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The purpose of this study is to explore the role individual innovativeness along with e-learning self-efficacy play in predicting the e-learning readiness of first- and second-year students of an open and distance education institutions in an African context.

Therefore, building on previous related research in this area, a quantitative approach was adopted to address the research questions and to establish whether a statistically significant relationship existed between individual innovativeness, e-learning self-efficacy, the independent variables; and e-learning readiness, the dependent variable. In total, 476 first- and second-years students of the university participated in the four-Likert-type scale survey. The research instrument which comprises 74 survey items was completed by 217 of the students. Statistical tools used for analysing data included both Pearson Product Moment Correlation coefficients and t-tests.

It was discovered that a strong positive and significant relationship was observed between individual innovativeness and e-learning readiness of first- and second-year students of the Yenagoa Study Centre of the National Open University of Nigeria (NOUN); a statistically significant relationship was also found between e-learning self-efficacy scores and the e-learning readiness of the first- and second-year students of the Yenagoa Study Centre of NOUN; there was a statistically significant joint relationship between the three variables under investigation; findings equally revealed that male respondents had higher e-learning readiness than their female counterparts.

Like every other study of this nature, this one also suffers some limitations. First, NOUN is a very large university with over half a million students spread across almost 78 study centres. This means that observation from just one study centre amounts to a very small sample size. This according to Schweighofer, Weitlaner, Ebner and Rothe (2019) jeopardises the generalisability and validity of study results. The authors also maintain that empirical data generated from surveys that usually rely participants' abilities to read and select responses without further interpretation by the researchers suffer from cognitive biases like social desirability. To address the above limitations, detailed studies involving all studies centres of NOUN be undertaken and other qualitative and or mixed research methodologies be adopted in the future.

The implications for this study are that people who are innately innovative will willingly accept technology and by extension, learning in technology-rich environments like those found in like NOUN whose mode of study is blended learning inherently found in open and distance learning (ODL) institution. Therefore, this study is significant as it will provide relevant information to the management and administrators of NOUN, policymakers and regulatory institutions for the development, deployment and implementation of e-learning strategies. Findings will also benefit e-learning initiatives undertaken by similar institutions that adopt the ODL mode of education in Nigeria and other developing countries.

Even though, studies on the antecedents of e-learning readiness have been widely conducted across diverse contexts, studies exploring the associations between individual innovativeness, e-learning self-efficacy and e-learning readiness are relatively hard to come by. The above two variables as predicting the e-learning readiness in the study context are comparatively new. This study thus focuses on the relationships between the individual innovativeness levels, e-learning self-efficacy beliefs of students and their e-learning readiness which ultimately determines their ability to sustain studies in an ODL institution.

Universities have shifted from face-to-face learning environments to e-learning in response to the COVID-19 pandemic. However, the sudden change to online teaching has raised concerns among lecturers about students' readiness for e-learning. This study investigates students' readiness for e-learning during the COVID-19 pandemic and specifically assesses any significant differences between students' gender, age, ethnicity, level of education, field of study and their readiness for an e-learning environment.

The study employed a non-experimental quantitative research design. Data were gathered from a sample of 298 undergraduate and 101 postgraduate students. WINSTEPS Rasch model measurement software was used to determine the reliability and validity of the research instrument. Descriptive, inferential statistics and differential item functioning (DIF) test were used to assess students' readiness for an e-learning mode of instruction with the latter specifically analysing students' demographic factors and their readiness for an e-learning environment.

Findings identified that most students are ready for an e-learning mode of instruction. Further analysis indicated that there were differences in students' readiness for e-learning based on their demographic profiles.

This study provides insights on students' readiness towards e-learning, discusses implications for e-learning practices in higher education institutions during the COVID-19 pandemic and offers recommendations for future research.

This study provides evidences of students' readiness for e-learning in respect to their gender, age, ethnicity, level of education and field of study. This information could help lecturers to reflect on their own teaching practices, adjust their teaching approaches and subsequently, develop appropriate e-learning methods that best suit the student diversity in their classrooms.

E‐learning is emerging as a potential delivery medium for education and training. This is evident from the increasing number of educational institutions and organizations adopting e‐learning. In India, there has been an upsurge in the number of students going for management education. But, before management institutes embark on this e‐learning journey, it is important to assess student readiness for this medium. The purpose of this paper is to examine the awareness levels, degree of familiarity and readiness to accept e‐learning environment.

Exploratory study and personal interviews were conducted to design the instrument which was administered to 240 students pursuing management education at the Indian Institute of Management, Ahmedabad (IIM‐A), which is a premier business school in India. A total of 154 duly filled questionnaires were used for data analysis. Factor analysis, cluster analysis and chi‐square test were carried out to meet the objectives of the study.

Factor analysis resulted in identification of five factors which were given names. Further, two clusters were identified among the respondents. To examine if the cluster profile varied in demographic variables, a chi‐square test showed that none of the demographic variables are statistically related to the clusters.

The sample was comprised of students of a business school and therefore it may not be representative of all students studying business management. Second, since the sample comprised only 17 female students, generalization of results is difficult.

The research holds relevance, as an assessment of prior exposure to technology and comfort level, attitude, behavior and motivation may determine the e‐learners’ readiness to adopt or not adopt this medium.

The paper brings forth student readiness for e‐learning as a medium of education in India. This may serve as a guide to those business schools which have started delivering management education or plan to deliver online education in future.

This study aims to propose a conceptual structural equation model to investigate the relationships among e‐learning system quality, e‐learning readiness, e‐learners' competency as well as learning outcomes, and to demonstrate the direct and indirect effect of e‐learning system quality and e‐learning readiness on learning outcomes from the perspectives of e‐learners' competency.

A questionnaire was distributed to 379 full‐time employees from ten technological companies in Taiwan who have had e‐learning experience (n=379). Data were analyzed by employing structural equation modeling.

Results reveal that both e‐learning system quality and e‐learning readiness have a direct and significant impact on e‐learners' competency. However, e‐learning system quality and e‐learning readiness influence learning outcomes indirectly through e‐learners' competency. In addition, e‐learners' competency has direct and positive significant influence on learning outcomes.

Based on these findings, organizations in Taiwan that would like to implement e‐learning with their employees should focus on improving individuals' online learning skills such as self‐direction, meta‐cognitive, and collaborative skills.

The findings created an understanding of what attributes of external and internal factors influence the outcome of e‐learning in high tech companies. In terms of research contributions, the study extends previous researches by identifying the mediating effect of e‐learning competency on the relationship between e‐learning system quality, e‐learning readiness and learning outcome. Organizations that would like to adopt e‐learning to improve employees' knowledge and skills will be able to apply strategies based on the findings from the research.

The study has identified the factors among students that can enable or inhibit students from using online learning platforms. Students enrolled at different levels, diversified streams and separate courses were surveyed for the investigation. The study also highlights the significant hitches faced in using or adopting e-learning.

Responses were collected from Indian students on a seven-point Likert-type scale using a structured questionnaire around the updated Technology Readiness Index's four dimensions. Adapted dimensions were evolved to identify the people's propensity to accept and reject the new technology.

The result of the survey highlights the students' positive attitude towards the e-learning approach. The diffusion of e-learning platforms occupies them with a feeling of optimism and innovativeness. However, discomfort in using the newly penetrated e-learning platforms was also found. Furthermore, no significant variances concerning the different demographics were detected.

The cross-sectional research approach was used for the investigation. However, it is evident that with the use and experience of technology, an increase in its acceptance follows. Thus, a longitudinal research approach should explore the differences between students' earlier and later involvement after experiencing the platform. A cross-country investigation is also needed to measure the technological biases among students.

With advancements in technology, the chances of diffusion of e-learning in traditional classrooms have risen. However, to encourage the student's engagement towards e-learning, the platform needs to be student and teacher-friendly. This study serves the purpose of exploring the determinants that will guide educational institutes and developers of online platforms in achieving excellence in enhancement and engagement among students.

The investigation adds to recognize the acceptance of e-learning among students by exploring its determinants using the Technology Readiness Index 2.0. The study has also explored the differences in readiness to use e-learning on differences in enrolment level, institute type and courses.

The purpose of this study is to assess Japanese university students’ readiness for taking e-learning language courses. The focus is placed on students’ self-analysis of their abilities to use their smart devices for remote language learning activities.

Japanese university students’ readiness for the shift towards remote learning has been measured by a self-reported online survey. The question items are based on three categories of Gay’s e-readiness models (2018). The survey was conducted before and after the fully online five-month English courses to examine to what extent students’ e-readiness had changed through the progress of the courses.

The results suggest that students have few difficulties using the university e-learning software provided. However, students reported limited enthusiasm and aptitude for the online English language learning components. These levels were approximately the same before and after the courses, with the exception of increased online learning confidence.

This study evaluates to what extent groups of Japanese university students’ e-readiness has changed over time. The survey looks at different perspectives including Web research, time management, enthusiasm for online language learning and their thoughts and opinions about interacting with their classmates. Although the sample size is small, the discussion considers the data in the context of the Japanese learning environment and existing e-readiness research, seeking to provide teaching insights for instructors and suggestions for further research.

Based on the literature on technology readiness, online learning readiness, and mobile computer anxiety, the purpose of this paper is to develop and validate a mobile learning readiness (MLR) scale which can be used to assess individuals’ readiness to embrace m-learning systems.

Based on previous literature, this study conceptualizes the construct of MLR and generates an initial 55-item MLR scale. A total of 319 responses are collected from a three-month internet-based survey. Based on the sample data, this study provides an empirical validation of the MLR construct and its underlying dimensionality, and develops a generic MLR scale with desirable psychometric properties, including reliability, content validity, criterion-related validity, convergent validity, discriminant validity, and nomological validity.

This study develops and validates a 19-item MLR scale with three dimensions (i.e. m-learning self-efficacy, optimism, and self-directed learning). A tentative norm of the MLR scale is presented, and the scale’s theoretical and practical applications are also discussed.

This study is a pioneering effort to develop and validate a MLR scale. The results of this study are helpful to researchers in building m-learning theories and to educators in assessing and promoting individuals’ acceptance of m-learning systems.

Due to the growing complexity involved in leveraging the endless possibilities of ICT on all levels, the technical competence of faculties of higher education institutions (HEI) and effective methods for fostering e-readiness has become questionable.

This research has developed and validated an empirically supported e-readiness scale, which can be used by HEIs to assess faculty members’ preparedness toward online teaching. The measurement model and the structural model were developed as the results of exploratory factor analysis and confirmatory factor analysis (n = 245). The previously identified components and their indicators were validated using the structural models and the final scale was developed with five dimensions (“online technological readiness, pedagogical readiness, institutional readiness, learning and delivery readiness and content readiness”).

The faculties’ e-readiness assessment tool, as a useful tool, could aid institutions in identifying problems that affect the implementation of e-learning or digitalization in the institutions and developing strategies in response.

Like any research this research also has some limitations and can be considered as future research probability like the responses for this research were collected from HEI in India; however, a cross-cultural study can be conducted to understand the parameters across the globe. Although the psychometric qualities of the e-readiness scale are acceptable, additional research in various higher educational environments, both nationally and internationally, is required to further establish the scale’s relevance, validation and generalizability.

Although many scales have been developed to assess the readiness level in the education sector, a scale, that holistically measures, the readiness level of faculties from an overall perspective was required. This scale can be used to recognize the e-readiness level of teachers in HEIs. This scale can also help the institutions assess the readiness level of their faculty members and address any improvements required in their teaching and learning pedagogy, further acknowledging training needs.

The development of e‐learning by government through policy, funding allocations, research‐based collaborative projects and alliances has increased recently in both developed and under‐developed nations. The paper notes that government, industry and corporate users are increasingly focusing on standardisation issues and the scalability of technology platforms to meet demand. This paper assesses the challenges for further development that e‐learning faces in the coming years, including: access to appropriate technology, scalability, measurement, and changed governance structures.

The purpose of this study is to investigate the factors that affect students’ behavioral intentions to use virtual classrooms at Princess Sumaya University for Technology (PSUT) in Jordan.

A quantitative research approach was adopted, an online survey method was used and the data were collected among students at PSUT in Jordan. A total of 511 responses were usable for analysis. A structural equation modeling partial least squares technique was used to examine the hypothesized model.

The findings reveal that the proposed factors have direct and indirect relationships with behavioral intentions to use virtual classrooms. They show that students’ satisfaction has a direct influence on behavioral intention, while other variables such as instructor characteristics, virtual classroom quality, perceived self-efficacy, perceived organizational support, perceived ease of use and perceived usefulness have an indirect effect on behavioral intentions to use virtual classrooms.

The study was conducted at PSUT in Jordan, which could limit the generalizability of the findings. Furthermore, the present study measured students’ behavioral intentions to use virtual classrooms and future research should consider the actual use of virtual classrooms.

The findings of this study offer significant and useful information to policymakers, instructors, developers and students regarding the use of virtual classrooms in universities. Based on students’ needs and readiness, the findings identify which factors to consider when developing an e-learning system to enhance learning and teaching performance.

This study extends existing knowledge by developing a conceptual model to identify the key factors of virtual classroom adoption in higher education institutions in Arab countries. This study contributes to the literature in the context of e-learning by validating an extended technology acceptance model from an Arab countries perspective and considering the differences in culture, learning style and physical environment compared to developed countries.