The Impact of Motivation and Personality on Academic Performance in Online and Blended Learning Environments

This study investigates the impact of students' motivation and personality traits on their academic performance in online and blended learning environments. It was conducted with students attending a mandatory introductory information technology course given in a university in Turkey. The Big Five Inventory and Motivated Strategies for Learning Questionnaire were completed by a total of 316 students. A learning management system (LMS) was used for online collaboration and accessing course materials. At the end of the course, information on the accessibility of LMS and students' academic performance including their exam results was obtained. The Bayesian Structural Equation Modeling was used to examine academic performance in terms of its relationship with motivation and personality. In the online learning environment, the results showed that the conscientiousness trait was significantly related to LMS use whereas in blended learning, there were no significant relations between personality traits and LMS use. Self-efficacy was found to be the predictor of LMS use in the online environment while task value and test anxiety were the predictors in the blended learning environment. Conscientiousness and LMS use were significantly related to course grades in both learning environments. Finally, self-efficacy for learning performance was also associated with course grades in the online learning environment

Work in Progress - A Modified Technology Acceptance Model for E-Assessment: Intentions of Engineering Students to Use Web-Based Assesment Tools

With the usage of information technologies in education field, e-assessment that uses information technology to assess students learning started to become popular. Web-based testing, a type of e-assessment, seems to have advantages when compared to traditional testing, like costing, reliability, ease of use etc. Although it seems to have advantages, students' intentions to use web-based assessment tools are needed to be researched to identify the factors that affect students' acceptance of such technologies as well as to enhance these tools by taking into account the needs of users. This paper presents the work in progress in order to determine the factors that affect engineering students' intentions to use web-based assessment systems. The study takes Technology Acceptance Model as a base for research model and by adding new external factors that affect users' intention towards to use web-based assessment which will help the improvement of web-based assessment tools by considering users needs

A Systematic Review of Technology Acceptance Model in e-Learning Context

In this study, a systematic review was performed to identify the factors that affect adoption of e-learning systems by end-users. There are different studies in literature that examine factors affecting end-users’ e-learning acceptance and adoption. However any single study has not examined existing literature systematically in this context. This systematic review will be helpful to the people who are interested in e-learning and its adoption by providing effective factors in the literature which strongly influence the users’ e-learning and related systems’ perception. More importantly, this systematic review helps to identify the needs of the literature

A Structural Model for Students' Adoption of Learning Management Systems: An Empirical Investigation in the Higher Education Context

With the recent advances in information technologies, Learning Management Systems have taken on a significant role in providing educational resources. The successful use of these systems in higher education is important for the implementation, management and continuous improvement of e-learning services to increase the quality of learning. This study aimed to identify the factors affecting higher education students' behavioral intention towards Learning Management Systems. A research model was proposed based on the belief factors of the technology acceptance model; namely perceived usefulness, perceived ease-of-use and external factors including self-efficacy, enjoyment, subjective norm, satisfaction, and interactivity and control. Then, a self-reported questionnaire was distributed online. A total of 470 higher education students participated in the survey. The proposed structural model was assessed and validated using structural equation modeling, in particular the partial least square method. The predictors of behavioral intention were identified as perceived usefulness, perceived ease of use, enjoyment, subjective norm, satisfaction, and interactivity and control with the validated structural model. The relationships between the influencing factors provided an insight about the students' behavioral intention towards the use of Learning Management Systems. It is expected that the academicians and practitioners will benefit from the design and findings of the current study in their future research