Investigating learners’ motivation towards a virtual reality learning environment: a pilot study in vehicle painting

Full text

Investigating learners’ motivation towards a virtual
reality learning environment: a pilot study in vehicle
painting
1st Miriam Mulders
University of Duisburg Essen Learning
Lab
Essen, Germany
miriam.mulders@uni-duisburg-essen.de
Abstract—The HandleVR project develops a Virtual Reality
(VR) training based on the 4C/ID model [1] to train vocational
competencies in the field of vehicle painting. The paper presents
the results of a pilot study with fourteen aspirant vehicle painters
who tested two prototypical tasks in VR and evaluated its
suitability, i.a. regarding their learning motivation. The results
indicate that VR training is highly motivating and some aspects
(e.g., a virtual trainer) in particular promote motivation. Further
research is needed to take advantage of these positive motivational
effects to support meaningful learning.
Keywords—virtual reality, motivation, immersive learning
environments
I. INTRODUCTION
Virtual Reality (VR) technologies are increasingly promoted
as a promising educational tool in diverse training settings [2],
[3]. They offer a variety of exciting and enjoyable learning
experiences and can elevate learners’ situational interest and
motivation more than conventional learning media [4]-[8].
Immersive environments create a sense of presence, which
motivates the learners to pay attention to the content, thereby
causing the learner to process the material more deeply and
persisting throughout the entire learning session, which can lead
to better learning outcomes than other learning media [9]-[11].
The purpose of this pilot study is to explore, which aspects
of VR learning environments, designed according to an
instructional design model, are stimulating learning and which
aspects are less motivating. First, I will introduce the construct
motivation, following its importance in the context of VR
learning environments. Subsequently, the underlying VR
learning environment, methods, and results of the pilot study
building upon it will be explained. Finally, I will identify factors
within VR learning environments that influence motivation and
that should be considered when conceptualizing highly
motivating and meaningful learning scenarios.
II. THEORETICAL BACKGROUND
A. Motivation
Motivation is defined as an internal state or condition that
activates, guides, maintains, or directs behavior [12]. This
psychological factor has found to affect learning effectiveness
by many researchers [13]-[18]. High motivation is associated
1The HandLeVR research project is funded by the Federal Minister of Education and
Research with partners from the University of Potsdam, the University of Duisburg-
Essen, ZWH e.V. and Mercedes Benz.
with situational interest. According to the interest theory [19],
[20], situational interest can stimulate and boost individual
motivation to learn [21]-[23]. Those who are highly motivated
are more likely to engage, put in more effort to understand the
learning material, and be resilient when overcoming obstacles in
understanding [21], [24]. A high level of motivation may cause
the learner to stay focused and invest more cognitive resources
to difficult parts of the task.
B. Motivation within VR learning environments
In VR learning environments, motivation is a potentially
important but an understudied factor. However, some studies
have already shown that VR learning applications can spark
situational interest and trigger a high level of motivation [25],
[26]. Further studies pointed to a positive correlation between
motivation and learning effectiveness [27]-[29]. Some research
is focused on specific aspects of VR learning environments that
trigger motivation. Next to motivating effects through the
realism of the scene, dynamic displays, and close-loop
interaction [29], physical interaction facilitates the learning
motivation [30]. Incorporating an intelligent feedback system
for progress will boost learner’s self-efficacy as well, which
would in turn enhance motivation [11]. Other studies reported
that a strong impact on motivation can be obtained through a
virtual learning companion or teacher, that provides constructive
feedback, shows sensitivity and interest to the individual
learning progress, and displays enthusiasm when achieving
good results and disappointment when failing [10], [31], [32].
Thus, [33] noted that “lifelike, interactive digital characters,
serving as mentors and role-playing actors, have been shown to
significantly improve learner motivation and retention.” (p.75).
III. METHODS
A. VR research project
In the research project HandLeVR 1, a highly validated
instructional design model, namely the 4C/ID model [1], is
applied to enable competence-based training in the field of
vehicle painting resulting in the “VR-painting shop”. The model
was originally developed to train complex cognitive skills and
provide instructional principles to design effective training
programs. It focuses on four principles of meaningful learning.
“Learning tasks” (1) imply that learners should train whole and
authentic tasks with rising complexity over time. In HandLeVR,
390
2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)
978-1-7281-7463-1/20/$31.00 ©2020 IEEE
DOI 10.1109/AIVR50618.2020.00081

this was achieved by implementing customer orders which are
taken from a German company for car painting. Furthermore,
the training of vehicle painters inherently requires a considerable
amount of instructions and feedback regarding correct
procedures and strategies as well as motion sequences.
Procedures and strategies are addressed by the principle of
“supportive information” (2), which supports schema
con
struction and the development of mental models.
In
HandLeVR, these information units were presented by oral or
written statements of a human virtual trainer, by slide shows
(e.g., about safety at work), by tables (e.g., about performance
criteria) and by short videos (e.g., a trainer explains how to
prepare work pieces). Motion sequences are addressed by the
principle of “just-in-time-information” (3), which provides
context-specific information and corrective feedback during
task execution. In HandLeVR,“just-in-time-information” is
provided by tools indicating the right motions during the
painting process (e.g., a beam that displays the distance to the
workpiece, see figure 1).
Last, the 4C/ID model offers
guidelines for “part-task practice” (4) for highly routine tasks.
“Part-task practice” is particularly important in vehicle painting
as the training of correct and smooth hand-eye-body-
coordination. In HandLeVR, additional training opportunities
with simplified rectangular workpieces are incorporated. After
each learning task, the apprentices receive feedback on their
performance in the form of individual performance parameters
(e.g., paint consumption) and in the form of a heat map, which
shows the coating thickness on the workpiece in color (see
figure 2).
Fig. 1. Paint booth with a workpiece and the user interface on the wall (left
image) and the current version of the paint gun indicating the right distance
(right)
Fig. 2. Heat map of a workp
iece (red: too thick, green: right thickness, blue:
too thin).
B. Pilot Study
Within the pilot study, the first prototype of “VR-painting
shop”is evaluated. Therefore, the study aims to investigate the
general motivation due to the VR learning environment as well
as specific aspects of VR learning environment that trigger
learning motivation. We hypothesize that (1) the “VR-painting
shop”itself
is in general a highly motivating learning tool and
(2) especially certain instructional principles (e.g., “supportive
information”, “just-in-time-information”, constructive feedback
by an intelligent virtual trainer) increase learning motivation.
Within one and a half years of project work, two prototypical
“learning tasks” were developed for VR according to 4C/ID
model [1]. This was done in cooperation with trainers and
trainees in vehicle painting
. The tasks have been evaluated and
re-developed iteratively. Both “learning tasks” illustrateasingle
layer refinishes on two different workpieces. A permanently
present virtual trainer guides the apprentice through the tasks. In
addition to the painting process itself, “learning tasks” contain
several permanently available „supportive information”,
mostly
for preparatory and follow-up activities (e.g., self-made videos
by apprentices about using personal protective equipment).
During the painting process, the apprentice is supported by a
beam indicating the right distance to the workpiece and by
constructive oral and written feedback by the virtual trainer. The
feedback system is adaptive and therefore intelligent. Feedback
is provided individually and depends on the learner's
performance (e.g., visual and acoustic signals in case of errors).
Following the “learning tasks”, simplified training opportunities
with additional support are offered.
In a two-day workshop, aspirant vehicle painters performed
these “learning tasks”. They work on the tasks alone and
independently without external help. Afterwards, they filled in
some questionnaires and were part of a discussion group. The
participants were fourteen aspirant vehicle painters recruited
from a large training provider near Potsdam, Germany (6
women, ages 17-24, M= 19.14, SD = 2.21).
The paper-based materials consisted of several
questionnaires. The FAM [34] records the current motivation in
learning and performance situations. It consists of four scales
(fear of failure, interest, probability of success, challenge) with
a total of 18 items (e.g., “I may not be able to complete the
task.”). Within a discussion group, aspirant vehicle painters
were asked to name more and less motivating elements of the
“VR-painting shop”regarding learning success.
IV. RESULTS
Means and standard deviations of the sample were calculated
(fear of failure: M= 1.97, SD = 0.95; interest: M= 4.36, SD =
1.21 ; challenge: M= 4.95, SD = 0.96 ; probability of success M
= 5.97, SD = 1.01) and compared to different standard values of
non-immersive learning tools [34], [35]. Compared to these
standard values, the
motivation concerning “VR
-painting shop”
is comparable or even higher. Especially the “fear of failure” is
less and the “probability of success” higher, partly more than
one standard deviation. Results of the discussion group revealed
that interaction with the virtual trainer and “supportive
information”, particularly the videos, were helpful and
motivating. Many aspirant vehicle painters emphasized that they
enjoyed communicating and interacting with the virtual trainer
as well as receiving feedback from him. They stated that they
are pleased to meet him again in the further “learning tasks”.
This result is consistent with prior research that stress the
391

importance of a virtual teacher [31]-[33]. Future VR learning
environments should rely on artificially intelligent trainers to
individually support learners and therefore increase learning
success. “Supportive information” was described as “nice
variety through media change” and “refreshingly different”.
“Just-in-time-i
nformation” could only partly
motivate learner.
Some of them were described as “confusing” and “overload”.
Just as some “just-in-time-information”, “part-task practice”
was not perceived as a motivating element, but as “monotonous”
and “boring without any additional value for learning”.
V. DISCUSSION
Results indicate that the “VR-painting shop”, designed
according to 4C/ID model
[1], as a training tool for aspirant
vehicle painters offers advantages for learners’ motivation.
Motivation in VR learning environments has not yet been
investigated sufficiently. Therefore, the pilot study points out the
importance of learners’ motivation within the learning process.
Investigating which aspects of “VR-painting shop”are less or
more motivating, was
somewhat
difficult. Concluding, a virtual
trainer and additional support in different presentation forms
were perceived as highly motivating, whereas other instructional
principles seem to fail to promote motivation. However, it
should be noted that the first prototypes of the “VR-painting
shop”were tested. Unsuccessful attempts to implement
instructional principles could be the reason for missing
motivational effects, too. Furthe
r research is needed to examine
which aspects of a VR learning environment promote
motivation to utilize benefits of a high learning motivation as
high frustration tolerance or high willingness to learn [21], [24].
Therefore, a larger sample, a more sophisticated experimental
design with control groups as well as various VR learning
environments in different training settings are necessary
.
Additionally, comparisons between inexperienced and
experienced learners as well as long-term studies are needed to
differentiate between initial situational interest triggered by a
new immersive medium (“novelty effect”) [36] and long-lasting
motivation caused by appropriate instructional methods.
Taken together, VR offers a very high potential in education
by making learning more motivating and engaging [37]
-
[39].
Following up on this research, this pilot study has two major
contributions: First, it indicates that training in VR in vocational
education for aspirant vehicle painters is highly motivating.
Second, some elements of the 4C/ID model [1] seem to be
suitable to create motivational “learning tasks”, especially the
„supportive information”and the virtual trainer. In the future,
we plan to conduct more research projects with more advanced
study designs (e.g., enhanced training applications, a larger
sample, long-term effects) to obtain these motivational benefits
to support meaningful learning.
REFERENCES
[1] J.J. Van Merriënboer and P. A.
Kirschner
, Ten steps to complex learning:
A systematic approach to four-component instructional design.
Routledge, 2018.
[2] D. Allcoat and A. Mühlenen, “Learning in virtual reality: Effects on
performance, emotion and engagement,” Research in Learning
Technology, vol. 26, 2018.
[3] T. A. Mikropoulo
s and A.
Natsis, A. “Educational virtual environments:
A ten-year review of empirical research (1999–2009),” Computers &
Education, vol. 56, no. 3, pp. 769–780, 2011.
[4] W, Kintsch, “Learning from text, levels of comprehension, or: Why
anyone would read a story anyway,” Poetics,
vol.
9, pp. 87–98, 1980.
[5] S. E. Wade, “How interest affects learning from text,” in The role of
interest in learning and development, K. A. Renninger, S. Hidi and A.
Krapp, Hillsdale, NJ: Erlbaum, 1992, pp. 255–278,
[6] M . Limniou, D. Roberts, D. and N.
Papadopoulos
, “Full immersive virtual
environment CAVETM in chemistry education,” Computer & Education,
vol. 51, 584–593, 2008.
[7] H.H. Mei and L. D. Sheng, “Applying situated learning in a virtual reality
system to enhance learning motivation,” International journal of
information and education technology, vol. 1, no. 4, pp. 298-302, 2011.
[8] B. D. Lund and T. Wang, “Effect of Virtual Reality on Learning
Motivation and Academic Performance: What Value May VR Have for
Library Instruction?,” Kansas Library Association College and University
Libraries Section Proceedings, vol. 9, no. 1, p. 4, 2019.
[9] K. C. Shim, J. S. Park, H. S. Kim, J. H. Kim, Y. C. Park and H. I. Ryu,
“Application of virtual reality technology in biology education,” Journal
of Biological Education, vol. 37, no. 2, pp. 71–74, 2003.
[10] H. M. Huang, U.
Rauch
and S. S. Liaw, “Investigating learners’ attitudes
toward virtual reality learning environments: Based on a constructivist
approach,” Computers & Education, vol. 55, no. 3, pp. 1171-1182, 2010.
[11] J. Parong and R. E. Mayer, “Learning science in immersive virtual
reality,”
Journal of Educational Psychology,
vol. 110, no. 6, 785, 2018.
[12] P. R. Kleinginna and A.M. Kleinginna, “A categorized list of motivation
definitions, with a suggestion for a conse nsual definition,” Motivation and
emotion, vol. 5, no. 3, pp. 263-291, 1981.
[13] M. C. Salzman, C. Dede,
R. B.
Loftin and J. Chen, “A model for
understanding how virtual reality aids complex conceptual learning,”
Presence: Teleoperators and Virtual Environments, vol. 8, no. 3, pp. 293-
316, 1999.
[14] M. Alavi and D. E. Leidner, “Research commentary: Technology-
mediated learning - A call for greater depth and breadth of research,”
Information Systems Research, vol. 12, no. 1, pp. 1-10, 2001.
[15] G. Piccoli, R. Ahmad and B. Ives, “Web-based virtual learning
environments: A research framework and a preliminary assessment of
effectiveness in basic IT skills training,”
MIS Quarterly,
vol. 25, no. 4,
pp. 401-426, 2001.
[16] R. Benbunan-Fich and S. R. Hiltz, „Mediators of the effectiveness of
online courses,” IEEE Transactions On Professional Communication, vol.
46, no. 4, pp. 298-312, 2003.
[17] A. Sutcliffe,
Multimedia and virtual reality. New York: Lawrence
Erlbaum Associates, 2003.
[18] Z. Wan, Y. Fang and D. J. Neufeld, “The role of information technology
in technology-mediated learning: A review of the past for the future,”
Journal of Information Systems Education, vol. 18, no. 2, pp. 183 –192,
2007.
[19] K. A.
Renninger
and S. Su, “Interest and its development,” The Oxford
handbook of human motivation, pp. 167-187, 2012.
[20] K. A. Renninger, J. E. Bachrach and S. E. Hidi, “Triggering and
maintaining interest in early phases of interest development,” Learning,
Culture and Social Interaction, vol.
23, 100260
, 2019.
[21] R. E. Mayer, E. Griffith, I. Naftaly and D. Rothman, “Increased
interestingness of extraneous details leads to decreased learning,” Journal
of Experimental Psychology: Applied, vol. 14, pp. 329 –339, 2008.
[22] U. Schiefele, “
Situational and individual interest
,” in Handbook of
motivation in school, K. R. Wentzel and A. Wigfield, 2009, pp. 197–223.
[23] A. Wigfield, S. Tonks, and S. L. Klauda, “Expectancy-value theory,” in
Handbook of motivation in school, 2nd ed., 2016, pp. 55–74.
[24]
K. Wentzel and D. B. Miele, Handbook of motivation at school, 2nd ed.,
New York, NY: Routledge, 2016.
[25] G. Makransky, S. Borre̺Gude and R. E. Mayer, “Motivational and
cognitive benefits of training in immersive virtual reality based on
multiple assessments,”
Journal of Computer Assisted Learning,
vol. 35,
no. 6, pp. 691-707, 2019.
392

[26] G. Makransky and L. Lilleholt, “A structural equation modeling
investigation of the emotional value of immersive virtual reality in
education,” Educational Technology Research and Development, vol. 66,
no. 5, pp. 1141-1164, 2018.
[27] M. Wilbourne, “
Intrinsic and extrinsic motivation orientations in the
classroom: Age differences and academic correlates,” Childhood
Education, vol. 82, no. 5, p. 311, 2006.
[28] M. Virvou, G. Katsionis, G. and K. Manos, “Combining software games
with education: Evaluation of its educational effectiveness,” Educational
Technology and Society, vol. 8, no. 2, pp. 54-65, 2005.
[29] E. A. L. Lee, K. W. Wong and C. C. Fung, “How does desktop virtual
reality enhance learning outcomes? A structural equation modeling
approach,” Computers & Education, vol. 55, no. 4, pp. 1424-1442, 2010.
[30] J. C. Yang, C. H.
Chen and
M. C. Jeng, “Integrating video-capture virtual
reality technology into a physically interactive learning environment for
English learning,” Compu ters & Education, vol. 55, no. 3, pp . 1346–1356,
2010.
[31] W. L. Johnson, J. W. Rickel and J. C. Lester, “Animated pedagogical
agents: face
-to-face interaction in interactive learning environments,”
International Journal of Artificial Intelligence in Education, vol. 11, pp.
47–78, 2000.
[32] L. Chittaro and R. Ranon, “Web3D technologies in learning, education
and training: Motivations, issues, opportunities,” Computers &
Education, vol. 49
, no.
1, pp. 3-18, 2007.
[33] E. M. Sims and W. Y. Pike, “Reusable, lifelike virtual humans for
mentoring and role-playing,” Computers & Education, vol. 49, no. 1, pp.
75–92, 2007.
[34] F. Rheinberg, R. Vollmeyer
and B. D.
Burns, „FAM: Ein Fragebogen zur
Erfassung aktueller Motivation in Lern-und Leistungssituationen
(Langversion, 2001),“ Diagnostica, vol. 2, pp. 57–66, 2001.
[35] G. Bachmann, G. (2009). Zielorientierungen und aktuelle Motivation:
eine Integration im Kontext des selbstregulierten Lernens,“ unpublished,
2009.
[36] W. Huang, “Investigating the Novelty Effect in Virtual Reality on Stem
Learning”, Doctoral dissertation, Arizona State University, 2020.
[37] L. Freina and M. Ott, “A literature review on immersive virtual reality in
education: state of the art and perspectives,” The international scientific
conference elearning and software for education, vol. 1, no. 133, pp. 10
-
1007, 2015.
[38] R. Garris, R. Ahlers and J. E. Driskell, J. E. “Games, motivation, and
learning: A research and practice model,” Simulation & gaming, vol. 33,
no. 4, pp. 441-467, 2002.
[39] M. Ott and M. Tavella, “
A contribution to the understanding of what
makes young students genuinely engaged in computer-based learning
tasks,” Procedia-Social and Behavioral Sciences, vol. 1, no. 1, pp. 184-
188, 2009.
393