Insights Into the Factors Influencing Student Motivation in Augmented Reality Learning Experiences in Vocational Education and Training Page: 3
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Motivational Factors in Augmented Reality
Universal Design for Learning (UDL)
The UDL is a validated framework that is based on neuroscience
research for addressing students' variability and avoids barriers
in the learning process (Meyer et al., 2014). The UDL defines
a set of principles that forms a practical framework for using
technology to maximize learning opportunities for every student
(Rose and Meyer, 2002). These three principles are: (1) Provide
multiple means of engagement; (2) Provide multiple means of
representation; and (3) Provide multiple means of action and
expression. These principles are divided into guidelines and a
wide variety of check points that provide recommendations on
how to address students' variability and avoid barriers in the
learning process. These guidelines and checkpoints that are based
on previous research provide insights into some aspects that have
a positive impact on learning and motivation. In this paper we
draw on the UDL framework together with the motivational
design for learning theory to explain the relationship between
some of the variables considered in this study (use of scaffolding,
real-time feedback, learning outcomes, degree of success, and time
on-task) with respect to student motivation. We draw on the
UDL to explain how and why these variables might affect student
motivation. In particular, we draw on the third UDL principle
which is closely related to student motivation as one of the drivers
of learning. Although the variables considered in this study do
not come only from the UDL framework, the UDL framework is
an important theoretical foundation that might provide us with
insights into how some variables might have a positive effect on
student motivation as one of the main aspects of expert learning.
AR and Student Motivation
Research on AR in education has shown that, among many other
advantages, AR experiences are useful for increasing student
motivation when compared to non-AR experiences (Radu, 2014;
Akqayir and Akqayir, 2017). Some studies have analyzed the
impact of AR on student motivation using the ARCS model of
motivation as summarized in Table 1. For each dimension, a (v)
indicates the dimensions in which AR had a remarkable effect and
a (+) symbol indicates a positive effect but not remarkable.
Together these studies have used the ARCS model of
motivation to represent the students' levels of motivation.
However, these studies do not clearly report which are the
components of each AR application that positively affect the
dimensions of the ARCS model of motivation. Consequently,
it is still unclear how an AR application might affect student
motivation. Apart from the ARCS model and the IMMS
instrument, some researchers have used other questionnaires
(and models) of motivation and they have found a positive
impact of AR on student motivation. For instance, the study by
Nachairit and Srisawasdi (2015) used the Scientific Motivation
Questionnaire (SMQ), Martin-Gutierrez and Meneses (2014)
used the R-SPQ-2F instrument. Other researchers have
developed their own questionnaires to collect data about
student motivation: Yin et al. (2013); Fonseca et al. (2014);
Restivo et al. (2014); Laine et al. (2016). However, all of these
studies also fall short in identifying the components of AR
applications that might help to increase student motivation.
According to Cheng and Tsai (2013), more research needs to be
conducted in other dimensions of the learning experience such
Predictors of Student Motivation
Some studies report features, aspects or traits that might have
impact on student motivation in ARLEs. Table 2 shows these
studies and the variables reported on each study.
Overall, these studies provide insights into the variables that
influence student motivation in ARLEs. However, these studies
do not clearly report how these variables are connected with the
components of AR applications and therefore it is not possible
to determine which components of AR applications might
produce a positive impact on student motivation. Thus, our study
aims to contribute to the identification of the components of
AR applications that might positively affect student motivation
(modeled by the ARCS model of motivation) in ARLEs. We
hypothesize that the identification of the components of AR
applications that positively affect student motivation might help
to inform the design and development of AR applications that
effectively increase student motivation.
The Mobile AR Application: Paint-cAR
Paint-cAR is a marker-based mobile AR application for
supporting the teaching and learning process of repairing paint
on a car in the context of the VET program on Car Maintenance.
Repairing paint on a car is a complex process comprising a
total of 30 steps divided into 6 phases (Cleaning, Sand down,
Applying putties, Applying sealers, Painting, and Applying Clear
Coats). Each phase has an average of five steps and each step
in the process represents a task that needs to be done by using
TABLE 1 1 Studies that used the ARCS model to analyze the impact of AR on student motivation.
Chen et al., 2016
Chiang et al., 2014
Ibanez et al., 2015
Di Serio et al., 2013
Chin et al., 2015
Wei etal., 2015
Frontiers in Psychology I www.frontiersin.org
Food chain (science)
Aquatic animals and plants (science)
Principles of electricity
Italian renaissance art
Creative design teaching
August 2018 1 Volume 9 1 Article 1486
Bacca et al.
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Bacca, Jorge; Baldiris, Silvia; Fabregat, Ramon & Kinshuk. Insights Into the Factors Influencing Student Motivation in Augmented Reality Learning Experiences in Vocational Education and Training, article, August 21, 2018; Lausanne, Switzerland. (https://digital.library.unt.edu/ark:/67531/metadc1234368/m1/3/: accessed March 19, 2019), University of North Texas Libraries, Digital Library, https://digital.library.unt.edu; crediting UNT College of Information.