Chapter 4 - Presentation, Interpretation and Analysis of Data

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Chapter 4

PRESENTATION, INTERPRETATION AND ANALYSIS OF DATA

This chapter details the various outcomes of the steps undertaken by the

researcher.

A total of 40 sets of the Task Performance Evaluation forms (inclusive of

the survey questions on feedback and features of the Vehicle Simulator for the

Experimental Group) were used.

The cooperative coordinators listed on Table 5 set the following dates for

the orientation and conduct of the experiment (pre-test, teaching-learning

intervention, and post-test):

Table 5 Details of Experiment Dates

Coordinator / Dates UPHSL PMMS

Name of Coordinator 2/O Elpidio P. Onte Capt. Manuel P. Natividad

Date of Orientation November 25, 2014 November 25, 2014

Date of Pre-Test November 25, 2014 November 25, 2014 Date of Lecture / Teaching Learning Intervention November 26, 2014 November 26, 2014 Date of Post-Test November 27, 2014 November 27, 2014

Date of Survey November 25, 2014 November 25, 2014

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Profile of the Respondents

A total of forty (40) participants participated in the experiment, i.e. twenty

(20) sophomore students from the University of Perpetual Help – Biñan and

twenty sophomore students from the Philippine Merchant Marine School in Las

Piñas. (Appendix J – Master list of Participants). All students have not yet used

the Vehicle Simulator and have just been given basic navigation principles, e.g.

rules of the road, et al, but are all considered not adept or skillful yet in

navigation. (Appendix K – Distribution of Participants by Year Level)

In each school, half of the students or ten (10) were placed in the Control

Group while the remaining ten (10) were in the Experimental Group. Thus, the

total number of students placed in the Control Group and Experimental Group is

twenty (20) and twenty (20), respectively.

The mean age of the students is 18.35, i.e. 19.20 for Control Group and

17.80 for Experimental Group. The oldest and the youngest overall are 24 and

16, i.e. 24 and 17 for Control Group, and 20 and 16 for Experimental Group.

This age range is the most impressionable stage in the lifecycle when it comes to

educational technology. (Appendix L – Distribution of Participants by Age)

The participants from both the Control Group and Experimental Group

have generally “Excellent” health condition. This simply implies that health will not be an impediment to the fair conduct of the experiment. (Appendix M –Distribution of Participants by Health Condition)

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The participants spent an average of 10.60 hours per week studying for

their subjects in school, i.e. 11.00 hours for the Control Group and 10.20 hours

for the Experimental Group. The number of hours per week spent by students

studying their lessons is quite commendable – practicing a specific competency,

e.g. navigation skills, requires dedication and undivided time for studies.

(Appendix N – Distribution of Participants’ Study Hours) The participants spent an average of 12.80 hours per week surfing the

Internet, i.e. 13.00 hours for the Control Group and 12.60 hours for the

Experimental Group. Surprisingly, the average number of hours surfing the

Internet is longer than the average number of hours studying. It may be argued

that some items surfed in the Internet are related to the participants’ studies. The

practice of navigation skills requires ample time in front of the computer with

Internet access. (Appendix O – Distribution of Participants’ Internet Surfing Hours)

All the participants own gadgets which would enable them to have access

to the Internet. The breakdown is as follows: 31 or 77.50% own smart phones; 4

or 10% own I-pads; 8 or 20% own laptops; 1 or 2.50% owns netbooks; and 11 or

27.50% owns PCs. Access to electronic devices or gadgets and the Internet is

important to be able to use the Vehicle Simulator (Appendix P – Distribution of

Participants’ Gadget Ownership)

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Practically all participants, i.e. 40 out of 40 or 100%, have access to the

Internet through their homes (18 or 45%), in school (30 or 75%), or in an Internet

shop (26 or 65%). Access to the Internet is an important requisite to using the

Vehicle Simulator. (Appendix Q – Distribution of Participants’ Access to Internet) In terms of computer literacy, 40 out of 40 participants or 100 % believed

they were “Very Good” while 0 or 0 % said their computer skills were “Good”, “Fair” or “Poor.” This simply means that, overall, the participants are very confident with the degree of proficiency in computer technology, a pre-requisite

skill they would need to operate the Vehicle Simulator. (Appendix R –Distribution of Participants’ Computer Literacy) In terms of conduciveness of the students’ homes for studying, 12 or 30% of the participants believed their homes were very conducive without distractions.

Meanwhile, 15 or 37.50% said it is quite conducive with minor distractions; 8 or

20% said it is quite challenging with major distractions; and 5 or 12.50% said it

was not conducive at all. It is important to have a conducive home environment

especially if studying, e.g. practicing navigation skills, is done at home. (Appendix

S – Distribution of Participants’ Home Conduciveness to Studying) Practically all of the participants, i.e. 40 out of 40 or 100%, have not

completed any course in navigation yet at the time of the experiment. They have

merely taken basic principles, e.g. rules of the road, which are essential prior to

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using simulators. This is important prior to the experiment. (Appendix T –Distribution of Participants’ Completion of a Navigation Course) None of the participants, i.e. 0 out of 40 or 0%, have been exposed to the

software Vehicle Simulator. This is also important prior to the experiment.

(Appendix U – Distribution of Participants’ Exposure to Vehicle Simulator) In terms of family support on the participants’ maritime studies, 14 or 35% of participants mentioned that their families were “Extremely Supportive.” Meanwhile, 15 or 37.50% said their families were “Supportive with Minor

Challenges”; 9 or 22.50% mentioned “Supportive with Major Challenges,” and 2 or 5.00% thought their families were “Not Supportive at All.” Since the Vehicle Simulator entails cost (i.e. $30 or PhP1,350), it is

important to have a supportive family for funding school expenses. (Appendix V

– Distribution of Participants’ Family Support on Maritime Studies)

Results of the Pre-Test

During the pre-test, the participants were required to perform individually

three navigation tasks, namely: collision regulation, Williamson turn, and position

fixing, for approximately 25-30 minutes. The researcher gauged their

performance of these tasks using the approved Task Performance Evaluation

form with 14 items to observe in collision regulation, 12 items in Williamson turn,

and 10 items in position fixing.

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Upon tabulation of the results, the actual results of the pre-test on both the

Control Group and the Experimental Group were as follows:

Table 6 Pre-Test Results

Task

Control Group Mean Scores Performance Level Experimental Group Mean Scores Performance Level

Collision Regulation 2.31 Low 2.58 Moderate Williamson Turn 2.25 Low 2.20 Low

Position Fixing 2.22 Low 2.38 Low Overall Mean Scores 2.26 Low 2.39 Low

Table 6 as indicated above simply means that the Control Group and

Experimental Group are very similar in their level of proficiency on the three tasks

based on the overall mean scores obtained. Details of the pre-test are shown in

Appendices W (Pre-Test Scores of the Control Group) and X (Pre-Test Scores of

Experimental Group).

After the pre-test, the Control Group was exposed to a traditional learning

intervention, i.e. lecture and video, conducted by the researcher on the three

topics. Meanwhile, the Experimental Group was exposed to an Internet-based

learning intervention, i.e. Vehicle Simulator, also conducted by the researcher on

the same three topics.

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Results of the Post-Test

The post-test was conducted immediately by the researcher and it yielded

the following results and interpretation.

Table 7 Post-Test Results

Task

Control Group Mean Scores Performance Level Experimental Group Mean Scores Performance Level

Collision Regulation 3.34 High 3.84 High Williamson Turn 3.29 High 3.87 High Position Fixing 3.36 High 3.95 High

Overall Mean Scores 3.33 High 3.88 High

Table 7 as indicated above shows that both groups achieved a “High” performance level score but it is also apparent that the Experimental Group was

almost 17% higher than the Control Group, i.e. 3.88 versus 3.33, and this can be

further analyzed using the Bloom’s Learning Objectives interpretation. Details of the post-test are shown in Appendices Y (Post-Test Scores of

the Control Group) and Z (Post-Test Scores of Experimental Group).

Bloom’s Learning Objectives Interpretation

Once converted into the Bloom’s Learning Objectives, the aggregate mean scores for all three tasks yielded a glaring difference between the two

groups in terms of the hierarchy of learning objectives, i.e. remembering,

understanding, application, analysis, evaluation, and creation.

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The pre-test scores converted into Bloom’s Learning Objectives as indicated in Table 8 yielded a “Moderate” performance level for both Control Group and Experimental Group. This simply means, they are practically starting

off on equal footing prior to any learning intervention.

Table 8 Pre-Test Scores on Bloom’s Learning Objectives

Task

Control Group Mean Scores Performance Level Experimental Group Mean Scores Performance Level

Remembering 2.32 Moderate 2.53 Moderate Understanding 2.25 Moderate 2.65 Moderate Application 2.57 Moderate 2.60 Moderate Analysis 2.23 Moderate 2.22 Moderate Evaluation 2.25 Moderate 2.28 Moderate Creation 2.20 Moderate 2.40 Moderate Mean Scores 2.30 Moderate 2.49 Moderate

Meanwhile, the post-test scores resulted in a significant difference in the

performance of the two groups. The Control Group achieved “Very High” scores in remembering and creation and “High” on the rest of the four other learning objective levels. The Experimental Group achieved “Very High” on all six learning objectives levels.

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Table 9 Post-Test Scores on Bloom’s Learning Objectives

Task

Control Group Mean Scores Performance Level Experimental Group Mean Scores Performance Level

Remembering 3.43 Very High 3.93 Very High Understanding 3.33 High 3.97 Very High Application 3.28 High 3.86 Very High Analysis 3.33 High 3.88 Very High Evaluation 3.38 High 3.91 Very High Creation 3.53 Very High 3.95 Very High Mean Scores 3.38 High 3.92 Very High

Bloom’s Learning Objectives Pre-Test and Post-Test Scores are detailed

in Appendices AA and AB, respectively.

T-Test of Significance on the Post-Test

The t-test of significance on the post-test for both control group (CG) and

experimental group (EG), one of the more important statistical treatments in this

study, yielded the following results:

Table 10 T-Test of Significance on the Post-Test

Task Value of t Accept or Reject H0 Interpretation

CG vs. EG Pre-Test 0.68 Accept No significant difference CG Pre-Test vs. Post-Test 12.037 Reject There is a significant difference EG Pre-Test vs. Post-Test 8.242 Reject There is a significant difference CG vs. EG Post-Test 7.427 Reject There is a significant difference

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The value of t at 3 degrees of freedom and 95% level of significance is a

constant, i.e. 5.841. Any score equal to or below it means that the null

hypothesis must be accepted, i.e. there is no significant difference in the mean

scores of the two groups.

Conversely, any score above it means that the null hypothesis must be

rejected, i.e. there is a significant difference in the means scores of the two

groups. Details of the computations of the T-Test Significance of the Post Test

are in Appendix AC.

Feedback on the Vehicle Simulator

After the experiment, the participants in the Experimental Group were

surveyed and asked on their feedback on the use of the Vehicle Simulator. A

total of ten (10) items (i.e. declarative statements) were enumerated in which

respondents expressed the degree of their agreement or disagreement. Upon

tabulation of the responses, the mean scores were calculated. The results were

shown on table 11.

Using the Spearman Rank Correlation, the responses of the students and

the teachers yielded the following correlation score:

rs = 0.80303 or high correlation

There were eight positive feedbacks wherein most student- and teacher-

respondents strongly agreed were:

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1. They would like to continue using the Vehicle Simulator.

(Sustainability)

2. They were able to practice well their navigation skills using the Vehicle

Simulator. (Competency-Building)

3. They found the Vehicle Simulator flexible to use. (Flexibility)

4. They found the Vehicle Simulator user-friendly. (User-Friendly)

5. They realized it is good to have the Vehicle Simulator in maritime

schools and training centers. (Accessibility)

6. They felt comfortable using the Vehicle Simulator. (Comfort)

7. They were excited in using the Vehicle Simulator. (Appealing)

8. They learned something very important while using the Vehicle

Simulator. (Educational Component)

Meanwhile, two positive feedbacks wherein majority of the students and

teachers merely agreed were:

1. They gained confidence while using the Vehicle Simulator.

(Confidence-Building)

2. They improved their communication skills while using the Vehicle

Simulator. (Language Proficiency Component)

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Table 11 Feedback on the Vehicle Simulator

No. Item

1 I am excited in using the Vehicle Simulator 2 I feel comfortable using the Vehicle Simulator 3 I gained confidence while using the Vehicle Simulator

4

I improved my communication skills while using the Vehicle Simulator

5

I learned something very important while using the Vehicle Simulator

6 I find the Vehicle Simulator flexible to use 7 I find the Vehicle Simulator user friendly -

8

I was able to practice well my navigation skills while using the Vehicle Simulator

9 I would like to continue using the Vehicle Simulator

10

It is good to have the Vehicle Simulator in maritime schools and training centers Students’ Score Teachers’ Score Students’ Rank Teachers’ Rank

2.85 3.67 6.5 7.0

2.70 3.83 8.0 4.0

2.35 3.17 9.5 9.0

2.35 2.83 9.5 10.0

2.85 3.50 6.5 8.0

3.10 3.83 3.0 4.0

3.05 3.83 4.0 4.0

3.15 3.83 1.0 4.0

3.10 4.00 2.0 1.0

3.00 3.83 5.0 4.0

Details of the tabulation responses of the Experimental Group participants

are in Appendix AD.

Overall, the Vehicle Simulator possesses all the strengths of an alternative

teaching and learning tool enumerated in the survey instrument. However,

teachers commented that the Vehicle Simulator may not be able to replace a full-

mission bridge simulator particularly of known brands such as Kongsberg,

Transas, and others, but it can be an alternative teaching and learning tool. Both

UPHB and PMMS are using Kongsberg.

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Features of the Vehicle Simulator

Still part of the survey conducted on the Experimental Group participants,

each one was asked to rank the features of the Vehicle Simulators from the ones

they liked most (strengths) down to the ones they liked least (potential

weaknesses). The results of the exercise were as follows:

Table 12 Features of the Vehicle Simulator

Features Students’ Rank Teachers’ Rank Mean Rank

Strength or Weakness

Complete features 1 1 1 Strength Applicable real-life situations 2 2 2 Strength Visuals are clear and great 3 3 3 Strength Instructions are clear and easy to follow 4 4 4 Strength

No technical problems encountered 5 5 5 Weakness Highly interactive 6 6 6 Weakness Easy to manipulate 7 7 7 Weakness

Courseware is accessible by Internet 8 8 8 Weakness

The responses of the Experimental Group participants on the features of

the Vehicle Simulator are detailed in Appendix AE. Using the Spearman Rank

Correlation, the responses of the students and teachers were alike, i.e. perfect

correlation.

rs = 1.00000 or perfect correlation

The Vehicle Simulator provides a good introduction to navigation courses

as it has complete features, approximates real-life situations, has clear and great

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visuals, and has clear and easy to follow instructions. These are the advantages

of the Vehicle Simulator.

However, sometimes technical problems were also encountered; it is not

as interactive as a full mission bridge simulator; it is not extremely easy to

manipulate; and it bears cost to be able to access it through Internet. These are

the disadvantages of the Vehicle Simulator.

Result of Survey on Branded Simulators

Apparently, the teachers of both schools are exposed only to Kongsberg.

Thus, other branded simulators were excluded in the survey. Only Kongsberg

and Vehicle Simulator were compared. The results are as follows:

Table 12 indicates that the Vehicle Simulator has good features as an

alternative teaching and learning tool in maritime programs.

Table 13 Survey on Branded Simulator

No. Item Vehicle Simulator Kongsberg

1 Easy to manipulate 2 Complete features 3 Applicable real-life situations

2.55 3.82 2.73 3.82 3.61 4.00 4 Visuals are clear and great 2.50 3.79 5 Instructions are clear and easy to follow 2.67 4.00 6 Highly interactive 3.89 4.00 7 Courseware is accessible by Internet 4.00 1.00 8 No technical problems encountered 1.92 2.00 9 Good maintenance and support system 2.56 3.89 10 Affordable price for schools & students 3.60 3.93

Mean 3.00 3.43

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Compared with Kongsberg, one of the leading branded full mission bridge

simulators and is currently being used by both UPH-B and PMMS, Vehicle

Simulator apparently has similar capabilities. Kongsberg, on the other hand, has

some glaring weaknesses such as affordability of its price, i.e. approximately

PhP10 million, its maintenance and support system, and technical problems

encountered.

This finding does not preclude that the Vehicle Simulator is without a

weakness. Assuming a batch of 1,000 maritime students enrolled in a basic

navigation course would be using the Vehicle Simulator, i.e. loaded into their

gadgets, the aggregate cost is estimated at PhP1.35 million. If a school charges

an average of PhP2,000 for laboratory fees, the Kongsberg acquisition cost may

be recovered within 5 semesters. If a school implements the adoption of a

supplemental tool like the Vehicle Simulator, it could help prolong the lifespan of

its full mission bridge simulator.

A more detailed breakdown of the scores between the Vehicle Simulator

and Kongsberg is indicated in Table 13 showing the specific items in each

criterion.

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Table 14 Breakdown of Comparative Assessment Simulators

No. Item

1 Complete features 1a Radar / ARPA 1b Steering Wheel 1c Engine Telegraph 1d Sound Signal 1e Lights and Shapes 1f ECDIS 1g Echo Sounder 1h Bow Thruster 1i Smoke Signals and Pyrotechnics 1j Vessel Characteristics Display 1k Bank Suction

Vehicle Simulator Kongsberg 2.55 3.82 3.00 4.00 3.00 4.00 3.00 4.00 3.00 4.00 3.00 4.00 3.00 4.00 3.00 4.00 3.00 4.00 1.33 4.00 1.00 4.00 1.00 3.00

1l Anchor 1m Mooring / Docking Ropes 1n Search and Rescue Capability 1o Ballast Water Regulator 1p Global Positioning System 1q LAN Connection 2 Easy to manipulate 2a Radar 2b Steering Wheel 2c Engine Telegraph 2d Sound Signal 2e Lights and Shapes 2f ECDIS 2g Echo Sounder 2h Bow Thruster 2i Smoke Signals and Pyrotechnics 2j Vessel Characteristics Display 2k Bank Suction 2l Anchor 3.00 4.00 3.00 4.00 1.00 4.00 1.00 3.00 4.00 4.00 4.00 3.00 2.73 3.82 3.00 4.00 3.00 4.00 3.67 4.00 3.33 4.00 3.33 4.00 3.00 4.00 3.00 4.00 3.00 4.00 1.00 4.00 1.00 4.00 3.00 3.00 3.00 4.00

2m Mooring / Docking Ropes 2n Search and Rescue Capability 2o Ballast Water Regulator 3.00 4.00 1.00 4.00 1.00 3.00

2p Global Positioning System

4.00 4.00 2q LAN Connection 4.00 3.00 3 May be applicable to real-life situations 3.61 4.00 3a Rule 13 – Overtaking Vessel (CR) 4.00 4.00 3b Rule 14 – Head-on Situation (CR) 4.00 4.00

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3c Rule 15 – Crossing Situation (CR)

4.00 4.00 3d Rule 16 – Action by Give-way Vessel (CR) 3.67 4.00 3e Rule 17 – Action by Stand-on Vessel (CR) 4.00 4.00 3f Man overboard in shallow water (WT) 2.00 4.00 3g Man overboard in deep water (WT) 3.00 4.00 3h Use of radar (PF) 3.00 4.00 3i Use of GPS (PF) 4.00 4.00 3j Conditions of poor visibility (PF) 4.00 4.00 3k Bad weather conditions (CR, WT, PF) 4.00 4.00 4 Visuals are complete, clear and great 2.50 3.79 4a Existence of major ports in the simulator’s library 1.00 4.00 4b Accurate depiction of landmarks and views 2.00 4.00 4c Clarity of resolution of images 4.00 4.00 4d Accurate simulation of various weather conditions 3.00 3.17 5 Instructions are clear & easy to follow 2.67 4.00 5a Dropdown menu is easy to read and operate 4.00 4.00 5b Translation facility is available 1.00 4.00 5c Availability of printed manual 3.00 4.00 6 Highly interactive 3.89 4.00 6a Features are functioning well 3.67 4.00 6b Reaction of simulator to user is real-time 4.00 4.00 6c Features are very engaging to the user 4.00 4.00 7 Courseware is accessible by Internet 4.00 1.00 7a Courseware is downloadable from the Internet 4.00 1.00 7b Internet bandwidth is strong and stable 4.00 1.00 8 No technical problems encountered 1.92 2.00 8a No possibility of going off accidentally 2.33 2.00 8b No possibility of slow or no response 2.00 2.00 8c No possibility of malfunction 2.33 2.00 8d No possibility of virus infection or attack 1.00 2.00 9 Good and swift maintenance support system 2.56 3.83 9a Presence of an online support system 3.67 3.83 9b Presence of a self-help mechanism 3.00 4.00 9c Presence trained support staff in the country 1.00 3.83 10 Affordable price for schools and students 3.60 3.93 10a Schools can easily afford the price of the simulator 3.00 4.00 10b Schools can generate savings & profit on simulation courses 3.33 3.83 10c Schools can recover fast their investment on the simulator 4.00 4.00

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10d Students can afford $30 (VS) or P2,000 course fee (KB) 10e Payment terms and mode of payment are easy & convenient 3.67 3.83

4.00 4.00

The students’ survey revealed that the Vehicle Simulator has its own set

of weaknesses or disadvantages as discussed earlier. The students engaged in

the experiment have yet to experience using Kongsberg. The researcher

believes that the above results also reveal the teachers’ perception of the potential of an Internet-based software such as the Vehicle Simulator as a strong

supplement for students to practice navigation skills and other mental processes.

Realistically, based on the foregoing findings the researcher believes that

Kongsberg has superior visuals, more complete features, and is more highly

interactive than the Vehicle Simulator. The Vehicle Simulator is a good

supplemental or alternative teaching and learning tool in basic navigation

courses while Kongsberg is ideal for intermediate and higher navigation courses.

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Chapter 5

SUMMARY OF FINDINGS, CONCLUSIONS AND RECOMMENDATIONS

This chapter consolidates the findings, draws conclusions and offer

recommendations. From the foregoing chapter, below is the summary of findings

as they are linked to the Statement of the Problem, Hypothesis, Synthesis of the

Review of Related Studies and Literature, Conclusions and Recommendations.

Table 15 Summary of Findings

No. Findings

1 When the t-test of significance of the post-test was done (Table 10), the following results were revealed:

Pre-Test vs. Post-Test for Control

Group: value of T = 12.037

Pre-test vs Post-Test for

Experimental Group: value of T = 8.242

Post-Test of Control Group vs.

Post-Test of Experimental Group: Value of T = 7.427 There is a significant difference in the performance of the Control Group and Experimental Group with the Vehicle Simulator users (EG) demonstrating far superior performance in collision regulation, Williamson turn, and position fixing.

This simply means that the null hypothesis must be rejected because there is a significant difference based on the results of the t-test of significance of the post-test.

Learners develop numerous skills through simulators. (Fripp, 1997; McGuire, 1976; Miller, 1985; Kayten, 1982; Multer, 1983; D’Amico, 1985; Hammell, 1985; Froese, 1988; Douwsman, 1993; CSMART, 2014) Use of simulators is compliant with CMO 31 (CHED, 2013; Baylon and Santos, 2011)

2 The mean scores in the experiment were converted into Bloom’s Learning Objectives

Interpretation

It was clear that the Experimental Group performance better (Very High) compared to the Control Group (High) in all aspects

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(Table 9) and the following overall mean scores were revealed: Control Group: 3.38 Experimental Group: 3.92

3 Being exposed to both full mission bridge simulators and PC-based simulators, the perception of the instructors were sought on 10 criteria, i.e. comparing the Vehicle

Simulator and Kongsberg (used by both schools) and the mean scores were revealed as follows:

Vehicle Simulator: 3.00

Kongsberg: 3.43

4 When the feedback was sought from both students and teachers on the features of the Vehicle

Simulator most liked and least liked using the Spearman Rank

Correlation, the results were:

rs = 0.80303 ( high correlation) (remembering, understanding, application, analysis, and evaluation). Therefore, reject both the first and second null hypotheses. Simulation captures all three learning domains – i.e. cognitive, affective and psychomotor. (Miller, 1985; Lintern, 1988; Hays and Singer, 1989; Herr, 2014; Edmonds, 1994) Simulators allow the learner to manifest all the learning objectives as postulated by Bloom – e.g. remembering, understanding, application, analysis, evaluation, and creation. (Miller, 1985; Meurn, 1990; Gredler, 1992) The instructors believe that Vehicle Simulator has similar capabilities as Kongsberg, the only brand used by the two schools regarded as a superior brand and the brand familiar to the instructors. Therefore, the null hypothesis must be accepted. More importantly, it was noted in the qualitative remarks that the Vehicle Simulators has a number of limitations. Hence, it cannot replace entirely a full mission bridge simulator. However, it is a good supplemental or alternative tool for teachers and students to use when practicing basic navigation skills. Simulators pose specific challenges. (Waag, 1981; Lintern and Koonce, 1992) The virtual realities created through the use of simulators prevent potential accidents in a regular apprenticeship or actual exercise. (Gosling, 2012; Jones, 1993; Sweeney and Groh, 1993) There is no significant difference in the perception of students and instructors on the features of the Vehicle Simulator. On the feedback of the two groups, there is a high correlation. On the features of the Vehicle Simulators, the two groups’ responses had a perfect correlation. Simulators build confidence of the learner. (Jones, 1993; Calaor, 2011)