Enhancing Vocational Training with Augmented Reality

Abstract

This paper introduces the Social Augmented Learning (SAL) application, with which Augmented Reality (AR) can be applied in vocational training and on-the-job training situations. In this way, complex interdependencies of modern industrial machines can be visualized immediately, which facilitates the transmission and training of knowledge-intensive work tasks and leads to an increased training quality. We show the current state of research of AR-use in vocational training and, based on the identified research gaps, formulate the requirements on which the SAL application is based. We will then describe the development, implementation and evaluation of this application, with a focus on the application design. In the context of SAL, we will then answer previously formulated research questions and show further potential for research in the field of vocational training with AR.

Full text

Enhancing Vocational Training with Augmented Reality
Christian Dominic Fehling
University of Wuppertal
Rainer-Gruenter-Str. 21
42119 Wuppertal
fehling@uni-wuppertal.de
+ 49 202 439-1027
Andreas Müller, Mario Aehnelt
Fraunhofer IGD
Joachim-Jungius-Straße 11
18059 Rostock
{andreas.mueller}{mario.aehnelt}@igd-r.fraunhofer.de
+49 381 4024-427
ABSTRACT
This paper introduces the Social Augmented Learning (SAL)
application, with which Augmented Reality (AR) can be
applied in vocational training and on-the-job training
situations. In this way, complex interdependencies of
modern industrial machines can be visualized immediately,
which facilitates the transmission and training of knowledge-
intensive work tasks and leads to an increased training
quality. We show the current state of research of AR-use in
vocational training and, based on the identified research
gaps, formulate the requirements on which the SAL
application is based. We will then describe the development,
implementation and evaluation of this application, with a
focus on the application design. In the context of SAL, we
will then answer previously formulated research questions
and show further potential for research in the field of
vocational training with AR.
Author Keywords
Augmented Reality; E-Learning; Social Learning; Content-
Authoring; Vocational Training; User Studies
ACM Classification Keywords
● Human-centered computing~Mixed / augmented
reality ● Human-centered computing~Computer supported
cooperative work ● Human-centered computing~User
studies
INTRODUCTION
The digital transformation as well as the associated boosts in
technological developments pose challenges for various
professional fields that should not be underestimated. In the
course of digitalization, work and qualification requirements
are changing whereas especially in the field of vocational
and advanced vocational training, the gap between
conventional teaching methods and the everyday work life of
trainees, that is shaped by information technologies, grows.
By embedding digital content in real environments,
Augmented Reality (AR) represents a promising instrument
to develop new forms of workplace-related instruction and
learning arrangements [10]. The positive effects of AR in this
context, for instance on the efficiency of instructions in
relation to an increased attention, participation and
motivation of users [11], were proven in various scenarios.
Furthermore, the experimental and exploratory character of
AR-activities can be combined well with situated and
constructivist learning theories [5].
Despite of this technological potential, AR is currently
seldom used in vocational training or workplace-related
teaching arrangements, respectively. Most notably, the
complexity of content production and maintenance is often
time consuming as well as cost- and labor-intensive and as
such is identified by the authors as an obstacle for a
successful and widespread integration, especially when
authentic 3D data is needed.
In this paper, we present Social Augmented Learning (SAL),
a solution for this problem in form of a high-level designing-
framework [9] that enables content providers from the field
of educational practice to autonomously generate and teach
AR-content, without prior experience in programming or in
creating 3D-objects. At the same time, SAL encompasses a
multimodal learning environment with which trainees can
work on learning content by employing 3D visualization and
AR. SAL was exemplarily implemented, tested, and
evaluated in the context of education in the professional field
of media technologists in print (specifically: sheet-fed offset
printing).
To begin with, this paper will show comparable attempts to
use AR in educational scenarios. After that, we will present
how SAL was developed right from the first draft to the
implementation in a chosen setting and up to the evaluation.
Out of this, we will derive possible implications for the
learning process with AR in a modern knowledge society as
well as further potential research topics.
RELATED WORKS
Terms like the Digital Factory and the Internet of Things
reflect the increasing connection between the real and the
digital world. Interconnected production processes lead to an
increased complexity in activity profiles and therefore to
increased demands on the employees. They not only have to
work in a real environment anymore, for instance on
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machines, but have to master at the same time the virtual,
digital world that permeates this reality like a fine net.
Augmented Reality is particularly suited for preparing
employees during their education for this fusion of real and
virtual work aspects.
Augmented Reality as such describes the interactive,
dynamic and correctly positioned combination of digital
information and data with real objects and surroundings
[1,13]. Even though a multisensory enhancement of
perception can principally be understood by this, current
applications are primarily dedicated to audio-visual use
cases. With these, digital content is either faded in the user’s
field of vision via head-mounted displays or mobile devices.
Augmented Reality in vocational training
Education in the operation and maintenance of machines
(from motor vehicles to the industrial plant) is often
paramount in the training process of industrial-technical
vocational training. These machines are not only getting
more complex – full accessibility (spatial as well as content-
related) cannot be guaranteed for every case due to
increasing automation. By overcoming the media gap
between real and digital training content, AR not only can
visualize machine elements that are otherwise hidden, but
also make the related processes and cause-effect
relationships accessible in a systematic context.
Some studies have already shown how AR can be used in
designing exploratory learning activities with Gamification-
approaches [12] or in expanding conventional learning
media with digital content [7]. During vocational training
and training at the workplace, for instance in the automotive
sector [2], during the assembly of electronic components
[14] as well as during the simulation of military crisis
scenarios [3,6], situations can be trained that would be too
expensive or risky otherwise.
Authoring of Augmented Reality Content
However, the development of AR-applications is an often
lengthy and expensive process. Although various authoring
tools facilitate the creation of AR-applications and -content
(Figure 1), they are often low- or high-level programming-
frameworks, respectively [9], or software development kits
that admittedly provide interfaces for AR-realization, but
have to be tied in applications of their own for this.
Tools that are used especially to create AR-content and that
are also accessible to technological amateurs can among
other things be identified in an AR-browser (e.g. Layar,
Wikitude). However, these are only partly suitable for
complex content – normally, Points of Interests can indeed
be created to link real places to digital content, yet the
interaction, for example with embedded 3D data, is often not,
or only to a limited extend, possible. Particularly for the
application of AR in vocational training, authoring tools are
missing that allow for the intuitive development of learning
content on the basis of authentic 3D data in the sense of a
high-level designing-framework [9].
Figure 1: Schematic view on digital media authoring (based on
[9] and modified to include AR-Authoring examples)
Research Questions
This paper presents with Social Augmented Learning a
solution to bridge these research gaps and answer the
following research questions:
 Which demands on authoring tools for the development
of AR-content can be identified, so that they can be used
by teachers and trainers alike?
 How should an AR-teaching and –learning application
be designed in order to create additional values for
workplace-learning and at formal learning venues with
it (e.g. positive effects on learning outcomes)?
 Can the influences of AR-learning on the transfer of
knowledge and training at the workplace be measured
and if so, how do these turn out quantitatively and
qualitatively?
For this purpose, we describe which parameters were
considered during software development, how the SAL-
application is designed, and how it can be successfully
employed during classes or at the workplace in order to learn
how to use modern machines.
APPROACH, IMPLEMENTATION AND EVALUATION
The SAL-application will be used in the training of media
technologists as well as by teachers to create and present
content, and also by learners for the purpose of self-regulated
learning activities. Next to authoring tools, methods are
needed that allow for self-regulated and exploratory learning
as well as instruments for teachers to carry out well-
structured lessons with the help of SAL.
 Learning tools enable learners to work autonomously as
well as in peer-groups to explore learning content and as
such use AR as a learning medium.
 Presentation tools aid teachers in designing and
implementing AR-based lessons, in which the learning
process on real machines is coupled with the learning of
digital content.
 Authoring tools in the form of WYSIWYG-editors
constitute the technological foundation of the
application, on the basis of which content can be
generated and distributed.

Figure 2: Screenshot of the 3d-visualization
Methodology
During the development of the SAL-application, a design-
based research strategy was adopted. For that, numerous
iterative loops were used in which a) new functions were
implemented, b) the applications were tested in situ in
practical user studies, and c) were then evaluated in order to
identify technical and content-related improvements of the
applications and the contents, respectively.
Application Design
The application design is inspired by the introduced use
cases of creating, presenting, and learning AR-contents. As
suggested, the core components will be first defined and used
to develop learning modules within the authoring tools.
Learning modules are based on a specific 3D model, which
can, for instance, comprise components of a printing
machine. Learning content is presented as sequentially
arranged slides within the modules, which can as such
encompass audiovisual subject content (e.g. text, graphic,
video) next to changes in state of the the 3D model on a per-
slide basis. In the process, the authoring tools follow the
“What You See Is What You Get” concept (WYSIWYG) so
that authors can check the development status of the learning
modules at any time (Figure 2). So-called actions enable
content creators to influence the 3D model without prior
knowledge in programming or designing 3D content. By this
means, single components can be faded in and out,
highlighted with colors, or animated specifically for
individual slides.
Complex interdependencies can be acted out, provided that
they are available as a finished animation. The issue-specific
learning modules that are thus generated can subsequently be
saved and distributed, with the used exchange format being
XML-based. The teaching and learning modes visualize
learning modules and furthermore, provide functions to
present and learn the contents, respectively.
User Studies and Evaluation
In the course of the project, several tests were carried out in
vocational schools, training enterprises, and job training
centers. In the first wave of user studies, 72 trainees and 13
trainers participated in a questionnaire with 35 different
indicator questions as well as 2 open questions and 5
questions to gather statistical data of the participants.
As part of the evaluation, the 35 indicator questions were
summarized in the following indices, with the number of
included questions noted in parenthesis:
Form of learning (5): Summary of questions regarding the
technical aspects of technology assisted learning.
Learning module (4): Evaluation of the quality and
presentation of the learning content.
Application (10): Questions specific to the technical aspects
of the evaluated prototype, e.g. usability and functionality.
Learning process (8): Questions regarding the roles of
trainee and trainer and potential differences in these roles
compared to conventional learning processes.
Teaching and Learning (3): Self-Evaluation of the trainees
regarding the learning success in relation to learning with
mobile devices.
Overall Impression (5): Summarized impressions regarding
the study, not included in table 1 because of redundancies in
the question-design to the aforementioned indices.
Indice
Median
β
p
Form of learning
1.8
.27
< .05
Learning module
1.9
.24
< .05
Application
2.2
.19
n.s.
Learning process
2.1
-.21
n.s.
Teaching and learning
1.7
.26
< .05
Table 1: Evaluation of the trainees, Indices of likert items.
Scale 1 (“totally agree”, “very good”) to 6 („strongly
disagree“, „inadequate“) (n=72)
The quantitative tests show that there is a significant
acceptance of the solution by the trainees, as well as by the
instructors and trainers. The data collected from the students
was further analyzed to evaluate the possible influences of
single indices on the overall impression, with the result that
the indices “Form of learning”, “Teaching and learning” and
“Learning module” are most influential.
In addition, a qualitative survey via guided interviews as well
as a comparative study were conducted, in which the
influence of learning with SAL compared to conventional
learning was determined [8]. A detailed discussion of the
results is outside the scope of this paper, but was already
published on the following website:
http://www.social-augmented-learning.de
CONCLUSIONS AND FURTHER WORK
The digitalization in all areas of life challenges vocational
training against the backdrop of changing work and
qualification requirements in a new way – however, it
contains at the same time many chances to improve the
quality of training. Learning and mastering complex
processes with the aid of a risk-free visualization that
overcomes media disruptions makes new forms of
interactive, collaborative learning possible, which could not
exist without the help of AR.

It was shown, that an application that is going to be used in
vocational training needs to provide tools for content creators
as well as teachers and learners that can be understood
intuitively. With SAL, we described how such tools are
realized on the basis of a WYSIWYG-editor, as well as the
effects of AR on workplace training.
ACKNOWLEDGMENTS
This work is supported by the German Federal Ministry of
Education and Research under Grant 01PF10010.
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