E-learning Continuance Intention Research Articles

Iranian medical students' E-learning continuance intention after end of COVID-19 pandemic.

Coronavirus disease (COVID-19) pandemic caused the closure of many face-to-face classes in Iran's universities of medical sciences, so e-learning was adopted as the alternative method. This study aims to examine the medical students' perspectives on e-learning continuance intention. In this quantitative study, the population included 1,453 students and the statistical sample size was determined to be 305 students using the Cochran formula. The participants were selected using stratified sampling method based on the field of study and the data were collected by e-learning evaluation questionnaire. The data were analyzed using SPSS 26.0 in addition to descriptive statistics. The results showed the mean perceived autonomy, perceived competence, and communication in e-learning, intrinsic motivation, information quality, e-learning applicability and students' satisfaction with e-learning courses were 2.61, 2.81, 2.91, 3.03, 2.98, 2.92, and 3.31, respectively. There was no significant correlation between the competence and applicability, user satisfaction and e-learning continuance intention. Moreover, e-learning continuance intention had the highest correlation with students' satisfaction (0.787) and information applicability (0.784), respectively. Medical students had a tendency to continue e-learning, even after controlling the COVID-19 outbreak, and health education policymakers can be of use in this opportunity to developing educational services.

Research on the Influence of E-Learning Quality on the Intention to Continue E-Learning: Evidence from SEM and fsQCA

This study explores how Chinese college students perceive the quality of e-learning and its impact on their adoption of online learning. The study develops an impact model of e-learning quality on continuous learning intention based on the stimulus-organism-response framework, technology acceptance model, and information system success model. The model is validated using a structural equation model (SEM) and fuzzy set qualitative comparative analysis (fsQCA) with data collected from 253 college students at a university in Eastern China. The SEM analysis shows that perceived ease of use and perceived usefulness positively influence e-learning continuance intention, while system quality and personalization have a positive impact on perceived ease of use, and learning community positively impacts perceived usefulness. The fsQCA analysis shows that college students’ willingness to continue e-learning is not solely dependent on a single factor of e-learning service quality but is also influenced by the interaction between various factors. Therefore, e-learning providers should take into account both external stimuli and internal perception factors when designing e-learning services. The findings of this study have practical implications for improving e-learning quality and enhancing the online learning experience. E-learning providers should consider the importance of system quality, personalization, and learning community in improving perceived ease of use and usefulness, which in turn can increase students’ intention to continue e-learning. The study also highlights the importance of considering the interaction between various factors that influence e-learning adoption rather than relying solely on individual factors.

Analysis of the Effect of Information Quality, System Quality, and Support Service Quality on User Satisfaction Levels and Its Implications for Blended E-Learning Continuance Intention to Use in the New Normal Era

Technology encourages e-learning to improve student learning and performance. The Covid-19 pandemic accelerated e-learning in Indonesian higher education. The learning method has transitioned from complete online learning to blended e-learning in new normal era. This research was conducted to determine the factors that influence students' intention to continue using blended e-learning using the IS Success Model. This research was conducted using a quantitative approach. Sampling was carried out by convenience sampling of 232 active students using blended e-learning in Indonesia. Data analysis was carried out with PLS-SEM. The hypothesis test shows that information, system, and support service quality affect blended e-learning student satisfaction. This research demonstrates that user happiness affects the intention to continue using blended e-learning

The Impact of Factors on E-Learning Continuance Intention in the Higher Education Sector in Pakistan

The Impact of Factors on E-Learning Continuance Intention in the Higher Education Sector in Pakistan

Antecedents of students’ e-learning continuance intention during COVID-19: An empirical study

This study aims at exploring the underlying determinants influencing students' continuance intention to use an e-Learning platform during the COVID-19 pandemic. Based on the technology acceptance model and expectation-confirmation model, the study investigated the role of contextual (i.e., social isolation), psychological (academic year loss and cyberchondria), and student support-related (government and institutional supports) determinants on students' continuance intention to use an e-Learning platform during the pandemic. The study collected data from 440 respondents and analyzed those with Structural Equation Modeling. The findings showed that an e-Learning continuance intention during the pandemic is affected by usefulness, ease of use, attitudes, and intention to use the e-Learning platform; while the behavioral intention is influenced by usefulness, ease of use, attitudes, contextual, psychological, and student support-related determinants; and attitudes are impacted by usefulness and ease of use. Moreover, usefulness is predicted by confirmation of expectation; e-satisfaction is forecasted by usefulness and confirmation of expectation; whereas, cyberchondria is influenced by social isolation; fear of academic year loss is influenced by cyberchondria. Finally, intention to use mediated the impact of usefulness, ease of use, attitudes, contextual, psychological, and student support-related determinants on continuance intention. The study contributes to e-Learning literature incorporating contextual, psychological, and student support-related determinants into the technology acceptance model and expectation-confirmation model, which guide policymakers to understand how all levels of students can be brought into the e-Learning platforms that eventually help to eliminate digital discrimination barrier in the academia during any emergency. The policymakers must be careful in designing eLearning platforms since students' e-learning continuance intention may vary due to unprecedented crises, such as COVID-19.

A Research on the Impact of Perceived Enjoyment, Performance Expectancy and Effort Expectancy on E-Learning Continuance Intention

This paper investigates the relationship between perceived enjoyment, performance expectancy, effort expectancy and the intention of continuance usage of e-learning system. The research bases on UTUAT model with revised of independent variables due to impact of Covid-19. The widespread of the pandemic has forced governments to impose social distancing method for extended periods in most of the countries. Many activities were impacted including education which was forced to move to online mode to support continuous learning. Such powerful unforeseeable factor casted a significant impact on the use of e-learning system. Learners and teachers must use e-learning regardless of preferences, supporting opinions, essential equipment availability, internet connection stability, … In short, factors that were proved to prone impact on intention to use e-learning before in the UTUAT model such as social influence and facilitating condition are no longer applicable in the Covid-19 context. As the world is transiting into the “new normal” life after Covid-19 vaccine coverage is sufficient, the decision of continuing the use of e-learning mode become obvious for most education institutions and the learners as well. Research results shows that perceived enjoyment carries a positive impact on performance expectancy, effort expectancy and e-learning system continuance intention. In addition, performance expectancy also impacts e-learning system continuance intention in a positive way. This research found no statistical evidence of effort expectancy impact on e-learning system continuance intention. Keywords: Perceived enjoyment, performance expectancy, effort expectancy, continuance intention. DOI: 10.7176/JESD/13-10-04 Publication date: May 31 st 2022

What roles do quality and cognitive absorption play in evaluating cloud-based e-learning system success? Evidence from medical professionals

Purpose The purpose of this study is to propose a hybrid model integrating the expectation-confirmation model with the views of cognitive absorption (CA) theory and updated DeLone and McLean information system success model to examine whether quality factors as antecedents to medical professionals’ beliefs can affect their continuance intention of the cloud-based e-learning system. Design/methodology/approach This study’s sampling frame was taken from among medical professionals working in hospitals with over 300 beds in Taiwan which had implemented the cloud-based learning management system (LMS) with a blend of asynchronous and synchronous technologies. Sample data for this study were collected from medical professionals at six hospitals in Taiwan. The data for this study were gathered by means of a paper-and-pencil survey, and each sample hospital that participated in this study was asked to identify a contact person who could distribute the survey questionnaires to medical professionals who had experience in using the cloud-based LMS in their learning. A total of 600 questionnaires were distributed, and 378 (63.0%) usable questionnaires were analyzed using structural equation modeling in this study. Findings This study proved that medical professionals’ perceived learner–content interaction quality, learner–system interaction quality, service quality, cloud storage service quality and learner–human interaction quality all positively caused their perceived usefulness, confirmation and CA elicited by the cloud-based e-learning system, which jointly explained their satisfaction with the system, and resulted in their continuance intention of the system. Research limitations/implications Several limitations and suggestions may open avenues for future research. First, the limitation of self-reported measures should be considered; future research may combine with qualitative data (e.g. semi-structured, narrative, in-depth interviews, focus group interviews and open-ended questions) to get more complete interpretations of medical professionals’ cloud-based e-learning continuance intention. Next, this study’s data were collected from hospitals in Taiwan only; given this study’s limited scope, future research may generalize this study’s sample to the respondents of other national cultural backgrounds and make cross-country comparisons to enhance the completeness of this study. Finally, this study’ results were based on cross-sectional data; future research may use a longitudinal analysis by taking into account the evolution of medical professionals’ cloud-based e-learning continuance intention over time. Originality/value This study fully evaluates interaction-related and cloud-related quality determinants through an understanding of medical professionals’ state of CA in explaining their cloud-based e-learning system continuance intention that is difficult to expound with only their utilitarian perception of the system. Hence, the results contribute to deep insights into an all-round quality evaluation in the field of medical professionals’ cloud-based e-learning continuance intention, and extrinsic and intrinsic motivators are both taken into consideration in this study’s theoretical development of medical professionals’ cloud-based e-learning continuance intention to acquire a more comprehensive and robust analysis.

Can tasks and learning be balanced? A dual-pathway model of cloud-based e-learning continuance intention and performance outcomes

PurposeThe purpose of this paper is to examine the roles of task-technology fit (TTF), learning-technology fit (LTF) and cognitive absorption (CA) in determining medical professionals’ cloud-based electronic learning (e-learning) system continuance intention and performance outcomes and evaluate whether medical professionals’ perceived impact on learning can affect their perceived impact on tasks within medical institutions.Design/methodology/approachSample data for this study were collected from medical professionals at six hospitals in Taiwan. A total of 600 questionnaires were distributed, and 373 (62.2%) usable questionnaires were analyzed using structural equation modeling in this study.FindingsIn this study, medical professionals’ perceived TTF and LTF as antecedents to their cloud-based e-learning continuance intention and performance outcomes were validated, and medical professionals’ perceived impact on learning had a positive effect on their perceived impact on tasks. Synthetically speaking, this study’s results strongly support the research model with all hypothesized links being significant.Originality/valueIt is particularly worth mentioning that this study introduces a new construct, “LTF,” to conceptualize, define and measure it, and further contributes to the application of capturing both expectation–confirmation model and CA (i.e. an intrinsic motivator) for completely explaining medical professionals’ perceived TTF and LTF as external variables to their cloud-based e-learning continuance intention and performance outcomes.

Investigating medical professionals' continuance intention of the cloud-based e-learning system: an extension of expectation–confirmation model with flow theory

PurposeThe purpose of this study is to propose an integrated model based on expectation–confirmation model (ECM), flow theory and human–organization–technology fit framework to examine whether human, organizational and technology factors as antecedents to medical professionals' beliefs can affect their continuance intention of the cloud-based e-learning system.Design/methodology/approachSample data for this study were collected from medical professionals at five hospitals in Taiwan. A total of 500 questionnaires were distributed, and 368 (73.6%) useable questionnaires were analyzed using structural equation modeling in this study.FindingsSynthetically speaking, human, organizational and technology factors, as antecedents to medical professionals' continuance intention of the cloud-based e-learning system have been examined, and the results strongly support the research model with all hypothesized links being significant.Originality/valueParticularly, it is worth mentioning that the application of capturing both ECM and flow theory for completely explaining three types of factors (i.e. human, organizational and technology factors) as external variables to medical professionals' cloud-based e-learning continuance intention is well documented, that is, information systems (IS) and nonIS determinants are simultaneously evaluated, and extrinsic and intrinsic motivators are both taken into consideration in this study's theoretical development of medical professionals' cloud-based e-learning continuance intention to acquire a more comprehensive and robust analysis.

The role of system quality and content quality in explaining e-learning continuance intention: An Evidence from Malaysian e-learning users

System quality and content quality has long been adopted to study e-learning acceptance. However, it’s role in explaining confirmation stage (continuance intention) is still in vague. The current study combines systems quality and content quality in a theoretical framework to examine it’s impact on users continuance intention. The research model and hypotheses was tested using 427 Malaysian e-learning users via SPSS. Results indicate that both predictors were significantly related to e-learning continuance intention. The findings from this study provide useful insights for further research

An integrated model of e-learning continuance intention in Indonesia

There had been some research concerning behaviour in using e-learning system. Most of the analysis focuses on the students' behavioural intention to use the system, without doing further analysis to find out their continuance intention to use it again. Therefore, this research aims to develop a model that describes the influencing factors on e-learning continuance intention of Indonesian students. Analysis in this research is focused on the investigations of the e-learning satisfaction, e-learning usefulness, and e-learning effectiveness, from the four main aspects: e-learning materials/multimedia, service quality, interaction, and learner's characteristics. By using structural equation modelling approach, several analyses were conducted to 635 respondents' data, obtained from various universities in Indonesia. This research found that almost all of the factors analysed in this research have a significant influence on continuance intention of Indonesian students, with e-learning satisfaction and e-learning usefulness as the main factors that influence directly, and navigation, reliability, tangibles, self-efficacy, and learner-content interaction as the main factors that influence indirectly.

An integrated model of e-learning continuance intention in Indonesia

There had been some research concerning behaviour in using e-learning system. Most of the analysis focuses on the students' behavioural intention to use the system, without doing further analysis to find out their continuance intention to use it again. Therefore, this research aims to develop a model that describes the influencing factors on e-learning continuance intention of Indonesian students. Analysis in this research is focused on the investigations of the e-learning satisfaction, e-learning usefulness, and e-learning effectiveness, from the four main aspects: e-learning materials/multimedia, service quality, interaction, and learner's characteristics. By using structural equation modelling approach, several analyses were conducted to 635 respondents' data, obtained from various universities in Indonesia. This research found that almost all of the factors analysed in this research have a significant influence on continuance intention of Indonesian students, with e-learning satisfaction and e-learning usefulness as the main factors that influence directly, and navigation, reliability, tangibles, self-efficacy, and learner-content interaction as the main factors that influence indirectly.

The Role of Satisfaction on Perceived Value and E-Learning Usage Continuity Relationship

This research is intended to explore the role of satisfaction on perceived value and e-learning continuance intention to use relationship’s in the learning process. In investigating the issue, this research is using 48 lecturers implementing e-learning in their teaching and learning as the sample. The sample is gathered by using a simple random sampling technique by spreading an online questionnaire to all population. Partial Least Square (PLS) approach, assisted by Smart PLS 3.2.7 is utilized to analyze the gathered data the analysis showed that perceived value has an impact on continuance intention with p value equals to 0.000 (H1 is supported). The result also indicated that satisfaction can act as a full mediating variable (indirect only mediating variable type) in the relationship between perceived value and e-learning continuance intention with p value equals to 0.000 and VAF 97% (H2 is supported). Theoretically, this research contributes to highlight the role of satisfaction in the perceived value and continuance intention relationship which was tested separately and partially in the previous researches.

Extending the expectation-confirmation model with quality and flow to explore nurses’ continued blended e-learning intention

Purpose– 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.Design/methodology/approach– 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.Findings– 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.Originality/value– 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.

E-Learning Continuance Intention Among Higher Learning Institution Students’ in Malaysia

E-Learning is the teaching and learning approach that used the network technology as an important medium to support the conventional class activities. It becomes the worldwide issues in higher education institution to facilitate their students with E-Learning technology. There are many research is done to determine the effectiveness of e- Learning. This study focuses on individual continuance intention for the e-Learning services in Universiti Teknologi MARA (UiTM) as a support for traditional classes. The objective of this study is to determine the level of e-Learning continuance intention and identify the factors that lead to the acceptance or reluctant of continuity in using e- Learning services in UiTM. The questionnaire used in this research is based on the decomposed technology acceptance model (TAM) in the context of e-learning service proposed by Juan Carlos Roca et al. This model stated that e-Learning user's continuance intention is determined by user's satisfaction level with the conjunction of information quality, service quality, system quality, perceived usefulness, perceived ease of use, confirmation and cognitive absorption. The respondents are among UiTM students that have an experience using e-Learning service in their studies. The statistical result of this study shows that continuance intention towards e-Learning among UiTM students is moderate. This result is influence by two main factors: low in interpersonal influence and information quality in our e-learning services. The results of this research provide clear guideline to the organization to improve their e-Learning services in terms to get the students engagement.

The Exploring of the Perceived Quality, Confirmation and Satisfaction on E-Learning Continuance Intention in the Context of E-Learning Environment

The Exploring of the Perceived Quality, Confirmation and Satisfaction on E-Learning Continuance Intention in the Context of E-Learning Environment

Understanding e-learning continuance intention: a negative critical incidents perspective

This study develops a model to examine the key drivers of users' continuance intention of e-learning, based on negative critical incidents (NCIs) standpoints. The developed research model is tested empirically using a field survey of 230 users. This study finds that users' past service encounters (NCIs), belief (perceived ease of use and usefulness), satisfaction (quality attributes cumulative satisfaction and overall satisfaction) and attitude are key antecedents of continued usage intention. Four dimensions of both NCIs and quality attributes in e-learning (administration procedures, e-learning system functionality, instructional process and human interaction) are explored in this study. Results indicate that NCIs in teaching and administration are comparatively more important in determining user satisfaction and continuance intention. Further analysis finds that the recorded lecture content and the response time to users are the most critical problems in teaching and administration. In practice, this model can identify the key problems of satisfaction and continuance intention to help managers and teachers react promptly or make right decisions about how to better achieve higher user retention rates.

E-Learning continuance intention: Moderating effects of user e-learning experience

This study explores the determinants of the e-learning continuance intention of users with different levels of e-learning experience and examines the moderating effects of e-learning experience on the relationships among the determinants. The research hypotheses are empirically validated using the responses received from a survey of 256 users. The results reveal that negative critical incidents and attitude are the main determinants of the users’ intention to continue using the e-learning, irrespective of their level of e-learning experience. In addition, the findings show that the user’s experience of the e-learning service plays a moderating role. The impact of negative critical incidents on perceived ease of use is greater for less experienced users. By contrast, the impact of negative critical incidents on perceived usefulness is greater for more experienced users. Perceived ease of use has a more critical effect on the attitude and continuance intention of less experienced users, whereas perceived usefulness is found to be a stronger determinant of the attitude and behavioral intention of more experienced users. Moreover, the relationship between satisfaction and continuance intention is stronger for less experienced users than for more experienced users. The implications of the present findings for research and managerial practice are analyzed and discussed.

Understanding e-learning continuance intention in the workplace: A self-determination theory perspective

Based on self-determination theory (SDT), this study proposed an extended Technology Acceptance Model (TAM) in the context of e-learning service. In the proposed model perceived usefulness, perceived playfulness and perceived ease of use are predicted to be influenced by perceived autonomy support, perceived competence and perceived relatedness. Although TAM has received fairly extensive attention in prior research, this study is one of the first to examine the effects of motivational factors affecting TAM constructs. The results show that applying SDT to e-learning in a work setting can be useful for predicting continuance intention.

Understanding e-learning continuance intention: An extension of the Technology Acceptance Model

Based on the expectancy disconfirmation theory, this study proposes a decomposed technology acceptance model in the context of an e-learning service. In the proposed model, the perceived performance component is decomposed into perceived quality and perceived usability. A sample of 172 respondents took part in this study. The results suggest that users’ continuance intention is determined by satisfaction, which in turn is jointly determined by perceived usefulness, information quality, confirmation, service quality, system quality, perceived ease of use and cognitive absorption.