Academic journal article Educational Technology & Society

An Analysis of the Technology Acceptance Model in Understanding University Students' Behavioral Intention to Use E-Learning

Academic journal article Educational Technology & Society

An Analysis of the Technology Acceptance Model in Understanding University Students' Behavioral Intention to Use E-Learning

Article excerpt

Introduction

A recent trend in higher education has been to set up e-learning systems that provide students with online access and learning content. What drives this trend are changes in students' demographic factors, in educational delivery market conditions, and in innovation technology itself (Concannon, Flynn, & Campbell, 2005). There are, however, numerous barriers to the integration of instructional technology into higher education, such as technology infrastructure, faculty effort, technology satisfaction, and graduates competency (Surry, Ensminger, & Haab, 2005). Even many higher online educational institutions have failed due to the high cost of technology, poor decisions, competition, and the absence of a business strategy (Elloumi, 2004). Many universities that provide e-learning face enormous difficulty in achieving successful strategies, including the delivery, effectiveness, and acceptance of the courses (Saade, 2003). Merely offering any conceivable course and attempting to replicate classroom experience online cannot meet the students' needs and may cause unexpected failure (Kilmurray, 2003). University students' persistent frustration in web-based education is another problem in terms of online learning. This drives more student-centered research of online education (Hara, 2000). With the growing reliance on information systems and increasing rapidity of the introduction of new technologies into learning environment, identifying the critical factors related to user acceptance of technology continues to be an important issue (Yi & Hwang, 2003).

Korea takes full advantage of ICT in supporting all levels of education and human-resource development, and e-learning is considered one of the important alternatives for current knowledge-based society (Kim & Santiago, 2005). Korea's e-learning readiness was ranked fifth in the world based on a report of the Economist Intelligence Unit (2003). Most universities have continued to offer partial, blended, or fully online e-learning courses since the late 1990s. At present, most off-line universities have either introduced an e-learning plan or have implemented e-learning. Despite quantitative growth of e-learning, there is growing concern that stresses quality assessment for e-learning in higher education in Korea (Lee, 2006). In addition, barriers in terms of e-learning utilization in universities or colleges still exist (Leem & Lim, 2007).

Consequently, developers and deliverers of e-learning need more understanding of how students perceive and react to elements of e-learning along with how to most effectively apply an e-learning approach to enhance learning (Koohang & Durante, 2003). In addition, knowing students' intentions and understanding the factors that influence students' beliefs about e-learning can help academic administrators and managers to create mechanisms for attracting more students to adopt this learning environment (Grandon, Alshare, & Kwan, 2005). Therefore, it is necessary to conduct research that deals more intensively with learners' perception of, attitude towards, and intention to use e-learning. However, little research has been done in Korea to empirically determine the relationship of university students' e-learning use with personal factors such as perceived usefulness, easiness, attitude, intention to use, and self-efficacy, with social factors such as subjective norm and organizational factors such as system accessibility.

Objectives

This study proposed an integrated theoretical framework of university students' e-learning acceptance and intention to use based mainly on the technology acceptance model (TAM). The objectives of the study were to analyze the relationship of university students' intention to use e-learning with selected constructs such as their attitude, perceived usefulness, perceived ease of use, self-efficacy of e-learning, subjective norm and system accessibility, and to develop a general linear structural model of e-learning acceptance of university students that would provide a school manager or an educator with implications for better implementing e-learning. …

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