Analysis of Behaviour of E-learning Users by Unified Teory of Acceptance and Use of Technology (UTAUT) Model A Case Study of Vocational Education in Halu Oleo University

Abstract

E-learning (EL) as a supporting tool in learning process has increasingly developed because the implementation of the tool will be helpful for both lecturers and students to be more interactive in delivering materials and to evaluate learning outcomes. Analysis of the user’s behavior was required to measure the success rate of the implementation of e-learning. One of the models used in the present study was Unified Theory of Acceptance and Use of Technology (UTAUT). The model was designed to explain the behavior of the users on the information technology. The main variable was behavioral intention with four elements namely performance expectancy, effort expectancy, social influence and facilitating conditions. Data were collected randomly from the students of vocational education, university of Halu Oleo by distributing questioners to the e-learner users. The data were then validated and analyzed using regression analysis. The results showed EL affected the behavioral intention, performance expectancy, effort expectancy, social influence and facilitating conditions.

Examining the Use Behaviour of Augmented Reality Technology Through Marlcardio: Adapting the Utaut Model

“…This contradicts the finding of Venkatesh et al (2003) in UTAUT model. Nonetheless, the findings of this study is similar in other technology adoption model findings (i.e: TAM; Davis, 1989 and TAM2;Venkatesh & Davis, 2000) and recent past studies (i.e : Bharati et al, 2018;Guest et al, 2018 andJaya et al, 2017). The result indicates that MARLCardio is easy to use and does not require a lot of mental effort to comprehend the usage.…”

“…Many past studies' findings show that PE had a significant impact towards UB of proposed technology. It is proven in studies by Guest et al (2018), Paulo et al (2018), Jaya et al (2017), Abdullah & Ward (2016) and Mou et al (2016). Unexpectedly, the present study found a contrary finding.…”

“…Thus, EE in this current study is defined as the extent of higher institution students that believe that they will be free of effort when using MARLCardio. Previous research findings provide comfirmatory evidence that there is a relationship between EE and UB (Bharati et al, 2018;Guest et al, 2018;Jaya et al, 2017;Abdullah &Ward, 2016 andMadigan et al, 2016). The relationship between the two variables has also been proven in a study by Shang & Wu (2017) and Lin et al (2015).…”

“…For the purpose of this study, PE is defined as the degree to which a higher institution student believes that using MARLCardio will help to improve their performance in learning process. Past studies' findings reported that PE always had positive impacts in determining the UB of proposed technology in different contexts of study (Bharati et al, 2018;Guest et al, 2018;Paulo et al, 2018;Jaya et al, 2017;Madigan et al, 2016 andAbdullah &Ward., 2016). In online services contexts of study, Lin et al (2014) and Mou et al (2016) found that perceived usefulness is one of the strong indicators in predicting the use of online services.…”

“…A number of previous studies discovered the positive and negative relationship between social influences (SI) and use behaviour of the proposed technology Madigan et al, 2016). Drawing on the UTAUT model, a study by Jaya et al (2017), Maillet et al (2015) and Hamari & Koivisto (2015) indicated that influences among friends or colleagues give a positive impact in a person's decision to use a proposed technology. In meta-analysis findings, Abdullah & Ward (2016) showed 27 out of 32 studies that confirmed the relationship of SI in determining the use of technology.…”