APPLICABILITY OF THE VEHICLE SIMULATOR AS AN ALTERNATIVE TEACHING AND LEARNING TOOL by William Picar

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila

APPLICABILITY OF THE VEHICLE SIMULATOR AS AN ALTERNATIVE TEACHING AND LEARNING TOOL

A Thesis Presented to the Faculty of the Graduate School of PHILIPPINE MERCHANT MARINE ACADEMY Manila

In Partial Fulfillment of the Requirements for the Degree Master in Maritime Education and Training

WILLIAM B. PICAR

June 2015

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila

Approval Sheet

In partial fulfillment of the requirements for the degree Master in Maritime Education and Training, this thesis entitled “Applicability of the Vehicle Simulator as a Teaching and Learning Tool” has been prepared and submitted by WILLIAM B. PICAR who is hereby recommended for oral examination.

DANNY A. CABULAY, MBA, CPA Adviser Approved by the committee on oral examination with a grade of _______.

CDR VALENTINO FERRE PMMA Chairperson

DR. WALTHOR MAOG Member

DR. NELSON PRIAS Member

Accepted and approved in partial fulfillment of the requirements for the degree Master in Maritime Education and Training.

ENGR. RONALD G. MAGSINO, MSc Dean, Graduate School

January 2015

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Graduate School, Manila Acknowledgment

The researcher conveys his sincerest and profoundest gratitude to numerous individuals who were instrumental in the completion of this research study. Firstly to Engr. Ronald Magsino, the Dean of Philippine Merchant Marine Academy Graduate School for his moral support; RADM Richard U Ritual PMMA, President of Philippine Merchant Marine Academy; Dr. Walthor Maog, Prof. Valentino Ferre,

Dr.Nelson Frias, the review

panel for their

impartial and

unselfish expressions of critical views and suggestions in polishing this thesis; and to Cdr Victoria Q Paraggua PMMA for patiently critiquing and proofreading the manuscript. The researcher also is indebted to Capt. Terence Uytingban and his colleagues at AJ Center for Excellence for their

support and encouragement;

Engr. Ilan Papini for allowing him to use his software as the subject of this thesis; Chief Engr. Billy Boregas, Dean; 2/O Elpidio Onte and instructors, studentrespondents of the University of Perpetual Help System Laguna; Capt. Isidoro Gambol, College Dean; Capt. Manuel Natividad, instructors and studentrespondents of the Philippine Merchant Marine School. The researcher would also like to thank Dean Danny Cabulay, for his unfailing guidance, moral support, and untiring effort extended in the development and throughout the completion of this thesis; friends, relatives, coiii

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Graduate School, Manila mentors and bosses at Magsaysay Training Center especially Capt. Capili and Capt. Genargue. Above all, with awe and humility, the researcher implores incessantly his praises and thanks to God Almighty for and by His wonderful grace, this research paper was completed.

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Graduate School, Manila Dedication

This thesis is sincerely dedicated to my loving and very supportive wife and children who have been my constant source of inspiration. They have given me the drive and discipline to tackle any task with enthusiasm and determination. Without their love and support, this project would not have been possible.

W.B.P.

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Graduate School, Manila Abstract

This is a pioneering study using the experimental method and its main purpose of this research is to determine the effectiveness of PC-based simulators like the Vehicle Simulator in teaching navigation subjects to Filipino maritime students. The students of the University of Perpetual Help System in Biñan, Laguna and the Philippine Merchant Marine School in Las Piñas, Metro Manila were the participants of this experiment. Two groups were formed, a control group which was exposed to a traditional strategy (i.e. video) and an experimental group which was exposed to the proposed learning strategy (i.e. the Vehicle Simulator). Both groups underwent pre-test and post-test evaluation of their navigation skills with three specific topics chosen by the researcher, namely: collision regulation, Williamson turn, and position fixing. The 40 respondent-participants are from the University of Perpetual Help – Biñan in Laguna and Philippine Merchant Marine School in Las Piñas City. None of the students have completed any navigation course in school (i.e. all neophytes). None of them were familiar with the software Vehicle Simulator or any other PC-based simulators. 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. vi

The researcher gauged their

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Graduate School, Manila 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. Actual results of the pre-test on both the Control Group and the Experimental Group showed that both groups yielded low mean scores, i.e. 2.26 and 2.39, respectively, a proof of their unfamiliarity with the tasks required. 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 while 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. The post-test yielded the following results and interpretation: both groups got high mean scores – 3.33 for the Control Group and 3.88 for the Experimental Group which was 17% higher than the other group.

While both groups

apparently improved, the Experimental Group learned better with a much higher mean score. 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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Graduate School, Manila The pre-test scores converted into Bloom’s Learning Objectives yielded a “Moderate” performance level for both Control Group and Experimental Group. 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 objective levels. The null hypothesis was rejected based on the result of the t-test of significance on the post-test. The Control Group and the Experimental Group Post-Test yielded a t value of 7.427 which was higher than the value of t at 3 degrees of freedom and 95% level of significance or 5.841. This means that the Vehicle Simulator is more effective than the traditional lecture and video technique and may be used as an alternative teaching and learning tool in navigation courses. After the experiment, the participants in the Experimental Group were surveyed and asked on their feedback on the use of the Vehicle Simulator. 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 teacherrespondents strongly agreed, namely: it was sustainable because they would like to continue using the Vehicle Simulator; it built competency as they were

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Graduate School, Manila able to practice well their navigation skills using the Vehicle Simulator; it was flexible as they found the Vehicle Simulator flexible to use; it was user-friendly having found the Vehicle Simulator easy to understand and manipulate; it was accessible through the Internet and they realized it is good to have the Vehicle Simulator in maritime schools and training centers; it was comfortable to use due to its handy and transportable features; it was appealing as they were excited while using the Vehicle Simulator; and it clearly has an engaging educational component as they learned something very important while using the software. In addition, there were two similar positive feedbacks agreed upon by both the students and teachers, namely:

it built confidence as the students

gained confidence while using the Vehicle Simulator; and it had a languageproficiency component as it improved their communication skills while using the Vehicle Simulator. 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 fullmission 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 were using Kongsberg for the laboratory courses. Also, the respondents were asked to rank the features of the Vehicle Simulators from the ones they liked most (strengths) down to the ones they liked

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Graduate School, Manila least (potential weaknesses).

The results of the exercise revealed both the

strengths and weaknesses of the Vehicle Simulator. Having complete features, being applicable to real-life situations, having great and clear visuals and easy to follow instructions were the apparent strengths of the software. Meanwhile, the technical problems encountered, the not-so-highly interactive nature of a PCbased simulator, being not too easy to manipulate, and cost of the software (i.e. $30 paid online) were identified as weaknesses. Based on the findings and conclusions, the following recommendations are hereby offered: endorse the Vehicle Simulator to maritime schools as a supplement to their existing navigation learning resources, equipment and technology; endorse the Vehicle Simulator to maritime training centers as a supplement to their existing training program; future researchers can expand this study covering a specific company on the effectiveness of the Vehicle Simulator as a teaching and learning tool for senior maritime students; review centers may consider the Vehicle Simulator as a learning tool for the practical test component of the board exam for deck officers; maritime high schools (post K-12 program) should incorporate in the curriculum simulation courses in preparation for collegiate courses; future researchers can replicate this study by evaluating the applicability of the Vehicle Simulator as an assessment tool (e.g. for MARINA); and Filipino IT specialists should develop a superior version of the Vehicle Simulator.

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Graduate School, Manila Table of Contents

Title

Page

Title Page ............................................................................................................. i Approval Sheet ....................................................................................................ii Acknowledgment ................................................................................................ iii Dedication ........................................................................................................... v Abstract ...............................................................................................................vi Table of Contents ...............................................................................................xi List of Tables .................................................................................................... xiii List of Figures ................................................................................................... xiv List of Appendices ............................................................................................xv Chapter 1 - The Problem and Its Background Introduction ................................................................................................ 1 Background of the Study............................................................................ 3 Theoretical Framework ............................................................................ 11 Conceptual Framework ............................................................................ 13 Statement of the Problem ........................................................................ 17 Hypothesis ............................................................................................... 18 Scope and Delimitations .......................................................................... 20 Significance of the Study ......................................................................... 20 Definition of Terms ................................................................................... 24

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Graduate School, Manila Chapter 2 - Review of Literature and Studies Related Literature .................................................................................... 31 Related Studies ....................................................................................... 36 Synthesis ................................................................................................. 44 Chapter 3 - Research Methodology Research Design ..................................................................................... 47 Respondents and Sampling Design ......................................................... 47 Locale of the Study .................................................................................. 49 Instrumentation and Validation of the Instrument ..................................... 50 Data Gathering Procedure ....................................................................... 51 Statistical Treatment of Data.................................................................... 53 Chapter 4 - Presentation, Interpretation and Analysis of Data ..................... 54 Chapter 5 - Summary of Findings, Conclusions and Recommendations Conclusions ............................................................................................. 74 Recommendations ................................................................................... 75 Linking the Findings to the Conclusions, Recommendations and Research Problems .......................................................................... 78 Bibliography...................................................................................................... 82 Appendices ....................................................................................................... 86 Curriculum Vitae ............................................................................................. 158

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Graduate School, Manila

List of Tables

Table

Page

Breakdown of Student Participant-Respondents ------------------------

Breakdown of Instructor-Respondents -------------------------------------

Interpretation of Scores – Task Performance Evaluation -------------

Interpretation of Scores – Bloom’s Learning Objectives --------------

Details of Experiment Dates -------------------------------------------------

Pre-Test Results ----------------------------------------------------------------

Post-Test Results ---------------------------------------------------------------

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

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

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

Feedback on the Vehicle Simulator ----------------------------------------

Features of the Vehicle Simulator ------------------------------------------

Survey on Branded Simulator -----------------------------------------------

Breakdown of Comparative Assessment Simulators ------------------

Summary of Findings ----------------------------------------------------------

Linking Summary of Findings with Statement of the Problem, et al. --------------------------------------------xiii

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Graduate School, Manila List of Figures

Figures

Page

Game Theory --------------------------------------------------------------------

Conceptual Framework (Envisioned Concept) ---------------------------

Conceptual Framework (Procedural) ---------------------------------------

xiv

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Graduate School, Manila List of Appendices

Appendix

Page

Profile of Student ----------------------------------------------------------------

Task Performance Evaluation Form (Collision Regulation) ----------

Task Performance Evaluation Form (Williamson Turn)----------------

Task Performance Evaluation Form (Position Fixing) ------------------

Feedback Survey Form for Students ---------------------------------------

Profile of Instructor --------------------------------------------------------------

Feedback Survey Form for Instructors -------------------------------------

Comparative Survey of Instructors ------------------------------------------

Master List of Participants -----------------------------------------------------

Distribution of Participants by Year Level --------------------------------- 100

Distribution of Participants by Age ------------------------------------------ 103

Distribution of Participants by Health Condition ------------------------- 105

Distribution of Participants by Study Hours ------------------------------- 108

Distribution of Participants by Internet Surfing Hours ------------------ 111

Distribution of Participants by Gadget Ownership ---------------------- 114

Distribution of Participants by Internet Access --------------------------- 117

Distribution of Participants by Computer Literacy ----------------------- 120 xv

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Graduate School, Manila R

Distribution of Participants by Conduciveness of Students’ Home for Studying ------------------------------------------------ 123

Distribution of Participants with Simulation Course --------------------- 126

Distribution of Participants with Vehicle Simulator Exposure -------- 129

Distribution of Participants by Family Support on Students’ Maritime Studies ---------------------------------------------------- 132

Pre-Test Scores of the Control Group -------------------------------------- 135

Pre-Test Scores of the Experimental Group ------------------------------ 137

Post-Test Scores of the Control Group ------------------------------------ 139

Post-Test Scores of the Experimental Group ---------------------------- 141

Bloom’s Learning Objectives of the Control Group --------------------- 143

AA Bloom’s Learning Objectives of the Experimental Group ------------- 144 AB T-Test Significance of the Post-Test---------------------------------------- 145 AC Feedback on the Vehicle Simulator ----------------------------------------- 147 AD Features of the Vehicle Simulator ------------------------------------------- 149 AE Results of Comparative Survey on Branded Simulators -------------- 151

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Graduate School, Manila

Chapter 1

THE PROBLEM AND ITS BACKGROUND

Introduction The theoretical rationale for the use of simulators for training is based on the concept of skill transfer, i.e. the ability to adapt skills learned in one context to performance or task execution in another. As no situation is ever identical to a previous experience, the fact that an individual becomes more skilled with each repetition of a similar task attests to the fact of transfer. Indeed, a faith in the "fact" of transfer constitutes the basic justification for all formal training programs. It is assumed that skills and knowledge learned in a classroom can be applied effectively to relevant situations outside the classroom. No training environment is exactly the same as the real situation. To ensure that all training goals are met, it may be appropriate to supplement the learning with apprenticeships or a similar formal mechanism to reinforce learning. For many generations, traditional classroom teaching has been regarded as an effective method for teaching theory.

Teaching methods usually include the

instructor lecturing to the class, with the possibility of use of an overhead projector, whiteboard, or sometimes a video clip to amplify training objectives. In the traditional setting, the instructor is in direct control and he may or may not invite questions and encourage discussion (Orey, 2010). 1

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Graduate School, Manila With the introduction of simulation techniques to the course syllabi, the instructor can now fill the gap between theory and application (MacElrevey, 1995). The instructor can create an interactive environment where instructor and students actively participate in a demonstration applying theory to the real-world. For the past 27 years that the researcher has been teaching in various maritime educational institutions, he has always been fascinated with the teaching and learning process of young seafarers. With the growing trend in computerizing many functions in the maritime industry, it is fitting to adopt newer technologies that would enhance the competence of new maritime graduates. Having taught courses in Navigation, Radar Simulator, Ship Handling, Electronic Chart Display and Information System (ECDIS), and Collision Regulation, the researcher has long been exposed to numerous teaching strategies, both traditional and emerging ones. While many schools already use simulators in their laboratory courses, the time spent by students is very limited. Hence, the chance of developing mastery in important competencies is potentially remote. Any skill needs continuous and rigorous practice to be able to reach a high level of competency. Thus, a PCbased simulator like the Vehicle Simulator, developed by Ilan Papini in 2009, a computer software engineer, is now seen as a potential tool that students may readily use to practice further their maritime skills at their own pace and time (Papini, 2009).

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Graduate School, Manila Thus, an experiment was conducted by the researcher in November until early December 2014 to maritime students of the University of Perpetual Help System in Biñan, Laguna and Philippine Merchant Marine School in Las Piñas, Metro Manila. Two groups were formed, a control group which was exposed to a traditional strategy (i.e. video) and an experimental group which was exposed to the proposed learning strategy (i.e. the Vehicle Simulator).

Both groups

underwent a pre-test and post-test evaluation of their navigation skills with three specific topics chosen by the researcher.

The students, as well as their

simulation course instructors, were surveyed to determine the applicability and limitations of the Vehicle Simulator as an alternative teaching and learning tool.

Background of the Study The 20th International Maritime Lecturers Association Convention reported that 80% of casualties in the maritime industry are attributed to human error and 65% of these are related to the inadequacy or lack of quality training. Performance on-board by seafarers can be improved through simulated training or the use of simulation tools. It was noted that a performance improvement of roughly 60% was achievable for inexperienced trainees and between 20% and 40% for experienced trainees, i.e. an overall average improvement of roughly 45% through the use of simulation. Considering these figures, properly applied simulator training can reduce accidents at sea by 14% (Cross, 2012).

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Graduate School, Manila In the Netherlands, subsequent discussion led to the idea of awarding some amount of sea time for simulator experience. Aside from simply improving performance, an incentive is provided by simulator training.

For example,

simulator time can be used to replace up to 60 days of sea-time – reducing the sea-time requirement from 360 days to 300. The ratio applied here is 1:4 – where 15 days of simulator time counts for 60 days of sea-time. But even though this is allowed in some countries, the Standards of Training, Certification and Watchkeeping (STCW) does not recognize the use of simulation time as a replacement for some portion of sea-time (Guest, 2012). Furthermore, report talked quite a bit about the use of simulators for assessment of competence and how the Maritime Institute Willem Barentsz is reducing the use of written exams which are still useful for assessing the knowledge underlying the competencies in favor of simulator-based assessment of competencies. The conclusion is that simulation time is a valuable tool both for maritime training and assessment, and that it is reasonable to expand its use and recognition in maritime education and training. A committee-developed case study of the U.S. Merchant Marine Academy cadet watchkeeping course that has used the Computer Aided Operations Research Facility (CAORF) simulator since the early 1980s strongly indicates that watchstanding knowledge, skills, and abilities can be significantly improved

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Graduate School, Manila using marine simulation and that this training carries over to watchstanding aboard ship. Simulators are used in a growing number of training programs. In addition to their long-standing use at some maritime academies and a number of private and union facilities, simulators have been widely used in commercial air carrier industry, and are increasingly being used in the nuclear power industry, and are used in medical training and a variety of other areas. Since objective evaluation of training effectiveness for any specific use is the exception rather than the rule, the committee believes that widespread use of simulators for training and the accompanying belief in their effectiveness constitutes anecdotal evidence of training effectiveness. One reason offered for the steady improvement in airline safety since the 1970s has been the use of advanced simulators to train pilots for situations too dangerous to try in the air. In the commercial air carrier industry, for example, it is believed that simulatorbased training has considerable value. This belief is bolstered by the observation that airline pilots who changed into a new role in the cockpit via simulator-based training, with no formal in-the-air training for that role, are competent. (National Academy of Sciences, 1996) Although the most obvious goal of using simulation is improving performance, cost effectiveness is also important. Simulators in the commercial air carrier and marine industries generally (although not invariably) cost less to

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Graduate School, Manila build and operate than the operational equipment being simulated. The commercial air carrier industry is able to conduct transition training to a new aircraft entirely in simulators and at substantial savings over costs of the same training conducted entirely in an actual aircraft. In the maritime industry, any calculation of savings comparing cost of using commercial ships solely as training platforms with those of simulators are almost entirely speculative. Training aboard commercial ships can be difficult or, in some cases, impractical because of risk, operating practices, and schedules. In addition, continuing training is mandatory in the commercial air carrier industry, while it is not in the marine industry. Without mandatory requirements, some shipping companies will not finance simulator-based training. The cost of simulator training varies widely, depending on the simulator facility used, the requirements of the particular training program, and the travel, housing, & food expenses for trainees. The committee was able get actual cost figures from several facility operators and developed the following general cost information – most computer-based simulator training programs appear to cost $500 to $700 per day per student. Manned-model simulator ship-handling training courses cost approximately twice that amount, or $1,000 to $1,400 per day per student. The general opinion of mariners who have taken simulator-based courses and the shipping companies who sponsored them is that those courses are

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Graduate School, Manila effective, if not optimal. Shipping companies are using simulators more frequently. In the absence of requirements, they would not be doing so if they thought the training was not cost effective. Some of the lessons in these training courses, however, may not completely or uniformly be applied in the real-world. Learning transfer may fall short because shipboard organization and operating practices have not, in many instances, been restructured to facilitate the introduction and use of these concepts. According to Goldberg (2012), an effective training program addresses the student's training needs with respect to knowledge, skills, and abilities. It exploits all media, from personal computer-based training to limited-task and full-mission simulators and applies the appropriate training tool to the specific level of training. For example, it would not be necessary to use a full-mission simulator for early instruction in the rules-of-the-road training.

Rather, a systematic

approach to training promotes convergence toward full-mission expertise by developing basic modules of skills in several steps. This approach encourages the assembly of increasingly complex skills modules until the trainee can exploit training on a full-mission simulator. Perception of realism is another important consideration (Hays and Singer, 1989). The sequence and manner in which simulation components are introduced to trainees can profoundly affect their perception of the training environment as a real life operating environment. For example, the first ship-

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Graduate School, Manila bridge simulator component that trainees experience is the bridge or wheelhouse mock-up. To ensure an adequate perception of realism, the mock-up needs to be believable so that the trainee and, for that matter, the instructor think of a real ship. On the other hand, basic microcomputer desktop simulators normally consist of a single microcomputer, a single monitor or screen projection, and an input device, usually a keyboard. In contrast to the full range of conditions generated with full-mission ship-bridge simulators, the training environment created by a microcomputer desktop simulator is greatly simplified. The cue domain of the desktop training environment is not only greatly simplified from actual operating conditions, but also differs significantly in manner, form, and correctness of the presentation.

For example, detail and accuracy of visual

displays are generally incomplete. Visual display images are smaller than real life because details are compressed as a result of screen size, and only one sector (e.g.,90 degrees) can be viewed. There is also a single-data entry device (such as a keyboard, mouse, or specially configured device) and only visual representation of equipment controls rather than actual controls. The operation of bridge equipment in microcomputers can be very artificial. Angular relationships are distorted for several reasons, including the relatively flat screen, the need to call up different screens through keyboard

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Graduate School, Manila entries to view other sectors and instrument displays, and a lack of depth perception. One alternative, to display on several screens, can be costly. The simplified training environment of desktop simulators may be modified by physically separating input devices to require participant movement, involving several individuals in the simulation, or by including multiple monitors. Several training system companies have developed software and entry devices that make it possible to emulate specific nautical systems, such as radars and global maritime distress safety systems.

Capabilities of some of these systems

approach are small-scale, limited-task simulators. Interest is growing among marine research and manufacturing companies in the development of high-fidelity maneuvering simulations for automatic linkage into passage planning and execution. Several maneuvering simulations using bird's eye-views or simulated bridge window views, or a combination, are available. Computer software is also used to some extent as expert systems aboard a small number of commercial ships with integrated bridge systems to assist in decision making and to control special maneuvers, such as constant radius turns (NCR, 1994). The substantial rise in computational power and the rapid spread of multi-media compact disk drives in desktop computers have stimulated considerable interest in the potential of these special-task simulator systems for training beyond traditional computer-aided learning.

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Graduate School, Manila Special-task simulators place the participant outside a functional mock-up of ship-bridge or bridge equipment. The training environment produced is highly simplified and typically requires artificial interactions between student and simulator, such as controlling all operations through keyboard commands and data entries. The participant must conceptualize the ship-bridge or bridge equipment more than a full-mission or multi-task simulator. The simplified environment of a special-task simulator can provide a highly focused learning experience for specific nautical knowledge needs and tasks. The trainee may not, however, react in the same manner as when aboard ship because the manner and form of the stimuli and interactions differ greatly from actual operating conditions, a task also beyond capability of a full-mission or multi-task simulator. This now forms a great driving force for the study and the research gap the study attempts to address. A simulator does not train per se but it is the way the simulator is used that yields the benefit. "It is easy to be impressed by the latest, largest full-mission simulator, but what is more important than the technology is how educational methodology is applied and whether it increases training effectiveness significantly, incrementally, or not at all." (Drown and Mercer, 1995) Can the vehicle simulator be able to withstand and pass critical evaluation paving its way to be used as an alternative tool in maritime schools?

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Graduate School, Manila This is an important inquiry that the researcher addressed during the course of this research undertaking. The researcher embarked on this study for three pressing reasons: 1) Profound enthusiasm for computers and technology which has become integral to the researcher’s day-to-day life experiences. 2) Conformity with professional competencies as being engaged in maritime training and mentoring using full mission bridge simulators. 3) Innovation

for

improvement

towards

the

state-of-the-art

maritime

instruction.

Theoretical Framework Numerous teaching and learning theories were examined by the researcher to find inspiration and firm basis to anchor this research topic. Howard Gardner’s Multiple Intelligence (Kincheloe, 2004), Maria Montessori’s Montessori Approach (Tabalzini, 2011), and Edward L. Thorndike’s Theory of Connectionism were considered (Hergenhahn, 2009). Gardner espoused that human beings are gifted with a variety of competencies only waiting to be unleashed and harnessed with the right stimulus. Montessori, on the other hand, believed that the learning process is facilitated better in the spirit of “play.” Meanwhile, Thorndike theorized that the connection between stimulus and response is strengthened through repeated use or practice. However, the most

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Graduate School, Manila appropriate theory which lends credence to this research is the Game Theory by John Von Neumann (MacRae, 1992).

Figure 1: Game Theory Framework Game Theory is a way of looking at a whole range of human behaviors as a game. Though initially developed by Von Neumann as written in his book Theory of Games and Economic Behavior in 1944, other gurus like Oskar Morgenstern, John Nash Jr., and many others until the time of Jean Tirole in 2014, have further enhanced the Game Theory.

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Graduate School, Manila Game Theory is a study of strategic decision making. Specifically, it is the study of mathematical models of conflict and cooperation between intelligent rational decision-makers. An alternative term suggested as a more descriptive name for the discipline is interactive decision theory. Game Theory is mainly used in economics, political science, and psychology, as well as logic, computer science, and biology. To be fully defined, a game must specify the following elements:

(a)

players of the game, (b) information available to each player, (c) actions available to each player, and (d) payoff for each outcome or as Rasmusen refers at PAPI (2006). A game theorist typically uses these elements, along with a solution concept of their choosing, to deduce a set of equilibrium strategies for each player such that, when these strategies are employed, no player can profit by unilaterally deviating from their strategy.

Conceptual Framework The paradigm of the study or conceptual framework is the original concept developed by the researcher on the topic on hand. It is a visual representation of the relationships of variables in the study and the expected outcome.

The

researcher adopted two frameworks, one to illustrate the envisioned concept and the other to depict the research process itself. The envisioned concept considers inherent characteristics of a learner as well as some intervening characteristics in determining whether or not the 13

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Graduate School, Manila learning objectives according to Bloom’s Taxonomy have been achieved using the Vehicle Simulator.

Figure 2: Paradigm of the Study (Envisioned Concept) The latest version of Bloom’s Taxonomy (Heer, 2014) places importance on a hierarchy of learning objectives from the most basic to the most complex or 14

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Graduate School, Manila highest level of learning on concepts, namely:

(a) remember concepts, (b)

understand concepts, (c) apply concepts, (d) analyze concepts and situations, (e) evaluate concepts and situations, and (f) create or develop something. On the other hand, the procedural aspect of the research is represented by a framework that adopts the Input-Process-Output-Outcome (IPOO) Model as indicated in Figure 3.

Figure 3: IPOO Model (Procedural) Since the students are both participants to the experiment and respondents to the feedback survey, their profiles were important inputs. The profile includes their age, gender, year level, health condition, intelligence level, and available time to study.

It is a given that all of them are Filipinos and

maritime students enrolled at the University of Perpetual Help System in Biñan, Laguna and Philippine Merchant Marine School in Las Piñas, Metro Manila. 15

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Graduate School, Manila Other valuable inputs are the teaching-learning resource materials (Vehicle Simulator for the experimental group and video for the control group) and the three topics to be taught to the student participant-respondents within two hours, i.e. collision regulation, Williamson turn, and position fixing. The process merely involved the conduct of the experiment between two groups and the feedback survey on the same group participating in the experiment. The experiment entailed four basic steps: (a) brief orientation is conducted to all participants; (b) all participants were subjected to a pre-test to determine their initial competency level; (c) all participants are taught the three topics with the experimental group using the Vehicle Simulator and the control group using a video lecture; and (d) all participants were subjected to a post-test to determine their new competency level. A task performance evaluation form (i.e. following specially-designed Rubrics) was used to determine

the

competency level of students on the three topics taught. The feedback survey to be participated in by the students and their respective simulation course instructors entails only four major items: (a) How did the students feel about using the assigned learning tool? (b) What features did the students like most in the assigned learning tool? (c) What features did the students like least in the assigned learning tool? (d) What suggestions do they have in improving the teaching-learning process on the said topics?

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Graduate School, Manila The anticipated output of the study basically answers two questions related to the research problem: (a) Is it feasible to use the Vehicle Simulator as an alternative teaching and learning tool?

(b) Is the Vehicle Simulator an

effective teaching and learning, tool? The ultimate goal of this study is a change in behavior or environment or outcome. It is anticipated that through the use of the said learning tool, the following question is addressed:

Were the navigation and seamanship

competencies of students enhanced by using the Vehicle Simulator?

Statement of the Problem This research focused on the issue:

Is it feasible to utilize Vehicle

Simulator as an alternative teaching and learning tool in maritime schools? This study sought to address the following questions: 1. Compared to more standard traditional methods being used in maritime schools, e.g. video, how effective is the Vehicle Simulator as a teaching and learning tool in specific competencies like collision regulation, Williamson turn, and position fixing? 2. Is there a significant difference in the applicability (advantages) and limitations (disadvantages) of the Vehicle Simulator as a teaching and learning tool in relation to other familiar branded simulators? 3. Is there a significant difference in the most liked and least liked features of the Vehicle Simulator? 17

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Graduate School, Manila

Hypothesis A hypothesis is an educated guess and for it to be valid, it must be tested through a scientific method. This study tested this null hypothesis: There is no difference between the mean performance of Vehicle Simulator users and non-users. H0a :

Null Hypothesis where

µ1 = µ 2

H0a = the null hypothesis comparing mean scores of Vehicle Simulator users group and non-users group μ1 =

mean of the Vehicle Simulator users group

μ2 =

mean of the non-users group

Considering the respondents’ critical evaluation on the use of the Vehicle Simulator as their alternative learning tool, there must be a scientific basis for their contrasting views, agreements, and disagreements. A second null hypothesis is formulated to compare the mean scores of the Vehicle Simulator users group prior and after the learning intervention using the said tool. Thus, the study also tested this second hypothesis: There is no significant difference in the mean performance of the Vehicle Simulator users group before and after the learning intervention.

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Graduate School, Manila

Null Hypothesis where

H0b :

µ1prt = µ1pot

H0b = the null hypothesis comparing the pre-test and post-test of Vehicle Simulator users group μ1prt = mean of the pre-test scores of Vehicle Simulator users group μ1pot = mean of the post-test score of the Vehicle users group

The third null hypothesis was presented to test the difference in the perception of the students and instructors on the features of the Vehicle Simulator. This study tested the hypothesis: There is no difference in the perception of students and instructors on the features of the Vehicle Simulator. Null Hypothesis where

H0c :

µ1s = µ1t

H0c = the null hypothesis comparing the perceptions of students and instructors on the features of the Vehicle Simulator μ1s = mean of the students’ perceptions μ1t = mean of the teachers’ perception

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Graduate School, Manila Scope and Delimitations The study focused solely on the Vehicle Simulator, software used by maritime educational and training institutions for Navigation and Seamanship courses. It was compared with traditional teaching methods such as video or film showing and not with any other method, e.g. other simulators. The study was conducted between November and December 2014. This study used two methods of data gathering, namely: experiment and survey. The experiment involved 40 students only. There were two surveys – one with the 20 students included in the experimental group and another with 20 students in the control group. The said purposive sample was brought about by budget and time constraints of the researcher. Two groups of students (20 each group) were tested to determine if there is a difference in scores between those who used the standard laboratory tool (video) and those who used the Vehicle Simulator.

Instructors in simulation courses of the two schools were also

surveyed.

Significance of the Study The pursuit of the topic has serious implications on a number of stakeholders both locally and abroad. This research is relevant to various groups and would have a significant impact to many sectors in the global maritime industry.

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Graduate School, Manila Researcher. Being a serious and dedicated maritime educator, the researcher can explore the full utilization of this teaching and learning tool. In the near future, the researcher can even enhance the features of the Vehicle Simulator with constant liaison with courseware developers and users, i.e. both teachers and students. The researcher intends to develop in the future his own innovative teaching strategies for maritime educators to emulate and utilize. Students. This study can become a potential solution to the perennial complaint of maritime students on constraints in learning effectively the course Electronic Navigation and other courses which can better be taught by simulation techniques.

Through this study, they would gain the needed proficiency in

comprehension and skills to prepare them in the actual job on-board and in acquiring a marine license as proof of basic competence. The features of the Vehicle Simulator may determine opportunities for self-learning to attain mastery level in specific skills such as shiphandling, navigation, and the Rules of the Road. Lack of time to practice, lack of physical facilities, and lack of teacher intervention are some constraints which may be addressed by the results of this study. Maritime Educators and Institutions. Computer-assisted learning has been used for some time by a number of schools, training, and other organizations that offer license-preparation courses. Available courseware includes tutorials to aid in the acquisition of knowledge and to practice

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Graduate School, Manila responding to questions in the multiple-choice format. There is a growing library of simulator software designed for marine applications. Considering the various subjects in the classroom that require simulation such as general navigation, radar navigation, piloting, ship handling, maneuvering, automatic radar plotting aids, rules-of-the-road training, port entry, and the global maritime distress safety system, this study would be at the maximum advantage for academe and organizations to achieve their ultimate objectives. Maritime schools need to invest on relevant and effective courseware as evidenced by their intention to espouse quality as they graduate competent seafarers ready to take and pass the license board examination and prepared to compete for job placements in local and foreign shipping lines.

This study

presents a credible alternative to enhance the competencies of maritime students, which consequently reflects the image and reputation of the schools. Maritime Industry. The maritime industry is comprised mainly of shipping companies and crewing or manning agencies who regard human capital as an integral part of their business. Technical competence is a key criterion in placing seafarers in reputable companies operating a diverse array of marine vessels. Hiring practices in the maritime industry, although not standard, are usually based on acceptance of a marine license as proof of basic competence. A newly employed deck officer is normally considered competent for initial employment and may be given significant responsibility the first day on the job

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Graduate School, Manila based solely on possession of the required license. This immediate expectation of competence may exist even when the officer is serving aboard an unfamiliar vessel, in unfamiliar ports and waters, with an unfamiliar crew. Simulation could potentially be used as a tool for initial evaluation and indoctrination into a particular company's operating practices in routine and emergency situations, prior to actual engagement. This would eliminate the present concern in situations where an officer is "hired blind." It can be made as a pre-employment requisite to pass the skills test that would determine basic skills a seafarer should know by heart, e.g. International Rules for preventing collision at sea, shiphandling and maneuvering, or Bridge Team Management. Use of simulation may also enable employers to shorten the period of onthe-job training required for promotion. Simulator training in company procedures and ship-specific operating practices, followed by an objective, performancebased evaluation of the skills acquired, appear to fill a void not previously addressed by traditional teaching and evaluating method. Government Agencies. This study would be useful to government agencies such as Maritime Industry Authority (MARINA) in conducting performance evaluation for licensing and other purposes. An endorsement of best practices in maritime education, such as the use of highly recognized and innovative tools which professionals and students alike can practice on, could improve confidence towards pursuing a maritime career. Practical tests as a

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Graduate School, Manila component of the licensure board examinations for seafarers may consider the use of the Vehicle Simulator. Country. The Philippines would benefit from this study being the leading supplier of seafarers globally. Filipino seafarers have always been recognized as hardworking and competent. The use of the Vehicle Simulator further enhances the Filipino seafarers’ competencies. It can also potentially accelerate our capability as a country in producing more competent seafarers to address the growing demand for such maritime professionals and workers in the industry.

This further asserts our current

standing in the global maritime industry as a leading supplier of human capital. Periodic checks by international maritime bodies may consider the diversity and acceptability of teaching strategies in higher maritime education institutions in the country to be able to get a pass mark in quality assessment inspections.

Definition of Terms To better appreciate and comprehend the various technical terms, acronyms and jargons used in this study, they are defined, described and elaborated as follows: Alternative Teaching and Learning Tool.

This refers to technique,

equipment, material, gadget, resource material or activity which a teacher may use to facilitate the learning process. In some cases, it is prescribed by an

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Graduate School, Manila educational or training institution. Creative teachers tend to develop their own teaching and learning tools. CAORF. Computer Aided Operations Research Facility CBT.

Computer-based Training is any course of instruction whose

primary means of delivery is a computer. A CBT course (sometimes called courseware) may be delivered via a software product installed on a single computer, through a corporate or educational intranet, or over the Internet as Web-based training. CHED. Commission on Higher Education is the government agency that regulates and supervises all higher education institutions including those offering maritime degrees. Collision Regulation. This refers to the “rules of the road” or navigation rules to be followed by ships and other vessels at sea to prevent collisions between two or more vessels. Control Group. This is a group of subjects to an experiment exposed to a typical environment and used as a comparison to the experimental group. DP.

Dynamic positioning is a computer controlled system that

automatically maintains the vessel’s position and heading by using its own propellers and thrusters. ECDIS. Electronic Display and Information System

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Graduate School, Manila Experimental Group.

This is a group of subjects in an experiment

exposed to the variable under study. Full Mission Bridge Simulator.

The full mission bridge is set on a

movable platform that recreates the sensation of rolling a large ship at sea. A similar effect is produced by the visualization system of four computer-generated visual representations of the navigation environment. Game Theory. A theoretical model developed by John Von Neumann espousing that in playing a simulated game, decisions are made and they have consequences. It allows the players to create their own unique or generic strategy to win or achieve the main goal of the game. Outcomes-based

Learning.

These

are

methods

that

focus

on empirically measuring student performance (the "outcome"). OBE contrasts with traditional education, which primarily focuses on the resources that are available to the student, which are called inputs. Performance Assessment, Post-Test.

An assessment given to a

learner to gauge what has been learned after a learning session. Position Fixing. This is the branch of navigation concerned with the use of a variety of visual and electronic methods to determine the position of a ship, aircraft or person on the surface of the earth. Pre-Test. Is an assessment given to a learner to gauge previous or stock knowledge on a particular topic or subject matter.

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Graduate School, Manila ROV. These are remotely operated vehicles. Rubrics. A rubric is a set of scoring guidelines for evaluating student work. Shiphandling. This is a fundamental skill of professional seamanship is being able to maneuver a vessel with accuracy and precision. Simulation. Is the imitation of the operation of a real-world process or system over time. Simulation Laboratory. A simulation laboratory is an interactive facility in a school or company wherein trainees or learners are given real-life exercises or experiments to practice a set of skills and convert them into competencies. Special Task Simulator.

This is a simulator capable of simulating

operation and/or maintenance of particular bridge instruments, and/or defined navigation/maneuvering scenarios. Vehicle Simulation Games.

These are genre of video games which

attempt to provide the player with a realistic interpretation of operating various kinds of vehicles. This includes automobiles, aircraft, watercraft, spacecraft, military vehicles, and a variety of other vehicles. Virtual Reality.

This is a computer simulation of a real or imaginary

system that enables a user to perform operations on the simulated system and shows the effects in real time.

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Graduate School, Manila Williamson Turn. A Williamson Turn is defined as putting the rudder hard over toward the side on which the person has gone overboard and keep it there until the ship is 35 to 50 degrees from the initial heading.

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Graduate School, Manila

Chapter 2

REVIEW OF RELATED STUDIES AND LITERATURE

Simulation is the imitation of the operation of a real-world process or system over time. The act of simulating something first requires that a model be developed.

This model represents the key characteristics or behaviors or

functions of the selected physical or abstract system or process. The model represents the system itself, whereas the simulation represents the operation of the system over time. Training simulation normally forms part of a program designed to educate employees or students about the skills needed to operate a business or perform a task, as well as persuade them to think outside the box and see the bigger picture.

This can lead to a better organized, more fluid system where all

employees understand their role in making the company successful. Or in case of students, they are able to master specific competencies expected of them in their future careers or organizations. In maritime education, examples of mostly used simulators are the ship’s bridge

simulators,

engine

room

simulators,

cargo

handling

simulators,

communication or GMDSS simulators, and ROV simulators. They often consist

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Graduate School, Manila of a replication of a ship’s bridge, while operating consoles and a number of screens on which the virtual surroundings are projected. The very first training simulation program available was developed and made commercial in 1956 by the American Management Association. It was called The Top Management Decision Game. This paved the way for thousands of other simulation products to be developed in numerous industries around the world which includes the maritime industry.

Today nearly all simulation

techniques are computer-based (Stuart, 2007) and they involve multi-level algorithms that calculate performance based on the decision entered (Fripp, 1997). Simulations are based around a real industry, hence, they try to use real data to be as accurate as possible and to provide a realistic experience. One of the more recent simulators in the market is the Vehicle Simulator invented and developed by Ilan Papini in 2009. Among its key features are (a) excellent learning tool, (b) includes a built in scenery and vehicle design, making it much simpler for users to create and share content than ever before, and (c) has a much denser scenery, an excellent physical simulation, and a totally flexible vehicle design (Papini, 2009). This chapter discusses the related studies and literature covering feasibility study and critical evaluation of using vehicle simulator as an alternative learning tool in maritime schools: an innovation opportunity. These studies are

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Graduate School, Manila gathered from books, journals, other periodicals, on-line sources, and published materials/articles that would provide sources of information for its completion. Many books and journals have been written about simulators being used in maritime learning. Studies about students’ performance in navigation have also been conducted here and abroad. The feasibility study of using and an opportunity to innovate vehicle simulator in maritime schools is related to the following studies that were reviewed by the researcher. These studies will help him assimilate facts that will lead to the thorough investigation of the problems related to his chosen topic, thus, giving him deeper insight which way the study might be pursued. Through the past few years, numerous studies and literature have been written about simulators locally and overseas.

Related Literature Foreign Literature Edmonds (1994) believes that scenario creation is crucial to optimizing the training value of individual exercises. Simply creating a realistic scenario does not necessarily result in operating conditions that will evoke desired student responses, create an effective illusion of reality, or create real life pressures. Developing situations intended to challenge or test the trainees is sometimes accomplished through scenarios involving role playing. In one possible situation, assignments could be reversed, with seniors placed in subordinate positions and 31

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Graduate School, Manila junior personnel in senior positions. The objective is to create a pressure situation in which it becomes apparent to participants that improved interpersonal dynamics and communications are needed to reduce the potential for human and organizational error. This form of role playing seems to work. It should, however, be very carefully debriefed to avoid any negative impact on the confidence of junior personnel whose performance may have resulted in a failed solution during the exercise. Sweeney and Groh (1993), on coordinated tug simulator-based on-board drills Morania oil tanker corporation, report shows that the company has a need for a credible third party to conduct the audits and contracted with a marine training consultant, who had also served as the simulation instructor for the computer-based training sessions. All vessels have now been audited. In the second year following training, the company decided to have their training consultant conduct on-board drills or "real-time" simulation. The testing and validation of simulations can be expensive. Once the data and adjustments are in the program, these aspects are basically not transportable. The price of simulation probably will not come down until economies of scale are achieved through more and wider use. Although insurance underwriters base rates on costs to the insurance industry, the company has been able to negotiate some rate reduction as a result of its documentation of training results and improved operator safety performance. Over the last three years, Morania has had a

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Graduate School, Manila reduction in personnel and indemnity and hull insurance rates, which is attributed in large measure to improve safety performance as a result of the training program. MOL Marine Consulting (MOLMC) upgraded one of its two owned simulators. The bridge simulator has been equipped with a Dynamic Positioning System (DPS), as well as an enlarged screen that replicates the field of vision from the bridge. With offshore at the core of MOL’s strategy, DPS is an essential tool when dealing with the transport and storage of crude oil and LNG. The company says the upgrades will allow it to simulate any situation and provide practical training in that situation (Maritime Simulation News, 2014). The Bouchard Transportation Company, Inc. and the State University of New York Maritime College (SUNY Maritime) opened in October 2014 its Bouchard Tug & Barge Simulation Center, a state-of-the-art training facility, incorporating the latest in Kongsberg’s Polaris Bridge Simulation technology. It utilizes an industry-inspired bridge console arrangement, with the latest hydrodynamic ship models and exercise areas. SUNY Maritime College and the Bouchard Transportation Co., Inc. are committed to educating future mariners; the young people who will lead the industry in the years to come. Working together, these two entities also are committed to training mariners currently working in the tug and barge industry, in

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Graduate School, Manila order to keep them abreast of new topics and procedures (Maritime Simulation News, 2014). The Center for Simulator Maritime Training in Almere, the Netherlands, is a new modern complex with state-of-the-art full-mission bridge simulators is focused on upgrading maritime skills of professionals particularly in the aspect of critical thinking, problem solving, ethical decision making, and confidence building. The two full-mission bridge simulators are equipped with NACOS 65-5 Integrated National Systems. The center also offers a Six-Part Task Simulators which are smaller systems with the same operating system used for pure instrument training, as planning stations, and for shiphandling simulation (CSMART, 2014) Gredler (1992) proposed in her book that a process approach be adopted in designing and evaluating simulation games in education. This will determine the effectiveness of the tool in reaching whatever goals it purports to achieve. According to Benjamin Bloom (Heer, 2014), learners have varying degrees of capacity to absorb new knowledge. The most basic of which is simply by use of rote learning techniques or simply memorization. The next level is beyond remembering facts but having a good comprehension or understanding of the concepts. Students who can articulate concepts are said to be of better understanding. The next higher level goes beyond merely understanding concepts. A learner must apply what he has learned. Practicing a skill or making

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Graduate School, Manila use of a concept is considered a higher learning goal. The ability to dissect, investigate and synthesize is a higher order learning goal according to Bloom. For example, one can get to the root cause of a problem through analysis. Subsequently, another higher level learning goal is evaluation – the ability to check or assess or test a concept. Through competent evaluation, one can readily make constructive suggestions on how to make things better. And finally, the highest manifestation of learning is when the learner was able to create something out of what he has learned. Thus, entrepreneurship students are expected to set up a real business, culinary students are expected to create menus out of dishes, accounting students are expected to produce financial reports, and maritime students are expected to develop something tangible like a policy manual or training module to pass on the technology to other seafarers or students. That is the highest order of learning as per Bloom’s model.

Local Literature In the Philippines, numerous training institutions are now using various simulators in many courses. The Maritime Training Center of the Philippines, for example, offers a number of simulator courses such as Ratings Forming Part of a Navigational Watch; Ratings Forming Part of an Engineering Watch; Steering Course; Radar Navigation, Radar Plotting and Use of ARPA; Radar Simulator Course; and Radar, ARPA, Bridge Teamwork, and Search and Rescue (TMTCP, 2014). 35

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Graduate School, Manila The Commission on Higher Education released CHED Memorandum Order No. 31 series of 2013 pertaining to amendment and supplemental policies, standards and guidelines to CMO 13 series of 2013. An important highlight of this CMO is the endorsement of the outcomes-based education in academic programs such as maritime education. This simply espouses that the best way to learn is to first determine what needs to be achieved. Once the desired results or “exit outcomes” have been determined, the strategies, processes, techniques, and means are put in place to achieve predetermined goals. In essence, it is working backwards with students being the center of the learning-teaching milieu (CHED, 2013).

Related Studies Foreign Studies McGuire (1976) in her paper “Simulation Technique in the Teaching and Testing of Problem Solving Skills” discusses extensively the various skills that are brought into play by simulation techniques such as data gathering, processing and interpretation skills; resource allocation and management skills; skill in ordering priorities in data seeking and decision; decision making skills; skills in manipulating a situation; skills in monitoring the effects of these manipulations; and readjusting decisions or actions to respond to the modified situation.

By imitating the decision sequential process which entails a

combination of such skills, simulation offers an exciting technology for both the 36

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Graduate School, Manila teaching and testing of problem-solving competencies. For this reason, some more or less exotic simulation techniques have long been enjoyed a deservedly favored status as instructional adjuncts in the education of business executives (business and management games), military personnel (war games and military exercises), professional pilot (Link Trainer), and even astronauts (spaceflight simulators). In the healthcare sciences, Galloway (2009) explains vividly how simulation strategies help transform novices into competent professionals in the nursing profession.

Such techniques vary widely from role plays, integrated

simulators, full simulation, etc. She also cited how simulation trainers and costs have sometimes become issues in carrying out effective simulation programs in healthcare education. The paper, “Gaming Meets Training” by Steven Gosling (2012) from the Nautical Institute in the U.K., looks at the disappearing line between simulation and gaming, and how the maritime

world can benefit from the advances in the

gaming industry to create immersive, interactive simulation environments. It discusses the “Team Safety” project, an EU funded research project to use 3D gaming in seafarer safety training. Another paper, “IT and Modern Technology in Maritime Education Training” from Mengya Qi of the Merchant Marine College in China looks at the effect of new technologies being employed in maritime training and education. It

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Graduate School, Manila also looks at the potential for interdisciplinary efforts to apply advances in other fields to existing problems in the maritime industry. Jones (1993), presented a study on the Perception of Simulator-Based Training. Study results are observations of Panama Canal Pilots on the Value of Ship-Bridge Simulation which are shown in the subsequent statements: “Getting the chance to practice maneuvers in Canal anchorage areas in the simulator has allowed me to develop more confidence while maneuvering in crowded anchorages, especially in Limon Bay anchorage." (Pilot understudy); "My communications skills have improved since I have trained on the simulator. Communications with other vessels, marine traffic, and signal stations has become clearer." (Pilot understudy); ''Backing and filling maneuvers in closed quarters have become a lot smoother since I have been able to practice them in the simulator." (Pilot understudy);

"Maneuvering container vessels with strong

winds abeam is one of the maneuvers that I have been able to practice in the simulator that has given me an edge when I have had to do it for real, especially in the approaches to Gutan Locks." (Licensed pilot, two-year experience); "I have been able to experience and better understand the interaction between vessels when passing each other" (Limited pilot). Additional perceptions are: "I had the opportunity to practice docking situations at dock 16B Cristobal before I actually had to do it for the first time. The simulator helped me obtain a better understanding of the situation." (Limited

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Graduate School, Manila pilot); "The vessel I was piloting suffered an engine failure. Since I had practiced exercises in the simulator, where this type of situation occurred, my response to the real event was quicker and more confident." (Panama Canal pilot); "While transiting the narrowest part of the Canal, the Culebre Cut, heavy fog set down and the visibility was reduced to almost nil. Having practiced this very scenario in the simulator, I was able to handle this situation in a calm and relaxed manner." (Panama Canal pilot); "The main disadvantage I have experienced in the simulator is the perspective looking from the bridge. It has taken me some time to get used to it, and it differs somewhat from what you see on board vessels." (Pilot Understudy);

"Simulator training has helped me understand and

set my priorities when making specific maneuvers" (Pilot in Training). The findings of this study corroborate with the fact that simulation provides an opportunity to correct bridge team management deficiencies and problems in personal styles without interfering with and jeopardizing. An early study conducted at the Computer Aided Operations Research Facility (CAORF), Kings Point, New York, reported that on entering a particular harbor, students who had received simulator training significantly outperformed students with the same background and experience, but with no simulator training (Miller et al., 1985). However, the methodology employed was elementary, and the results are not conclusive.

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Graduate School, Manila Available research generally supports the proposition that there is a meaningful transfer of knowledge and skills developed through simulator-based training to actual operations (Kayten et al., 1982; Multer et al.1983; D'Amico et al., 1985; Hammell et al., 1985; Miller et al., O'Hara and Saxe, 1985; Froese, 1988; Douwsma, 1993). If there is a concern, it is the lack of reinforcement of newly learned skills in the traditional workplace. Failure to reinforce skills onboard ship is a contributing cause in the failure to transfer knowledge from simulators to real life. It is difficult to determine the validity and degree of equivalency between simulator training and shipboard experience without an evaluation of transfer. The issue is whether it can be determined that skills learned in a simulator can be employed aboard ship. The most systematic way to test the application of this training to shipboard performance would be to systematically compare shipboard performance of simulator-trained individuals (as group) to performance of a group whose only difference is the lack of simulator training. Logistically, these studies are difficult to execute within the commercial air carrier industry and may even be more difficult to execute in the marine industry, which lacks systematic organizational structure. Use of simulators for training is based on the assumption of transfer (i.e., skills and knowledge learned in the classroom can be applied effectively to relevant situations outside the classroom). One unresolved question is a

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Graduate School, Manila quantitative assessment of the transferability of simulator training to the real world, historically, commercial air carrier industry. Studies undertaken in the late 1940s by Williams and associates (Flexman et al., 1972) established the effectiveness of flight simulators for training pilots to fly light, single-engine aircraft. The methodologies developed for these evaluations have been used to demonstrate the effectiveness of simulators for the instruction of a variety of flight skills

(Povenmire and Roscoe, 1971, 1973; Waag, 1981; Lintern et al., 1989,

1990). These methodologies have been adapted to assess training effectiveness from specific simulator features. While some studies support the notion that higher levels of fidelity add to training effectiveness (Lintern et al., 1987; 1990; Hays and Singer, 1989), but others do not (Waag, 1981; Hays and Singer, 1989; Lintern et al., 1989; Lintern and

Koonce, 1992). For example, research has

failed to support the belief in the commercial air carrier community that motion systems add to the training effectiveness of a simulator. Despite the widespread acceptance of motion systems, the scientific evidence is inconsistent. Meurn (1990), reports the curricula for the U.S. Merchant Marine Academy's (USMMA) full-mission, ship-bridge simulator-based watchkeeping course and its implementation. The recorded grades for 31 courses involving 233 three- to four-person cadet watch teams (approximately 900 cadets) over a 10year period (October 1985 to March 1994) were reviewed. The objectives are to

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Graduate School, Manila examine the application of instructional systems design concepts to quantitatively identify trends in cadet performance over the course of instruction, and to develop insights and lessons about the application of simulator-based training for third mate candidates with limited, prior nautical experience. The data that were available were not collected as part of a research experiment. There were no control groups, nor was there follow-up monitoring of real-world performance. It was not possible, therefore, to compare course performance data for ship-bridge simulator-based training with the results of traditional training. Also, there were no data to assess transfer effectiveness for the individuals who participated in the training. The analysis presented in this study indicates that the development of watchstander knowledge, skills, and abilities can be significantly improved using simulators as a training medium.

The data are not available to determine

whether ship-bridge simulator-based training is more effective and efficient than traditional training. The analysis

does suggest, however, that the ability to

control the learning process (including the ability to design scenarios, monitor performance, and debrief cadet participants), in contrast to the lesser control over learning situations about ships at sea, leads to improvements in efficiency. The U.S. Maritime Administration (MarAd) and the USCG from the mid1970s through the mid-1980s using the ship-bridge simulator at the Computer Aided Operations Research Facility (CAORF), Kings Point, New York studied

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Graduate School, Manila extensive mariner performance. This research initially focused on developing a clearer understanding of factors that affect human performance. The research methodologies that were employed were affected, to some extent, by the fact that researchers were learning how to use ship-bridge simulators in research. The simulator itself was sophisticated for its time. As a result, before the experiments could proceed, mariners who participated in the research had to learn how to accomplish certain critical tasks, such as measuring distances, in the simulator environment. Although the results of these experiments are a useful starting point, they have not been systematically updated with the changes in operating conditions in the merchant fleets. Comparative analysis conducted by the Danish Maritime Institute (DMI) for real life and simulated entries of a large passengers ferry to a new berth revealed that the swept path plots of simulated runs had closer tolerance than the real harbor entries. The report attributed this result to variable starting point for the real life tests because of environmental conditions. The report also found that visual references were more frequently relied on in actual operations than in the simulator where there was more frequent use of the simulator's instrumentation. Based on responses to inquiries by the test's participants, this result was attributed to "problems with the estimation of speed and distance in the simulator". The heavier reliance on instruments in the simulation may have

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Graduate School, Manila been responsible to some extent for the tighter tolerances, although examination of this possibility was not reported as a research objective. There are no data to determine whether this is the case; there are no data or research to determine whether the results of ship-bridge and desktop simulators are comparable; and there are no data to determine whether different cognitive skills are used to achieve the results. Local Studies Baylon and Santos (2011) studied the scenario of maritime education in the Philippines and noted numerous challenges. One of their findings was that many maritime education and training institutions lack the latest technology in terms of facilities and equipment such as simulators and other supporting technologies. Calaor (2001) wrote a paper on simulation games in education within the Philippine setting. The paper took a serious look at the effects on the learners’ inter-ethnic attitude on simulation games.

Synthesis Following the aforementioned review of related studies and literature, there are many insights deduced such as: a. Learners develop numerous skills through simulation techniques. These set of skills include critical thinking, resource allocation, information

processing,

decision 44

making,

team

management,

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Graduate School, Manila situational awareness, strategic planning, time management, and problem solving. (Fripp, 1997; McGuire, 1976; Miller, 1985; Kayten, 1982; Multer, 1983; D’Amico, 1985; Hammell, 1985; Froese, 1988; Douwsman, 1993; CSMART, 2014) b. Simulation technique poses specific challenges such as cost of software programs, trainer or teacher training, venue selection, intellectual property rights, and support maintenance, etc.

(Waag,

1981; Lintern and Koonce, 1992) c. Use of simulators in training has benefits such as savings (in the case of shipping lines), skills mastery, higher perception of quality of training & education (in the case of schools), higher probability of hurdling licensure board examinations (for graduating maritime students), etc. (Papini, 2009; TMTCP, 2014) d. Simulation technique builds confidence of the learner.

There is a

saying that practice makes perfect. Navigation and seamanship are broad skills that can be mastered over time through continuous and rigorous practice. Through simulation, a virtual reality is experienced and the learner begins to gradually increase his competence level. (Jones, 1993; Calaor, 2011) e. The virtual realities created through the use of simulators prevent potential accidents in a regular apprenticeship or actual exercise.

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Graduate School, Manila Practicing a skill in a real-life setting may be too risky and costly. (Gosling, 2012; Jones, 1993; Sweeney and Groh, 1993) f. More companies and schools are now using simulators and many are even continuously upgrading their facilities and resources. Through the outcomes-based learning approach, many schools are now investing on simulators.

(Stuart, 2007; Galloway, 2009; Flexman,

1972; Meurn, 1990; Maritime Simulation News, 2014) g. The use of simulators is compliant with CHED Memorandum 31 series of 2013 requiring schools to adopt outcomes-based approaches to teaching and learning. (CHED, 2013; Baylon and Santos, 2011) h. Simulators capture all three learning domains – i.e. cognitive, affective and psychomotor. (Miller, 1985; Lintern, 1988; Hays and Singer, 1989; Herr, 2014; Edmonds, 1994) i.

Simulators allow the learner to manifest all the learning objectives as postulated by Bloom, i.e. create, evaluate, analyze, apply, understand and remember. (Miller, 1985; Meurn, 1990; Gredler, 1992)

The test of a teaching tool that readily adapts to the learning style of today’s younger learners (as mentioned in d, h, and i) that is both compliant to government education policies (c, f, and g) and has features favored by both teachers and learners (a, b, c, and e) is the research gap this study sought to address. 46

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Chapter 3

RESEARCH METHODOLOGY

This chapter discusses the methods and procedures that were used in this study. These are presented in the following sections: Research Design, Sampling Design, Respondents, Data Collection, and Statistical Treatment.

Research Design This study used a hybrid of descriptive-experimental method of research through a task performance evaluation, feedback survey, and practical experiment administered to 40 respondent-participants. Survey questionnaires which have been previously prepared (see Appendices) were distributed and answered by respondents. This constitutes the data to be analyzed that led to the investigation of any correlation that exists between the Vehicle Simulator users and non-users’ competence and other factors like age, health condition, intelligence level, etc.

Respondents and Sampling Design The respondent-participants to the experiment and survey are Filipino students of the University of Perpetual Help in Biñan, Laguna and the Philippine Merchant Marine School in Las Piñas, Metro Manila. They are ideally students who have not yet undertaken any subject on navigation or any subject using 47

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila simulators but have taken basic topics like Rules of the Road and have not yet been exposed to simulators. Sophomores are the ideal candidates as respondent-participants. The non-probability purposive sampling process was employed in this study. Due to some budgetary and time constraints, the researcher chose only a group of 40 maritime cadets who were taken as sample to represent userrespondents of Vehicle Simulator. The respondents were split into two groups, namely: one group composed of 20 students was taught using the Vehicle Simulator and another group of 20 students was taught using traditional method (i.e. video). The breakdown of the student participant-respondents to the experiment and feedback survey is as follows: Table 1 Breakdown of Student-Respondents Respondents

UPHB Students

PMMS Students

Total

Experimental Group Control Group

10 10

20 20

Total

Meanwhile, the breakdown for instructor-respondents to the feedback survey is detailed in Table 2.

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Graduate School, Manila Table 2 Breakdown of Instructor-Respondents UPHB Instructors

PMMS Instructors

Total

The participant-respondents were selected using random sampling. Thus, in a class of 40 students, the top 5 brightest students and the 5 students with the least academic rank are automatically excluded. The 20 students per school were selected at random from the remaining 30 students. This procedure was applied to both UPHB and PMMS.

Locale of the Study The study was conducted at the College of Maritime Education of the University of Perpetual Help Biñan in Laguna and the Philippine Merchant Marine School in Las Piñas in Metro Manila. UPHB is located only about 30 kilometers away from the vicinity of Metro Manila area. The researcher chose these schools as venue for the experiment and survey, apart from the high standard quality of education they have, due to easy access to respondents and being a former faculty of the UPHB, and having contacts with PMMS. The schools’ proximity to the researcher’s residence is another consideration for the choice.

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Graduate School, Manila Instrumentation and Validation of the Instrument The study entailed two basic instruments:

(a) Task Performance

Evaluation on three topics, namely: Collision Regulation with 14 items, Williamson Turn with 12 items, and Position Fixing with 10 items; and (b) Feedback Survey on effectiveness (i.e. 10 items) of the Vehicle Simulator, as well as ranking of the features (i.e. 8 items) of the said simulation tool. A detailed profile of the student was required of all respondentparticipants. The same applies to the instructor-respondents.

For a more

detailed appreciation of the instrument, please refer to Appendices A, B, C, D, E, F, G, and H. Each item in the task performance evaluation was assessed using a 4point Likert scale (i.e. ranging from 1 to 4) indicating the extent of the respondent’s agreement or disagreement. The scale points mean: 1- Poor (P); 2 - Fair (F); 3 – Good (G); and 4 – Very Good (VG). Likewise, corresponding level has its verbal interpretation as shown in the legend: Table 3 Interpretation of Scores – Task Performance Evaluation Rating Scale

Verbal Interpretation

Performance Level

1.00 – 1.75 1.76 – 2.50 2.51 – 3.25 3.26 – 4.00

Poor (P) Fair (F) Good (G) Very Good (VG)

Very Low (VL) Low (L) Moderate (M) High (H)

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Graduate School, Manila The scores obtained from the Task Performance Evaluation were converted into Bloom’s Learning Objectives to determine how well the participants to the experiment have learned in terms of the hierarchy – i.e. remembering, understanding, application, analysis, evaluation, and creation. The converted scores were interpreted using the following scale with verbal interpretation and performance level indicators: Table 4 Interpretation of Scores – Bloom’s Learning Objectives Rating Scale

Verbal Interpretation

Performance Level

1.00 – 1.60 1.61 – 2.20 2.21 – 2.80 2.81 – 3.40 3.41 – 4.00

Poor (P) Fair (F) Good (G) Very Good (VG) Excellent (E)

Very Low (VL) Low (L) Moderate (M) High (H) Very High (VH)

Meanwhile, the feedback survey on the respondent-participants for the experiment were asked only 10 questions following a 4-Likert scale model for part 1 of the survey instrument and were asked to rank eight (8) characteristics of the Vehicle Simulator in the part 2 of the survey instrument, i.e. ranking them from 1 (liked most) to 8 (liked least). The instruments were validated by the experts assigned by the college dean, i.e. expert review.

Data Gathering Procedure The collection of research data was divided into three parts: experiment phase, (b) experiment phase, (c) post-experiment phase. 51

(a) pre-

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Graduate School, Manila Pre-Experiment Phase Prior to the experiment, the researcher undertook the following steps: 1. Sought approval of research instruments (i.e. task performance evaluation form and the feedback survey form) as validated. 2. Wrote a letter of request to the university to use the respondentparticipants to the experiment and survey. 3. Determined the acceptable sample size and the criteria for selection of respondent-participants. 4. Identified the specific respondent-participants to be tapped for the experiment and survey. 5. Arranged for the venue and the materials to be used. Experiment Phase During the actual experiment, the following steps were undertaken: 1. Scheduled and announced the dates of the meetings with respondentparticipants 2. Gave orientation to all respondent-participants on the objectives and mechanics of the experiment. 3. Conducted a pre-test to all respondent-participants. 4. Divided the respondent-participants into two groups with approximately similar intelligence level as pre-determined by their college professor.

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Graduate School, Manila 5. Taught both groups three topics, namely collision regulation, Williamson turn, and position fixing, using the Vehicle Simulator (for the experimental group) and video (for the control group). 6. Conducted a post-test to all respondent-participants. 7. Conducted a brief feedback survey with the respondent-participants. Post-Experiment Phase After the experiment, the researcher undertook the following steps: 1. Collected and collated all filled out task performance evaluation forms and feedback survey forms. 2. Tallied results of the task performance evaluation and feedback survey. 3. Utilized appropriate statistical tools in analyzing the results. 4. Interpreted the results of the statistical analysis.

Statistical Treatment of Data The data to be collected were tallied, recorded and analyzed. To determine the difference in performance between the users of vehicle simulator and the non-users, measures of central location (i.e. arithmetic mean), t-test of significance on the post-test, and Spearman rank correlation were used by the researcher. The researcher simply used Excel spreadsheets with built-in formulas to facilitate the tabulation and analysis.

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Graduate School, Manila 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

Date of Pre-Test

November 25, 2014

Date of Lecture / TeachingLearning Intervention

November 26, 2014

Date of Post-Test

November 27, 2014

Date of Survey

November 25, 2014

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Graduate School, Manila 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)

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila 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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Graduate School, Manila 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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Graduate School, Manila 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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Graduate School, Manila 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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Graduate School, Manila 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.

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila 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 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

Task

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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Graduate School, Manila Table 9 Post-Test Scores on Bloom’s Learning Objectives 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

Task

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 Value of t

Accept or Reject H0

Interpretation

0.68

No significant difference

CG Pre-Test vs. Post-Test

12.037

Reject

EG Pre-Test vs. Post-Test

8.242

Reject

CG vs. EG Post-Test

7.427

Reject

Task

CG vs. EG Pre-Test

There is a significant difference There is a significant difference There is a significant difference

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Graduate School, Manila 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 teacherrespondents strongly agreed were:

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila 1. They

would

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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Graduate School, Manila Table 11 Feedback on the Vehicle Simulator No.

1 2 3 4 5 6 7 8 9 10

Item

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

3.15

3.83

1.0

4.0

3.10

4.00

2.0

1.0

3.00

3.83

5.0

4.0

I am excited in using the Vehicle Simulator I feel comfortable using the Vehicle Simulator I gained confidence while using the Vehicle Simulator I improved my communication skills while using the Vehicle Simulator I learned something very important while using the Vehicle Simulator I find the Vehicle Simulator flexible to use I find the Vehicle Simulator userfriendly I was able to practice well my navigation skills while using the Vehicle Simulator I would like to continue using the Vehicle Simulator It is good to have the Vehicle Simulator in maritime schools and training centers

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 fullmission 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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Graduate School, Manila 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

Complete features Applicable real-life situations Visuals are clear and great

Students’ Rank 1 2 3

Teachers’ Rank 1 2 3

Mean Rank 1 2 3

Strength or Weakness Strength Strength Strength

Instructions are clear and easy to follow No technical problems encountered Highly interactive Easy to manipulate Courseware is accessible by Internet

4 5 6 7 8

Strength Weakness Weakness Weakness Weakness

Features

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

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila 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.

1 2 3 4 5 6 7 8 9 10

Vehicle Simulator

Item

Easy to manipulate Complete features Applicable real-life situations Visuals are clear and great Instructions are clear and easy to follow Highly interactive Courseware is accessible by Internet No technical problems encountered Good maintenance and support system Affordable price for schools & students Mean

2.55 2.73 3.61 2.50 2.67 3.89 4.00 1.92 2.56 3.60 3.00

Kongsberg

3.82 3.82 4.00 3.79 4.00 4.00 1.00 2.00 3.89 3.93 3.43

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Graduate School, Manila

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.

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Table 14 Breakdown of Comparative Assessment Simulators No.

1 1a 1b 1c 1d 1e 1f 1g 1h 1i 1j 1k 1l 1m 1n 1o 1p 1q 2 2a 2b 2c 2d 2e 2f 2g 2h 2i 2j 2k 2l 2m 2n 2o 2p 2q 3 3a 3b

Item

Complete features Radar / ARPA Steering Wheel Engine Telegraph Sound Signal Lights and Shapes ECDIS Echo Sounder Bow Thruster Smoke Signals and Pyrotechnics Vessel Characteristics Display Bank Suction Anchor Mooring / Docking Ropes Search and Rescue Capability Ballast Water Regulator Global Positioning System LAN Connection Easy to manipulate Radar Steering Wheel Engine Telegraph Sound Signal Lights and Shapes ECDIS Echo Sounder Bow Thruster Smoke Signals and Pyrotechnics Vessel Characteristics Display Bank Suction Anchor Mooring / Docking Ropes Search and Rescue Capability Ballast Water Regulator Global Positioning System LAN Connection May be applicable to real-life situations Rule 13 – Overtaking Vessel (CR) Rule 14 – Head-on Situation (CR) 69

Vehicle Simulator

Kongsberg

2.55 3.00 3.00 3.00 3.00 3.00 3.00 3.00 3.00 1.33 1.00 1.00 3.00 3.00 1.00 1.00 4.00 4.00 2.73 3.00 3.00 3.67 3.33 3.33 3.00 3.00 3.00 1.00 1.00 3.00 3.00 3.00 1.00 1.00 4.00 4.00 3.61 4.00 4.00

3.82 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 3.00 4.00 4.00 4.00 3.00 4.00 3.00 3.82 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 3.00 4.00 4.00 4.00 3.00 4.00 3.00 4.00 4.00 4.00

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Graduate School, Manila 3c 3d 3e 3f 3g 3h 3i 3j 3k 4 4a 4b 4c 4d 5 5a 5b 5c 6 6a 6b 6c 7 7a 7b 8 8a 8b 8c 8d 9 9a 9b 9c 10 10a 10b 10c

Rule 15 – Crossing Situation (CR) Rule 16 – Action by Give-way Vessel (CR) Rule 17 – Action by Stand-on Vessel (CR) Man overboard in shallow water (WT) Man overboard in deep water (WT) Use of radar (PF) Use of GPS (PF) Conditions of poor visibility (PF) Bad weather conditions (CR, WT, PF) Visuals are complete, clear and great Existence of major ports in the simulator’s library Accurate depiction of landmarks and views Clarity of resolution of images Accurate simulation of various weather conditions Instructions are clear & easy to follow Dropdown menu is easy to read and operate Translation facility is available Availability of printed manual Highly interactive Features are functioning well Reaction of simulator to user is real-time Features are very engaging to the user Courseware is accessible by Internet Courseware is downloadable from the Internet Internet bandwidth is strong and stable No technical problems encountered No possibility of going off accidentally No possibility of slow or no response No possibility of malfunction No possibility of virus infection or attack Good and swift maintenance support system Presence of an online support system Presence of a self-help mechanism Presence trained support staff in the country Affordable price for schools and students Schools can easily afford the price of the simulator Schools can generate savings & profit on simulation courses Schools can recover fast their investment on the simulator

4.00 3.67 4.00 2.00 3.00 3.00 4.00 4.00 4.00 2.50

4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 3.79

1.00

4.00

2.00 4.00

4.00 4.00

3.00

3.17

2.67 4.00 1.00 3.00 3.89 3.67 4.00 4.00 4.00

4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 1.00

4.00

1.00

4.00 1.92 2.33 2.00 2.33 1.00 2.56 3.67 3.00 1.00 3.60

1.00 2.00 2.00 2.00 2.00 2.00 3.83 3.83 4.00 3.83 3.93

3.00

4.00

3.33

3.83

4.00

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Graduate School, Manila 10d 10e

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

3.67

3.83

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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Graduate School, Manila 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

Interpretation

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.

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

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) It was clear that the Experimental Group performance better (Very High) compared to the Control Group (High) in all aspects 72

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

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

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)

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Graduate School, Manila The post-test scores of both the control group and the experimental group were higher than the pre-test scores which simply mean that the teaching and learning interventions conducted were effective. However, it was revealed that the scores of those who were in the experimental group were much higher than that of the control group. This implies that the Vehicle Simulator is more effective than traditional non-PC based methods like lecture and videos. Comparing the Vehicle Simulator with a brand simulator like Kongsberg proved that there is no perfect simulator so far because both have glaring weaknesses. While Kongsberg is noted to be superior to PC-based simulators like the Vehicle Simulator it also has some weaknesses. Overall, they are very similar.

Conclusions Based on the results of the experiment and survey conducted for this study, as indicated in the statistical treatment of the research data, the following conclusions were derived. First, the Vehicle Simulator can be used as an alternative teaching and learning tool for maritime students. Maritime students cannot realistically access a full mission bridge simulator in school without proper scheduling by their instructors and they cannot use the simulator as frequently as they want. Thus, the hours spent on practicing navigational skills are extremely limited. However, a PC-based simulator like the Vehicle Simulator is accessible to anyone 24/7 on 74

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila demand basis. For a one-time minimal fee, a student can have unlimited access to the software program installed in any gadget, e.g. personal computer, laptop, mobile phone, netbook, I-pad, etc. Second, the Vehicle Simulator cannot replace branded full mission bridge simulators as it has some weaknesses as perceived by both students and teachers. Despite the convenience and ease of access presented by the Vehicle Simulator, it cannot fully replace the full mission bridge simulator due to some obvious advantages of the latter.

The Vehicle Simulator has numerous

disadvantages like features lacking, sense realism, etc. The standard simulator approved by MARINA for schools and training centers is the full mission bridge such as Kongsberg and Transas brands.

Third, the Vehicle Simulator is not a perfect teaching and learning tool. It has some advantages as well as disadvantages. Despite its weakness, Vehicle Simulator is still a good alternative tool for education and training purposes.

Recommendations Based on the aforementioned conclusions, the following recommendations are hereby offered: 1a.

Endorse the Vehicle Simulator to maritime schools as a supplement to their existing navigation learning resources, equipment and technology.

Particularly in very large maritime schools with

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila enrollment ranging from 1,000 and above, it is virtually impossible for all students enrolled in Navigation courses to practice frequently their navigation skills in the school’s full mission bridge simulator laboratories. This is where PC-based simulators like the Vehicle Simulator can come in handy and helpful. 1b.

Endorse the Vehicle Simulator to maritime training centers as a supplement to their existing training program.

The situation is

similar to large training centers with 500 and above enrollees. The cost of the Vehicle Simulator could be recovered through a built-in training fee system. 1c.

Future researchers can expand this study by comparing Vehicle Simulator’s effectiveness with full mission bridge simulators as a teaching and learning tool for senior maritime students.

This

specific experiment conducted by the researcher was focused on first to second year college students. It would be interesting to find out if the Vehicle Simulator is still helpful at all to the higher level maritime students who are presumably more skilled in navigation already. 2a.

Review centers may consider the Vehicle Simulator as a learning tool for the practical test component of the board exam for deck officers. While not entirely considered yet by MARINA, practicing

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Graduate School, Manila navigation skills through a PC-based simulator may be helpful to board examination reviewees, particularly in the practical test component. 2b.

Maritime high schools (K-12 program) should incorporate in the curriculum simulation courses in preparation for collegiate courses. This can be an interesting feature of the Grades 11 and 12 curriculum as young students are able to get a very good glimpse of navigation courses, begin to develop navigation skills, and nurture their interest in the profession. Approximately 200 to 250 hours of practice on navigation skills can be fruitful and beneficial to maritime high school students.

3a.

Future researchers can replicate this study by evaluating the applicability of the Vehicle Simulator as an assessment tool (e.g. for MARINA).

While not yet approved by MARINA, it can be an

interesting topic to explore the possibility using PC-based simulators for the said purpose. 3b.

Filipino IT specialists should develop a superior version of the Vehicle Simulator. Since Vehicle Simulator has been proven not to be a perfect software yet, it would an interesting challenge for computer programmers and analysts to develop a software that

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Graduate School, Manila perfectly addresses the current weakness of PC-based simulator as well as the weaknesses of full mission bridge simulators. The above recommendations are the researcher’s humble contribution to maritime research and to the maritime industry in general. Hopefully, maritime educators would have a paradigm shift in terms of looking at accessible and affordable technology for the students in various higher education institutions. Conversely, this research allows maritime educators to improve their teaching methodologies.

Linking the Findings to the Conclusions, Recommendations and Research Problems To prove that the findings derived in the experiment conducted are directly linked to the research problems, the conclusions and recommendations and to the review of related studies and literature and hypothesis, the table below details the connections among these various components. Table 16 Linking Summary of Findings with Statement of the Problem, et al. Item Statement of the Problem

Hypothesis

Reference SOP 1

H0a H0b

Details Compared to standard more traditional methods being used in maritime schools, how effective is the Vehicle Simulator as a teaching and learning tool in specific competencies like collision regulation, Williamson turn, and position fixing? There is no significant difference in the performance of Vehicle Simulator users and non-users. There is no significant difference in the 78

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Graduate School, Manila

Findings

Synthesis of Review of Related Studies and Literature

Conclusions

Recommendations

mean performance of Vehicle Simulator users group before and after the learning intervention. t-test of There is a significant difference in the significance performance of the Control Group and of the post- Experimental Group with the Vehicle test Simulator users (EG) demonstrating far superior performance in collision regulation, Williamson turn, and position fixing. Bloom’s When the scores were converted to Learning Bloom’s Learning Objectives, it was clear Objectives that the Experimental Group performance better (Very High) compared to the Control Group (High). Therefore, reject both the first and second null hypotheses. (a) Learners develop numerous skills through simulators. (g) Use of simulators is compliant with CMO 31 (h) Simulation captures all three learning domains – i.e. cognitive, affective and psychomotor. (i) Simulators allow the learner to manifest all the learning objectives as postulated by Bloom – e.g. remembering, understanding, application, analysis, evaluation, and creation. (1) Vehicle Simulator can be used as an alternative teaching and learning tool for maritime students. 1a Endorse the Vehicle Simulator to maritime schools as a supplement to their existing navigation learning resources, equipment and technology. 1b Endorse the Vehicle Simulator to maritime training centers as a supplement to their existing training program. 1c Future researchers can expand this study by company Vehicle Simulator’s effectiveness as a teaching and learning 79

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila tool for senior maritime students. Item Statement of the Problem

Hypothesis

Findings

Reference SOP 2

H0c

Arithmetic Mean

Synthesis of Review of Related Studies and Literature

(b) (d) (e)

Conclusions

(2)

Recommendations

Details Is there a significant difference in the applicability (advantages) and limitations (disadvantages) of the Vehicle Simulator as a teaching and learning tool in relation to other branded simulators? There is no difference in the perception of students and instructors on the features of the Vehicle Simulator. The instructors believe that 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. Simulators build confidence of the learner. The virtual realities created through the use of simulators prevent potential accidents in a regular apprenticeship or actual exercise. Vehicle Simulator cannot replace branded full mission bridge simulators as it has some weaknesses as perceived by both students and teachers. Review centers may consider the Vehicle Simulator as a learning tool for the practical test component of the board exam for deck officers. Maritime high schools (post K-12 program) should incorporate in the curriculum simulation courses in preparation for 80

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila collegiate courses. Item Statement of the Problem Hypothesis

Findings

Synthesis of Review of Related Studies and Literature Conclusions

Recommendations

Reference SOP 3

Details Is there a significant difference in the most liked and least liked features of the Vehicle Simulator? c H0 There is no difference in the perception of students and instructors on the features of the Vehicle Simulator. Spearman There is no significant difference in the Rank perception of students and instructors on Correlation 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. Therefore, the null hypothesis must be accepted. The Vehicle Simulator is perceived as similar but not superior to branded full mission bridge simulators like Kongsberg. There are some aspects of Vehicle Simulators which can be improved such as ease of manipulation, complete features, visuals, and instructions. However, technical problems are also encountered; it is not as interactive as a full mission bridge simulator; it is not extremely to manipulate; and it bears cost to be able to access it through Internet. (b) Simulators pose specific challenges. (c) Use of simulators in training has benefits (f) More companies and schools are now using simulators. (3) The Vehicle Simulator is not a perfect teaching and learning tool. It has some advantages as well as disadvantages. 3a Future researchers can replicate this study by evaluating the applicability of the Vehicle Simulator as an assessment tool (e.g. for MARINA). 3b Filipino IT specialists should develop a superior version of the Vehicle Simulator. 81

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Graduate School, Manila Bibliography

Baylon, Angelica M. and Eduardo Ma. R. Santos (2011). The Challenges in Philippine Maritime Education and Training. International Journal of Innovative Interdisciplinary Research. Issue No. 1, pp. 34-43. Calaor, Nanette (2001). Simulation Games: Effects on Learners’ Inter-Ethnic Attitudes. Philippine eLib. Commission on Higher Education (2014). CHED Memorandum Order No. 31 Series of 2013 Pertaining to Amendment and Supplemental Policies, Standards and Guidelines to CMO 13 Series of 2013. Quezon City. Cross, Stephen (2012). 20th International Maritime Lecturers Association. New York:Maritime Professional. CSMART (2014). Center for Simulator Maritime Training. Almere:CSMART. D'Amico, A.D., W.C. Miller, and C. Saxe (1985). A Preliminary Evaluation of Transfer of Simulator Training to the Real-World. Report No. CAORF 508126-02. New York:National Maritime Research Center. Dennis, Kerry A. and Don Harris (2009). Computer-Based Simulation as an Adjunct to Ab Initio Flight Training. International Journal of Aviation Psychology, Volume 8, Issue No. 3, pp. 261-276. Taylor & Francis Online. Douwsma, D.G. (1993). Using Frameworks to Produce Cost-Effective Simulator Training. Newfoundland:International Conference on Maritime Simulation and Ship Maneuverability. Drown, D.F. and R.F. Mercer (1995). Applying Marine Simulation to Improve Mariner Professional Development. New York:American Society of Civil Engineers. Edmonds, D. (1994). Weighing the Pros & Cons of Simulator Training, Computer-Based Training, and Computer Testing and Assessment. PC Maritime Ltd.

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Graduate School, Manila Flexman, R. E., S. N. Roscoe, A. C., Williams & B. H. Williges (1972). Studies in Pilot Training: The Anatomy of Transfer. Aviation Research Monographs, Vol. 2, No. 1. Savoy:University of Illinois, Institute of Aviation. Galloway, Susan (2009). Simulation Techniques to Bridge the Gap Between Novice and Competent Healthcare Professionals. The Online Journal of Issues in Nursing, Vol. 14, Issue No. 2. Olmstead Township:ANA. Goldberg, Murray (2012). Understanding eLearning in Maritime Job Learning and Familiarization. New York:Maritime Professional. Gosling, Steven (2012). Gaming Meets Training. The Maritime Professional. Hays, R. (1995). Personal Communication to Committee on Ship-Bridge Simulation Training. Washington D.C.:National Research Council. Hays, R.T. and M.J. Singer (1989). Simulation Fidelity in Training System Design. New York:Springer-Verlag. Heer, Rex (2014). A Model of Learning Objectives – Based on a Taxonomy of Learning, Teaching and Assessing: A Revision of Bloom’s Taxonomy of Learning Objectives. Ames:Iowa State University. Hergenhahn, B. R. (2009). An Introduction to the History of Psychology. Independence:Cengage Learning. International Maritime Organization (1993). STCW 1978: International Convention on Standards of Training, Certification, and Watchkeeping. London:IMO. International Maritime Organization (1994). World Maritime Day: Better Standards, Training, and Certification – IMO's Response to Human Error. London:IMO News. Jones, Saunders (1993). Perception of Simulator-Based Training. Simulated Voyages. Washington, D.C.:National Academy Press.

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Graduate School, Manila Kayten, P., W.M. Korsoh, W.C. Miller, E.J. Kaufman, K. E. Williams, and T.C. King Jr. (1982). Assessment of Simulator-Based Training for the Enhancement of Cadet Watch Officer. Kings Point, New York:National Maritime Research Center. Kincheloe, Joe (2004). Multiple Intelligences Reconsidered. New York:Peter Lang. Koonce, Jefferson M. and William J. Bramble Jr. (2009). Personal ComputerBased Flight Training Devices. International Journal of Aviation Psychology, Vol. 8, Issue No. 3, pp. 277-292. Francis & Taylor Online. MacRae, Norman (1992). John von Neumann: The Scientific Genius Who Pioneered the Modern Computer, Game Theory, Nuclear Deterrence and Much More. New York:Pantheon Press. McGuire, Christine (1976). Simulation Technique in the Teaching and Testing of Problem Solving Skills. Journal of Research in Science Teaching. Vol. 13, Issue No. 2, pp. 89-100. New York:Wiley Periodicals, Inc. Mengya, Qi. IT and Modern Technology in Maritime Education Training. Miller, W.C., C. Saxe and A.D. D’Amico (1985). A Preliminary Evaluation of Transfer of Simulator Training to the Real-World. Report No. CAORF 508126-02. New York:National Maritime Research Center. MOL Marine Consulting (2014). MOL Upgrades Bridge Simulator. Maritime Simulation News. Multer, J., A.D. D’Amico, K. Williams, and C. Saxe (1983). Efficiency of Simulation in the Acquisition of Shiphandling Knowledge as a Function of Previous Experience. Report No. CAORF 52-8102-02. New York:National Maritime Research Center. Orey, Michael (2010). Emerging Perspectives on Learning, Teaching and Technology.

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Graduate School, Manila Ortiz, Gustavo (2009). Effectiveness of PC-Based Flight Simulation. The International Journal of Aviation Psychology, Vol. 4, Issue No. 3, pp. 285292. Taylor & Francis Online. Papini, Ilan (2009). The Vehicle Simulator. Israel:Vehicle Simulator. Povenmire, H.K. and S.N. Roscoe (1973). Incremental Transfer Effectiveness of a Ground-Based General Aviation Trainer. Human Factors, Vol. 15, Issue No. 6, pp. 534-542. Rasmusen, Eric (2006). Law and Game Theory. Cheltenham:Edward Elgar Publishing. SUNY Maritime. (2014). SUNY Maritime Opens Bouchard Tug and Barge Simulation Center. Maritime Simulation News. Sweeney, James and Herb Groh (1996). Simulated Voyages: Using Simulation Technology to Train and License Mariners The Maritime Training Center of the Philippines (2014). Manila: TMTCP.

Simulator Courses.

Trabalzini, Paola (2011). Maria Montessori through the Seasons of the Method. Burton: National American Montessori Teachers Association. Waag, Wayne L. (1981). Training Effectiveness of Visual and Motion Effectiveness. Amazon.com Webster, W. (1992). Shiphandling Simulation: Application to Waterway Design. Washington, D.C.:National Academy Press.

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Graduate School, Manila

Appendices

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Graduate School, Manila Appendix A – Profile of Student PROFILE OF STUDENT Name

School

Age Health Condition

Course

Year Level

Condition of bodily functions such as eyes, ears, extremities, reflexes, blood pressure, respiratory & digestive organs, brain, etc.

(4) Excellent

(3) Good

(2) Fair

(1) Poor

This item will be filled out by the class instructor based on the latest record (rank from 6 to 35)

Academic Rank in Class

Time Spent Studying

How many hours do you spend studying at home or school in a week

13+hrs/week

9-12 hrs/week

5-8 hrs/week

0-4 hrs/week

Time Spent Surfing Internet

How many hours do you spend surfing the internet at home or anywhere else?

13+hrs/week

9-12 hrs/week

5-8 hrs/week

0-4 hrs/week

Gadgets Owned

Smart Phone

I-Pad

How do you access a computer with Internet? (check all that is applicable)

Laptop

At home

Netbook In school

PC In an Internet shop

Describe the conduciveness of home for studying?

A – Very conducive with no distractions

B – Quite conducive with minor distractions

C- Quite challenging with major distractions

D – Extremely challenging & virtually impossible to study

Computer Literacy

A – Very Good

B - Good

C - Fair

D - Poor

Have you taken a simulation course before? Describe your family’s support on your maritime studies?

Yes

A – Extremely supportive

Have you used the Vehicle Simulator before?

B – Supportive with minor challenges

C - Supportive with major challenges

Yes

D – Not very supportive at all

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Graduate School, Manila Appendix B – Task Performance Evaluation Form – Collision Regulation

The instructor will observe the student in performing the assigned task with 3 to 5 minutes. Each task is score from 1 to 4. Code Task CR1R

The student must articulate in a nutshell the meaning of Rule No. 8 of the International Rules of the Road

CR2U

The student can identify the giveway vessel and privilege vessel

CR3A

The student appears to be a calm and confident attitude during the entire exercise

CR4A

The student displayed presence of mind and is visually focused on the view at the bridge

CR5A

The student maneuvered the vessel within ample time to prevent possible collision

CR6A

The student slackened the speed of the vessel sufficiently

CR7A

The student correctly

CR8A

The student used the radio to communicate with the other vessel

CR9A

The student observe safe distance between the two vessels

CR10A

The student increased the speed after passing through the other vessel

used

the

radar

Very Good

Good

Fair

Poor

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Graduate School, Manila CR11Z

The student is fully aware of the risk of collision by using wisely a combination of navigational equipment

CR12E

The student assessed correctly the course and speed of the other vessel

CR13E

The student made a decision to alter course of his vessel to prevent collision

CR14C

The student was able to successfully create a strategy to prevent a collision

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Graduate School, Manila Appendix C – Task Performance Evaluation Form – Williamson Turn

The instructor will observe the student in performing the assigned task with 5 to 7 minutes. Each task is score from 1 to 4.

Code

4 3 2 1 Very Good Fair Poor Good

Task

WT1R

The student must articulate in a nutshell the meaning of Williamson Turn

WT2U

The student expressed seriousness of the situation

WT3A

The student display a calm but confident attitude

WT4A

The student displayed presence of mind and is visually focused on the view at the bridge

WT5A

The student pressed the simulator MOB button as acknowledgment of the situation

WT6A

The student demonstrate correct control of the speed of the vessel

WT7A

The student used the radar correctly

WT8A

The student used the radio to communicate with other crew members for rescue operations

WT9A

The student observed safe distance between the vessel and the man overboard

WT10Z

The student used wisely a combination of navigational equipment to execute the Williamson Turn

WT11E

The student assessed correctly the point where he should maneuver to be able to get back at the man overboard

WT12E

The student was able to develop a strategy to successfully reach the location of the man overboard within the least time possible

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Graduate School, Manila Appendix D – Task Performance Evaluation Form – Position Fixing

The instructor will observe the student in performing the assigned task with 3 to 5 minutes. Each task is score from 1 to 4. Code

4 3 2 1 Very Good Fair Poor Good

Task PF1R

The student must articulate in a nutshell the meaning of Position Fixing

PF2U

The student is aware that he is either in the right or wrong course

PF3A

The student display a calm but confident attitude

PF4A

The student displayed presence of mind and is visually focused on the view at the bridge

PF5A

The student demonstrate correct control of the speed of the vessel

PF6A

The student used the radar correctly

PF7A

The student must know how to apply dead reckoning

PF8Z

The student was able to compare GPS position and DR position using a combination of navigational equipment

PF9E

The student assessed correctly the landmark he must use to determine the vessel line of position (LOP)

PF10C

The student was able to successfully identify the vessel’s correct position

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Graduate School, Manila Appendix E – Feedback Survey Form for Students Instructions: Please answer the following items as honestly as possible after undergoing the post-test evaluation. Kindly put a tick mark on the space corresponding the following scores: 1 – Strongly Disagree 2 – Disagree 3 – Agree 4 – Strongly Agree No. 1 2 3 4 5 6 7 8 9 10

Item I am excited in using the Vehicle Simulator I feel comfortable using the Vehicle Simulator I gained confidence while using the Vehicle Simulator I improved my communication skills while using the Vehicle Simulator I learned something very important while using the Vehicle Simulator I find the Vehicle Simulator flexible to use I find the Vehicle Simulator user-friendly I was able to practice well my navigation skills while using the Vehicle Simulator I would like to continue using the Vehicle Simulator It is good to have the Vehicle Simulator in maritime schools and training centers

Out the following eight features of the Vehicle Simulator, rank them from 1, 2, 3 up to 8 (with 1 as the feature you like most and 8 as the feature you like least). A

Feature Easy to manipulate

B C

Complete features Applicable real-life situations

Visuals are clear and great

Rank

Feature E Instructions are clear & easy to follow F Highly interactive G Courseware is accessible by Internet H No technical problems encountered

Any suggestion on the use of the Vehicle Simulator ________________________________________________________________ 92

Rank

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Graduate School, Manila Appendix F – Profile of Instructor PROFILE OF INSTRUCTOR Name

Age

School

Courses

Year Level

Taught

Number of years in teaching simulation courses

Less than 3 years

3-6 years

6+ years

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Graduate School, Manila Appendix G – Feedback Survey From for Instructors Instructions: Please answer the following items as honestly as possible. Kindly put a tick mark on the space corresponding the following scores: 1 – Strongly Disagree 2 – Disagree 3 – Agree 4 – Strongly Agree No. 1 2 3 4 5 6 7 8 9 10

Out the following eight features of the Vehicle Simulator, rank them from 1, 2, 3 up to 8 (with 1 as the feature you like most and 8 as the feature you like least). A

Feature Easy to manipulate

Rank

Complete features

Applicable real-life situations

Visuals are clear and great

G Courseware is accessible by Internet H No technical problems encountered

Feature Instructions are clear & easy to follow Highly interactive

Any suggestion on the use of the Vehicle Simulator ________________________________________________________________ 94

Rank

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Graduate School, Manila Appendix H – Comparative Survey for Instructors

Instructions: Please answer the following items as honestly as possible. Kindly put a tick mark on the space corresponding the following scores: 1 – Strongly Disagree 2 – Disagree 3 – Agree 4 – Strong Agree No. 1 1a 1b 1c 1d 1e 1f 1g 1h 1i 1j 1k 1l 1m 1n 1o 1p 1q 2 2a 2b 2c 2d 2e 2f 2g 2h 2i 2j 2k 2l 2m 2n

Item Complete features Radar / ARPA Steering Wheel Engine Telegraph Sound Signal Lights and Shapes ECDIS Echo Sounder Bow Thruster Smoke Signals and Pyrotechnics Vessel Characteristics Display Bank Suction Anchor Mooring / Docking Ropes Search and Rescue Capability Ballast Water Regulator Global Positioning System LAN Connection Easy to manipulate Radar Steering Wheel Engine Telegraph Sound Signal Lights and Shapes ECDIS Echo Sounder Bow Thruster Smoke Signals and Pyrotechnics Vessel Characteristics Display Bank Suction Anchor Mooring / Docking Ropes Search and Rescue Capability

Vehicle Simulator

Kongsberg

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila 2o 2p 2q 3 3a 3b 3c 3d 3e 3f 3g 3h 3i 3j 3k 4 4a 4b 4c 4d 5 5a 5b 5c 6 6a 6b 6c 7 7a 7b 8 8a 8b 8c 8d 9 9a 9b 9c 10 10a 10b

Ballast Water Regulator Global Positioning System LAN Connection May be applicable to real-life situations Rule 13 – Overtaking Vessel (CR) Rule 14 – Head-on Situation (CR) Rule 15 – Crossing Situation (CR) Rule 16 – Action by Give-way Vessel (CR) Rule 17 – Action by Stand-on Vessel (CR) Man overboard in shallow water (WT) Man overboard in deep water (WT) Use of radar (PF) Use of GPS (PF) Conditions of poor visibility (PF) Bad weather conditions (CR, WT, PF) Visuals are complete, clear and great Existence of major ports in the simulator’s library Accurate depiction of landmarks and views Clarity of resolution of images Accurate simulation of various weather conditions Instructions are clear & easy to follow Dropdown menu is easy to read and operate Translation facility is available Availability of printed manual Highly interactive Features are functioning well Reaction of simulator to user is real-time Features are very engaging to the user Courseware is accessible by Internet Courseware is downloadable from the Internet Internet bandwidth is strong and stable No technical problems encountered No possibility of going off accidentally No possibility of slow or no response No possibility of malfunction No possibility of virus infection or attack Good and swift maintenance support system Presence of an online support system Presence of a self-help mechanism Presence trained support staff in the country Affordable price for schools and students Schools can easily afford the price of the simulator Schools can generate savings & profit on simulation courses

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila 10c 10d 10e

Schools can recover fast their investment on the simulator Students can afford $30 (VS) or P2,000 course fee (KB) Payment terms and mode of payment are easy & convenient

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix I – Master List of Participants School Group

University of Perpetual Help – Biñan Full Name

Student Code

Control

Cabantug, Michael Angelo

UP1

Control Control Control Control Control Control Control Control Control Experimental Experimental Experimental Experimental Experimental Experimental Experimental Experimental Experimental Experimental

Layog, Bryan Jason M. Arguelles,Heiko F. Dapol, Franz Mikko I. Innocencio, Kenneth Eddie B. Iloso, Michael A. Delos Santos, John Carlo C. Maniclang, Patrich Paulo V. Manlapaz, Glydel Ocampo, Emerson G. Perio, Joshua R. Sotto, John Petterson Tagle, Raymond S. Alonzo, Marvin P. Bautista Jr., Gerry O. Ifurung, Francis S. Aguila, Kim AJ M. Reyes Jr. Edgardo V. Desalit, Christian Jay R. Nebreja, Gecelle A. Total Number of Participants

UP1 UP3 UP4 UP5 UP6 UP7 UP8 UP9 UP10 UP11 UP12 UP13 UP14 UP15 UP16 UP17 UP18 UP19 UP20 20

School Group Control Control Control Control Control Control Control Control Control

Philippine Merchant Marine School Full Name Solema, Al Christian C. De Castro, John Carlo Magallano, Arnel J. Gomez, Rizaldy T. Ballesteros, Romel D. Tiu, Jim Patrick I. Jacinto, Judah Benhur R. Ramos, John Karlo M. Luceros, Denniel P.

Student Code PM1 PM1 PM3 PM4 PM5 PM6 PM7 PM8 PM9

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Control Experimental Experimental Experimental Experimental Experimental Experimental Experimental Experimental Experimental Experimental

Palconit, James N. Venus, John Vincent F. Parcon, John Vincent T. Baldonado, Jan Altair Den P. Pampuan, Ruth Christia L. Dorado, Kevin A. Macalalad, John Lester B. Alangco, Edwin Atendido, John Benchard A. Labini, Jose A. Pietro, Kim Vincent A. Total Number of Participants

PM10 PM11 PM12 PM13 PM14 PM15 PM16 PM17 PM18 PM19 PM20 20

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix J – Distribution of Participants by Year Level YEAR LEVEL Group

Student Code

1st Year

2nd Year

UP1

UP2

UP3

UP4

UP5

UP6

UP7

UP8

UP9

UP10

0.00

10.00

Total Percentage

0.00%

100.00%

Group

Student Code

1st Year

2nd Year

PM1

PM2

PM3

PM4

PM5

PM6

PM7

PM8

100

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila CG

PM9

PM10

0.00

10.00

0.00%

100.00%

0.00

20.00

Total Percentage

Group Total Percentage

0.00%

100.00%

Group

Student Code

1st Year

2nd Year

UP11

UP12

UP13

UP14

UP15

UP16

UP17

UP18

UP19

UP20

Total Percentage

101

0.00

10.00

0.00%

100.00%

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Group

Student Code

PM11

PM12

PM13

PM14

PM15

PM16

PM17

PM18

PM19

PM20

Total Percentage

Group Total Percentage

Overall Total Percentage

102

1st Year

2nd Year

0.00

10.00

0.00%

100.00%

0.00

20.00

0.00%

100.00%

0.00

40.00

0.00%

100.00%

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix K – Distribution of Participants by Age AGE Group CG CG CG CG CG CG CG CG CG CG Mean

Student Code UP1 UP2 UP3 UP4 UP5 UP6 UP7 UP8 UP9 UP10

Age 19 20 19 18 19 19 20 21 18 18 19.10

Group

Student Code

Age

PM1

PM2

PM3

PM4

PM5

PM6

PM7

PM8

PM9

PM10

Mean

19.30

Group Mean

19.20

103

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila

Group

Student Code

Age

UP11

UP12

UP13

UP14

UP15

UP16

UP17

UP18

UP19

UP20

Mean

18.10

Group

Student Code

Age

PM11

PM12

PM13

PM14

PM15

PM16

PM17

PM18

PM19

PM20

Mean

17.50

Group Mean

17.80

Overall Mean

18.35

104

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila

Appendix L – Distribution of Participants by Health Condition HEALTH CONDITION Group

Student Code

Excellent

UP1

UP2

UP3

UP4

UP5

UP6

UP7

UP8

UP9

UP10

Total

Good

Fair

Poor

8.00

2.00

0.00

Percentage

80.00%

20.00%

0.00%

Group

Student Code

Excellent

Good

Fair

Poor

PM1

PM2

PM3

PM4

PM5

105

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila CG

PM6

PM7

PM8

PM9

PM10

Total Percentage

Group Total

1 1

9.00

1.00

0.00

90.00%

10.00%

0.00%

17.00

3.00

0.00

Percentage

85.00%

15.00%

0.00%

Group

Student Code

Excellent

Good

Fair

Poor

UP11

UP12

UP13

UP14

UP15

UP16

UP17

UP18

UP19

UP20

1 10.00

0.00

100.00%

0.00%

Total Percentage

106

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Group

Student Code

Excellent

PM11

PM12

PM13

PM14

PM15

PM16

PM17

PM18

PM19

PM20

Total Percentage

Group Total Percentage

Overall Total Percentage

Good

Fair

Poor

9.00

1.00

0.00

90.00%

10.00%

0.00%

19.00

1.00

0.00

95.00%

5.00%

0.00%

36.00

4.00

0.00

90.00%

10.00%

0.00%

107

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix M – Distribution of Participants’ Study Hours TIME SPENT STUDYING PER WEEK 13+ hours

9-12 hours

Group

Student Code

UP1

UP2

UP3

UP4

UP5

UP6

UP7

UP8

UP9

UP10

Total

5-8 hours

0-4 hours

1 1

1 1 1

5.00

4.00

1.00

0.00

Percentage

50.00%

40.00%

10.00%

0.00%

Group

Student Code

13+ hours

9-12 hours

5-8 hours

0-4 hours

PM1

PM2

PM3

PM4

PM5

PM6

PM7

1 1 1 1

108

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila CG

PM8

PM9

PM10

Total Percentage

1 1 1 4.00

Group Total

40.00%

9.00

4.00

1.00

40.00%

10.00%

8.00

2.00

1.00

Percentage

45.00%

40.00%

10.00%

5.00%

Group

Student Code

13+ hours

9-12 hours

5-8 hours

0-4 hours

UP11

UP12

UP13

UP14

UP15

UP16

UP17

UP18

UP19

UP20

Total Percentage

1 1 1 1 1 1 5.00

50.00%

109

1.00

2.00

10.00%

20.00%

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila 13+ hours

9-12 hours

Group

Student Code

PM11

PM12

PM13

PM14

PM15

PM16

PM17

PM18

PM19

PM20

Total Percentage

Group Total Percentage

Overall Total Percentage

1 1

1 1 1

50.00%

10.00 %

50.00%

19.00 %

0-4 hours 1

5.00 %

5-8 hours

47.50%

110

3.00

1.00

30.00%

10.00%

4.00

3.00

20.00%

15.00%

12.00

5.00

4.00

30.00%

12.50%

10.00%

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix N – Distribution of Participants’ Internet Surfing Hours TIME SPENT INTERNET SURFING PER WEEK Group

Student Code

13+ hours

UP1

UP2

UP3

UP4

UP5

UP6

UP7

UP8

UP9

UP10

Total

9-12 hours

5-8 hours

0-4 hours

8.00

2.00

0.00

Percentage

80.00%

20.00%

0.00%

Group

Student Code

13+ hours

9-12 hours

5-8 hours

0-4 hours

PM1

PM2

PM3

PM4

PM5

PM6

PM7

111

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila CG

PM8

PM9

PM10

Total Percentage

Group Total

1 1 1 7.00

3.00

0.00

70.00%

30.00%

0.00%

15.00

5.00

0.00

Percentage

75.00%

25.00%

0.00%

Group

Student Code

13+ hours

9-12 hours

5-8 hours

0-4 hours

UP11

UP12

UP13

UP14

UP15

UP16

UP17

UP18

UP19

UP20

Total

1 8.00

2.00

0.00

Percentage

80.00%

20.00%

0.00%

Group

Student Code

13+ hours

9-12 hours

5-8 hours

0-4 hours

PM11

112

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila EG

PM12

PM13

PM14

PM15

PM16

PM17

PM18

PM19

PM20

Total Percentage

Group Total Percentage

Overall Total Percentage

1 1

1 1 1 5.00

5.00

0.00

50.00%

0.00%

13.00

7.00

0.00

65.00%

35.00%

0.00%

28.00

12.00

0.00

70.00%

30.00%

0.00%

113

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix O – Distribution of Participants’ Gadget Ownership GADGETS OWNED Student Code

Smart Phone

UP1

UP2

UP3

I-Pad

Laptop

Netbook

PC 1

UP4

UP5

UP6

UP7

UP8

UP9

UP10

1 7.00

1.00

0.00

5.00

70.00%

10.00%

0.00%

50.00%

Student Code

Smart Phone

I-Pad

Laptop

Netbook

PM1

PM2

PM3

PM4

PM5

PM6

PM7

114

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila PM8

PM9

PM10

1 6.00

1.00

2.00

0.00

1.00

60.00%

10.00%

20.00%

0.00%

10.00%

13.00

2.00

3.00

0.00

6.00

65.00%

10.00%

15.00%

0.00%

30.00%

Student Code

Smart Phone

I-Pad

Laptop

Netbook

UP11

UP12

UP13

UP14

UP15

UP16

UP17

UP18

UP19 UP20

1 1 9.00

0.00

2.00

0.00

2.00

90.00%

0.00%

20.00%

0.00%

20.00%

Student Code

Smart Phone

I-Pad

Laptop

Netbook

PM11

115

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila PM12

PM13

PM14

PM15

PM16

PM17

PM18

PM19

9.00

2.00

3.00

1.00

3.00

90.00%

20.00%

30.00%

10.00%

30.00%

18.00

2.00

5.00

1.00

5.00

90.00%

10.00%

25.00%

5.00%

25.00%

31.00

4.00

8.00

1.00

11.00

77.50%

10.00%

20.00%

2.50%

27.50%

PM20

116

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix P – Distribution of Participants’ Access to Internet ACCESS TO INTERNET In School

Internet Shop

UP1

UP2

UP3

UP4

UP5

UP6

UP7

UP8

UP9

UP10

3.00

8.00

7.00

Group

Student Code

At Home

1 1

Total

1 1

Percentage

30.00%

80.00%

70.00%

Group

Student Code

At Home

In School

Internet Shop

PM1

PM2

PM3

PM4

PM5

PM6

1 1 1

1 1

117

1 1

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila CG

PM7

PM8

PM9

PM10

1 1 1

Total Percentage

Group Total

5.00

7.00

6.00

50.00%

70.00%

60.00%

8.00

15.00

13.00

Percentage

40.00%

75.00%

65.00%

Group

Student Code

At Home

In School

Internet Shop

UP11

UP12

UP13

UP14

UP15

UP16

UP17

UP18

UP19

UP20

1 1

Total

1 1

6.00

8.00

6.00

Percentage

60.00%

80.00%

60.00%

Group

Student Code

At Home

In School

Internet

118

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Shop EG

PM11

PM12

PM13

PM14

PM15

PM16

PM17

PM18

PM19

PM20

4.00

7.00

40.00%

70.00%

10.00

15.00

13.00

50.00%

75.00%

65.00%

18.00

30.00

26.00

45.00%

75.00%

65.00%

Overall Total Percentage

1 1

Group Total Percentage

Total Percentage

119

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix Q – Distribution of Participants Computer Literacy COMPUTER LITERACY Group

Student Code

Very Good

UP1

UP2

UP3

UP4

UP5

UP6

UP7

UP8

UP9

UP10

Total

Good

Fair

Poor

8.00

2.00

0.00

Percentage

80.00%

20.00%

0.00%

Group

Student Code

Very Good

Good

Fair

Poor

PM1

PM2

PM3

PM4

PM5

PM6

PM7

120

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila CG

PM8

PM9

PM10

Total Percentage

Group Total

9.00

1.00

0.00

90.00%

10.00%

0.00%

17.00

3.00

0.00

Percentage

85.00%

15.00%

0.00%

Group

Student Code

Very Good

Good

Fair

Poor

UP11

UP12

UP13

UP14

UP15

UP16

UP17

UP18

UP19

UP20

Total Percentage

9.00

1.00

0.00

90.00%

10.00%

0.00%

121

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Group

Student Code

Very Good

PM11

PM12

PM13

PM14

PM15

PM16

PM17

PM18

PM19

PM20

Total Percentage

Group Total Percentage

Overall Total Percentage

Good

Fair

Poor

8.00

2.00

0.00

80.00%

20.00%

0.00%

17.00

3.00

0.00

85.00%

15.00%

0.00%

34.00

6.00

0.00

85.00%

15.00%

0.00%

122

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix R – Distribution of Conduciveness to Learning of Participants’ Homes CONDUCIVENESS OF THE HOME FOR STUDYING Very Conducive

Quite Conducive

Quite Challenging

Group

Student Code

UP1

UP2

UP3

UP4

UP5

UP6

UP7

UP8

UP9

UP10

Total

Ext. Challenging

1 1

1 1 1 2.00

5.00

2.00

1.00

Percentage

20.00%

50.00%

20.00%

10.00%

Group

Student Code

Very Conducive

Quite Conducive

Quite Challenging

Ext. Challenging

PM1

PM2

PM3

PM4

PM5

PM6

1 1 1

123

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila CG

PM7

PM8

PM9

PM10

Total Percentage

Group Total

1 1 1 1 3.00

4.00

2.00

1.00

30.00%

40.00%

20.00%

10.00%

5.00

9.00

4.00

2.00

Percentage

25.00%

45.00%

20.00%

10.00%

Group

Student Code

Very Conducive

Quite Conducive

Quite Challenging

Ext. Challenging

UP11

UP12

UP13

UP14

UP15

UP16

UP17

UP18

UP19

UP20

Total

1 1 1 1 1 1 1 1 1 1 3.00

3.00

2.00

Percentage

30.00%

20.00%

Group

Student Code

Very Conducive

Quite Conducive

Quite Challenging

Ext. Challenging

124

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila EG

PM11

PM12

PM13

PM14

PM15

PM16

PM17

PM18

PM19

PM20

Total Percentage

Group Total Percentage

Overall Total Percentage

1 1 1 1 1 1 1 1 1 1 4.00

3.00

2.00

1.00

40.00%

30.00%

20.00%

10.00%

7.00

6.00

4.00

3.00

35.00%

30.00%

20.00%

15.00%

12.00

15.00

8.00

5.00

30.00%

37.50%

20.00%

12.50%

125

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix S – Distribution of Participants with Simulation Course TAKEN SIMULATION COURSE YES

Group

Student Code

UP1

UP2

UP3

UP4

UP5

UP6

UP7

UP8

UP9

UP10

Total

0.00

10.00

Percentage

0.00%

100.00%

Group

Student Code

YES

PM1

PM2

PM3

PM4

PM5

PM6

126

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila CG

PM7

PM8

PM9

PM10

Total Percentage

Group Total

0.00

10.00

0.00%

100.00%

0.00

20.00

Percentage

0.00%

100.00%

Group

Student Code

YES

UP11

UP12

UP13

UP14

UP15

UP16

UP17

UP18

UP19

UP20

Total

0.00

10.00

Percentage

0.00%

100.00%

Group

Student Code

YES

127

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila EG

PM11

PM12

PM13

PM14

PM15

PM16

PM17

PM18

PM19

PM20

Total Percentage

Group Total Percentage

Overall Total Percentage

128

0.00

10.00

0.00%

100.00%

0.00

20.00

0.00%

100.00%

0.00

40.00

0.00%

100.00%

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix T – Distribution of Participants with Vehicle Simulator Exposure USED VEHICLE SIMULATOR PREVIOUSLY YES

Group

Student Code

UP1

UP2

UP3

UP4

UP5

UP6

UP7

UP8

UP9

UP10

Total

0.00

10.00

Percentage

0.00%

100.00%

Group

Student Code

YES

PM1

PM2

PM3

PM4

PM5

PM6

129

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila CG

PM7

PM8

PM9

PM10

Total Percentage

Group Total

0.00

10.00

0.00%

100.00%

0.00

20.00

Percentage

0.00%

100.00%

Group

Student Code

YES

UP11

UP12

UP13

UP14

UP15

UP16

UP17

UP18

UP19

UP20

Total Percentage

130

0.00

10.00

0.00%

100.00%

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila YES

Group

Student Code

PM11

PM12

PM13

PM14

PM15

PM16

PM17

PM18

PM19

PM20

Total Percentage

Group Total Percentage

Overall Total Percentage

131

0.00

10.00

0.00%

100.00%

0.00

20.00

0.00%

100.00%

0.00

40.00

0.00%

100.00%

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix U – Distribution of Participants’ Family Support on Studies DESCRIPTION OF FAMILY SUPPORT ON MARITIME STUDIES Ext. Supportive

Supportive-Minor

Supportive-Major

Group

Student Code

UP1

UP2

UP3

UP4

UP5

UP6

UP7

UP8

UP9

UP10

Total

Not Supportive

1 1 1 1 1

1 1 1 3.00

5.00

2.00

0.00

Percentage

30.00%

50.00%

20.00%

0.00%

Group

Student Code

Ext. Supportive

Supportive-Minor

Supportive-Major

Not Supportive

PM1

PM2

PM3

PM4

PM5

PM6

PM7

1 1 1 1

132

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila CG

PM8

PM9

PM10

Total Percentage

Group Total

1 1 1 3.00

5.00

1.00

30.00%

50.00%

10.00%

6.00

10.00

3.00

1.00

Percentage

30.00%

50.00%

15.00%

5.00%

Group

Student Code

Ext. Supportive

Supportive-Minor

Supportive-Major

Not Supportive

UP11

UP12

UP13

UP14

UP15

UP16

UP17

UP18

UP19

UP20

Total Percentage

1 1 1 1 1 1 1 1 1 4.00

3.00

2.00

1.00

40.00%

30.00%

20.00%

10.00%

133

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Group

Student Code

Ext. Supportive

PM11

PM12

PM13

PM14

PM15

PM16

PM17

PM18

PM19

PM20

Total Percentage

Group Total Percentage

Overall Total Percentage

Supportive-Minor

Supportive-Major

Not Supportive

1 1 1 1 1

1 4.00

2.00

4.00

0.00

40.00%

20.00%

40.00%

0.00%

8.00

5.00

6.00

1.00

40.00%

25.00%

30.00%

5.00%

14.00

15.00

9.00

2.00

35.00%

37.50%

22.50%

5.00%

134

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix V – Pre-Test Scores of the Control Group OVERALL Objectives)

SCORES

(Learning

Student Code

Remembering

Understanding

Application

Analysis

Evaluation

Creation

UP1

2.33

2.73

3.00

2.50

UP2

2.00

2.83

2.67

2.50

2.00

UP3

2.00

2.77

2.33

2.00

UP4

2.33

2.70

2.00

2.33

2.00

UP5

2.00

2.77

2.33

2.50

UP6

2.00

2.68

2.00

UP7

2.33

2.86

2.33

2.00

UP8

2.00

2.68

2.00

2.17

2.00

UP9

2.33

2.66

2.33

2.00

2.50

UP10

2.67

2.68

2.33

2.00

Task Mean

2.20

2.74

2.33

2.15

Student Code

Remembering

Understanding

Application

Analysis

Evaluation

Creation

PM1

2.33

2.00

2.27

2.00

2.33

2.50

PM2

2.33

2.00

2.27

2.00

PM3

2.33

2.00

2.43

2.00

PM4

2.00

2.33

2.00

PM5

2.67

2.42

2.00

PM6

2.33

2.00

2.52

2.00

PM7

2.33

2.67

2.35

2.00

PM8

2.33

2.42

2.33

2.50

135

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila PM9

2.67

2.33

2.66

2.67

3.00

PM10

3.00

2.67

2.38

2.33

2.50

Task Mean

2.43

2.30

2.40

2.13

2.17

2.25

Group Mean

2.32

2.25

2.57

2.23

2.25

2.20

136

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix W – Pre-Test Scores of the Experimental Group OVERALL Objectives)

SCORES

(Learning

Student Code

Remembering

Understanding

Application

Analysis

Evaluation

Creation

UP11

2.67

2.38

2.00

UP12

2.33

2.67

2.53

2.00

UP13

2.67

2.59

2.33

2.17

2.50

UP14

2.67

2.00

2.62

2.00

2.17

3.00

UP15

2.00

2.67

2.48

2.00

2.33

2.00

UP16

2.33

2.67

2.51

2.00

2.17

2.50

UP17

2.00

3.00

2.51

2.00

UP18

2.33

3.00

2.44

2.00

2.17

2.00

UP19

2.67

3.00

2.44

2.00

UP20

2.67

2.33

2.44

2.00

2.17

2.00

Task Mean

2.43

2.67

2.49

2.03

2.12

2.20

Student Code

Remembering

Understanding

Application

Analysis

Evaluation

Creation

PM11

2.67

3.00

2.96

2.67

3.00

PM12

3.00

2.85

2.33

2.67

3.00

PM13

3.00

2.67

3.05

2.67

2.50

PM14

3.00

3.40

3.00

PM15

3.00

3.40

3.00

PM16

3.00

2.67

2.63

2.33

2.50

PM17

3.00

2.65

2.33

2.50

PM18

2.33

2.60

2.33

2.50

137

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila PM19

2.33

2.67

2.58

2.33

2.50

PM20

2.00

1.65

1.67

2.50

Task Mean

2.73

2.78

2.47

2.50

2.70

Group Mean

2.58

2.70

2.64

2.25

2.31

2.45

138

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix X – Post-Test Scores of the Control Group OVERALL Objectives)

SCORES

(Learning

Student Code

Remembering

Understanding

Application

Analysis

Evaluation

Creation

UP1

3.67

3.33

3.23

3.67

4.00

UP2

3.67

3.36

3.00

3.50

UP3

3.33

3.22

4.00

3.83

3.00

UP4

3.67

3.45

3.00

4.00

UP5

3.67

3.00

3.25

3.00

3.83

3.00

UP6

3.33

3.28

3.33

3.00

3.50

UP7

3.67

3.00

3.14

3.33

3.67

4.00

UP8

3.33

3.13

3.33

3.17

3.50

UP9

3.00

3.41

3.00

3.67

3.50

UP10

3.67

3.00

3.43

3.67

3.33

3.50

Task Mean

3.50

3.27

3.29

3.33

3.42

3.55

Student Code

Remembering

Understanding

Application

Analysis

Evaluation

Creation

PM1

3.33

3.67

3.40

3.33

3.50

3.00

PM2

3.00

3.06

3.33

3.17

3.50

PM3

4.00

3.00

3.40

3.00

3.67

3.50

PM4

3.00

3.67

3.24

3.67

3.17

3.50

PM5

3.33

3.67

3.29

3.00

3.67

4.00

PM6

3.33

3.67

3.26

3.33

3.00

PM7

3.00

3.33

3.37

3.33

4.00

PM8

4.00

3.33

3.24

3.67

3.33

3.00

139

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila PM9

3.00

3.33

3.26

3.00

3.17

3.50

PM10

3.67

3.33

3.18

3.67

3.33

4.00

Task Mean

3.37

3.40

3.27

3.33

3.50

Group Mean

3.43

3.33

3.28

3.33

3.38

3.53

140

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix Y – Post-Test of the Experimental Group OVERALL Objectives)

SCORES

(Learning

Student Code

Remembering

Understanding

Application

Analysis

Evaluation

Creation

UP11

4.00

3.82

4.00

UP12

4.00

3.90

4.00

3.67

4.00

UP13

4.00

3.82

4.00

3.83

4.00

UP14

4.00

3.82

4.00

UP15

4.00

3.77

4.00

UP16

3.67

3.62

3.67

3.50

UP17

4.00

3.92

3.67

4.00

UP18

4.00

3.90

3.67

4.00

UP19

4.00

3.82

3.67

4.00

UP20

4.00

3.92

3.67

4.00

Task Mean

3.97

3.83

3.92

3.95

Student Code

Remembering

Understanding

Application

Analysis

Evaluation

Creation

PM11

4.00

3.78

4.00

3.50

PM12

3.33

4.00

3.87

4.00

PM13

4.00

3.87

4.00

PM14

4.00

3.95

4.00

PM15

4.00

3.87

4.00

PM16

3.67

4.00

3.91

3.67

4.00

PM17

4.00

3.67

3.91

4.00

3.67

4.00

PM18

4.00

3.93

3.67

4.00

141

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila PM19

4.00

3.78

4.00

PM20

4.00

3.91

4.00

Task Mean

3.90

3.97

3.88

3.93

3.90

3.95

Group Mean

3.93

3.97

3.86

3.88

3.91

3.95

142

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix Z – Bloom’s Learning Objectives – Control Group

Level

Learning Objectives Control Group

Pre-Test Mean Score

Interpretation

Post-Test Mean Score

Interpretation

Remembering

2.32

Moderate

3.43

Very High

Understanding

2.25

Moderate

3.33

High

Application

2.57

Moderate

3.28

High

Analysis

2.23

Moderate

3.33

High

Evaluation

2.25

Moderate

3.38

High

Creation

2.20

Moderate

3.53

Very High

Overall Mean

2.30

Moderate

3.38

High

143

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix AA – Bloom’s Learning Objectives – Experimental Group

Level

Learning Objectives Experimental Group

Pre-Test Mean Score

Interpretation

Post-Test Mean Score

Interpretation

Remembering

2.58

Moderate

3.93

Very High

Understanding

2.70

Moderate

3.97

Very High

Application

2.64

Moderate

3.86

Very High

Analysis

2.25

Moderate

3.88

Very High

Evaluation

2.31

Moderate

3.91

Very High

Creation

2.45

Moderate

3.95

Very High

Overall Mean

2.49

Moderate

3.92

Very High

144

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix AB – T-Test Significance of the Post-Test Control Group - Post-Test

Overall

UP1 to UP10

3.30

3.37

3.36

3.34

PM1 to PM10

3.37

3.22

3.36

3.32

Mean of Control Group

3.34

3.29

3.36

3.33

Control Group - Post-Test

Overall

UP1 to UP10

0.10

0.13

0.14

0.38

PM1 to PM10

0.27

0.20

0.16

0.63

d2 of Control Group

0.37

0.33

0.31

1.00

Experimental Group - Post-Test

Overall

UP11 to UP20

3.79

3.83

4.00

3.87

PM11 to PM20

3.90

3.91

3.89

3.90

Mean of Experimental Group

3.84

3.87

3.95

3.88

Experimental Group - Post-Test

Overall

UP11 to UP20

0.74

0.07

0.03

0.83

PM11 to PM20

0.08

0.04

0.18

0.29

d2 of Experimental Group

0.81

0.10

0.21

1.12

CG vs EG Post-Test Scores

{s2p}

0.0560

Standard Error of CG-EG

145

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila est.

σCG-EG

0.0748

Value of t

7.427

5.841

Reject H0

EG Pre-Test vs Post-Test Scores

{s2p}

0.3302

Standard Error of CG-EG est.

σCG-EG

0.1817

Value of t

8.242

5.841

146

Reject H0

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix AC – Feedback on the Vehicle Simulator

Student Code

Item 1

Item 2

Item 3

Item 4

Item 5

Item 6

Item 7

Item 8

Item 9

Item 10

UP11

UP12

UP13

UP14

UP15

UP16

UP17

UP18

UP19

UP20

Mean Score

3.50

3.00

3.50

3.80

4.00

3.90

3.70

Student Code

Item 1

Item 2

Item 3

Item 4

Item 5

Item 6

Item 7

Item 8

Item 9

Item 10

PM11

PM12

PM13

PM14

PM15

PM16

PM17

PM18

PM19

147

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila PM20

Mean Score

3.60

3.40

2.90

3.00

3.60

3.90

3.80

3.90

3.80

3.55

3.45

2.95

3.00

3.55

3.85

3.80

3.95

3.90

3.75

Teacher Code

Item 1

Item 2

Item 3

Item 4

Item 5

Item 6

Item 7

Item 8

Item 9

Item 10

UPT1

UPT2

UPT3

Mean Score

3.33

3.67

3.33

3.67

4.00

3.67

Teacher Code

Item 1

Item 2

Item 3

Item 4

Item 5

Item 6

Item 7

Item 8

Item 9

Item 10

PMT1

PMT2

PMT3

Mean Score

4.00

3.00

2.33

3.33

4.00

3.67

4.00

3.67

3.83

3.17

2.83

3.50

3.83

4.00

3.83

3.61

3.64

3.06

2.92

3.53

3.84

3.82

3.89

3.95

3.79

Combined

Combined Students Teachers Rank

148

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix AD – Features of the Vehicle Simulator Student Code

Item A

Item B

Item C

Item D

Item E

Item F

Item G

Item H

UP11

UP12

UP13

UP14

UP15

UP16

UP17

UP18

UP19

UP20

Mean Score

6.90

1.40

2.70

2.90

4.10

6.30

7.20

4.50

Student Code

Item A

Item B

Item C

Item D

Item E

Item F

Item G

Item H

PM11

PM12

PM13

PM14

PM15

PM16

PM17

PM18

PM19

PM20

149

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Mean Score

6.80

2.00

2.10

3.30

4.00

6.20

7.30

4.30

6.85

1.70

2.40

3.10

4.05

6.25

7.25

4.40

Teacher Code

Item A

Item B

Item C

Item D

Item E

Item F

Item G

Item H

UPT1

UPT2

UPT3

Mean Score

6.33

1.67

2.33

5.00

5.67

7.00

6.00

Teacher Code

Item A

Item B

Item C

Item D

Item E

Item F

Item G

Item H

PMT1

PMT2

PMT3

Mean Score

4.00

2.00

3.67

3.00

5.33

4.33

7.67

6.00

5.17

1.83

2.67

5.17

5.00

7.33

6.00

6.01

1.77

2.53

2.88

4.61

5.63

7.29

5.20

Combined

Combined Students Teachers Final Rank

150

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Appendix AE – Results of Comparative Survey on Branded Simulators Vehicle Simulator

Combined

No.

Item

FUP1

F-UP2

F-UP3

UP Mean

F-PM1

F-PM2

F-PM3

PM Mean

3.00

1.33

1.00

3.00

1.00

4.00

2.53

2.59

2.55

2.59

2.53

2.55

3.00

3.67

151

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila

3.33

3.00

1.00

3.00

1.00

4.00

2.65

2.82

2.71

2.73

2.71

2.76

2.71

2.73

4.00

3.67

4.00

2.00

3.00

4.00

152

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila

3.64

3.55

3.61

3.64

3.55

3.61

1.00

2.00

4.00

3.00

2.50

4.00

1.00

3.00

2.67

3.67

4.00

3.67

4.00

3.89

4.00

3.67

3.89

4.00

2.33

2.00

2.33

1.00

1.75

2.00

1.92

2.00

1.75

2.00

1.92

3.67

3.00

1.00

2.33

2.67

2.56

2.33

2.67

2.56

153

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila 10

10a

3.00

10b

3.33

10c

4.00

10d

3.67

10e

4.00

3.60

3.80

3.40

3.60

3.80

3.40

3.60

2.93

3.06

3.01

3.00

3.03

2.97

3.00

Mean

Kongsberg

Combined

No.

Item

F-UP1

F-UP2

F-UP3

UP Mean

F-PM1

F-PM2

F-PM3

PM Mean

4.00

3.00

4.00

3.00

4.00

154

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila 1q

3.00

3.82

4.00

3.00

4.00

3.00

4.00

3.00

3.82

4.00

155

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila

4.00

3.00

3.33

3.17

3.75

4.00

3.83

3.79

4.00

1.00

2.00

156

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila

Mean

2.00

3.67

4.00

3.83

4.00

3.67

3.83

3.67

4.00

3.89

4.00

3.67

3.89

10a

4.00

10b

4.00

3.67

3.83

10c

4.00

10d

3.67

4.00

3.83

10e

4.00

3.80

3.93

4.00

3.80

4.00

3.93

3.41

3.44

3.42

3.44

3.42

3.43

157

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Curriculum Vitae

WILLIAM B. PICAR Block 22, Lot 28, Phase IV-C, Monteverde General Mariano Alvarez, Cavite Mobile No.: 0921-2989835 E-mail Address: wbpicar@gmail.com or williambpicar@yahoo.com

EDUCATION Bachelor’s Degree:

Degree Bachelor of Science in Marine Transportation Philippine Merchant Marine Academy San Narciso, Zambales June 1977 – March 1981

Master’s Degree:

Master in Maritime Education and Training Philippine Merchant Marine Academy Port Area, Manila January 2013 – April 2015

EXPERIENCE Head – Training, Assessment and Placement Asian Institute of Maritime Studies Pasay City Instructor Magsaysay Training Center U.N. Avenue, Ermita, Manila Instructor Asian Institute of Maritime Studies Pasay City

158

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Instructor AJ Center for Excellence Manila Instructor Philippine Nautical and Technological College Manila Instructor Magsaysay Institute of Shipping Manila Instructor University of Perpetual Help – Laguna Biñan, Laguna Instructor PHILCAMSAT Makati City Instructor West Bay College Muntinlupa City Instructor Maritime Academy for Asia and the Pacific Mariveles, Bataan Instructor Philippine Merchant Marine Academy Iba, Zambales Master / Second Officer – NWO Aboitiz – Jebsens Port Area, Ermita, Manila Master / Second Officer Manpower Resources of Asia Manila

159

PHILIPPINE MERCHANT MARINE ACADEMY

Graduate School, Manila Second Officer Avantgarde Shipping Manila Second Officer Midocean Philippines Manila Third Officer Hammonia Marine Services Manila

LICENSURE EXAMINATIONS TAKEN Second Mate Deck Officer Licensure Examination January 1995 Philippine Regulation Commission Certificate of Competency for Master (limited to 3,000 gross tonnage) July 2009 Philippine Regulation Commission

PROFESSIONAL AFFILIATION PMMA Alumni Association PERSONAL DATA Date of Birth: Place of Birth: Gender: Nationality: Wife: Children:

October 16, 1959 Fort Bonifacio, Makati City Male Filipino Olivia T. Picar Mary Joy Grace T. Picar Rei McGyver T. Picar Rei John T. Picar

160

APPLICABILITY OF THE VEHICLE SIMULATOR AS AN ALTERNATIVE TEACHING AND LEARNING TOOL

Articles inside

Instrumentation and Validation of the Instrument

D Task Performance Evaluation Form (Position Fixing

Chapter 4 - Presentation, Interpretation and Analysis of Data

Bibliography

B Task Performance Evaluation Form (Collision Regulation

Breakdown of Comparative Assessment Simulators ------------------ 69

C Task Performance Evaluation Form (Williamson Turn

Interpretation of Scores – Bloom’s Learning Objectives -------------- 51