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Electronic learning (e‐learning) has gradually become an important part of university education. There is a trend among universities in Taiwan to offer more and more e‐learning courses. The effectiveness of teaching or learning in an e‐learning system can be quantified by multi‐criteria measures. The purpose of this study was to evaluate the effectiveness of teaching or learning in an e‐learning system measures in linguistic preferences.

A generalized quantitative evaluation model that considers both the interdependence among measures and the fuzziness of subjective perception is currently lacking in the literature. The results indicated that the fuzzy analytical network process is a simple, suitable, and effective method of identifying the primary measures that influence the effectiveness of e‐learning, specifically in the context of interdependent measures and varying linguistic preferences.

The most significant measures of e‐learning effectiveness were the quality of the e‐learning system and learner attractiveness. Enhanced usage of multimedia features can attract learner attention and may eventually increase learner attractiveness. Reducing the waiting time for learning materials to load may improve the quality of the system. Furthermore, the management should actively maintain and improve the responsiveness of instructors to learner inquiries.

The main contributions of this study are twofold. First, the evaluation can be considered as a complex‐dependence, hierarchical decision‐making problem. This study contains a review of the literature and identifies 21 criteria and five aspects to measure e‐learning system effectiveness. Second, this study integrates fuzzy set theory and the ANP to develop an evaluation model that prioritizes the relative weights of the proposed measures. The proposed method can be used to handle dependence within a set of measures and to construct a hierarchical structure.

E-learning has become an increasingly prevalent learning approach in higher educational institutions due to the fast growth of internet technologies in India. This paper aims to mainly focus on evaluating the effectiveness of the e-learning experience from students’ perceptive.

“Survey” method has been used to collect the data with the help of a structured questionnaire from the students who have registered on COURSERA (www.coursera.org/) website for e-learning. The questionnaire consisted of two sections e-learning system and e-learning effectiveness. E-learning system included items related to system quality, information quality and service quality. E-learning effectiveness dimension included user satisfaction and net benefits. The items in this section were measured on a five-point Likert scale ranging from strongly disagrees to strongly agree. The data collected have been analyzed using the SPSS version 17.0 and AMOS version 21.0.

Results show that system quality and service quality contribute more in e-learning system compared to information quality. Students perception may be that information available on the website may not be very useful as it’s a one-way mode of communication. The researcher also found that the three dimensions (system quality, service quality and information quality) of e-learning system contributes to user satisfaction and net benefits. Students are satisfied with e-learning websites and intent to continue to use it in future as well. They also found it beneficial as it helps them in career growth and making them employable.

This paper proposed a second-order model of e-learning system and a second-order model e-learning effectiveness. E-learning system has been defined by three first-order constructs: a system quality, service quality and information quality. E-learning effectiveness has been defined by two first-order constructs: a user satisfaction and net benefits. The predictability of the proposed model is high to explain the impact of e-learning system on e-learning effectiveness.

The majority of e‐learning empirical research studies have focused on the two research streams: outcome comparison studies with classroom‐based learning and studies examining potential predictors of e‐learning success. The determinants of e‐learning success include interactions, instructor support and mentoring, information delivery technology, course content, self‐motivation, learning styles, and course structure. Most of these empirical studies failed to include the technological dimension as an antecedent of effectiveness of e‐learning systems. The purpose of this paper is to empirically test the effects of e‐learning management systems (LMS), self‐efficacy and self‐regulated learning on learner satisfaction and system effectiveness.

This research model is an extension of the information systems success model of DeLone and McLean and the virtual learning environment effectiveness model of Piccoli et al. The research model was tested using the structural equation modelling‐based Partial Least Squares (PLS) methodology.

First, use of e‐LMS is not positively related to systems quality, information quality, self‐managed learning, and user satisfaction. Second, the findings strongly support the previous works of Rai, et al., Livari, and Freeze, et al. These three studies found strong positive relationships between information quality and user‐satisfaction and between systems quality and user‐satisfaction in a voluntary or mandatory use context. Third, perceived user satisfaction with e‐LMS is a very strong predictor of system effectiveness. This is in accordance with the findings and conclusions discussed in the literature on student satisfaction (Freeze et al., Eom et al., Rai et al., Livari). Of the four factors hypothesized to affect user satisfaction with e‐LMS, only two (systems quality and information quality) are supported at p<0.01.

This paper provides empirical evidence to support that e‐learner satisfaction is an important predictor of e‐LMS effectiveness and that systems quality and information quality have significant direct impacts on the perceived satisfaction of e‐learners with e‐LMS.

This study provides new empirical evidence that e‐learners' self‐regulated learning behavior may not lead to a higher level of e‐learners' satisfaction with e‐LMS, but it may lead to a higher level of satisfaction with web‐based courses.

This study aims to understand how public sector organizations can successfully implement organizational information systems (IS). It identifies the factors that contribute to the success of organizational IS implementation in public universities.

Both qualitative and quantitative research methods are used. The proposed research model is based on previous studies and primary qualitative research, including in-depth interviews, telephone surveys and mail surveys using semi-structured questionnaires to identify the determinants and measures of implementation success. Based on the first mail survey’s results, quantitative research is conducted to test the research hypotheses. The data are gathered from university personnel at 40 public universities, and the study focuses on the implementation of student registration systems.

The results suggest that successful implementation of organizational IS includes the decisions of both those in authority and users. The external and internal organization and individual user factors have direct relationships with the measure of implementation success, which suggests significant differences between authorities and users.

The analysis is based on the viewpoint of public university personnel; however, the findings suggest the need for further research on other public organizational IS as well as other public service operations.

The study clearly suggests a set of factors to guide public universities in successfully implementing organizational IS for local conditions of a developing country.

The study contributes to the understanding of effective IS implementation in public universities in a developing country.

The purpose of this study is to investigate the influences of system and instructor factors on e‐learning effectiveness under the interactions of computer self‐efficacy. In this study, the factors of the e‐learning system are functionality, interaction, and response. The factors of the e‐learning instructor are attitude, technical skills, and instructional method. The moderating effects of learners' computer self‐efficacy are examined.

The study surveyed general employees in the financial services industry in Taiwan. A questionnaire was developed to measure participants' perceptions. Four hundred questionnaires were sent out, and 362 were returned. Of these, 314 were valid, leading to a return rate of 78.5 percent.

The results of data analysis indicate that both system and instructor factors have significant positive influences on e‐learning effectiveness. Learners' computer self‐efficacy has a moderating effect on the relationship between system functionality and training effectiveness. The higher the computer self‐efficacy, the stronger is the relationship between functionality and effectiveness, and vice versa. However, computer self‐efficacy does not have a significant moderating effect on the relationship between other independent variables and training effectiveness.

Since both system and instructor factors have positive influences on e‐learning effectiveness, HRD managers need to pay more attention to issues in both areas. High computer self‐efficacy can result in better training effectiveness; therefore, it is necessary to pay attention to enhancing employee computer skills and their confidence in using e‐learning.

The use of e‐learning is largely predicated upon the assumption that it can facilitate improvements in student learning and therefore can be more effective than conventional techniques. This assumption has been supported by some in the literature but has been questioned by a continuing body of contrary or indifferent evidence. The purpose of this paper is to improve the theoretical understanding of the variables influencing e‐learning effectiveness, the manner in which these variables have been studied to date, and to propose a suitable conceptual model of e‐learning effectiveness to aid its evaluation.

The paper revisits and critically reviews major contributions to the e‐learning effectiveness literature.

Owing to a variety of issues prevalent in the literature, it is clear that the variables influencing effectiveness are multifarious and few researchers impose adequate controls or factor them into research designs. Drawing on the work of Dewey, Englebart, and Kaplan, a conceptual framework of e‐learning effectiveness is proposed. This model maps out the key variables involved in the study of e‐learning effectiveness and the interactions between variables.

It is anticipated that such a model will assist researchers in developing future evaluative studies which are both sufficiently robust and holistic in design. It is also hypothesised that studies designed using the conceptual model will be more likely to yield results corroborating the ability of e‐learning to affect improvements in student learning.

E-learning environments and services (ELES) adoption and success rates challenge ELES designers, practitioners and organisations. Enterprise decision makers continue to seek effective instruments in launching such systems. The purpose of this paper is to understand users’ perceptions of ELES effectiveness and develop a theoretical framework which improves understanding of success factors for adoption.

Grounded theory method is used to reflect on the relationships between changing users’ requirements and expectations, technological advances and ELES effectiveness models. A longitudinal study collecting data from social media blogs over four years was authenticated based on the context evaluation, language structure and conversational constructs.

Identification of a new core dimension named “Concept Functionality” which can be used to understand the relationships between e-learning effectiveness factors including the relationships with other domains such as security. The findings are also used to validate major existing models for the success of ELES.

The new framework potentially improves system design process in the fields of education technology, enterprise systems, etc.

Concept functionality dimension can offer more insights to understand ELES effectiveness and further improve system design process in a variety of domains including enterprise systems, process modelling and education technology.

The purpose of this paper is to evaluate the critical success factors for sustainable e‐learning in an e‐learning ecosystem framework. Three critical components of the e‐learning ecosystem including principles and methods, processes and systems, and substance and content are considered based on a comprehensive review of the relevant literature in e‐learning.

Systematic interviews are conducted with experts in e‐learning for identifying the critical success factors to sustainable e‐learning within an e‐learning ecosystem framework. This leads to the development of an e‐learning success model that describes the underlying relationship between and among the identified critical success factors.

A comprehensive analysis of the interview results shows that there are several barriers to the effective adoption of the proposed e‐learning success model for improving the effectiveness of e‐learning. These barriers include a lack of understanding of the technologies behind various pedagogies, insufficiencies of the popular learning management systems, and the sustainability of the learning objects repositories.

The paper highlights the criticality of synergizing the three components of e‐learning ecosystems namely pedagogies, technologies and management of learning resources for achieving a sustainable e‐learning success.

A better understanding of these barriers would help e‐learning stakeholders develop appropriate strategies and policies for the implementation of the proposed e‐learning success model towards creating a sustainable e‐learning environment.

Specific contributions of this research to the entire e‐learning community are discussed with recommendations for concerted policy measures to eliminate the identified barriers in the process of adopting the developed e‐learning success model.

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.

Guidelines for the design of knowledge-based e-learning usability systems are absent from the current recognized set of usability design heuristics and from an established evaluation methodology of e-learning system developments. Such systems can help Web designers and instructional designers design for different user needs and decide which properties are of a higher priority, thus meriting more design and development efforts. The authors aim to help students develop higher-order thinking skills, such as application, evaluation and syntheses of knowledge.

The authors applied Merrill ' s first principles of instruction and usability properties as pedagogical and usability design guidelines, knowledge management (KM) and hierarchical task analysis as methodological knowledge bases. The authors proposed a KM e-learning usability framework which frames our mapping of Web usability attributes to e-learning usability properties. The authors aim to investigate whether adopting Merrill ' s first principles of instruction and usability properties as knowledge-based guidelines/design factors would help learners develop higher-order thinking skills and whether this design would result in positive technology acceptance. The authors also developed a method matrix to map the selected methods of cognitive engineering to its potential uses in the KM e-learning usability framework of this paper and mapped e-learning usability tools with components in the KM e-learning usability system.

Findings indicated that our design effectively helped learners to demonstrate higher-order thinking skills and positive technology acceptance, promising indications toward the design and development of knowledge-based usability frameworks and systems.

The sample size of this paper is small. Hence, conclusions are not generalizable at this moment.

The authors’ contributions are twofold: First, the authors proposed a KM e-learning usability framework, which frames the mapping of KM processes to e-learning principles and usability properties. Second, the authors proposed a method matrix which maps the selected methods of cognitive engineering to its potential uses in their KM e-learning usability framework. Based on these mappings and focusing on the usability properties navigation and learning support, the authors used ICT/Web2.0 tools to present/visualize information more clearly and more sensibly/manageably to students, to help trigger new knowledge and develop higher-order thinking skills, such as application, evaluation and syntheses of knowledge and articulate information from different perspectives throughout the KM life cycle.