Examining the integrated influence of fairness and quality on learners' satisfaction and Web-based learning continuance intention

Abstract.  As with any other information system (IS), the success of Web-based learning depends largely on user satisfaction and other factors that eventually increase users' intentions to continue using the service (continuance intention). This research integrates the IS success model and fairness theory to construct a model for investigating the motivations behind learners' intentions to continue using Web-based learning. Our model theorizes that the three dimensions of quality (i.e. information, system and service) and the three dimensions of fairness (i.e. distributive, procedural and interactional) affect learners' satisfaction. We also argue that satisfaction and the three dimensions of fairness will influence learners' intention to continue using Web-based learning. The hypothesized model is validated empirically using data collected from 289 learners of a Web-based learning service. The results show that information quality, system quality, system use, distributive fairness and interactional fairness exhibit significant positive effects on satisfaction. Also, procedural fairness and satisfaction play significant roles in shaping learners' intention to continue using Web-based learning.     

Understanding Web-based learning continuance intention: The role of subjective task value

The success of Web-based learning depends on learner loyalty, i.e., subsequent continued usage (continuance). We extended the Unified Theory of Acceptance and Use of Technology (UTAUT) by introducing components of subjective task value into a model for studying learners’ continuance intentions in Web-based learning. Based on survey data from 286 respondents, SEM was employed to assess the model. The results indicated that performance expectancy, effort expectancy, computer self-efficacy, attainment value, utility value, and intrinsic value were significant predictors of individuals’ intentions to continue using Web-based learning, while anxiety had a significant negative effect. The results suggested the beneficial effect of positive subjective task value on stimulating learners’ intentions to continue using Web-based learning, which is as important as performance expectancy and effort expectancy. Implications and limitations of our study are discussed.     

Understanding customers' loyalty intentions towards online shopping: an integration of technology acceptance model and fairness theory

As with any other information system (IS), the success of online shopping depends largely on customer satisfaction and other factors that will eventually increase customers' loyalty intentions. This article integrates two major variables of technology acceptance model (TAM), trust, and fairness to construct a model for investigating the motivations behind customers' loyalty intentions towards online shopping. The hypothesised model is validated empirically using data collected from 311 customers of an online shopping store. The results indicated that distributive, procedural and interactional fairness were strong predictors of trust, which in turn influenced satisfaction. Distributive fairness and interactional fairness exhibited significant positive effects on satisfaction. Perceived usefulness and satisfaction influenced loyalty intention towards online shopping. Perceived ease of use acts indirectly on loyalty intention through the mediating effect of perceived usefulness. Implications for theory and practice and future research directions are discussed.     

Users’ attitudes toward Web-based collaborative learning systems for knowledge management

The Web-based technology is a potential tool for supported collaborative learning that may enrich learning performance, such as individual knowledge construction or group knowledge sharing. Thus, understanding Web-based collaborative learning for knowledge management is a critical issue. The present study is to investigate learners’ attitudes toward Web-based collaborative learning systems. Based on this research, the results of factor analysis show that five attitude factors (system functions, system satisfaction, collaborative activities, learners’ characteristics, and system acceptance) should be examined at the same time when building a Web-based collaborative learning system. The results also provide an acceptance model for understanding users’ behavioral intention of facilitating Web-based collaborative systems.     

An intelligent learning diagnosis system for Web-based thematic learning platform

This work proposes an intelligent learning diagnosis system that supports a Web-based thematic learning model, which aims to cultivate learners’ ability of knowledge integration by giving the learners the opportunities to select the learning topics that they are interested, and gain knowledge on the specific topics by surfing on the Internet to search related learning courseware and discussing what they have learned with their colleagues. Based on the log files that record the learners’ past online learning behavior, an intelligent diagnosis system is used to give appropriate learning guidance to assist the learners in improving their study behaviors and grade online class participation for the instructor. The achievement of the learners’ final reports can also be predicted by the diagnosis system accurately. Our experimental results reveal that the proposed learning diagnosis system can efficiently help learners to expand their knowledge while surfing in cyberspace Web-based “theme-based learning” model.     

Surveying instructor and learner attitudes toward e-learning

The trend of using e-learning as a learning and/or teaching tool is now rapidly expanding into education. Although e-learning environments are popular, there is minimal research on instructors’ and learners’ attitudes toward these kinds of learning environments. The purpose of this study is to explore instructors’ and learners’ attitudes toward e-learning usage. Accordingly, 30 instructors and 168 college students are asked to answer two different questionnaires for investigating their perceptions. After statistical analysis, the results demonstrate that instructors have very positive perceptions toward using e-learning as a teaching assisted tool. Furthermore, behavioral intention to use e-learning is influenced by perceived usefulness and self-efficacy. Regarding to learners’ attitudes, self-paced, teacher-led, and multimedia instruction are major factors to affect learners’ attitudes toward e-learning as an effective learning tool. Based on the findings, this research proposes guidelines for developing e-learning environments.     

What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction

E-learning is emerging as the new paradigm of modern education. Worldwide, the e-learning market has a growth rate of 35.6%, but failures exist. Little is known about why many users stop their online learning after their initial experience. Previous research done under different task environments has suggested a variety of factors affecting user satisfaction with e-Learning. This study developed an integrated model with six dimensions: learners, instructors, courses, technology, design, and environment. A survey was conducted to investigate the critical factors affecting learners’ satisfaction in e-Learning. The results revealed that learner computer anxiety, instructor attitude toward e-Learning, e-Learning course flexibility, e-Learning course quality, perceived usefulness, perceived ease of use, and diversity in assessments are the critical factors affecting learners’ perceived satisfaction. The results show institutions how to improve learner satisfaction and further strengthen their e-Learning implementation.     

Explaining and predicting users’ continuance intention toward e-learning: An extension of the expectation–confirmation model

Although e-learning has been prompted to various education levels, the intention to continue using such systems is still very low, and the acceptance-discontinuance anomaly phenomenon (i.e., users discontinue using e-learning after initially accepting it) is a common occurrence. This paper synthesizes the expectation–confirmation model (ECM), the technology acceptance model (TAM), the theory of planned behavior (TPB), and the flow theory to hypothesize a theoretical model to explain and predict the users’ intentions to continue using e-learning. The hypothesized model is validated empirically using a sample collected from 363 learners of a Web-based learning program designed for continuing education. The results demonstrate that satisfaction has the most significant effect on users’ continuance intention, followed by perceived usefulness, attitude, concentration, subjective norm, and perceived behavior control as significant but weaker predictors. The implications of these findings for e-learning practitioners are discussed at the end of this work.     

Investigating students’ perceived satisfaction,behavioral intention,and effectiveness of e-learning: A case study of the Blackboard system

Although the benefits of e-learning have been discussed in various previous studies; it is a critical issue of better understanding the reasons why some learners are dissatisfied with the e-learning experience. Therefore, this research investigates learners’ satisfaction, behavioral intentions, and the effectiveness of the Blackboard e-learning system. A total of 424 university students were surveyed using a standard questionnaire. The results showed that perceived self-efficacy is a critical factor that influences learners’ satisfaction with the Blackboard e-learning system. Perceived usefulness and perceived satisfaction both contribute to the learners’ behavioral intention to use the e-learning system. Furthermore, e-learning effectiveness can be influenced by multimedia instruction, interactive learning activities, and e-learning system quality. This research proposes a conceptual model for understanding learners’ satisfaction, behavioral intention, and effectiveness of using the e-learning system.     

Usability, quality, value and e-learning continuance decisions

Previous research suggests that an eventual information technology (IT) success depend on both its initial adoption (acceptance) and subsequent continued usage (continuance). Expectancy disconfirmation theory (EDT) has been successfully used to predict users’ intention to continue using information technologies. This study proposed a decomposed EDT model to examine cognitive beliefs and affect that influence users’ continuance decision in the context of e-learning service. The proposed model extended EDT by decomposing the perceived performance component into usability, quality, and value. Research hypotheses derived from this model are empirically validated using the responses to a survey on e-learning usage among 183 users. The results suggest that users’ continuance intention is determined by satisfaction, which in turn is jointly determined by perceived usability, perceived quality, perceived value, and usability disconfirmation.