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Purpose>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.Design/methodology/approach>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.Findings>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.Research limitations/implications>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.Practical implications>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.Originality/value>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.

PurposeThe 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.Design/methodology/approachResponses 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.FindingsThe 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.Research limitations/implicationsThe 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.Practical implicationsWith 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.Originality/valueThe 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.

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

Student interactions in distance learning have been a critical element of the transactional distance theory. Research shows that student interactions have a positive effect on learning outcomes. However, little is known about how student interactions can be improved. The need to understand student interactions and to determine the relationships between the variables that are effective in these interactions has become evident. This study aims to investigate the impact of e-learning readiness and the motivations of students in distance learning on student interactions. In addition, it was examined whether motivation mediated the relationship between e-readiness and student interactions. The study was conducted with 172 students enrolled in a postgraduate program conducted by distance learning. Results showed that students' e-learning readiness and motivation are essential predictors of student interactions in distance learning. Furthermore, it was found that motivation had a mediation effect on the relationship between e-learning readiness and student interactions. The results of the research are helpful for both instructional designers and instructors of distance learning who want to reduce the transactional distance by increasing student interactions.

E-learning is an educational method which aims to provide educational or training programs for students or trainees at any time and at any place using information and communication technology (ICT). Increasing numbers of higher education institutions have adopted e-learning in order to take advantage of the opportunities that it offers. Through e-learning, learners can access resources and information from anywhere and at any time. However, the successful implementation of e-learning relies on the readiness to be able to initiate this system because, without proper readiness, the project will probably fail. E-learning readiness refers to the assessment of how ready an institution is to adopt and implement e-learning. E-learning readiness helps higher education institutions to measure their stages of readiness, identify any gaps, and then redesign its strategy in order to adopt the e-learning system. One of the most important aspects of e-learning readiness is the technological aspect, which plays an important role in implementing an effective and efficient e-learning system. There is a lack of agreement about the factors that shape the technological aspects of e-learning readiness; hence, a clear gap has been identified in the knowledge on the technological aspects of e-learning readiness. The aim of this paper is to review the technological factors of e-learning readiness by performing the Delphi technique, and develop an initial model for technological aspects of e-learning readiness in higher education institutions. It is anticipated that this model can help institutions of higher education to identify and understand the technological aspects that must be considered when assessing the readiness to apply an e-learning project.

The study aimed to understand pre-service teachers' mobile learning readiness with Theory of Planned Behavior using external salient beliefs. There were nine hypotheses tested with a total of 533 pre-service teachers in two cities in Turkey. Several scales adapted from Cheon et al. (2012) included 10 psychological variables. The results indicated that the TPB model explained 58% of the variance in intention to adopt mobile learning. The results of structural equation modeling (SEM) showed that the proposed model of the current study has acceptable fit data. The results of the SEM revealed that attitude, subjective norm and perceived behavioral control have significant impact on intention to adopt mobile learning. In addition, salient beliefs had an influence on the constructs of TPB. Therefore, all the hypotheses within the model were statistically supported in understanding determinants of mobile learning readiness. All in all, the study approved the effectiveness of well-structured cognitive psychological model in understanding pre-service teachers' intention towards adoption of mobile learning in the Turkish context. The study has important implications for researchers, educators, education stakeholders, policy makers and mobile learning application designers.

Online instructors in higher education play a key role in the success or failure of electronic learning systems (ELSs). Their expertise in and use of technology tools in ELSs influence the quality of information presented, their system use and satisfaction during course delivery. This study adapted Holsapple and Lee-Post’s (Decis Sci J Innov Educ 4(1):67–85, 2006 ) model to examine online instructor e-learning readiness (e-readiness) at the online campus of a Caribbean university, and to assess their levels of e-readiness and impact before, during and after course delivery. Responses from 208 online instructors were analysed from an online survey. Results show that while the cohort was 90.6 % e-ready, only 72.6 % were individually e-ready by having access to a dedicated network connection for substantial periods of time, routinely communicating with persons using electronic technologies, being self-motivated and independent learners, with a predisposition towards embracing and using new technologies. During the pre-course phase, online instructor e-readiness had a moderate impact on both technical (ELS quality and service quality) and non-technical (information quality) aspects of the ELS. During course delivery, its influence decreased with the technical aspect (ELS use) but increased with the non-technical aspect of the course (instructor satisfaction). At course completion, the main benefit was enhanced teaching skills while lack of contact with others was the main challenge. The results could be used to identify characteristics of online instructors suitable for the online environment, monitor their impact during the phases of a course, and serve as a benchmark for comparing levels of e-readiness across institutions.

Gamification has gained a lot of attention in recent years as a possible way to foster students’ motivation and learning behavior. As a high drop-out rate is associated with distance learning, in particular with students often struggling to engage with the material, the implementation of gamification may support and enhance more successful online learning. A distance learning Bachelor degree class was selected as a case study to investigate the implementation of a Moodle-based gamification concept as well as different variables associated in using a mixed-methods-approach. Eight students were interviewed and 32 participated in an online survey. Significant positive correlations were found between students’ online learning readiness in the dimension of technical competencies and both types of autonomous motivation (identified and intrinsic motivation). A significant positive correlation was also found between self-reported attitudes towards gaming and the dimension of coping of study-satisfaction. As expected, students who indicated rather low online learning readiness tended to show non-autonomous motivation (amotivation). Surprisingly, some students reported autonomous motivation, despite having expressed a rather dismissive attitude towards playing online and computer games in general. Acquiring digital badges reportedly felt like appreciation directly awarded by the students’ instructor. Progress bars were positively evaluated and were accepted as a management tool for individual learning strategies.

PurposeThe article aims examine an integrated model of the technology acceptance model (TAM), the unified theory of acceptance and use of technology (UTAUT) and DeLone and McLean information systems (D&M IS) success model to determine the effects of online learning readiness (OLR) on learners' online learning system (OLS) usage and their satisfaction. The authors also investigate the relationship between performance expectancy, effort expectancy, social influence and OLR of students. Moreover, this work examines the mediate role of learner satisfaction in the linking of OLS usage and performance in Vietnamese higher education.Design/methodology/approachA total of 558 valid questionnaires were collected from students at five large universities in Vietnam to test the fit of proposed model, measurement model and structural relationships between constructs by using partial least squares (PLS) path analytics.FindingsPerformance expectancy, effort expectancy and social influence have significant positive effects on OLR of students in online learning context. OLR has a positive impact on both learner satisfaction and OLS usage. The learner performance is significantly influenced by satisfaction while it is indirectly affected by OLS usage via satisfaction. In addition, OLS usage plays as a partial mediation variable in the relationship between OLR and satisfaction. The path model could explain 56% of variance of the learner performance.Research limitations/implicationsThis study has a few limitations. First, this study is cross-sectional, which allows the elaboration of correlations between variables but lacks confidence in causality exploration. Second, the self-reported data are inherently subjective, which might generate biased results in measuring learner performance.Practical implicationsThis research has implications for instructors and higher education organizations. The findings provide insights for instructors to manage efficiently the OLS adoption of students. Higher education organizations should understand and identify factors in terms of OLR, OLS usage, learner satisfaction and learner performance when OLSs are implemented in university. Performance expectancy, effort expectancy and social influence have been criticized for considering OLR.Originality/valueThis is the first empirical study to determine relationship between performance expectancy, effort expectancy, social influence, OLR, OLS usage, satisfaction and performance in the context of online learning environment in Vietnam.

This study explores the relationship between student readiness for online learning and its impacts on engagement, satisfaction, and academic achievement in Indonesian higher education. Using a mixed-methods design, the quantitative phase employed Structural Equation Modeling (SEM) to reveal that online learning readiness significantly affects student engagement and satisfaction, though its direct effect on academic achievement is weaker. Engagement emerged as a key intermediary that enhances academic outcomes when students are well-prepared for online learning. Qualitative insights further highlighted the importance of technological competence and self-directed learning. The study emphasizes that fostering both technological and pedagogical readiness is crucial for enhancing engagement and satisfaction, thereby indirectly improving academic performance. These insights provide practical guidance for educators and policymakers to optimize online learning frameworks in similar contexts.