JUCS - Journal of Universal Computer Science 24(8): 1072-1089, doi: 10.3217/jucs-024-08-1072
Analysis of Behavioral Intention to Use Cloud-Based Tools in a MOOC: A Technology Acceptance Model Approach
Miguel Morales Chan‡, Roberto Barchino Plata§, Jose Amelio Medina§, Carlos Alario-Hoyos|, Rocael Hernández Rizzardini¶, Monica de la Roca‡‡ Galileo University, Guatemala City, Guatemala§ University of Alcala, Madrid, Spain| Universidad Carlos III de Madrid, Madrid, Spain¶ Galileo University, Guatemala, Guatemala
Corresponding author: Miguel Chan ( amorales@galileo.edu ) © Miguel Chan, Roberto Plata, Jose Medina, Carlos Alario-Hoyos, Rocael Rizzardini, Monica Roca. This article is freely available under the J.UCS Open Content License. Citation:
Chan MM, Plata RB, Medina JA, Alario-Hoyos C, Rizzardini RH, Roca M (2018) Analysis of Behavioral Intention to Use Cloud-Based Tools in a MOOC: A Technology Acceptance Model Approach. JUCS - Journal of Universal Computer Science 24(8): 1072-1089. https://doi.org/10.3217/jucs-024-08-1072 |  |
Abstract
MOOC students' adoption of cloud-based tools has the potential to enrich the learning process and enhance the management of knowledge. The aims of this study are to evaluate the behavioral intention to use cloud-based tools in MOOC context, and to explore the factors that influence this intention, based on extended technology of acceptance model (TAM). This paper reports the findings of a case study conducted on the edX platform. Survey data collected from 133 end-users were analyzed by using structured equation modeling (SEM) to validate the causal relationship among the various constructs of the research model proposed. The findings suggested that the perceived ease of use and the perceived usefulness influence the attitude toward the cloud-based tools used in a MOOC.
Keywords
Cloud-based tools, MOOC, Codeboard, technology acceptance model, structural equation modeling