Evaluating student acceptance level of e-learning systems

The e-learning information systems are widely used in universities to improve their courses, although this does not always achieve the objective of facilitating the teaching-learning process, there are several factors that avoid it. The aim of this study was to adapt a research model that describes the behaviour of use and the intended use of e-learning systems in Ecuador students, based on the Technology Acceptance Model (TAM) developed by Fred Davis. A self-report questionnaire was designed to examine the student's acceptance and attitude towards e-learning system. Data from 263 undergraduate and graduate students were collected in a University of Ecuador. The model is composed of eight constructs, namely, technical support, computer self-efficacy, subjective norms, satisfaction, perceived usefulness, perceived ease of use, intention to use the system and use the system. The model was estimated using structural equation modelling (SEM), for which the software was used R. It was found that the technical support and computer self-efficacy served as the two anchors of significant perception of fundamental constructs in TAM. Satisfaction became the sole determining factor in predicting use, while subjective norms were significant to the prediction of intention to use e-learning system. Overall, subjective norms, computer self-efficacy and perceived ease of use were able to explain the most variation observed in the intention of the students to use e-learning system.Postprint (published version

Evaluating student acceptance level of e-learning systems

The e-learning information systems are widely used in universities to improve their courses, although this does not always achieve the objective of facilitating the teaching-learning process, there are several factors that avoid it. The aim of this study was to adapt a research model that describes the behaviour of use and the intended use of e-learning systems in Ecuador students, based on the Technology Acceptance Model (TAM) developed by Fred Davis. A self-report questionnaire was designed to examine the student's acceptance and attitude towards e-learning system. Data from 263 undergraduate and graduate students were collected in a University of Ecuador. The model is composed of eight constructs, namely, technical support, computer self-efficacy, subjective norms, satisfaction, perceived usefulness, perceived ease of use, intention to use the system and use the system. The model was estimated using structural equation modelling (SEM), for which the software was used R. It was found that the technical support and computer self-efficacy served as the two anchors of significant perception of fundamental constructs in TAM. Satisfaction became the sole determining factor in predicting use, while subjective norms were significant to the prediction of intention to use e-learning system. Overall, subjective norms, computer self-efficacy and perceived ease of use were able to explain the most variation observed in the intention of the students to use e-learning system

Evaluating student acceptance level of e-learning systems

The e-learning information systems are widely used in universities to improve their courses, although this does not always achieve the objective of facilitating the teaching-learning process, there are several factors that avoid it. The aim of this study was to adapt a research model that describes the behaviour of use and the intended use of e-learning systems in Ecuador students, based on the Technology Acceptance Model (TAM) developed by Fred Davis. A self-report questionnaire was designed to examine the student's acceptance and attitude towards e-learning system. Data from 263 undergraduate and graduate students were collected in a University of Ecuador. The model is composed of eight constructs, namely, technical support, computer self-efficacy, subjective norms, satisfaction, perceived usefulness, perceived ease of use, intention to use the system and use the system. The model was estimated using structural equation modelling (SEM), for which the software was used R. It was found that the technical support and computer self-efficacy served as the two anchors of significant perception of fundamental constructs in TAM. Satisfaction became the sole determining factor in predicting use, while subjective norms were significant to the prediction of intention to use e-learning system. Overall, subjective norms, computer self-efficacy and perceived ease of use were able to explain the most variation observed in the intention of the students to use e-learning system