Emerging Technologies Acceptance in Online Tutorials: Tutors’ and Students’ Behavior

Susilo, Adhi (2013) Emerging Technologies Acceptance in Online Tutorials: Tutors’ and Students’ Behavior. Doctoral thesis, Simon Fraser University.

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Abstract

The goal of this study was to investigate the factors that may affect tutors’ and students’ intentions to use emerging technologies (ETs) in online tutorials. Based on a literature review, this study proposed a theoretical model predicting tutors’ and students’ intentions to use ETs based on their ETs reaction (ETsR), ETs understanding (ETsU) and technology competencies (TCs). Consequently, it examined the relationships of three independent variables to the dependent variable, intention to use ETs. A Web-based survey was designed to empirically assess the effect of the aforementioned constructs on tutors’ and students’ intentions to use ETs in online tutorials. The web-based survey was developed as a multi-item measure using a Likert-type scale. Existing validated items were used to develop the web-based survey. The target population of this study was tutors and students of the Open University of Indonesia (Universitas Terbuka-UT). This constituted 436 potential survey tutor participants and 3,385 student participants. The data collected consisted of 159 responses from tutors (126 fully completed), representing a response rate of 36.5% and 1,734 responses from students (1,201 fully completed), 51.2% response rate. Four statistical methods were used to formulate and test predictive models: Exploratory Factor Analysis (EFA), Multiple Linear Regression (MLR), Ordinal Logistic Regression (OLR) and Binary Logistic Regression (BLR). Based on tutor data, results were mixed since each variable was significant in the different analysis. However, from the qualitative data, TC was the most important contributor to BI. The theoretical model was able to predict instructors’ and students’ intention to use ETs in online tutorials. However, not all three independent variables showed significant relationships with the dependent variable. Based on student data, results of MLR and OLR analyses were consistent on emerging technologies reaction (ETsR) and technology competencies (TC) as having the greatest weight on predicting students’ intentions to use ETs, while ETsU was found to have the least weight. Therefore, Universitas Terbuka should concentrate its efforts to improve tutors’ and students’ technology competencies as it was found to be the most significant factor.

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