engage students in both the physical and virtual platforms. In addition to face-to-face classroom teaching, the high-quality system in e-learning would facilitate the effective delivery of quality information to learners. Useful, relevant, and recent information, which is well-organized and effectively presented to students, may have a long-term effect on their retention rate. Educators may create interactive teaching materials using e-learning authoring tools and software that could engage active learning among students. As a result, the number of students completing their studies could increase and the attrition rate may subsequently be reduced.

In this study, the model indicates that student satisfaction is a significant mediator. Thus, the institution can take into consideration of the mediation effect in improving student satisfaction and increasing the quality of the e-learning systems for students to have a better chance to achieve their academic success. Stakeholders responsible for designing, implementing, and evaluating the e-learning courses can adopt the proposed model in this study to heighten the success of those important aspects in the e-learning systems. Institutions could also target the aspects they need to focus on in enhancing successful e-learning system adoption in the nursing education.

There are a few limitations to this study. First, the sample was drawn from two private universities. As more nursing institutions adopt e-learning or online learning modes for undergraduate nursing programs, the population may not be generalized to all states in the future. Second, many confounding variables beyond the researcher’s control could have influenced the students’ perceptions of the benefits of using the e-learning system for their studies. These uncontrolled variables may include the participants’ demographic background, the quality of the e-learning systems, the quality of educators/facilitators, the quality of the university resources and its student support system from each study site.

The research framework was found to be a reliable and significant model in this study. Findings of the study reveal that e-learning quality and student satisfaction are accurate predictors of learning outcomes, and student satisfaction is a significant mediator in the model. Most of the findings are consistent with past literature in which system quality/service quality/information quality, student satisfaction, and learning outcomes are positively correlated significantly among nursing undergraduates in e-learning programs. This study enables educators and support staff to leverage the significance of e-learning quality success factors in higher education, particularly, in e-learning nursing context in Malaysia. Future studies are recommended to further explore potential predictors that will further enhance the quality of e-learning nursing education.