An Empirical Analysis of Mobile Learning Acceptance in Puerto Rico's Higher Learning Institutions

An Empirical Analysis of Mobile Learning Acceptance in Puerto Rico's Higher Learning Institutions

Irvin Renzell Heard
DOI: 10.4018/IJSITA.2017040101
OnDemand:
(Individual Articles)
Available
$37.50
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

This empirical research article employs a quantitative research methodology based on existing research on the Technology Acceptance Model (TAM) to model how college students in Puerto Rico perceive, accept and reject mobile learning technologies before university implementation. This study identifies the factors, perceptions, and attitudes of mobile learning acceptance at the individual level. The TAM themes included in this study are: attitude (A), behavioral intentions (BI), ease of access (EoA), ease of use (EoU), external influence (EI), quality of service (QoS), student readiness (SR), university support (US) and usefulness (U). The article's objective is to examine the determinants and behavioral intentions to use M-learning in higher learning institutions in Puerto Rico. By understanding the determinants, universities, and organizations that deliver educational content can develop intervention programs aimed at increasing user acceptance of M-learning.
Article Preview
Top

Introduction

Technology acceptance has remained an area of continued research, due to technology's continued evolutions. Currently, there is a vast increase in the use of mobile devices and services throughout the world on a social-economical level and geographical locations. The implementation of M-learning technology exhibits an element of uncertainty with decision makers regarding the aspects of adoption. The uncertainty stems from the complexity of users forming attitudes and intentions towards mobile learning technology before any efforts of actual use are applied. The actions towards usage and intentions to use are formed after the introduction of new technology, thus actual usage may not be directly related to or a consequence of the attitudes and intentions to use (Davis, Bagozzi, & Warshaw, 1989). This case study applies the theoretical basis of TAM to explain the impact of external variables such as systems objectives, design, computer self-efficacy and training on the subjective beliefs i.e. behavioral aspects, attitudes toward use, and actual system use (Davis, 1989; Ibrahim & Jaafar, 2011). The objective is to analyze the determining factors of user acceptance and its correlation with M-learning technology in Puerto Rico to develop a predictive path model.

Background of Study

The researcher identified a gap in the literature between the students' acceptance of technology and universities in Puerto Rico (teachers and decision makers) thus conformed into the underlining objectives of examining the social influences and cognitive process of the end user to achieve acceptance. The researcher conducted a quantitative case study of 150 participants through a questionnaire to discover, identify the most influential factors of technology acceptance and capturing the student's perceptions and attitudes that impact mobile learning acceptance in Puerto Rico's higher learning institutions utilizing the key constructs from previous TAM studies adhering to the core principles.

The questionnaire contained grouped questions and factors that assist the prediction of M-learning acceptance. The study was descriptive in nature and formulated to describe the distribution of perceptions. The respondents answered 38 questions on a 7-point Likert scale ranging from strongly disagree (1) to strongly agree (7) and three open-ended questions that were optional. The qualitative questions were only used to better understand the student's perceptions and attitudes towards mobile learning in that region of Latin America.

Complete Article List

Search this Journal:
Reset
Open Access Articles: Forthcoming
Volume 10: 4 Issues (2019)
Volume 9: 4 Issues (2018)
Volume 8: 4 Issues (2017)
Volume 7: 4 Issues (2016)
Volume 6: 4 Issues (2015)
Volume 5: 4 Issues (2014)
Volume 4: 4 Issues (2013)
Volume 3: 4 Issues (2012)
Volume 2: 4 Issues (2011)
Volume 1: 4 Issues (2010)
View Complete Journal Contents Listing