A Virtual Reality based Engine Training System

A Prototype Development & Evaluation

Tami Im, Deukyoung An,

Oh-Young Kwon and Sang-Youn Kim

Online Lifelong Education Institute, Korea University of Education and Technology, Cheon-An, Korea

Keywords: Virtual Training, Vocational Training, Engineering Education, Engagement, Immersion.

Abstract: A Virtual Reality based Engine Training System (VRETS) was developed and tested in this study. This

training system was developed to use a head mounted display and a motion detector to pursue realistic engine

dissembling and assembling training with natural interaction. 26 college students participated in the user test

of this training system. The results of the user test show high interest, immersion, satisfaction, and perceived

learning effectiveness of VRETS. Participants also reported that they could easily and naturally operate

VRETS, and they also had full control of the content.

1 INTRODUCTION

Needs of interactive training system has been

increased to enhance students’ motivation and

training effectiveness. Students tend to deeply

participate and join training which offers chances of

interaction and direct feedback with various

modalities (Clark and Mayer, 2011). Engaging

students to the training is one of important issues

which is one of key indicators of students’

achievements (Ibanez et al., 2014; Freitas, 2006).

Learning by doing is particularly emphasized in

vocational training due to the importance on transfer

of learning. Main purpose of vocational training is to

improve trainees’ performance as a result of the

training. Thus, designing and developing training

environment which is close to real-world and high-

relevance tasks is critical for the success of vocational

training.

Based on this background, new types of vocational

training method have been suggested recently. Virtual

reality is one of useful technology for training which

allows safe training environment, immediate

feedback, and repetition without limitation with

anytime/anywhere benefits (Bozgeyikli et al., 2016).

2 RELATED WORK

2.1 Virtual Reality Platform

At the early stage of virtual reality technology, big

scale virtual reality platforms such as CAVE and

multi-channel display were used for training. These

platforms were for educating big group of people in a

room setting.

Along with the rapid growth of virtual reality

technology, small-sized virtual reality devices such as

HMD (Head Mounted Display) and Leap Motion are

mostly preferred in virtual training. HMD and Leap

Motion are useful for individualized, immersive, and

interactive training.

HMD has increasingly applied to training systems

due to its high immersion, real-time interaction and

wide applications (Peden et al., 2016). The size and

cost of HMD is becoming more and more reasonable,

it is getting popular device for training purpose. Leap

Motion is a marker-less motion capture device

tracking hand, wrist and forearm position

(Smeragliuolo et al., 2016). One benefit of Leap

Motion is low cost that makes it possible to use for

training purpose as well.

2.2 Virtual Reality based Training

Virtual reality has been applied as an effective

training tool in the area of flight simulation, special

education, laparoscopic surgery and rehabilitation

262

Im, T., An, D., Kwon, O-Y. and Kim, S-Y.

A Virtual Reality based Engine Training System - A Prototype Development & Evaluation.

DOI: 10.5220/0006263702620267

In Proceedings of the 9th International Conference on Computer Supported Education (CSEDU 2017) - Volume 1, pages 262-267

ISBN: 978-989-758-239-4

training. Ke and Im (2013) developed a virtual reality

based social interaction training simulation for high

functioning ASD children using SecondLife and

found positive effects on performance of responding,

initiation, greeting, positive conservation ending and

social competence. Bozgeyikli et al. (2016) explored

different types of locomotion techniques with ASD

individuals and figured out they felt comfortable with

joystick and point & teleport techniques. A virtual

reality dance training system using motion capture

technology was proposed by Chan et al. (2011) and

positive effects on improving students’ dancing skill

as well as increasing motivation was found from the

study. A meta-analysis research was conducted with

virtual reality training in laparoscopic surgery and it

was found that virtual reality simulation is

significantly effective than video trainers (Alakeret

al., 2016). Researchers concluded that using

Proficiency-based virtual reality training with

supervision accompanied by prompt instruction and

feedback, and haptic feedback would be the most

effective way of virtual reality training.

However, there are still limited number of virtual

reality based training exits in the area of technical

training and most of them are development case study

focusing on technical elements with no user test or

evaluation. For example, Choi et al. (2015) developed

a virtual reality based operation system for steel

making process and presented the structure and

elements of the system. In this study, a virtual reality

based engine training system was suggested along

with results of a detailed user test.

3 VIRTUAL REALITY BASED

ENGINE TRAINING SYSTEM

(VRETS)

3.1 System Architecture

We implemented a virtual reality based engine

training system (VRETS) which empowers users to

see and to manipulate virtual objects. The VRETS

was configured to allow two or more users into a

single private lesson from any location. The proposed

VRETS consists of a natural interaction module, a

head mounted display (HMD), and a virtual reality

server as shown in Figure 1. In this system, the natural

interaction module plays a role of sensing a trajectory

of a human hand. When a user moves his/her hands,

the natural interaction module captures the motion in

real time and conveys the motion to the virtual reality

server. There are four major parts in the virtual reality

server. A motion recognizing part computes and

understands the trajectory of a user’s hands. Based on

the computed trajectory, a transformation part

calculates the position of a user’s hands in the

absolute coordinate which uses X, Y, and Z axis to

establish a point in a common origin. In the absolute

coordinate, a collision detection part computes the

collision between a user’s hand and a target virtual

object, and furthermore it calculates new positions of

the target object in virtual environment. Finally, all

virtual objects are redrawn in the new positions by a

graphic rendering part and then are displayed on the

head mounted display (HMD).

Figure 1: System structure of the proposed training system.

3.2 Interactive Virtual Reality

Contents

The most important thing in constructing virtual

training systems is to minimize a gap between virtual

and real worlds. The minimization of the gap can be

achieved by creating realistic virtual world (virtual

environment) with high quality images. Virtual

environment was constructed using a PC with 3.4

GHz i7 processors. A sleek head mounted display

(Oculus Rift) was used for allowing users to see and

enjoy computer generated virtual objects. All virtual

objects were modelled with 3DMax and the model

was subsequently simplified by a triangulated surface

mesh simplification method (Algorri and Schmitt,

1996) for achieving real-time rendering on our PC.

After that, we prepared two-dimensional image file to

be applied to the surface of the model. The prepared

image (texture) is mapped onto a target object’s

surface in 3D space. The model was then shaded

using C# with unity 3D as a graphic engine and

rendered at about 30 frames/sec (Figure 2).

User

Natural

Interaction

Module

HMD

Virtual Reality Server

Motion

Recognizing

Part

Graphic

Rendering

Part

Transformation

Part

Collision

Detection Part

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Figure 2: Constructed virtual environment.

Figure 3: Coordinate frame of the proposed system.

Although high quality images are essential to provide

a better sense of reality to users, it is not easy to

increase the degree of the users’ immersion to the

level users truly want. A promising way of improving

upon this problem is to construct a natural interaction

module which allows a user to intuitively manipulate

virtual objects with his/her gesture or motion. We

constructed a natural interaction module that captures

a user’s motion as shown in Figure 3. The natural

interaction module is made with an infrared (IR)

camera, a commercial motion detector (Leap motion

controller), and three IR reflectors. We applied a

coordinate frame on the IR camera. This coordinate

frame is used as the reference frame. The IR camera

captures three IR detectors which are attached to the

HMD to measure a user’s head motion. The

commercial motion detector was attached to the

HMD to track a user’s hand in real time. Therefore, a

user can watch and enjoy every parts of virtual world

by turning his/her head and can manipulate the parts

with his/her hands as if he/she interacts with objects

in real world. VRETS provides feedback with sound

based on the results of success or failure of each

mission.

4 EVALUATION & RESULTS

4.1 Participants

26 college students were recruited for the user test.

Average age of participants was 23 years old ranging

from 20~27. There were 15 male students and 11

female participants (Table 1).

Table 1: Gender.

Male 15

Female 11

Total 26

Majority of participants have majors in engineering

department. 5 students have prior experience of

Virtual Reality Applications and 21 students have

never tried VR related application before (Figure 4).

Figure 4: Participants’ Prior experience of VR.

4.2 User Test

The purpose of user test for this study was to explore

how people think, feel, react toward VRETS. For this

user test, participants came to a virtual reality lab at

KOREATECH one by one. Two of researchers led

user test and observed participants’ interaction with

the content. Before starting user test, one of

researcher clearly explained the purpose and the

procedure of test to each participant. A brief guide

about how to manipulate the virtual engine training

system was provided. Once a brief introduction of the

test was over, participants put on Oculus Rift with

Leap Motion and tried the VRETS (Figure 5).

Participants should disassemble an engine within the

virtual training system and reassemble it by

themselves. They could ask help to researchers if they

need.

The aspects of user experience that were explored

in this study are listed as below.

 Arousing Interest

 Immersion

 Interaction

 Ease of Operation

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264

 Locus of Control

 Perceived Learning Effectiveness

 Satisfaction

Figure 5: Scenes from User Test.

4.3 Materials

A questionnaire was modified for this study based on

prior research studies regarding user experience,

game evaluation and motion sickness with a 5-point

Likert scale. Participants filled out the questionnaire

once completing their mission with VRETS.

4.4 Results

4.4.1 Interest

The mean score of participants’ interest to VRETS is

4.69 and the standard deviation is .471 (Figure 6). 70%

of participants answered that VRETS was very

interesting to them.

Many participants responded that they were

interested in VRETS due to the high reality of the

system. This is from participants’ comment related to

interest.

“It was very interesting to me because VRETS

looks very real to me. It looks almost like a real

engine.”

Some participants found similarity between

VRETS and games.

“Even though this was first time to see engine

system, I enjoyed VRETS and thought it very

interesting since I could work on this content like

playing a game.”

4.4.2 Immersion

The mean score of participants’ immersion to VRETS

is 4.19 and the standard deviation is .801 (Figure 7).

85% of participants felt immersion to VRETS when

they were using the system. Participants seem to

experience immersion to VRETS from the feeling of

they were actually working on a real engine by

Figure 6: Mean and SD of Interest scores.

themselves. They reported they did not feel much gap

between VRETS and real engine.

“Disassembling and assembling a real engine is

not that easy due the difficulty of access as a student.

However, VRETS allowed me working with engine

and I felt I was practicing with a real engine by myself.

I fully concentrated on VRETS and enjoyed it.”

Figure 7: Mean and SD of Immersion scores.

4.4.3 Interaction

The mean score of participants’ responses about

interaction in VRETS is 4.04 and the standard

deviation is .774 (Figure 8). The question was about

how participants feel when they interact in VRETS

using Oculus Rift and Leap Motion. 88% of

participants answered interaction in VRETS was

natural and smooth. Many participants commented

that movement of hand and motion detect was natural

as real in VRETS.

“The hand in VRETS looked like my real hand. The

A Virtual Reality based Engine Training System - A Prototype Development & Evaluation

265

position of virtual hand and real hand was adequate.

Quality of engine visualization was very high.”

It seems like natural interaction in VRETS have

positive impact on participants’ interest, immersion,

and satisfaction.

Figure 8: Mean and SD of Interaction scores.

4.4.4 Ease of Operation

The mean score of ease of operation is 4.62 and the

standard deviation is .51 (Figure 9). 96% of

participants reported that operating VRETS was very

easy for them.

“This was my first time to experience VR contents. I

was little worried about what if I made mistakes

during VRETS operation. However, it was very easy

to use this content and so much fun.”

Figure 9: Mean and SD of Easy of Operation scores.

4.4.5 Locus of Control

The mean score of participants’ thought to locus of

control is 4.08 and the standard deviation is .845

(Figure 10). 80% of participants felt they had full

control of VRETS during their operation. Locus of

control is an important factor for motivation and

satisfaction.

Figure 10: Mean and SD of Locus of Control scores.

4.4.6 Perceived Learning Effectiveness

The mean score of participants’ perceived learning

effectiveness of VRETS is 3.85 and the standard

deviation is 1.0 (Figure 11). 70% of participants

perceived that VRETS would be effective for engine

training.

Figure 11: Mean and SD of Perceived Learning

Effectiveness scores.

4.4.7 Satisfaction

The mean score of satisfaction to VRETS is 4.46 and

the standard deviation is .506 (Figure 12). We could

find many reasons for high satisfaction to VRETS

from participants’ comments. First, having an

opportunity to manipulate virtual engine that is very

close to real engine made participants satisfied.

Second, many participants enjoyed natural

interactions through the virtual hand and motion

detect technology in VRETS. Third, participants

showed positive attitude on VRETS since it gives

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ownership to them and allows try and errors

repeatedly. Fourth, participants mentioned they felt

safe to work on VRETS comparing to real engine

situation.

Figure 12: Mean and SD of Satisfaction scores.

5 CONCLUSIONS

In this study, a virtual reality based engine training

system (VRETS) is proposed. We used Oculus Rift

and Leap Motion to provide natural interaction during

engine disassembling and assembling simulation.

Through these VR devices, VRETS use can see their

hand on the content, which is a result of real time

tracking. In addition, VRETS user can experience 360

degree of virtual world by turning his/her head with

Oculus Rift and can manipulate the parts with his/her

hands as if he/she interacts with objects in real world.

Immediate feedback with sound was provided in the

content.

The results of user test show high interest,

immersion, satisfaction, and perceived learning

effectiveness to VRETS. Participants also reported

that VRETS was easy to operate, interaction was

natural, and they had full control of the content. We

suggest that realistic virtual environment is important

for users’ immersion, interest and satisfaction from

the results of this study. Designing natural interaction

would be also critical to enhance user experience with

virtual reality training system. We suggest that true

value of virtual reality based training as creating real

world like demonstration and experiment for users in

a safe virtual environment.

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