Full length articleMobile-Based Assessment: Integrating acceptance and motivational factors into a combined model of Self-Determination Theory and Technology Acceptance
Introduction
With the rapid growth of mobile technologies and the widespread adoption of BYOD policies, Mobile-Based Assessment (MBA) has started to emerge as another delivery mode of assessment - alternative and/or complementary to paper- or computer-based testing (Johnson et al., 2016). MBA offers a number of benefits such as easier administration, time and location independence, ubiquity and context awareness, adaptivity, personalization and social interactivity (Nikou & Economides, 2013).However, despite the important learning opportunities that MBA may provide, its successful development depends on user acceptance. The current study investigates acceptance and motivational factors that influence the acceptance of Mobile-Based Assessment.
The study is based on the Self-Determination Theory (SDT) of Motivation (Deci & Ryan, 2002) and the Technology Acceptance Model (TAM) (Davis, 1989) and has two research objectives.
The first objective is to build a model about the acceptance of mobile-based assessment. While many studies exist about mobile learning acceptance (Liu et al., 2010, Park et al., 2012), no study exists to investigate the acceptance of mobile-based assessment. The current study explores students' acceptance of mobile-based assessment introducing the following external variables: educational content with feedback, students’ mobile device-self efficacy, interactivity and collaboration during the assessment process, and the ubiquity features of mobile device. The study examines the impact of these factors on the behavioral intention to use MBA.
The second objective is to introduce motivational variables into technology acceptance. Researchers argue that in order to achieve a more inclusive approach to technology acceptance in educational contexts, there is a need to introduce motivational variables into the technology acceptance models (Pedrotti & Nistor, 2016). The current study introduces into TAM, the SDT motivational variables of autonomy, competence and relatedness and examines their impact on perceived ease of use and perceived usefulness, predicting behavioral intention to use. While studies exist that relate SDT with information technology (Chen and Jang, 2010, Lee et al., 2015) and e-learning acceptance (Sørebø, Halvari, Gulli, & Kristiansen, 2009), to the best of our knowledge, no study exists to investigate mobile-based acceptance based on both TAM and SDT. Our study is aiming to propose a combined model of both acceptance and motivational factors towards the prediction of students’ behavioral intention to use mobile-based assessment.
The study is organized as follows: the next section provides a brief literature review about the Technology Acceptance Model, Self-Determination Theory of Motivation and a combined view of Technology Acceptance and Self-Determination for e-learning and mobile learning and assessment, providing the rationale for modeling MBA acceptance based on SDT and TAM. Next, the study presents the proposed conceptual model with the hypotheses to be tested. Following that, the sections of methodology (participants, instruments and procedure) and the data analysis and results follow. Discussions and conclusions for the impact in education follow next along with the study limitations and future work.
Section snippets
Technology acceptance model
A critical factor for the successful implementation of any information system is its user acceptance. Technology Acceptance Model (TAM) (Davis, 1989) is a well-established model that is based on the psychological interaction of a user with technology and it addresses the issue of how users accept and use information technology. TAM utilizes the constructs of Perceived Usefulness (PU), Perceived Ease of Use (PEOU) and Attitudes Towards Usage (ATU) to explain and predict technology system
Conceptual framework and hypotheses
Based on the Self-Determination Theory of Motivation (SDT) (Deci & Ryan, 1985) and the original Technology Acceptance Model (TAM) (Davis, 1989), the current study is aiming at providing a combined model of SDT and TAM in order to explain and predict Behavioral Intention to Use (BIU) Mobile-Based Assessment. For that purpose, we have developed the following hypotheses.
Participants
The participants were 140 students drawn from five classes from a senior-level high school in an urban area in Europe. Students were enrolled in an environmental course about biodiversity. All students taught by the same STEM instructor, an experience science teacher. There were 65 males (46%) and 75 females (54%). The average age of students was 16.7 (SD = 1.15). All students had had already used mobile devices either for communication, information searching and entertainment purposes or for
Data analysis and results
Partial Least-Squares (PLS) with Smart PLS 2.0 (Ringle, Wende, & Will, 2005) was used as the analysis technique to predict factors influencing mobile-based assessment adoption. Our sample size exceeds the recommended value of 50 e.g.10 times the largest number of independent variables impacting a depended variable (Chin, 1998).
Discussions and conclusions
The current study introduces motivational factors into technology acceptance, in the context of mobile-based assessment, proposing Mobile Based Assessment-Motivational and Acceptance Model (MBA-MAM). While researchers have already recognized the importance of integrating motivational factors into technology acceptance (Fagan et al., 2008, Pedrotti and Nistor, 2016), not many studies exist with few exceptions (Lee et al., 2015, Zhou, 2016). The study employs the constructs of autonomy,
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