Investigating critical success factors in online learning environments in higher education systems in the Caribbean*

ABSTRACT

Online learning has grown as a key method in education management over the last couple of decades. Studies have shown that significant investments in this technology are being made by universities, yet the full benefits expected have not been realized due to issues and challenges experienced by stakeholders such as learners and instructors in adopting and effectively using e-learning. This is especially true in developing economies where they may be attempting online delivery modes for the first time. In this study, we explore the question “What are the factors that influence university students’ adoption and use of an e-learning system in the context of the English-speaking Caribbean?” using an extended technology acceptance model framework. Partial least squares analysis was used to test the derived research model and found that critical success factors influencing students’ perception and use in online learning settings, particularly those within a developing economy conditions, include supportive cultural practices, access to computers, system or online environment availability, computer and online learning self-efficacy, user perception of usefulness and ease of use. These results have significant implications for university executives and policy-makers as they consider adopting online learning delivery modalities for users.     

An empirical investigation linking learners’ adoption of blended learning to their intention of full e-learning

Learning management system (LMS) is playing a major role in higher academic institutions worldwide. Even though full e-learning is becoming a feasible strategy for a number of institutions in the world, some institutions, especially those in developing countries, are resisting a full e-learning environment. Consequently, these academic institutions initially adopt LMS for blended learning to assess their readiness for full e-learning transformation. There are a number of studies that investigate the determinants of full e-learning, but very limited studies investigate the link between learners’ perception of blended learning and full e-learning. The objective of this study was to link learners’ adoption (perceived ease of use, perceived usefulness (PU) and satisfaction) of LMS in blended learning and their personal characteristics (self-efficacy, technology experience and personal innovativeness) to their intention to use full e-learning. Data were collected through a questionnaire from 512 learners in Oman. The study found that personal innovativeness, PU and satisfaction of LMS in blended learning are significant to learners’ intention to engage in full e-learning. Thus, learners’ adoption of LMS in blended learning boosts their intention to full e-learning. The results provide useful insights for practitioners and researchers on full e-learning planning and strategy.     

Promoting online learners’ continuance intention: An integrated flow framework

Despite the rapid growth and significant benefits of online learning, retaining students in online courses remains a key challenge. This study empirically tests an integrated model that simultaneously examines factors influencing students’ attainment of flow experience in online learning and the impacts of flow on their online learning continuance intention. The results identified telepresence as the most significant factor influencing students’ flow experience in online learning. Perceived hedonic value played the most important mediating role transmitting the effects of flow on students’ continuance intention. The implications of the study for both research and practice are discussed.     

Learning style as a factor which affects the quality of e-learning

With the aid of the Internet, many organizations and schools have adopted the idea of applying the e-learning system, which is considered as one of the most important services provided by the Internet. The purpose of this paper is to investigate the factors affecting the acceptance and use of e-learning system. There are a number of implicit and explicit frameworks designed to inform e-learning practice. Some of them suggest key components that influence the quality of the e-learning experience: technology, pedagogy, organizational context and creativity. Instructor feedback and student learning styles, significantly affect the perceived learning outcomes of e-learning students. Namely, quality of education will significantly be enhanced if instructors modify their teaching styles to accommodate the learning styles of all students in their classes. When the teacher creates the lesson plan, it is desirable that he or she puts as many activities as possible which will reflect different learning styles. Whereas, students have diverse backgrounds, abilities, and knowledge bases, teachers who are able to use various instructional strategies have been shown to be more effective than those who just use single strategies.     

The role of experience and innovation characteristics in the adoption and continued use of e-learning websites

With the advent of e-learning technologies in the past decade, the accessibility of training, teaching, and learning has drastically increased. The challenge for the education enterprise now is how to attract learners to their e-learning services. In this study, a technology adoption model is developed to predict the users’ intention of adoption and their continued use behavior. The results show significant evidence in support of the hypothesis. The findings indicate that perceptions of relative advantage and compatibility are significantly related to users’ intention to use e-learning. Also, the intention is significantly related to their actual use of e-learning. Furthermore, the technology adoption of learners with prior e-learning experience is different from those without prior e-learning experience. These findings may contribute to deeper understanding of e-learning users’ perceptions in terms of adoption and continued use behavior.     

Student’s perceptions towards using e-learning via Facebook

Research on utilising social networks for teaching and learning is relatively scarce in the context of information systems. There is far more emphasis on studying the usage of social networks towards fulfilling individuals’ basic social needs. This study uses the unified theory of acceptance and use of technology (UTAUT2) to analyse students’ intention to use and use of e-learning via Facebook. It incorporates playfulness into the UTAUT2 model and categorises the determinants of intention to use e-learning via Facebook into three categories, namely, hedonic values, utilitarian values, and communication values. The data were collected in a two-stage survey from 170 undergraduate students, and the model was tested using structural equation modelling. We found that hedonic motivation, perceived playfulness, and performance expectancy were strong determinants of students’ intention to use e-learning, while habit and facilitating conditions all positively affected students’ use of e-learning via Facebook. The results of this study report new knowledge that academic institutions can utilise to create appropriate e-learning environments for teaching and learning. A number of theoretical and managerial implications for universities’ implementation technologies were also identified.     

Multi-dimensional students’ evaluation of e-learning systems in the higher education context: An empirical investigation

There has been little research on assessment of learning management systems (LMS) within educational organizations as both a web-based learning system for e-learning and as a supportive tool for blended learning environments. This study proposes a conceptual e-learning assessment model, hexagonal e-learning assessment model (HELAM) suggesting a multi-dimensional approach for LMS evaluation via six dimensions: (1) system quality, (2) service quality, (3) content quality, (4) learner perspective, (5) instructor attitudes, and (6) supportive issues. A survey instrument based on HELAM has been developed and applied to 84 learners. This sample consists of students at both undergraduate and graduate levels who are users of a web-based learning management system, U-Link, at Brunel University, UK. The survey instrument has been tested for content validity, reliability, and criterion-based predictive validity. The analytical results strongly support the appropriateness of the proposed model in evaluating LMSs through learners’ satisfaction. The explanatory factor analysis showed that each of the six dimensions of the proposed model had a significant effect on the learners’ perceived satisfaction. Findings of this research will be valuable for both academics and practitioners of e-learning systems.     

Developing early warning systems to predict students’ online learning performance

An early warning system can help to identify at-risk students, or predict student learning performance by analyzing learning portfolios recorded in a learning management system (LMS). Although previous studies have shown the applicability of determining learner behaviors from an LMS, most investigated datasets are not assembled from online learning courses or from whole learning activities undertaken on courses that can be analyzed to evaluate students’ academic achievement. Previous studies generally focus on the construction of predictors for learner performance evaluation after a course has ended, and neglect the practical value of an “early warning” system to predict at-risk students while a course is in progress. We collected the complete learning activities of an online undergraduate course and applied data-mining techniques to develop an early warning system. Our results showed that, time-dependent variables extracted from LMS are critical factors for online learning. After students have used an LMS for a period of time, our early warning system effectively characterizes their current learning performance. Data-mining techniques are useful in the construction of early warning systems; based on our experimental results, classification and regression tree (CART), supplemented by AdaBoost is the best classifier for the evaluation of learning performance investigated by this study.     

Adapting the Technology Acceptance Model to evaluate the innovative potential of e-learning systems

This paper describes an experience where the Technology Acceptance Model (TAM) has been adapted for use in the evaluation of methodological and technological innovations determined by the introduction of a new e-learning system in an Italian online university. While the original TAM allows one to assess acceptance and adoption of a new technology, in this case there was also a need to consider all the phases of use of the system (course design, running and evaluation), all the users of the system (students, teachers and e-learning management), and all the system’s components (the e-learning platform, the learning resources and mostly the underlying pedagogical approach). The resulting model, which is an extension of the original TAM, is a three-dimensional one, with three aspects to be considered on each axis (phases of use, users and components). For each of the 27 combinations of these aspects, indicators of usefulness and ease-of-use have been identified. When available, data concerning actual use (derived from the tracking functions of the platform) and effectiveness (based on teachers’ adoption of new tools and students’ learning outcomes) have also been used to complement the data.     

Behavioral intention,use behavior and the acceptance of electronic learning systems: Differences between higher education and lifelong learning

Widespread implementation of e-learning systems – learning management systems, virtual learning environments – across higher education institutions has aroused great interest on the study of e-learning acceptance. Acceptance studies focus on the predictors of system adoption and use, with behavioral intention to use the system as a proxy for actual use. This study proposes a TAM3-based model – with the inclusion of two additional variables: personal innovativeness in the domain of information technology and perceived interaction – to study the factors influencing the acceptance of e-learning systems. Attention is also brought towards the role of behavioral intention, especially in its relation with use behavior. In order to do so, two different settings were considered: higher education and lifelong learning; data was gathered from a survey administrated to Spanish graduate and lifelong learning students, and partial least squares analysis was used to test the research model. Results supported TAM relations, except for the intention-behavior linkage, and unveiled a dual nature of perceived usefulness – with one component related to efficiency and performance, and another component related to flexibility. The adequacy of applying TAM3-based models in educational contexts and suitability of actual system usage measures are also discussed.     

Sharing instructors experience of learning management system: A technology perspective of user satisfaction in distance learning course

The use of educational technology increased rapidly in higher education. Learning Management System (LMS) is the most popular educational technology system used in distance learning. There are only a few studies have been carried out to measure instructors satisfaction in distance learning courses, although instructors satisfaction is considered as very important for the course involvement and increasing the students interactions with the course content. Hence, this study proposed a detailed framework to measure instructors’ satisfaction of using LMS. The findings prove that perceived usefulness and service quality are taking the highest share on affecting the instructor satisfactions. This study limited to higher education’s instructors and used a questionnaire survey to collect the data. Hence, the LMS should be designed based on the needs of the instructors as well as the students, by adopting the latest technologies. In the contrary, building LMS without taking the instructors’ satisfaction into account will affect negatively the distance learning course outcomes.     

Evaluation of the interactivity of students in virtual learning environments using a multicriteria approach and data mining

This work seeks to provide a new multicriteria approach to evaluate and classify the level of interactivity of students in learning management systems (LMS). We describe, step by step, the complete methodological development process of the evaluation model as well as detailing the results obtained when applying it to a higher education teaching experience. This research demonstrates that the combined use of multicriteria decision methodologies and data mining prove to be particularly suitable for identifying behavioural patterns of the users through the analysis of records generated in LMS. The results reveal that the behavioural patterns in LMS offer certain indicators as to students’ academic performance, although the study does not permit to state that those students who adopt passive attitudes in these spheres may necessarily produce low academic performance.     

Effect of personal factors to use ICTs on e-learning adoption: comparison between learner and instructor in developing countries

This research investigated some key factors influencing an individual’s behavior to use e-learning in developing countries through social cognitive theory for examining the adoption of e-learning by instructors and learners, who are the key e-learning users. This paper focused on the personal capacity of Information and Communications Technologies and also investigated the mediating effects of computer self-efficacy (CSE) and performance expectation on intention to use e-learning. The results indicate that performance expectation and CSE were crucial factors influencing behavior intention to use e-learning systems for both instructors and learners. This study also found that computer experience and personal innovativeness in the domain of information technology were prominent factors for instructors. In addition, some differences and similarities were identified in the results for instructors and learners. This study used structure equation model, partial least squares, for data analysis, and data were collected from universities in Indonesia.     

Service-Oriented E-Learning Platforms: From Monolithic Systems to Flexible Services

The learning management system (LMS) has dominated Internet-based education for the past two decades. However, the traditional LMS is failing to keep pace with advances in Internet technologies and social interactions online. To support technological diversity, current frameworks such as the e-learning framework (ELF), the IMS abstract framework, and the open knowledge initiative (OKI) have defined the initial steps toward service-oriented e-learning platforms. Next-generation platforms will be based on these service-oriented visions. The authors discuss LMS evolution and present core challenges that must be addressed to achieve information interoperability in next-generation e-learning platforms     

Development path of basic education based on 5G technology and multimedia embedded system

At the moment, the reason is given great interest, pioneering in various fields and point exposure to 5G technology in terms of e-learning. Online learning experience is about existing technology and online bachelor's degree. The survey is about what students are offered that can be carried out with the development of 5G technology in the future just provided. For this purpose, the main multimedia application properties are considered. An analysis of the literature and numerical evaluation is obtained, compared to LTE, which is based on the performance services provided in theory and 5G analysis and simulation results. Education K-12, higher education, trying to find the best way to educate students. The increased amount of data is accepted by 5G (or delayed) due to the lower latency, which can be an excellent capability for VR or other hyper-realistic support experience. Support for embedded systems, their language and culture extends to the platform provides an interface of building blocks needed by other developers.     

Developing Engagement in the Learning Management System Supported by Learning Analytics

Learning analytics is an emerging technique of analysing student participation and engagement. The recent COVID-19 pandemic has significantly increased the role of learning management systems (LMSs). LMSs previously only complemented face-to-face teaching, something which has not been possible between 2019 to 2020. To date, the existing body of literature on LMSs has not analysed learning in the context of the pandemic, where an LMS serves as the only interface between students and instructors. Consequently, productive results will remain elusive if the key factors that contribute towards engaging students in learning are not first identified. Therefore, this study aimed to perform an extensive literature review with which to design and develop a student engagement model for holistic involvement in an LMS. The required data was collected from an LMS that is currently utilised by a local Malaysian university. The model was validated by a panel of experts as well as discussions with students. It is our hope that the result of this study will help other institutions of higher learning determine factors of low engagement in their respective LMSs.     

The influence of system characteristics on e-learning use

The benefits of an e-learning system will not be maximized unless learners use the system. This study proposed and tested alternative models that seek to explain student intention to use an e-learning system when the system is used as a supplementary learning tool within a traditional class or a stand-alone distance education method. The models integrated determinants from the well-established technology acceptance model as well as system and participant characteristics cited in the research literature. Following a demonstration and use phase of the e-learning system, data were collected from 259 college students. Structural equation modeling provided better support for a model that hypothesized stronger effects of system characteristics on e-learning system use. Implications for both researchers and practitioners are discussed.     

Using an Interactive Online Tutorial to Expand Library Instruction

This article presents the design and assessment of an online, interactive, information literacy tutorial for first-year composition students at a community college. The objective of the tutorial was to use technology to teach basic research skills effectively, thereby extending the staff-limited reach of in-person information literacy programs. The tutorial used different types of interactivity to promote student learning in an online environment. Interface design and e-learning best practices enhanced the user experience and usability of the tutorial. Through sound pedagogical and design principles, students exhibited learning in all areas.     

Multi-dimensional students’ evaluation of e-learning systems in the higher education context: An empirical investigation

There has been little research on assessment of learning management systems (LMS) within educational organizations as both a web-based learning system for e-learning and as a supportive tool for blended learning environments. This study proposes a conceptual e-learning assessment model, hexagonal e-learning assessment model (HELAM) suggesting a multi-dimensional approach for LMS evaluation via six dimensions: (1) system quality, (2) service quality, (3) content quality, (4) learner perspective, (5) instructor attitudes, and (6) supportive issues. A survey instrument based on HELAM has been developed and applied to 84 learners. This sample consists of students at both undergraduate and graduate levels who are users of a web-based learning management system, U-Link, at Brunel University, UK. The survey instrument has been tested for content validity, reliability, and criterion-based predictive validity. The analytical results strongly support the appropriateness of the proposed model in evaluating LMSs through learners’ satisfaction. The explanatory factor analysis showed that each of the six dimensions of the proposed model had a significant effect on the learners’ perceived satisfaction. Findings of this research will be valuable for both academics and practitioners of e-learning systems.     

An empirical development of critical value factors (CVF) of online learning activities: An application of activity theory and cognitive value theory

According to activity theory, activities are at the center of human behavior. Extensive attention has been given in literature to the success and effectiveness of online learning programs. Value theory suggests that human perceived value is a critical construct in investigating what is important to individuals. However, very limited attention has been given in literature to the role of users’ perceived value of learning activities in educational settings. Scholars suggest that additional studies on learning activities are needed in order to progress the current knowledge of the use of information systems in education. Therefore, this study investigated issues related to learners’ perceived value by uncovering the critical value factors (CVFs) of online learning activities. Participants in this study included 209 graduate students attending an online learning program. This study extended the first phase done in a prior research to uncover the CVFs of online learning activities. Results of this research study produced five reliable CVFs: (a) collaborative, social, and passive learning activities; (b) formal communication activities; (c) formal learning activities; (d) logistic activities; and (e) printing activities.