Search results

The effect of e-learning success relies on the learning management system and its effectiveness provided to the learners. As a result, higher education institutions (HEIs) are expanding using various e-learning platforms and focusing on system and information quality. This study adopts the ISS (information system success) model to assess students' perception of e-learning system success (e-LSS).

A quantitative research approach was used to analyse 151 students' perceptions collected from HEIs in Oman. The survey instrument was built on prior research related to DeLone and McLean’s ISS model, and expert opinion was involved for validation. The snowball sampling method was used to collect the data, and participants' anonymity and confidentiality were maintained as part of the ethical process. The reliability of data was tested using Cronbach's alpha analysis. A statistical tool like correlation was used to examine the relationship between the study variables (system quality, information quality, user satisfaction and e-LSS).

This study’s results revealed that students positively perceived system usage, and users' satisfaction with e-learning systems (e-LSs) was high. Moreover, the correlation results indicated that the system and information quality aspects of e-learning significantly influence e-LSS.

The study results on students' perspective towards e-learning information systems can be advantageous to HEIs and various stakeholders like policymakers, and e-learning platforms. It may support and assist the HEIs and corporate firms in deciding on e-learning platforms for students and learners, respectively. Moreover, the consolidated findings will contribute to the existing literature on e-learning success factors from students’ perspectives.

This study examines the students' perception of e-LSS in Oman HEIs and advocates prospects for further in-depth study and analysis.

The e-learning-based approach is critical in keeping the wheels of education turning in the face of the COVID-19 epidemic. In this scenario, analyzing the implementation of the e-learning system is required to properly grasp the needs. The purpose of this paper is to demonstrate the relationship between technical system quality, information quality, service quality, educational system quality, support system quality, learner quality, instructor quality, perceived satisfaction, perceived usefulness, e-learning system use and benefits.

This study was carried out by giving online questionnaires to students attending private institutions in Indonesia. A total of 593 students participated in the study and provided responses. The structural equation model, which is supported by the program WarpPLS7.0, is used to analyze the data.

Maintaining the quality of the technological system, the information system, the learners and the educational system can help achieve the goal of increasing perceived utility. In the meanwhile, factors such as inadequate service quality, educational system quality, support system quality and teacher quality can all pose challenges to perceived levels of satisfaction. To get the most out of e-learning apps, users' expectations about how fun, useful and easy to use they are need to be met.

This study was carried out in the midst of the COVID-19 epidemic with a restricted number of participants from Indonesian institutions of higher education. This research has the potential to be expanded into a variety of different types of higher education in the future.

The main thing that will determine whether an e-learning system model works is the quality of the learners.

The institution should think about changing the material offered in the e-learning system to make it easier for students to grasp by describing the current material and providing digital handouts of lecturers' explanations. This study expanded the e-learning system success model and applied it to the evaluation of e-learning deployment in Indonesian higher education. This study will improve student comprehension of the e-learning model and contribute to the body of knowledge about e-learning applications and technology.

The main purpose of this study is to examine whether quality factors as the antecedents to learner beliefs can affect learners' intention to use an e‐learning system.

This study gathered sample data from eight high‐tech companies in Taiwan. A total of 680 questionnaires were randomly distributed, 522 questionnaires were returned for a response rate of 76.76 percent, and 483 usable questionnaires were analyzed, with a usable response rate of 71.03 percent. Data were analyzed by using structural equation modeling.

Information quality, service quality, system quality, and instructor quality, as the antecedents of e‐learning acceptance can provide detailed accounts of the key forces underpinning employees' perception with regard to their beliefs (i.e. perceived usefulness, perceived ease of use, and perceived enjoyment), and this situation can further enhance employees' usage intention of the e‐learning system.

Based on the extended technology acceptance model and the updated DeLone and McLean information systems success model, this study integrates related e‐learning quality factors including information quality, service quality, and system quality into the research model and further contributes additionally to the identification of instructor quality that may lead to e‐learning acceptance. Also, it should be noted that the empirical evidence on capturing both extrinsic and intrinsic motivators for completely explaining quality antecedents of e‐learning acceptance is well documented in this study. Hence, this study contributes significantly to the body of research on evaluating the quality antecedents of e‐learning acceptance.

The purpose of this paper is to propose a hybrid model based on the expectation-confirmation model (ECM), flow theory, and updated DeLone and McLean information system (IS) success model to examine whether quality factors as the antecedents to nurse beliefs affected nurses’ intention to continue using the blended electronic learning (e-learning) system.

Sample data for this study were collected from nurses at five hospitals in Taiwan. A total of 500 questionnaires were distributed, 396 (79.2 percent) questionnaires were returned. Consequently, 378 usable questionnaires were analyzed in this study, with a usable response rate of 75.6 percent. Collected data were analyzed using structural equation modeling.

Information quality, system quality, support service quality, and instructor quality contribute significantly to perceived usefulness (PU), confirmation, and flow, which together explain nurses’ satisfaction with the usage of the blended e-learning system, and this in turn leads to their continued system usage intention.

First, the application of the ECM with the view of updated DeLone and McLean IS success model reveals deep insights into quality evaluation (including information quality, system quality, and support service quality) in the field of nurses’ e-learning continuance intention. Especially, this study additionally contributes to the identification of instructor quality that may lead to nurses’ continued blended e-learning usage intention. Next, the empirical evidence on capturing both extrinsic motivator (i.e. PU) and intrinsic motivator (i.e. flow) for completely explaining quality antecedents of nurses’ blended e-learning continuance intention is well documented.

During the COVID-19 pandemic, educational institutions were forced to shut down, causing massive disruption of the education system. This paper aims to determine the critical factors for the intention to participate in e-learning during COVID-19.

Data were collected by surveying 131 university students and structural equation modelling technique using PLS-SEM was employed to analysis the data.

The results showed that the COVID-19 related factors such as perceived challenges and COVID-19 awareness not only directly impact students' intention but also such effects are mediated through perceived usefulness and perceived ease of use of e-learning systems. However, the results showed that the educational institution's preparedness does not directly impact the intention of students to participate in e-learning during COVID-19. The results also showed that the gender and length of the use of e-learning systems impact students' e-learning systems use.

These results demonstrated that, regardless of how well the educational institutions are prepared to promote the use of e-learning systems, other COVID-19-related challenges play a crucial role in forming the intention of students to participate in e-learning during the COVID-19 pandemic. Theoretical and practical implications are provided.

The purpose of this study is to propose a research model based on expectation-confirmation model (ECM) to examine whether interactivity and course quality factors (i.e. course content quality, course design quality) as antecedents to student beliefs can influence students' satisfaction and continuance intention of the cloud-based electronic learning (e-learning) system within the educational institution.

Sample data were collected from students enrolled in a comprehensive university in Taiwan. A total of 600 questionnaires were distributed in the campus, and 515 (85.8%) useable questionnaires were analyzed using structural equation modeling.

Findings showed that students' perceptions of interactivity, course content quality and course design quality positively significantly contributed to their perceived usefulness, confirmation and satisfaction with the cloud-based e-learning system, which in turn directly or indirectly led to their continuance intention of the system. Thus, the results strongly supported the research model based on ECM via positioning key constructs as the drivers with all hypothesized links being significant.

This study identifies three factors (i.e. interactivity, course content quality, course design quality) as drivers from the learner perspective within the cloud-based e-learning environment, and links these factors to students' satisfaction and continuance intention of the cloud-based e-learning system based on ECM. It is particularly worth mentioning that the three drivers can serve as precursors for recognizing the determinants that are crucial to understand students' satisfaction and continuance intention of the cloud-based e-learning system. Hence, this study may provide new insights in nourishing the cloud-based e-learning continuance literature in the future.

This study aims to propose and validate a model for e-Learning success based on students’ experiences in the “new normal.” To achieve this goal, this study focused on answering three research questions: (1) What are the students’ experiential factors that impact e-Learning? (2) How do these experiential factors affect e-Learning success? (3) In what ways does a multimethod provide a comprehensive perspective and an in-depth understanding of students’ e-Learning experiences in the new normal?

This study applied a mixed-methods sequential approach using exploratory, confirmatory and complementary studies. First, this study undertook a text-mining exploratory analysis of the review data to extract e-Learning topics. Then, based on the Information Systems (IS) success model, this study identified an integrated framework drawn from the results of the text-mining analysis. Second, this study proposed an e-Learning, experience-based success model and corresponding hypotheses and conducted a confirmatory study with surveys to validate the model. Third, this study conducted in-depth interviews to better identify the phenomenon of interest.

The five factors extracted from the first stage are system quality, lecture content, teaching quality, online interaction and achievement. This study subsequently confirmed the significant relationships between the e-Learning success factors in the second stage based on the IS success model. Finally, a complementary study identified the importance of interactivity for e-Learning success in the new normal.

To the best of the authors’ knowledge, this paper is the first to develop an e-Learning success model using a comprehensive mixed-methods approach.

This paper aims to provide a methodological road for the next generation of e‐learning environments.

This paper considers a survey of recent publications (1995‐2002), which aim to provide practical and theoretical indications and advice, which are coupled with practical experimentations.

The paper provides road‐mapping elements, indicating the impact on services and systems to be expected by this design approach.

The survey is based on a selection of sources and it is not exhaustive. The methodology experiments that are used for argumentation are based on the authors’ platform.

The paper presents a useful source of knowledge for researchers and advanced students.

This paper identifies a road for advanced e‐learning systems, and can help researchers and those in industry who desire to introduce and understand the design methodological context of advanced e‐learning systems.

Students' satisfaction with e-learning outcomes is a vital component in determining the adoption of e-learning systems. Understanding the antecedent factors impacting students' satisfaction with e-learning outcomes helps decision-makers at the higher education to take the necessary actions to enhance the quality of students' performance, especially during the exceptional times, such as the COVID-19 pandemic.

This paper aims to determine and analyse the antecedent factors influencing students' satisfaction with e-learning outcomes during the pandemic. Structural equation modelling (SEM) is used to analysis a proposed research model.

The SEM results show that digital communities in e-learning, information technology (quality and accessibility) and the online course design quality directly influence students' satisfaction with e-learning outcomes. More interestingly, results show that the COVID-19-related factors (1) awareness of the COVID-19, (2) perceived challenges (negatively) and (3) the educational institutions' preparedness also influence e-learning outcomes.

The results suggest that the decision-makers at the educational institutions should consider adopting a blended learning system approach to deliver e-learning during the emergency, such as the COVID-19 outbreak situation.

This is one of the first studies in higher education context, which seek to identify the antecedent factors that influence students' satisfaction with e-learning outcomes during the COVID-19 pandemic.

The purpose of this paper is to demonstrate the importance of undertaking a systemic view of learning management systems (LMSs) evaluation addressing the conceptualization and measurement of e‐learning systems success in higher education.

The paper adopts a quantitative case perspective and derives a conceptual model for e‐learning assessment (Hexagonal e‐learning assessment model – HELAM). The model is empirically tested for validity and reliability in the university setting.

Qualitative and quantitative findings have been presented, which will be valuable for academics and practitioners doing research in e‐learning evaluation. The findings support the flexibility and relevance of HELAM as an e‐learning assessment model. It highlights a number of success measures which are grouped under six dimensions.

Further research efforts should explore new dimensions or test the causal relationships among proposed dimensions within the boundary of e‐learning. In that, the paper is limited contextually where attention should be made not to generalize the findings beyond the empirical findings within the case analysis.

The paper supports a practitioner perspective through a consideration of a holistic approach to e‐learning assessment. E‐learning system developers may find the findings useful when designing and implementing the LMS.

The paper is original as the conceptual model has been derived through both theoretical constructs and empirical analysis. It provides an innovative approach to e‐learning assessment.