Analysis of Behavioral Intention to Use Cloud-Based Tools in a MOOC: A Technology Acceptance Model Approach

Miguel Morales Chan (Galileo University, Guatemala)

Roberto Barchino Plata (University of Alcala, Spain)

Jose Amelio Medina (University of Alcala, Spain)

Carlos Alario-Hoyos (Universidad Carlos III de Madrid, Spain)

Rocael Hernández Rizzardini (Galileo University, Guatemala)

Monica de la Roca (Galileo University, Guatemala)

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, Codeboard, MOOC, structural equation modeling, technology acceptance model

Categories: L.3.0, L.3.3, L.3.5, L.3.6