Master of Science in Nursing

PREDICTORS OF NURSING GRADUATES’ PERFORMANCE IN LICENSURE EXAMINATION

A Master’s Thesis Presented to the Faculty, Graduate School Department College of Nursing and Health Sciences, Palawan State University Tiniguiban Heights, Puerto Princesa City

In Partial Fulfillment of the requirements for the degree,

Master of Science in Nursing

by

HERMANITO B. CONSAD II, RN

OCTOBER 2015

Republic of the Philippines PALAWAN STATE UNIVERSITY Puerto Princesa City College of Nursing and Health Sciences

APPROVAL SHEET In partial fulfilment of the requirements for the degree, Master of Science in Nursing, this thesis entitled: PREDICTORS OF NURSING GRADUATES’ PERFORMANCE IN LICENSURE EXAMINATION prepared and submitted by HERMANITO B. CONSAD II is hereby recommended for acceptance.

FRANCES MURIEL L. TUQUERO, Ph. D. Adviser

APPROVED as partial fulfilment of the requirements for the degree Master of Science in Nursing by the Committee on Oral Examination with a grade of ___________

APRIL GRACE O. LIAO, RM, RN, MAN Member

SONIA D. YGLORIA, RN, MAN Member

LERNA L. AYCO, Ed. D. Chairperson In partial fulfilment of the requirements for the degree, Master of Science in Nursing, this graduate thesis entitled “Predictors of Nursing Graduates’ Performance in Licensure Examination” is hereby APPROVED and ACCEPTED.

SONIA D. YGLORIA, RN, MAN Dean Date

ABSTRACT

HERMANITO B. CONSAD II, “PREDICTORS OF NURSING GRADUATES’ PERFORMANCE IN LICENSURE EXAMINATION.” A master’s thesis presented for the degree of Master of Science in Nursing, Palawan State University, Puerto Princesa City. Adviser: FRANCES MURIEL L. TUQUERO, Ph. D.

This study is aimed at determining the relationship between the grades of nursing core and tool subjects and the board exam rating of nursing graduates from Palawan State University from 2007 to 2009. The study tried to predict the variables that can help improve the rating in the Nurse Licensure Examination of PSU Bachelor of Science in Nursing graduates using the descriptive-correlational ex post facto method of research was employed in the study. Data were gathered from the relevant offices of Palawan State University. Frequency, percentage and standard multiple regression were the statistical tools used in the study. There were 77 valid cases. The findings suggest a significant correlation between grades in tool subjects and board examination rating as well as grades in nursing core subjects and board examination rating. This imply that higher rating in tool and nursing core subjects predict higher ratings in the Nurse Licensure Examination. Improvement of student performance in nursing and tool subjects should therefore be aimed by the College of Nursing and Health Sciences (CNHS) for a higher chance of passing the licensure examination.

Furthermore, CNHS should further strengthen its instruction capability especially in the tool and nursing core subjects by employing necessary measures that would ensure objectivity in rating the students’ performance.

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ACKNOWLEDGEMENT The researcher would like to convey his sincerest gratitude to the following people whose contribution made this work possible: To his adviser, DR. FRANCES MURIEL L. TUQUERO, for her guidance and valuable suggestions, and for sharing her precious time despite her hectic schedule. To his Dean, SONIA D. YGLORIA, RN, MAN, for allowing the researcher to access the files of the graduates and for the encouragement to finish this work; To PROF. THELMA S. CASANOVA, the University Registrar, for allowing the researcher to access the files of the nursing graduates; to MS. JOCELYN Z. SARRA, staff at the University Registrar’s Office, who patiently retrieved and photocopied the needed files for this study; To the Panel of Examiners, for their valuable suggestions and for scrutinizing this work for further improvement; To DR. LERNA L. AYCO, who is very approachable and accommodating, for her guidance and free consultation service on matters concerning statistics; To Professor JULIETA P. WY, former dean of CNHS, his research mentor, for sharing her knowledge, skills, and wisdom which help the researcher develop his research capability to conquer the complex field of research; To DR. GRACE N. ABRINA, Director, PSU Student Affairs Office for allowing the researcher to access the files of the graduates and her staff, especially MS. VANESSA TAN, PSU Guidance Counsellor, for sharing the NAT results of the nursing graduates;

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To PROF. LOURDES SALVADOR and her staff at the University Library, for their assistance in finding the necessary references for this study; To the GRADUATES of Batch 2007 to 2009 of Palawan State UniversityCollege of Nursing and Health Sciences, who inspired the researcher to conduct the study in the pursuit of excellence in nursing education; To his sister MS. GRACHEN B. CONSAD, for allowing the researcher to use her laptop during the entire process of this study; To his wife SUWENDRA and kids JEZRELLE JOHN & KENJJE AC, the source of inspiration and motivation to continue and finish the study, for their patience in accompanying the researcher while staying late at night. Above all, to our GOD ALMIGHTY, for the knowledge and wisdom and for the talent He had bestowed to the researcher; the glory and honor is Yours, always and forever. To all of you who made this endeavor possible, the researcher will forever be indebted, DAGHAN KAAYONG SALAMAT SA INYONG TANAN, I will not be able to finish this study without your help. So thank you for taking part in this wonderful quest.

HB CONSAD II

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TABLE OF CONTENTS

Title

Page

Abstract

iii

Acknowledgement

v

List of Tables

ix

List of Figures

x

CHAPTER 1: INTRODUCTION

1

Background of the Study

1

Statement of the Problem

4

Significance of the Study

4

Scope and Delimitations

5

CHAPTER 2: REVIEW OF RELATED LITERATURE AND STUDIES

9

Related Literature and Studies

9

Theoretical Framework

15

Research Paradigm

15

Research Hypothesis

17

Definition of Terms

18

CHAPTER 3: RESEARCH METHODOLOGY Research Design

20 20

vii

Research Locale, Population, and Sampling

20

Research Instrument

21

Data Gathering Procedure

22

Statistical Treatment

22

CHAPTER4: PRESENTATION, INTERPRETATION, AND ANALYSIS OF DATA

23

CHAPTER 5: SUMMARY, CONCLUSION, AND RECOMMENDATION

30

Summary of Findings

30

Conclusions

31

Recommendations

32

BIBLIOGRAPHY

35

APPENDICES

38

Appendix A Letters

39

Appendix B Executive Summary

49

Appendix C Multiple Regression Computation Results

52

Appendix D Raw Data

60

CURRICULUM VITAE

67

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List of Tables Table 1 Graduate’s Performance in Tool Subjects and Nursing Core Subjects

23

Table 2 Graduate’s Performance in Licensure Examination for Nurses

24

Table 3 Cross Tabulation of Graduate’s Performance in Tool Subjects and Board Exam

25

Table 4 Cross Tabulation of Graduate’s Performance in Nursing Core Subjects and Board Exam

26

Table 5 Predictors of Nursing Board Examination Rating (Tool Subjects)

27

Table 6 Predictors of Nursing Board Examination Rating (Nursing Core Subjects)

29

ix

List of Figures Figure 1

Research Paradigm

17

x

CHAPTER I INTRODUCTION

Background of the Study

Quality nursing education is very crucial since nurses are stewards of health. The theories that nursing students learn in school are their weapon to effectively manage their patient’s health. Nursing schools therefore should impose the highest standard possible in order to produce the best nurses not only in terms of theoretical foundation but as well as their skills developed. Not so long ago, from 1981 to 1990 only 36 schools were given approval and recognition by the Philippine government to offer a nursing program. Soon after the western countries open up their doors to foreign nurses and nursing schools proliferated like mushrooms. From 1991 to 2003, there were already 237 schools offering the nursing program, a staggering 558% increase compared to the previous decade (Baldago, 2004). The proliferation of these nursing schools greatly affected the quality of nurses being produced. The Palawan State University College of Nursing and Health Sciences (PSUCNHS) first offered the nursing program in school year 2003-2004 with a progressive curriculum in Associate in Health Science Education (AHSE), a preparatory curriculum leading to Bachelor of Science in Nursing. The College of Nursing and Health Sciences (CNHS) then was under the College of Sciences as a separate department offering AHSE and midwifery program. It formally opened its nursing program in June 2004. In school year 2006-2007, CNHS was established as a separate college. Its first dean, Professor

Violeta R. Yadao limited its door only to few “best” enrollees considering that the College then had limited classrooms and clinical instructors to accommodate students. The College imposed an admission and retention policy wherein only high school students with a general average of 85%, will take the University entrance exam and get a passing rate in the exam. For the retention policy, students need to maintain a grade of 2.5 in all their subjects in order to advance to the next level. Another requirement is passing the Nursing Aptitude Test which is usually given every second semester of Level I. Students found to be deficient in any of the policies mentioned are advised to shift to another course or to transfer to another school offering the same program. In April 2007, the University graduated the first batch of the nursing program and in December of the same year, 55 took the licensure examination for nurses. Of the 55 examinees, 54 successfully became registered nurses. This was the defining moment in the history of the nursing program of the University. The University made history not only in Palawan and in Region IV-B but also in the entire country when it bested all nursing schools under Category B with a passing rate of 98.18%. However, since then, the passing rate of the University, although way above the national passing rate, continues to go down. In 2011, it got its lowest passing rate ever at 48.58%. Nursing schools in the Philippines with less than 30% of the national passing rate are facing closure. Starting 2013, nursing schools that poorly performed in the Nurse Licensure Examination (NLE) for three consecutive school years from 2010-2011 to 2012-2013 were closed. This move to closely monitor the performance of nursing schools by the Commission on Higher Education (CHED) is stipulated in CHED Memo 14 series of 2009 article XI. The policy stated however that only the result of the first timers will

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be given consideration in the evaluation of the performance of the nursing schools. The aim of the CHED is to remove nursing schools who are offering substandard quality nursing education and at the same time improve the quality of nursing education in the country. In a span of a decade from 1997 to 2006, there were 250,127 total board takers who took the Nurse Licensure Examination and 49.3% or 123,433 successfully became registered nurses. However, in just four years, from 2007 to 2010, the number of board exam takers rose to 278% or a total of 695,949 and only 33.05% or 229,984 successfully became registered nurses (abbaphilippines.com, 2011). With the consistent decrease in performance of PSU graduates in the licensure exams for nursing in the last four (4) years, it is logical to think that the University’s nursing program might also become a candidate for closure. The researcher believes that one intervention that can be done to hopefully increase the chance of nursing graduates to pass the board exam is performance prediction. While it is recognized that there is no exact way of predicting the examinee’s performance in any board exam, it is to the best interest of the University that this be looked at.

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Statement of the Problem This study generally aimed to determine the factor that may have affected or served as predictors of the nursing board examination performance of PSU nursing graduates in 2007 to 2009. Specifically, it sought to answer the following questions: 1. What is the performance rating of nursing graduates in terms of the following a. tool subjects; and b. nursing core subjects? 2. What is the performance of nursing graduates in the nursing board examination? 3. What is the relationship between the performance of the graduates in terms of the following: a. tool subjects and nursing board examination; b. nursing core subjects and nursing board examination?

Significance of the Study To the Palawan State University College of Nursing and Health Sciences, this can serve as a basis in policy making in order to make the necessary adjustments that would stop the present downtrend of its graduates in terms of performance in the nurse licensure examination. Furthermore, it can also serve as basis for curriculum adjustment that will address the present problem of PSU-CNHS as cited above. To the PSU-CNHS administrators, the study can serve as a reference in terms of policy-making related to admission and selection as well as retention.

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To the instructors of the College and service colleges especially those teaching the tool subjects namely English, Science and Math, results of the study on the significant relationship between the nursing graduates’ academic performance and the licensure exam scores can help them reevaluate their teaching strategies and subject syllabi that would fit the current need of the nursing students. To the nursing students at present, results can give them the hint as to which subjects or admission test scores can be considered predictor variables of their licensure exam scores and hence become their focus of study/review while still studying. To the readers and other stakeholders, this study will give them an idea on what to contribute to improve the nursing program of Palawan State University.

Scope and Delimitation This study is confined to Palawan State University College of Nursing and Health Sciences. It dwelt on the assumed predictive factors of nursing board examination performance that include academic performance in tool subjects (English, Math, Science) and nursing core subjects of the graduates. Academic performance is evaluated using the general weighted averages in the nursing core subjects and the tool subjects of the nursing curriculum. For the purpose of this study, only the following nursing core subjects were included: Primary Health Care 11 (PHC 11), Primary Health Care 12 (PHC 12), Nursing Care Management Subjects (100, 101, 102, 103, 104, 105). The tool subjects were composed of Mathematics (College Algebra), English subjects namely Communication Arts, Skills and Composition, Speech and Oral Communication and Writing for Academic Purposes. Science subjects on the other hand include Anatomy and

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Physiology (Biosci13) and Microbiology with Parsitology (Biosci14). This is based on the old curriculum prescribed by CHED Memo 31 series of 2001. Members of PSU BSN Batch 2007 to 2009 who took the nurse licensure examination from 2007 to present were the respondents of this study. Only the graduates with complete data in their tool and nursing core subjects as well as their licensure rating were included in the study. This study was conducted from October 2012 to October 2015.

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CHAPTER II REVIEW OF RELATED LITERATURE AND STUDIES

This chapter provides key points and basis of the study undertaken. Foreign and local literatures were employed to better understand how the factors were utilized to assess a graduate in terms of his/her performance in the licensure exam. Related studies, both foreign and local, were also cited to determine consistencies among the results. The chapter also presents the theoretical and conceptual framework of the study, the research paradigm, and the research hypothesis.

Legal Basis of Program Offering and Nursing Core Subjects The Palawan State University College of Nursing and Health Sciences had its nursing curriculum approved by its Board of Regent via BOR Resolution #7 series of 2003 and further amended by BOR Resolution #29 series of 2007. It has the following nursing professional subjects: Introduction to Nursing Research, Strategies in Health Education, Community Health Development, Foundations of Nursing (NCM 100), Promotive & Preventive Nursing Care Management (NCM 101), Curative & Rehabilitative Nursing Care Management I (NCM 103). NCM 103 Related Learning Experience, Curative &Rehabilitative Nursing Care Management II (NCM 104), and Nursing Management and Leadership (NCM 105). Except for the first three nursing professional subjects, the rest have lectures and clinical duty. NCM 103 on the other hand, is purely clinical duty. Aside from the nursing professional subjects, the following subjects are part of the health related subjects, Primary Health Care I & II, Health

Economics with Taxation and Agrarian Reform, Bioethics, Basic Nutrition, and Science, Technology and Society (CHED Memo 31 s. 2001, PSU BSN Curriculum). There are several requirements to comply prior to admission in the nursing program. Furthermore, a student is required to maintain a general weighted average for him/her to be retained in the program.

Legal Basis of Admission & Retention Policies Article IX of CHED Memo 14 series of 2009 stated that nursing schools should have their admission, retention and promotion policies. It further requires the schools to have an entrance examination covering the following areas: English, Science, Math, and Inductive Reasoning. The earlier issued CHED memorandum, (CHED Memo 30 series of 2001), Article X, Section 1 requires students desiring to enrol in nursing to belong to the upper forty percent (40%) of the graduating class as further mandated by the Philippine Nursing Act of 1991. This provision, however is deleted in the latest Philippine Nursing Act of 2002, thus the promulgation of admission, retention, and promotion policies is delegated to schools offering the program. The Palawan State University College of Nursing and Health Sciences has its own admission, promotion and retention policies. New entrants to the program must have a general average of 85% in high school, has passed the entrance examination of the University, and has to undergo and pass the intake interview conducted by the College. As for promoting its students, Nursing Aptitude Test is required to be taken and the students should pass the test as part of the promotion requirement to Level III for the old curriculum (CMO 31 s. 2001) and Level II for the

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new curriculum (CMO 14, s 2009). In order for a student to remain in the program, he/she must have a general weighted average of 2.50 or better in all subjects

Scope of Nursing Board Examination The Board of Nursing issued broad pointers as scope for the nurse licensure examination. Based on Board of Nursing Resolution No. 27 series of 1994, the Integrated Comprehensive Nurse Licensure Examination consists of four concepts surrounding the major goals of nursing namely promotive goal, preventive goal, curative goal, and rehabilitative goal. These concepts replaced the previous composition of the examination and is more specific than the new scope, namely Fundamentals of Nursing, Maternal and Child Health Nursing, Community Health Nursing, Nursing of Adolescents, Adults, and Aged, and Mental Health Nursing BON Res # 27 s 1994 as cited by Baldago (2004). The Philippine Board of Nursing in their attached website of the Professional Regulation Commission published an outline of the topics for the Licensure Examination which includes Foundations of Nursing Practice including Professional Adjustments, Maternal and Child Health Nursing, Community Health Nursing and Communicable Disease Nursing, Nursing Care of Adolescents, Adults and Aged, and Mental Health and Psychiatric Nursing.

.

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Local and Foreign Studies on Predictors Affecting Examination Performance In the study conducted by Neri (2008), academic performance in the nursing core subjects was used as her basis in predicting the performance in the board exam as well as the clinical performance, guided review performance, and in-house review performance. She concluded that Nursing Licensure Examination passers are usually those students who are performing well in their academics in both classroom and clinical exposure and in in-house reviews. Furthermore, passers have higher intellective profile compared to non-passers (Neri, 2008). Ong, Bañico, and Palompon (2012) in their study using College Entrance Examination performance on IQ test, nursing aptitude test, composite score of science, math and English tests, college grade point average and pre-board examination performance concluded that these variables have correlations with licensure examination performance. However, grade point average and pre-board examination were the only variables found to significantly predict the licensure examination performance. Moreover, Garcia (2012) found out that general point average in Microbiology and Parasitology and performance in Nursing Board Examination review were the best predictors for board examination performance. Meanwhile, Navarro et al (2011) found that employing college admission test, Nursing Aptitude Test and academic performance are significant predictors of performance in the Nursing Board Examination. This is supported by the study of Lacubtan and Juan (2011) who found general weighted average (GWA) and Nursing Aptitude Test (NAT) as correlated with licensure examination performance.

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In other countries, Stuenkel (2006) found in his study that graduates with better grades in pharmacology, maternal-child, mental health, community, pathophysiology, medical-surgical, and leadership have greater chance of passing the NCLEX examination. He concluded that those with higher average in those subjects have greater chance of passing the said examination. Addiionally, Daley, Kirkpatrick, Frazier, Chung and Moser in their study in 1999 and 2000, found two variables that correlated with NCLEX success: final course grade for a senior medical-surgical nursing course and cumulative program grade point average (GPA). This was somehow supported using students’ records from 1991 to 2001, Haas, Nugent, and Rule (2004), noted that students who passed the NCLEX have GPA which is 0.3 higher than those who failed. However, Giddens and Glockner (2005) in their study employing critical thinking as a predictor of passing the NCLEX noted that said variable is reliable as predictor only to those who passed the examination but not for those who failed. Mcgahee et. al.(2010) noted that the main variable that predicts NCLEX success is the proficiency in theoretical foundations and pathophysiology. He however explained that there is no single variable that can be a predictor in passing the They further noted that nursing education is multi-dimensional and that no single class or experience will stand alone, courses build upon prior learning experiences, and students must use knowledge and skills from each course in the final analysis. Beeman and Waterhouse (2001), in their study regarding the predictor of passing the National Council Licensure Examination (NCLEX) examination maintained that the most common predictor of failures in the licensure exam are grades. According to the

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authors higher grades in pathophysiology and other nursing core subjects correlate with success in the same licensure examination. This is further supported by Mcgahee et al (2010), Bonmass, Monnie and Kowalski (2010) who studied the relationship between Nursing Entrance Test and Educational Resources. They found out that students who passed the National Council Licensure Examination (NCLEX) have scored significantly higher in the standardized exam like the College Admission exam and the Nursing Entrance Examination. The National Council of State Boards of Nursing (NCSBN) findings were also woth noting. The Oklahoma Board of Nursing emphasized that passing rate decreases as the time of taking the examination increases meaning the longer length of time the examinees decide in taking the NCLEX the lesser are their chance of passing the examination. Below are the contents of the report of the Oklahoma State Board of Nursing (www.ok.gov, accessed June 24, 2011) where the following commonalities were noted: 

The use of accessible sources of data to evaluate the correlation between admission scores, grade point average, NCLEX predictor examination scores, and NCLEX pass rate are not regularly done by some programs. Thus, making informed decisions about changes in the program that will result to improvement in NCLEX pass rate is affected.



Most programs have just recently begun the use of NCLEX predictor examinations as part of the program requirement. This limits the data on the efficacy of these examinations and on appropriate follow-up plans..

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

Crediting of points in theory courses for attendance, participation, and completion of assignments results to grade inflation and is a factor leading to a low NCLEX pass rate in some nursing education programs.



Minimum academic requirements for admission to the program are not clearly identified. Instead, a point system may be used to select those who are deemed to be better qualified. The use of point systems in admission decisions may be appropriate but point systems fail when applicant numbers decline. Identifying minimum academic requirements such as minimum scores on standardized preentrance examinations may be necessary to ensure that students admitted have a reasonable chance of success in the program and on the NCLEX examination.



High number of work hours, family commitments, English as a second language, and low admission points are the characteristics of students identified by programs as factors leading to NCLEX failure.



Resignation of the program director, faculty turnover, inexperienced faculty, lack of knowledge regarding the NCLEX examination and/or test development, and increased use of adjunct faculty, problems within the program, were some of the factors noted as having an impact on the NCLEX pass rate.

Yet, according to the Oklahoma Board of Nursing (2011), which studied the baccalaureate nursing program, performance in the National Council Licensure Examination (NCLEX) is predictive of the following: ACT/SAT score, other preentrance examination scores, pre-admission grade point average, nursing course grade point average, scores on NCLEX predictor examinations, and repeats of science or

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nursing courses. Other psychosocial variables that may predict NCLEX success/failure include number of hours worked per week, English as a second language, ethnic minority status, low motivation scores on standardized assessments, and length of time between graduation and taking the examination (OBN). On the other hand, California Board of Nursing (2001) identified several factors that negatively affect NCLEX examiners which include students’ employment hours and family responsibilities, having English as a second language, withdrawing from or failing a science course more than once, graduates’ delaying taking the exam five months or more, and limited knowledge by nursing faculty of the NCLEX test plan. The Iowa State Board of Nursing (2005) in a report on the institutional survey of nursing schools noted the following as factors affecting the drop in passing rate in the NCLEX: low admission standards, increased enrollment, faculty shortages, faculty turnover, faculty inexperience in teaching methods and test construction, student's attitudes and lack of focus on the program, lack of student's preparation for the NCLEX, length of time between student's completion of the program and taking the NCLEX, student's stress levels due to employment and family responsibilities, program curriculum and progression criteria and NCLEX test plan change.

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Theoretical Framework Shewart’s Theory of Prediction states, “A phenomenon will be said to be in control when, through the use of past experience, we can predict at least within limits, how the phenomenon may be expected to vary in the future. Here it is understood that the prediction within limits means that we can state, at least approximately, the probability that the observed phenomenon will fall within given limits” (Shewart, 1931). Predicting student’s performance to perform well in any given exam is a big help not only to the student him/herself but as well as to the institution he/she represented. Necessary adjustments can be made once the parameters are set. However, unlike production where quality can be easily controlled, factors affecting student performance vary. In this study, the factors considered is the academic performance of graduates in nursing core subjects and selected tool subjects. As suggested by Shewart’s Theory of Prediction, factors that will be found to have significant relationship with the performance in the licensure exam can be used as predictors of the likely outcomes or partly explain the licensure exam results. However, because of the type of study (which is correlational not experimental) these factors/predictors cannot be consciously considered as the very causes of passing or failing in the exam. Individuality of the students is a factor that is hard to predict. What complicates more is the fact that predicting is not aimed at 100 percent accuracy as this is not about producing a product out from a machine. It is about producing graduates that will at least perform positively that is to pass the board exam for nurses.

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Shewart’s theory is primarily designed for production purposes where variables can be easily predicted and can easily be controlled. The individuality of the subjects may vary and there may be other factors that closely relate and affect their performances.

Research Paradigm

Graduates’ performance rating in a. Tool subjects b. Nursing core subjects

Nursing Licensure / Board Examination Rating

Figure 1. Conceptual Framework The figure shows the schematic diagram of the variables being studied. The performance rating of the graduates in the tool and the nursing core subjects influence their rating in the Nurse Licensure Examination. According to Shewart’s Theory of Prediction, a phenomenon can be predicted within based on past evidence. The academic performance of nursing graduates in nursing core subjects and tool subjects were given emphasis. The assumption in this study is that academic performance of nursing graduates in nursing core subjects and tool subjects play a huge rule to help predict their performance in the licensure examination for nurses. However, this being just a correlation study, the researcher recognizes that other factors may also contribute and may help predict the performance of graduates in the nursing licensure examination which are beyond the scope of this research. This may include: inexperience of faculty members, fast turnout of nursing faculty members, admission exam rating, nursing

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aptitude examination rating, mock board examination performance and in-house review performance. Academic performance is composed of the general weighted averages in the nursing core subjects and the tool subjects. The respondent’s performance in the licensure examination is determined by their ratings.

Research Hypothesis 1. There is significant relationship between the obtained rating of the graduates in the nursing board examination and the following variables a. tool subjects and b. nursing core subjects.

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Definition of Terms For purposes of clarification, the following terms are defined operationally. General Weighted Average (GWA)-This pertains to the overall average of the students in their nursing core subjects and tool subjects that include science, math and English. This is measured using the scoring scale used by the University as follows: Average Satisfactory Highly Satisfactory Outstanding Excellent

GWA of 3.0-2.26 or 75 to 82.99 percent GWA of 2.25 or 83-85.99 percent GWA of 2.0 to 1.76or 86-88.99 percent GWA of 1.75 to 1.26 or 89-91.99 percent GWA of 1.25 to 1.0 or 92-100 percent

Nursing Board Examination rating-This refers to the numerical rating of the nursing graduates in the nursing board examination. Nursing Core Subjects/courses-This is composed of the following nursing subjects: PHC 11, PHC 12, NCM 100, NCM 101, NCM 102, NCM 103, NCM 104, NCM 105 (Primary Health Care (PHC) 11 & 12; Nursing Care Management (NCM) 100 to 105) Nursing graduates-refers to the graduates of Palawan State University College of Nursing and Health Sciences batch 2007, 2008, and 2009. Performance rating-this refers to the verbal interpretation in relation to the numerical rating obtained by the nursing graduates in their tool and nursing core subjects as follows Average Satisfactory Highly Satisfactory Outstanding Excellent

with Grades equivalent to 3.0-2.26 or 75 to 82.99 with Grades equivalent to 2.25 or 83-85.99 with Grades equivalent to 2.0 to 1.76or 86-88.99 with Grades equivalent to 1.75 to 1.26 or 89-91.99 with Grades equivalent to 1.25 to 1.0 or 92-100

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Tool subjects- this refers to all the English subjects namely Communication Arts, Skills and Composition, Speech and Oral Communication and Writing for Academic Purposes, Science subjects namely Anatomy and Physiology (Bio Sci 13) and Microbiology with Parasitology (Bio Sci14), and College Algebra (Math). Furthermore, Eng Ave is the weighted average rating of the three (3) English subjects.

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CHAPTER III RESEARCH METHODOLOGY

This chapter presents the discussion of the research methods used in the undertaking as well as the research design and statistical tool utilized for data analysis. The chapter likewise includes the detailed explanation of the research population, data gathering procedures, and the data validity and reliability.

Research Design

The research design used in this study is the descriptive-correlational ex post facto method. This study analyzed documentary evidence from previous batches of nursing graduates of Palawan State University from 2007 to 2009.

The descriptive method

explains the found new truth in the phenomenon under investigation. It is also valuable whenever the subjects vary among themselves and when one is interested to know the extent to which different conditions and situations are obtained among the subjects (Calmorin & Calmorin, 2008). The correlational method was used to determine the predictor variables with strong affinity to the dependent variable. In this study, the performance rating in the tool and nursing core subjects as well as the numerical rating in the nursing board examination of the graduates were analysed and interpreted which form the basis in drawing the conclusion.

Research Locale, Population, and Sampling

This study was conducted at the College of Nursing and Health Sciences, Palawan State University main campus located in Puerto Princesa City, Palawan, Philippines. The population of the study were the nursing graduates of PSU College of Nursing and Health Sciences batch 2007, 2008 and 2009. The study employed a systematic random sampling. Graduates included are only those whose data are complete such as grades in academic performance and licensure rating. This is regardless of the year, they took the exam.

Research Instrument

Review of records was utilized to collect the data necessary for the study. The graduates’ performance rating, both numerical and verbal, in the nursing core subjects and tool subjects, and board exam rating were collected. The researcher submitted letter of request to the offices involved to request a copy of the data of the graduates. This includes the CNHS Dean’s Office for the board rating and the University Registrar’s Office for the graduates’ grades in nursing core subjects and tool subjects.

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Data Gathering Procedures

A letter of request was forwarded to the Dean of the College of Nursing and Health Sciences and the PSU Registrar’s Office. Data requested from the CNHS Dean’s office were graduates’ files on the PRC-issued Board Examination School Performance Report. The data requested from the University Registrar’s Office were the grades of graduates in nursing core subjects and tool subjects.

Statistical Treatment Descriptive statistics is one of the statistical tools that were utilized in this study specifically frequency and percentage to determine the distribution of the data among the variables of the population under study. Standard Multiple Regression was used to determine the relationship between two or more variables namely the nursing board examination rating from Subject 1 to 5 and the nursing core subjects and the tool subjects and a response variable by fitting a linear equation to observed data. The formula for multiple regression equation for predicting Y is expressed as follows: (1)

Y '  A  B1 X1  B2 X 2  B3 X 3

The null hypothesis (H0) was tested at .05 level of significance.

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Chapter IV DATA PRESENTATION AND ANALYSIS This chapter focuses on the presentation, interpretation, and analysis of the data obtained from the graduate’s record in nursing and tool subjects rating as well as their nursing board examination numerical rating.

Table 1 Graduate’s Performance in Tool Subjects and Nursing Core Subjects n=77

Graduate's Performance in

Average Freq

Tool Subjects Nursing Core Subjects TOTAL

%

Satisfactory Freq

%

Highly Satisfactory Freq %

Outstanding Freq

%

3 1 4

4% 1% 3%

17 2 19

22% 34 44% 23 30% 3% 53 69% 21 27% 12% 87 56% 44 29% Mean Performance Tool Subject Nursing Core Subject 2.1446 (Satisfactory) 2.0629 (Satisfactory)

Total

77 77 154

LEGEND:

Average Satisfactory Highly Satisfactory Outstanding Excellent


The data in Table 1 shows the categorization of nursing graduates according to their performance in the tool and nursing core subjects based from their general weighted average. There are 77 respondents per subject cluster for a total of 154. Of the 154, a majority fifty-six percent (56%) or 87 graduates were rated as Satisfactory, followed by twenty-nine percent (29%) or 44 graduates who were rated Highly Satisfactory. Only three percent (3%) or four (4) graduates were rated as Outstanding.

Based on their performance in the tool subjects, the biggest portion of forty-four percent (44%) or 34 graduates were rated Satisfactory, followed by thirty percent (30%) or 23 graduates who were rated Highly Satisfactory. Only four percent (4%) or three (3) graduates were rated Outstanding. For the nursing core subjects performance, majority of sixty-nine percent (69%) or 53 graduates were rated Satisfactory. A considerable portion of twenty-seven percent (27%) or 21 graduates were rated Highly Satisfactory, and only one percent (1%) or one (1) graduate was rated as having Outstanding performance in the nursing core subjects. By performance, in both the tool and nursing core subjects based from the data presented, it can be said that majority of the nursing graduates of Palawan State University performed satisfactorily. In fact, graduates with performance rating from Satisfactory to Outstanding comprised a total of 88%.

Table 2 Graduates’ Performance in the Licensure Examination for Nurses n=77 Licensure Examination Performance PASSED FAILED TOTAL

Frequency

Percentage

69 8

90% 10% 100%

77

The above data presents the performance of the graduates in the licensure examination for nurses. Of the 77 respondent graduates, 69 or ninety percent (90%) passed the licensure examination for nurses while only eight (8) or ten percent (10%) failed.

24

Table 3 Cross Tabulation of Graduates Performance in Tool Subjects and Board Exam n=77 Graduate's Performance in

Tool Subjects Performance Average

Highly Satisfactory

Outstanding

Board Exam Passed Failed TOTAL

TOTAL

Satisfactory

Freq

%

Freq

%

Freq

%

Freq

%

Freq

%

13 4 17

19% 50%

30 4 34

43% 50%

23 0 23

33% 0%

3 0 3

4% 0%

69 8

100% 100%

77

LEGEND: Average Satisfactory Highly Satisfactory Outstanding Excellent


Table 3 shows the cross tabulation of the performance of graduates in tool subjects and licensure examination. Of the 69 graduates who passed the licensure examination, 30 were rated as Satisfactory, followed by 23 who were rated as Highly Satisfactory. Only three (3) were rated as Outstanding in their tool subject performance. On the other hand, among the graduates who failed in the licensure examination, four (4) were rated as average and four (4) were rated as satisfactory in their tool subject performance. Table 3 shows that of the 69 nursing graduates or ninety percent (90%) who passed the board examination a majority of 30 graduates (43%) satisfactorily completed the tool subjects.

25

In the history of licensure examination for nurses in the Philippines, the national passing rate has not so far reached 50%. Thus, based from the data above, it can be assumed that PSU batches 2007-2009 nursing graduates with satisfactory rating in tool subjects are performing well in the Nurse Licensure Examination.

Table 4 Cross Tabulation of Graduates Performance in Nursing Core Subjects and Board Exam n=77 Graduate's Performance in

Nursing Core Subject TOTAL Average

Board Exam

Satisfactory

Highly Satisfactory

Outstanding

Freq

%

Freq

%

Freq

%

Freq

%

Freq

%

PASSED

1

1.50%

46

67%

21

30%

1

1.50%

69

100%

FAILED

1 2

13%

7 53

87%

0 21

0%

0

0%

8 77

100%

TOTAL

1

LEGEND: Average Satisfactory Highly Satisfactory Outstanding Excellent


Table 4 shows the cross tabulation of nursing graduates performance in nursing core subjects and the nurse licensure examination. Of the 77 examinees, 69 (90%) passed the licensure examination, of those who passed, 46 or 67% got a satisfactory rating and 21 or 30% got a highly satisfactory rating in core subjects. Only seven (7) of the eight (8) graduates who failed in the licensure examination satisfactorily completed the core subjects.

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It can be safely assumed based from the above data, that nursing graduates for batches 2007 to 2009 with better performance in the nursing core subjects also had passed the nurse licensure examination. Table 5 Predictors of Nursing Board Examination Rating Tool Subjects Multiple Regression Summary of Results Model Summary *R .523a

Adjusted R Square .233

F 6.778

Sig. .000

ANOVA

Coefficients Predictor Variable Math EngAve Biosci13 Biosci14

Beta Standardized Coefficients -.149 -.361 .026 -.282

Significance p < 0.05 .181 .002 .812 .011

Legend1: Value of r (R) -0.5≤ r ≤0.5 -0.8< r < -0.5 or 0.5 < r < 0.8 r ≤ -0.8 or r ≥ 0.8

Relationship Weak Moderate Strong

Math -College Algebra EngAve-GWA of Communication Arts, Skills and Composition, Speech and Oral Communication, and Writing for Academic Purposes Biosci13-Anatomy and Physiology Biosci14-Microbiology with Parasitology

Multiple regression analyses were conducted to predict the relationship between the set of tool subjects (Biosci14, Math, Biosci13, EngAve) and NLE Rating. Table 5 summarizes the multiple regression results. Using the enter method of linear regression, the model of the four predictors produced R = .523, F (4, 72) = 6.778, p < .05 (Sig.

1

(Jay L. Devore, Probability and Statistics for Engineering and the Sciences, Eighth Edition, 2012)

27

=.000). As seen above, the group of tool subjects has moderately positive (R=0.523) correlation with the NLE rating. Statistically speaking, this indicates that graduates with higher grades in the tool subjects have higher NLE Rating. Furthermore, graduates with lower grades in tool subjects have lower NLE rating. The Adjusted R Square suggests that 23.3% variability of the NLE rating is explained by the tool subjects. The Coefficients shows the individual relationships of the tool subjects to the NLE Rating. As can be seen above EngAve (p=0.002) and Biosci14 (p=0.001) are the two tool subjects that made the most impact in the model to predict the outcome of the graduate’s NLE Rating. The data shows that tool subjects have significant relationship with the NLE Rating. It can be assumed that better grades in the tool subjects predict passing rating in the Nurse Licensure Examination. The tool subjects that have significant influence to the model are EngAve (weighted average rating of the three (3) English subjects namely Communication Arts, Skills and Composition, Speech and Oral Communication and Writing for Academic Purposes) and Biosci14 (Microbiology with Parasitology). The results are supported by the findings of the National Council for Licensure Examination (NCLEX) as cited by the Oklahoma State Board of Nursing and California Board of Nursing that proficiency in English as a second language and Microbiology & Parasitology have significant role in passing the NCLEX licensure examination. This also affirms the result of the study conducted by Garcia (2012) that general point average in Microbiology and Parasitology are best predictors in Nurse Licensure Examination performance. Furthermore, the results of this study affirms the study of Beeman and

28

Waterhouse (2001) that grades are the common predictors in the licensure examination, that higher grades correlate with passing the NCLEX examination. Table 6 Predictors of Nursing Licensure Rating Core Subjects Multiple Regression Summary of Results Model Summary *R .541

Adjusted R Square .219

F 3.667

Sig. .001

ANOVA

Coefficients Predictor Variable PHC11 PHC12 NCM100 NCM101 NCM102 NCM103 NCM104 NCM105

Beta Standardized Coefficients .076 -.265 -.282 .025 .048 .038 -.111 -.231

Significance p < 0.05 .574 .043 .019 .837 .738 .745 .393 .098

*Legend: Value of r (R) -0.5≤ r ≤0.5 -0.8< r < -0.5 or 0.5 < r < 0.8 r ≤ -0.8 or r ≥ 0.8

Relationship Weak Moderate Strong

*(Jay L. Devore, Probability and Statistics for Engineering and the Sciences, Eighth Edition, 2012) PHC-Primary Health Care; NCM-Nursing Care Management

Multiple regression analyses were conducted to predict the relationship between the set of nursing core subjects (PHC11, PHC12, NCM100, NCM101, NCM102, NCM103, NCM104, NCM105) and NLE Rating. Table 6 shows the summaries of multiple regression results. Using the enter method of linear regression, the model of the eight predictors produced R = .541, F (8, 68) = 3.667, p < .05 (Sig. =.001). As seen

29

above, the group of core subjects has positive correlation with the NLE rating. Statistically speaking, this indicates that graduates with higher grades in the nursing core subjects have higher NLE Rating. Furthermore, graduates with lower grades in nursing core subjects have lower NLE rating. The Adjusted R Square suggests that 22% variability of the NLE rating is explained by the effects of nursing core subjects. The Coefficients show the individual relationships of the nursing core subjects to the NLE Rating. As can be seen above, PHC12 (p=0.043) and NCM100 (p=0.019) are the two core subjects that made the most impact in the model to predict the outcome of the graduate’s NLE Rating. The data shows that nursing core subjects have significant relationship with the NLE Rating. It can be assumed that better grades in the nursing core subjects predict better rating in the Nurse Licensure Examination. The nursing core subjects that have significant influence to the model are PHC122 (Primary Health Care 12) and NCM1003 (Nursing Care Management 100). The results relate with the data from the study of Stuenkel (2006), Daley, Kirkpatrick, Frazier, Chung and Moser (1999, 2000), Haas, Nugent, and Rule (2004), Beeman and Waterhouse (2001), the Oklahoma State Board of Nursing, and California Board of Nursing that better grades in nursing subjects have significant role in passing the NCLEX licensure examination. Furthermore, the results of this study affirms the study of Neri (2008), Navarro et al (2011), Ong, Bañico, and Palompon (2012), that

2

Primary Health Care II-Concepts and principles in the provision of basic health care in terms of health promotion/maintenance and disease prevention at the community level. 5 units (3 units lecture, 2 units RLE) 3 Foundations of Nursing-Overview of nursing as a service, an art, and a profession. It shall include a discussion on the different roles of a nurse emphasizing on health promotion, illness prevention utilizing the nursing process as a basis for nursing practice. 3 units (2 units Lecture , 1 unit RLE)

30

students with better grades in nursing subjects have better chance of passing the Philippine Nursing Licensure Examination. Furthermore the results of this study supports the study of Beeman and Waterhouse (2001) that grades are the common predictors in the licensure examination and that higher grades correlate with passing the licensure examination.

31

Chapter V SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS This chapter presents the result summary based from the previous chapter. Conclusions presented are based from the statistical outcome of the study.

Summary of Findings The performance rating of nursing graduates in terms of tool subjects and nursing core subjects. Majority of the nursing graduates from batch 2007 to 2009 were rated Satisfactory in their performance in both the tool subjects and the nursing core subjects. A total of 88% of graduates were rated from Satisfactory to Outstanding in their academic performance.

The performance of nursing graduates in the Nurse Licensure Examination. Ninety percent (90%) or 69 out of 77 PSU nursing graduates passed the licensure examination for nurses while only eight (8) or ten percent (10%) failed.

The performance of nursing graduates in the Nurse Licensure Examination based from their performance in tool subjects and nursing core subjects. In the cross tabulation table on graduate’s performance in the tool subjects and the nursing core subjects with the Nursing Licensure Examination, it shows that the better the performance rating of the graduates in the tool subjects and nursing core subjects, the better the chance of passing rate in the nursing board examination.

Predictive variables of the graduates rating in the nursing licensure examination. Tool subjects have predictive association with the rating in the nursing board examination. Of all the tool subjects, English and Biosci14 have most influence in the success or failure of the graduates in the nursing board examination. The higher the grades in English and Biosci14, the better the rating in the nursing board examination. The nursing core subjects have positive correlation with the rating of the nursing licensure examination. The better the rating in the nursing core subjects the better the graduates rating in the nurse licensure examination.

Conclusions Nursing graduates of Palawan State University College of Nursing batches 2007 to 2009 are performing satisfactorily in their tool and nursing core subjects. In the Nurse Licensure Examination, the passing rate of PSU-CNHS Nursing graduates are way above the national passing rate. The findings of the study strongly suggest that there is a significant positive correlation between the tool and nursing core subjects and the rating of the graduates in the Nurse Licensure Examination. Statistical analysis shows that higher grades in tool and nursing core subjects lead to higher rating in the Nurse Licensure Examination. On the other hand, lower rating in the tool and nursing core subjects lead to lower rating in the Nurse Licensure Examination.

31

Recommendations Based from the conclusion of the study it is recommended that the College of Nursing and Health Sciences should further strengthen its instruction by adhering to the standards set. For the tool subjects especially English, students’ comprehension should be developed since 100% of the licensure question is written in English. This is especially because English proficiency as supported by the study results, could predict better nursing board examination performance. For the nursing core subjects, all efforts should be made to see to it that instruction covers all the concepts. Mastery of the different nursing concepts increases graduates’ proficiency. Increase in proficiency means better performance in the licensure examination, as what the statistical results of this suggest. Students’ performances should also be objectively rated by strengthening their retention policies. Though the grades in both tool and nursing core subjects are predictors of higher numerical rating in the board examination, it is also recommended that the students should be rated in an objectively manner such that their grades will be based from their actual performance in both classroom and clinical setting. It is also suggested that despite the variability of the content in the nurse board examination, the College must uphold the standard and continue to explore possibilities that could help improve the performance of its graduates in the board examination. The level of English proficiency in both writing and speaking as well as comprehension may also become part of the admission requirements of incoming and transferee nursing students to PSU. Entrants with weaknesses in this aspect can further be

32

assisted during their stay in the University. Alternatively, those who have low scores in English in the entrance examination may be admitted in the College but these students are to be required to undergo English proficiency class like the English O which was a requirement for incoming freshmen whose English rating in the entrance exam was low. The College may also keep the evaluation record and monitor the students’ progress to make sure that once they graduate, their English proficiency is satisfactory. For Palawan State University, this study can be replicated in other colleges which graduates are to take licensure examinations to help predict their performance and make ways and means to increase their chance of passing the board examinations. For future researchers who want to pursue the same line of inquiry, it is suggested that admission score, NAT score, high school general average, Competency Appraisal performance, and review class performance including mock board examination will be included as variables to be evaluated.

33

BIBLIOGRAPHY

Books and Journals Baldago, Lily Ann R., Philippine Nursing Act of 2002, Annotated, Anvil Publishing Inc., Pasig City, © 2004, pp. 13, 24 Basilio, Faith B., et. al, Fundamental Statistics, Trinitas Publishing Incorporated, Meycauayan, Bulacan, © 2003 Beeman PB, Waterhouse JK., NCLEX-RN Performance: Predicting Success on the Computerized Examination. Department of Nursing, College of Health and Nursing Sciences, University of Delaware, Newark, DE 19716, USA. Journal on Professional Nurses. 2001 Jul-Aug;17(4):158-65.\ Calmorin, L. P. &Calmorin, M. A., Methods of Research and Thesis Writing, Rex Bookstore, Rex Printing Company, © 2007 Daley, Linda K., Bonnie L. Kirkpatrick, Susan K. Frazier, Misook L. Chung, and Debra K. Moser. "Predictors of NCLEX-RN success in a baccalaureate nursing program as a foundation for remediation." Journal of Nursing Education 42, no. 9 (2003): 390-398. Devore, Jay L., Probability and Statistics for Engineering and the Sciences, 8th Edition, Brooks/Cole 20 Channel Center Street, Boston, MA 02210, USA, 2012 Fraenkel, J. R., Wallen, N. E., How to Design and Evaluate Research in Education, 6th Edition, McGrawhill , 2007 Garcia, Enrico C. "Correlates of board examination performance of nursing graduates of Lyceum–St. Cabrini College of Allied Medicine." Lyceum of the Philippines– Laguna Research Journal 1, no. 1 (2012). George, Julia B., Nursing Theories: The Base for Professional Nursing Practice, 5th Edition, published by Pearson Education Inc., publishing as Prentice Hall, © 2002 Giddens J, Gloeckner GW., The Relationship of Critical Thinking to Performance on the NCLEX-RN. University of New Mexico, Albuquerque, NM 87131-0001, USA. [email protected], Nursing Education Journal. 2005 Feb;44(2):85-9. Haas RE, Nugent KE, Rule RA., The use of discriminant function analysis to predict student success on the NCLEX-RN. Nursing Anesthesia Program, E3-229 Jennings, Medical College of Georgia School ofNursing, Augusta, GA 30912, USA. [email protected]. Journal Nurse Educ. 2004 Oct;43(10):440-6.

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McGahee, Thayer W., L. Gramling, and T. F. Reid. "NCLEX-RN success: Are there predictors." Southern Online Journal of Nursing Research 10, no. 4 (2010): 208-221. Navarro, Remedios T., Aurelia T. Vitamog, R. J. C. Tierra, and Donna Marie J. Gonzalez. "Predictors of nursing board examination performance." JPAIR Multidisciplinary Journal 6, no. 1 (2011): 232-246. Neri, Donna Lou E. "Academic, clinical and inhouse review performances as predictors of outcomes in nursing licensure examination." Liceo Journal of Higher Education Research 6, no. 1 (2010). Ong, M., Daisy R. Palompon, and Lucia Bañico. "Predictors of Nurses’ Licensure Examination Performance of Graduates in Cebu Normal University Philippines." International Peer Reviewed Journal Volume2. pp 3 24 (2012). Stuenkel, Diane L. "At-risk students: do theory grades+ standardized examinations= success?." Nurse Educator 31.5 (2006): 207-212. Polit, Denise F., Beck, Cheryl T., Nursing Research: Generating Evidence for Nursing Practice 8th Edition, Lippincott Williams and Wilkins, © 2008 Neri, Donna Lou E, Intellective Variables as Predictors to Nursing Examination Performance, Liceo Journal of Higher Education Research, Social Science section, Unpublished Materials Lacubtan, J. C. R., & Juan, M. P., Nursing Aptitude Test And General Weighted Average Of Bachelor Of Science In Nursing Graduates Batch 2008 And 2009 At Palawan State University In Relation To Passing The Nursing Licensure Examination, Palawan State University-Puerto Princesa, 2011 CHED Memorandum CHED Memorandum 30 series of 2001 CHED Memorandum No. 9 series of 2009 Websites http://www.ok.gov/nursing/nclextf.pdfvisited 6/24/11 http://www.rn.ca.gov/pdfs/forms/brnspring2001.pdf visited 6/24/2012 http://www.state.ia.us/nursing/images/pdf/RN_NCLEX_Report1.pdf visited 6/24/11 http://www.bworldonline.com/Research/economicindicators.php?id=0377, 2011

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http://www.abbaphilippines.com/images/news/new_board_exams.gif, 2011 http://www.abs-cbnnews.com/exam-results/02/19/11/prc-29711-new-nurses, 2011 http://www.prc.gov.ph/prb/default.aspx?id=33&content=193 http://www.youtube.com/watch?v=AMqB0K5Tt6M 5/25/14 Software SPSS Statistics 17.0, release 17.0.0 Aug. 23, 2008 Microsoft Excel 2007

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APPENDICES

APPENDIX A Republic of the Philippines PALAWAN STATE UNIVERSITY Puerto Princesa City

June 20, 2012

DR. FRANCES MURIEL L. TUQUERO Director, University Extension Office This University

Madam: I am in the final phase of completing my Master of Science in Nursing degree from this University. Currently, I enrolled in the thesis writing course at the College of Nursing and Health Sciences Graduate School. In relation to this, I would like to request to be my adviser for my master’s thesis entitled “PREDICTORS OF NURSING GRADUATES’ PERFORMANCE IN LICENSURE EXAMINATION”. I fervently pray for your positive response on this matter.

Sincerely yours,

(Sgd.) HERMANITO B. CONSAD II MSN Student

Cc: Dean’s Office

39

Republic of the Philippines PALAWAN STATE UNIVERSITY Puerto Princesa City

June 20, 2012

SONIA D. YGLORIA, RN, MAN Dean, CNHS This University

Thru Channel

Madam: Greetings of prosperity and good health. I am in the final phase of my Master of Science in Nursing degree in this University. To complete and hopefully graduate by October this year I am currently enrolled in the Thesis Writing course. In connection with this, I would like to request your good office that I be allowed to have DR. FRANCES MURIEL L. TUQUERO to be my adviser for my thesis entitled “PREDICTORS OF NURSING GRADUATES’ PERFORMANCE IN LICENSURE EXAMINATION”. I fervently pray for your approval of this request.

Sincerely yours,

(Sgd) HERMANITO B. CONSAD II MSN Student

40


November 19, 2012

SONIA D. YGLORIA, RN, MAN Dean This College

Madam: The undersigned would like to request for a thesis proposal defense on November 27, 2012, Tuesday 9:00 am at the CNHS Research Office. Furthermore, the following are also requested as panel of examiners for the activity mentioned. Panel Chairman:

Dr. Lerna L. Ayco

LTS University Coordinator Faculty Member, CTE

Sonia D. Ygloria Mary Joy A. Habaradas

Dean, CNHS Research Coordinator, CNHS

Panel Members:

Hoping for your favorable action on the matter.

Respectfully yours,

(Sgd) HERMANITO B. CONSAD II Graduate Student Cc:

Dr. FM Tuquero Dr. L Ayco MJA Habaradas

41


February 20, 2013


Madam: The undersigned is now in the stage of data gathering for my thesis entitled “PREDICTORS OF NURSING GRADUATES’ PERFORMANCES IN LICENSURE EXAMINATION”. In line with this, I would like to request permission from your good office to allow me to access the files of the BS Nursing program graduates of the College from 2007 to 2010. Furthermore, I would like also to request for the list of official graduates of the same year duly approved by the Academic Council and the Board of Regents. Hoping for your favorable action on this matter.

Sincerely yours,

HERMANITO B. CONSAD II MSN Student

Noted by:

(Sgd.) FRANCES MURIEL L. TUQUERO, Ph. D. Thesis Adviser

42

Republic of the Philippines PALAWAN STATE UNVERSITY Puerto Princesa City College of Nursing and Health Sciences

November 11, 2013


Madam: In relation to my master’s thesis entitled “PREDICTORS OF NURSING GRADUATES’ PERFORMANCE IN LICENSURE EXAMINATION” I would like to request a copy of the Nursing Aptitude Test result (from 2007-2011) and the PRC Report of Ratings on the performance of our nursing graduates in the Nurse Licensure Examination from 2007 to 2011. In the event that the data from PRC is not readily available in your office, the undersigned would like to ask your assistance in requesting the same from the Professional Regulation Commission-Manila, I will shoulder the necessary expenses. The data are necessary to finish my thesis and hopefully to graduate by April 2014. I am hoping for your immediate response on the matter.

Sincerely yours,

HERMANITO B. CONSAD II MSN Student

Noted by:

(Sgd.) DR. FRANCES MURIEL L. TUQUERO Adviser

43

Republic of the Philippines PALAWAN STATE UNIVERSITY Puerto Princesa City November 11, 2013 THELMA S. CASANOVA University Registrar This University

Madam: In relation to my master’s thesis entitled “PREDICTORS OF NURSING GRADUATES’ PERFORMANCE IN LICENSURE EXAMINATION” I would like to request a copy of the grades of the nursing graduates from 2007 to 2011 in the following subjects 1. 2. 3. 4. 5. 6.

NCM 100 , NCM 101, NCM 102, NCM 103, NCM 104, NCM 105 (didactics & RLE) English 1, 2, & 3 College Algebra (Math 1B) General Chemistry Biochemistry Physics

The data are necessary to finish my thesis and hopefully graduate by April 2014. I understand that your staff is busy at the moment in the enrolment but should you allow me to access the files of the graduates, I shall be happy to do the retrieval of the records and photocopy them using a portable copier that I could use to hasten the task. Attached herewith are the names of the graduates from 2007 to 2010. Rest assured that the documents will be kept with utmost confidentiality and will be used only for the purpose mentioned. I am hoping for your immediate response on the matter.

Sincerely yours,

(Sgd.) HERMANITO B. CONSAD II MSN Student Noted by: (Sgd.) DR. FRANCES MURIEL L. TUQUERO Adviser

44

Republic of the Philippines PALAWAN STATE UNVERSITY Puerto Princesa City

November 11, 2013

DR. GRACE N. ABRINA Director, Student Affairs Office This University

Madam: In relation to my master’s thesis entitled “PREDICTORS OF NURSING GRADUATES’ PERFORMANCE IN LICENSURE EXAMINATION” I would like to request a copy of the entrance exam results of nursing graduates from 2007 to 2010. The data are necessary to finish my thesis and hopefully graduate by April 2014. Rest assured that the documents will be kept with utmost confidentiality and will be used only for the purpose mentioned. I am hoping for your immediate response on the matter.

Sincerely yours,

(Sgd.) HERMANITO B. CONSAD II MSN Student

Noted by:

(Sgd.) DR. FRANCES MURIEL L. TUQUERO Adviser

45

Attachments List of Graduates 2007 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39

Abid, Bryan Christopher Alanis, Gloria Vanessa V. Arcegono, Virgel T. Astillar. Piety Grace P. Bea, Kristine P. Bollon, DIANE Bernadette S. Cabanting, Say C. Camacho, Dolly April F. Chu. Cathy A. Daquioag, Ivan L. De Jesus, Rheenah A. Decolongon, Aljetsvl Dumayas, Ma. Zendriad .. Evangelista, Earl M. Federanga, Shery Ann L. V Flores, Maria Andrealyn M' Francisco Arnold M. Franco; Ma. Bernadette P. Brahim, Paineir B. Javarez, Dindo C. Jimenez, Genevieve M. Juanich, Grace A. Katon, Jeanne Aubrey P. Lahan, Regg Rio Allan M. Lopez, Swani Faith G.. Maceda, Mary Jane M Magallanes, Jericm. , Magbanua, Marc Ravir H. . Malacad, Cherry D. Malagday, Jeffrey 0. Mapa, Relan B. Ocbina. Maria Liza C. Olson, Marian T. Paala, Joan S. Pagaduan, Mart Oliver T. Palao, Marian May V. Rabanal, Joey Vincent P. Rebato, Johnard B. San Diego. Chris A.

40 41

46

Tomines, Maria Luia V. Ynzon, Charlene A.

List of Graduates 2008 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42

Abid, Chinnie April N. Alcantara, Angelita A. Apao,Minerva S. Arzaga, Joseph Vincent R. Arzaga, Maria Theresa V. Bacuel, John Rey S. Badenas, Angelica Joy M. Balibadlan, Karizza Lawrence D. Baradas, Irish Claire J. Bito-Onon, Lorenzo L. Cabiguen, Karen Grace L. Cabiguen, Brenn Parangue M. Canoy, Shiela May Fresnillo Casanova,Mary Liane Sebido Catain Jr, Jesus B. Cayabo, Anne Kristine Cayaon Cayao, Donabel Nugui Cervancia, Jemadette Madriian Cordestable, Sierra May Franco De Mesa, Tom Angelo Arzaga Decano, Gino Mancel Sibal Espaola, Early Rose Ladiet Feliciano, Joanne Garcia Gacita, Noemi Garcia Garcia, Anne Grace Torres Goh, Randolph Alvarado Gonzales, Bryner Kheith Iligan Gulane, Josylyn Parreisio Liao, Roulette Ustares Madduma, Cindy Pacia Mascareisjas, Ryan John Manalon Mendenilla, Ivan R. Mendoza Jr., James Albert Liao Neri, Ronald Ryan Bundac Paala, Joan Sorique Ronquillo, Leah Gabunia Roque, Jonas Ralf Miranda Salinas, Karen Ruth Estoesta San Agustin, Maree Charlotte Ubay Seracarpio, Reann Brigitte Mingua Singson, Melody Buncag Sudara, Rolex Cardijon

47 48 49 50 51 52

47

Tividad, Mypher Ternida Ustares, Anabel Mosqueda Vanilla, Jeffrey Fernando Ventura, Ray Justin Cacho Yapparcon, John Fer G Zara Jr, Rolando G.

43 44 45 46

Sumudivila, Rovee Lomigo Tan, Francia Velina D Timbal, Kristina Martinez Timones, Roville Allan Martin Beran

List of Graduates 2009 1 Atilano, Jefferson D. 2 Balingbing, Diosa F. 3 Begino, May Charles C. 4 Bollon, Denise Valerie S. 5 Castro, Maureen Joy G. 6 Dagot, Noriel S. 7 David, Jesabelle L. 8 Flor, Karen Grace T. 9 Flores, Ferlje Anne T. 10 Fresnillo, April Christy C. 11 Gener, Marlone M. 12 Gonzaga, Maricel O. 13 Gonzales, Kathleen Joy O. 14 Imao, Fatima Kauthar S. 15 Jaranilla, Jesybel Kate A. 16 Jaranilla, Marielle Gracelyn A. 17 Lampa, Hernando I. 18 Mangatora, Abdul Malic M. 19 Mawa, Genelyn D. 20 Mendoza, Kurt Noreen R. 21 Namuco,Revel Tracy Q. 22 Nastor, Myla U. 23 Navalta, Lorydia D. 24 Pajarillo, Karen R. 25 Parreño, Jovan S. 26 Roque, Jeris Hannah M. 27 Sandalan, Catherine I. 28 Tajan, Pearl Joy E. 29 Ustares, Anna Lisa G. 30 Valera, Ivan A. 31 Valerio, Francis V. 32 Villacruz, Rizza P. 33 Ybanez, Dmna Mae F.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35

48

List of Graduates 2010 Abanto, Leonie Alarios, Marixel Arguelles, Divine Grace Balocas, Geraldine Bonbon, Dan Joseph Cabiguen, Charmaine Gay Cervantes, Iii, Segundo Corbe, Melissa Cristobal, Camille Daluddung, Eleanor Dela Cruz, Airen Delos Santos, Jose Rolando Divinasflores, Julius Enriquez, April Erynko, Francis Garciano, Elson Jagmis, Lora Lou Llado, Aileen Magbanua, Conn Clarence Malabayabas, Joy Eden Manaois, Richielle Mae Mendoza, Czarina Jasmin Mendoza, Enoch Namuco, Armaine Krizel Pacaldo, Valeen Eleanore Pacho, Sherry Anne Picoy, Ma. Jonah Pinangay, Joan Punla, Rovi Rabang, Ana May Sobremisana, Ruel Tocalo, Vena Leomila Usman, Lezel Villaver, Dulce Yara, Jane

EXECUTIVE SUMMARY Title of the study:

“PREDICTORS OF NURSING GRADUATES’ PERFORMANCE IN LICENSURE EXAMINATION”

Pages:

78

Researchers:

Hermanito B. Consad II

Adviser:

FRANCES MURIEL L. TUQUERO, Ph. D.



1. What is the performance rating of nursing graduates in terms of the following a. tool subjects; and Frequency b. nursing core and subjects? percentage

2. What is the performance of Frequency nursing graduates in the and nursing board examination? percentage 3. What is the performance of graduates in the nursing Frequency board examination based and from their performance rating percentage in

Findings

Conclusions

Majority of the nursing graduates from batch 2007 to 2009 were rated Satisfactory in their performance both in the tool subjects and the nursing core subjects. The graduates are performing satisfactorily in their academics. Ninety percent of the graduates passed the Nurse Licensure Examination Cross tabulation table shows that better performance in tool and nursing core subjects has bigger the chance of 49

Nursing graduates of Palawan State University College of Nursing and Health Sciences are performing satisfactorily in their tool and nursing core subjects. 90% of PSU-CNHS nursing graduates passed the NLE. Cross tabulation shows that better performance rating in the tool and nursing core subjects increases the chance of passing the NLE.

Recommendations The College of Nursing and Health Sciences of Palawan State University should strengthen their instructions for the tool and nursing core subjects. Academic rating of the students should be objectively done.



a. tool subjects; and b. nursing core subjects? c. exam? 4. What is the relationship Standard between the performance of Multiple the graduates in terms of the Regression following: a. tool subjects and nursing board examination; b. nursing core subjects and nursing board examination?

Findings passing the examination.

Conclusions

licensure

Statistically speaking, higher grades in the tool and nursing core subjects leads to higher rating in the Nurse Licensure Examination.

50

The findings of the study strongly suggest that there is a significant positive correlation of the tool and nursing core subjects to the rating of the graduates in the Nurse Licensure Examination. By statistical analysis, higher grades in tool and nursing core subjects lead to higher rating in the Nurse Licensure Examination. On the other hand, lower rating in the tool and nursing core subjects lead to lower rating in the Nurse Licensure Examination. This means that the NLE rating of the graduates can be explained by the relationship of the tool and nursing core subjects. The result of the study is in congruence of the previous study conducted by Stuenkel (2006), Daley, Kirkpatrick, Frazier, Chung and Moser (1999, 2000), Haas, Nugent, and Rule (2004), Beeman and Waterhouse (2001), the Oklahoma State Board of Nursing, and California Board of Nursing that better grades in nursing subjects have significant role in passing the NCLEX licensure examination. Furthermore, the results of

Recommendations



Findings

Conclusions this study affirms the study of Neri (2008) that students with better grades in nursing subjects have higher chance of passing the Philippine Nursing Licensure Examination. Further noted that the results of this study relates the study of Beeman and Waterhouse (2001) that grades are the common predictors in the licensure examination, that higher grades correlate with passing the licensure examination.

51

Recommendations

APPENDIX C Multiple Regression Computation Results Tool Subjects REGRESSION /MISSING PAIRWISE /STATISTICS COEFF OUTS CI(95) R ANOVA /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT NLERating /METHOD=ENTER Math EngAve Biosci13 Biosci14 /SCATTERPLOT=(*ZRESID ,*ZPRED) /RESIDUALS NORMPROB(ZRESID).

Regression Notes Output Created Comments

25-AUG-2015 05:23:26

Data

Input

Active Dataset Filter Weight Split File N of Rows in Working Data File Definition of Missing

Missing Handling

Value Cases Used

52

E:\ \Important Files\Research Matters\Master's Thesis koLatest\NAT-NLE performance\Stat\New folder\Latest\combine 07-09 data latest.sav DataSet1 77 User-defined missing values are treated as missing. Correlation coefficients for each pair of variables are based on all the cases with valid data for that pair. Regression statistics are based on these correlations.

REGRESSION /MISSING PAIRWISE /STATISTICS COEFF OUTS CI(95) R ANOVA /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT NLERating /METHOD=ENTER Math EngAve Biosci13 Biosci14 /SCATTERPLOT=(*ZRESID ,*ZPRED) /RESIDUALS NORMPROB(ZRESID). 00:00:00.80 00:00:00.91 2948 bytes

Syntax

Processor Time Elapsed Time Memory Required Additional Memory Required for Residual 544 bytes Plots

Resources

[DataSet1] E:\ \Important Files\Research Matters\Master's Thesis ko-Latest\NAT-NLE performance\Stat\New folder\Latest\combine 07-09 data latest.sav

Model

Variables Entered/Removeda Variables Variables Method Entered Removed

Biosci14, Math, 1 Biosci13, EngAveb a. Dependent Variable: NLERating b. All requested variables entered.

53

. Enter

Model Summaryb Model R R Square Adjusted R Std. Error of Square the Estimate a 1 .523 .274 .233 3.04553 a. Predictors: (Constant), Biosci14, Math, Biosci13, EngAve b. Dependent Variable: NLERating

Model

Sum of Squares 251.460

Regression

ANOVAa df Mean Square 4

62.865

F

Sig. .000b

6.778

1

Residual 667.820 72 9.275 Total 919.280 76 a. Dependent Variable: NLERating b. Predictors: (Constant), Biosci14, Math, Biosci13, EngAve

Model

1

(Constant) Math

Unstandardized Coefficients B Std. Error 96.599 3.556 -.994 .737

EngAve Biosci13 Biosci14

-5.062 .241 -2.939

1.543 1.009 1.119

Coefficientsa Standardized Coefficients Beta

t

Sig.

27.167 -.149 -1.350

.000 .181

-.361 -3.280 .026 .239 -.282 -2.626

.002 .812 .011

95.0% Confidence Interval for B Lower Upper Bound Bound 89.511 103.687 -2.463 .474 -8.139 -1.770 -5.171

-1.986 2.252 -.708

a. Dependent Variable: NLERating

Predicted Value Residual Std. Predicted Value Std. Residual

Residuals Statisticsa Minimum Maximum Mean Std. Deviation 74.6807 82.5440 79.0000 1.81898 -9.74758 5.91930 .00000 2.96430

N 77 77

-2.375

1.948

.000

1.000

77

-3.201

1.944

.000

.973

77

a. Dependent Variable: NLERating

54

Charts

55

Multiple Regression Computation Results Nursing Core Subjects REGRESSION /MISSING PAIRWISE /STATISTICS COEFF OUTS CI(95) R ANOVA /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT NLERating /METHOD=ENTER PHC11 PHC12 NCM100 NCM101 NCM102 NCM103 NCM104 NCM105 /SCATTERPLOT=(*ZRESID ,*ZPRED) /RESIDUALS NORMPROB(ZRESID).

Regression Notes Output Created Comments

25-AUG-2015 05:31:36

Data

E:\ \Important Files\Research Matters\Master's Thesis ko-Latest\NAT-NLE performance\Stat\New folder\Latest\combine 07-09 data latest.sav DataSet1

Active Dataset Filter Input Weight Split File N of Rows in Working Data 77 File Definition of User-defined missing values are treated as missing. Missing Missing Value Correlation coefficients for each pair of variables are Handling Cases Used based on all the cases with valid data for that pair. Regression statistics are based on these correlations.

56

Syntax

Processor Time

Resources

REGRESSION /MISSING PAIRWISE /STATISTICS COEFF OUTS CI(95) R ANOVA /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT NLERating /METHOD=ENTER PHC11 PHC12 NCM100 NCM101 NCM102 NCM103 NCM104 NCM105 /SCATTERPLOT=(*ZRESID ,*ZPRED) /RESIDUALS NORMPROB(ZRESID). 00:00:00.83

Elapsed Time Memory 4996 bytes Required Additional Memory 512 bytes Required for Residual Plots

00:00:00.81

[DataSet1] E:\ \Important Files\Research Matters\Master's Thesis ko-Latest\NAT-NLE performance\Stat\New folder\Latest\combine 07-09 data latest.sav

Model

Variables Entered/Removeda Variables Variables Method Entered Removed

NCM105, NCM100, NCM103, PHC12, 1 NCM101, NCM104, PHC11, NCM102b a. Dependent Variable: NLERating b. All requested variables entered.

57

. Enter

Model Summaryb Model R R Square Adjusted R Std. Error of Square the Estimate a 1 .549 .301 .219 3.07317 a. Predictors: (Constant), NCM105, NCM100, NCM103, PHC12, NCM101, NCM104, PHC11, NCM102 b. Dependent Variable: NLERating

Model

Sum of Squares

ANOVAa df Mean Square

F

Sig.

Regression 277.061 8 34.633 3.667 .001b 1 Residual 642.219 68 9.444 Total 919.280 76 a. Dependent Variable: NLERating b. Predictors: (Constant), NCM105, NCM100, NCM103, PHC12, NCM101, NCM104, PHC11, NCM102

Model

1

Unstandardized Coefficients B Std. Error

(Constant) 103.469 PHC11 1.051 PHC12 -3.935 NCM100 -4.815

7.202 1.861 1.907 2.001

NCM101 NCM102

2.464 2.459

.508 .826

NCM103 .848 2.594 NCM104 -2.888 3.358 NCM105 -3.954 2.358 a. Dependent Variable: NLERating

Coefficientsa Standardized Coefficients Beta

t

14.367 .076 .565 -.265 -2.063 -.282 -2.406

Sig.

95.0% Confidence Interval for B Lower Upper Bound Bound

.000 .574 .043 .019

89.098 -2.663 -7.740 -8.808

117.840 4.764 -.129 -.822

.206 .336

.837 .738

-4.409 -4.080

5.424 5.732

.038 .327 -.111 -.860 -.231 -1.677

.745 .393 .098

-4.328 -9.589 -8.660

6.024 3.814 .752

.025 .048

58

Residuals Statisticsa Minimum Maximum Mean Std. Deviation 73.2411 83.6173 79.0000 1.90933 -9.65377 6.15895 .00000 2.90693

Predicted Value Residual Std. Predicted -3.016 Value Std. Residual -3.141 a. Dependent Variable: NLERating Charts

N 77 77

2.418

.000

1.000

77

2.004

.000

.946

77

59

Appendix D RAW DATA Tool Subjects Responde nt 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38

Math 11 1.25 2.75 1.25 1.25 2.50 1.25 2.75 1.75 1.75 2.50 1.75 2.75 2.25 2.00 1.50 2.25 1.50 2.75 2.50 2.50 2.25 2.25 3.00 1.50 2.75 2.50 3.00 2.25 2.50 2.25 3.00 2.25 2.25 1.50 2.50 2.00 2.00 2.00

Eng 11 1.75 2.00 1.50 1.50 1.75 1.75 1.75 1.75 1.75 2.00 1.75 1.00 2.25 2.00 1.50 1.75 2.00 1.75 2.00 1.75 1.75 2.25 2.00 1.75 2.00 1.50 1.50 1.50 1.75 1.50 2.00 1.75 2.25 1.50 1.75 1.50 1.50 1.50

Eng 12 1.50 1.75 1.75 2.25 1.75 1.75 1.75 1.75 2.25 2.00 1.75 1.25 2.00 2.00 1.75 1.75 2.25 1.75 1.75 1.75 1.50 2.00 2.50 1.75 2.00 2.25 1.75 1.50 2.25 2.00 2.50 2.00 3.00 2.25 1.75 1.75 1.75 2.25

Eng 3 2.00 1.75 1.75 2.00 1.75 1.75 1.75 1.75 1.75 1.75 1.75 1.50 2.25 1.75 2.00 1.75 2.25 2.00 2.00 2.00 1.75 2.25 2.75 1.50 2.00 2.25 2.00 2.00 1.75 2.00 2.00 1.75 2.25 2.00 2.00 2.00 2.00 2.00

Bio Sci 13 2.00 1.50 1.75 1.75 2.25 2.00 2.25 1.75 1.50 2.25 3.00 2.00 1.75 2.00 1.75 2.00 2.00 2.25 2.25 2.25 2.00 1.75 2.25 2.00 2.25 2.50 2.50 2.25 2.25 2.25 1.75 2.75 2.50 2.50 2.50 2.00 2.50 2.50

60

Bio Sci 14/L 2.50 1.50 2.25 2.50 2.00 2.25 2.00 2.00 1.50 2.25 2.50 2.50 2.00 2.50 2.25 2.00 2.75 2.50 2.25 2.00 2.50 1.75 1.75 2.25 2.25 2.25 1.50 1.75 2.00 2.00 1.75 2.25 2.00 1.75 1.50 1.75 2.00 1.50

GW A 1.88 1.82 1.74 1.89 2.02 1.83 2.06 1.80 1.71 2.14 2.19 1.88 2.05 2.06 1.81 1.93 2.14 2.19 2.14 2.06 1.99 2.00 2.33 1.83 2.21 2.24 2.06 1.90 2.10 2.02 2.11 2.19 2.37 1.96 2.02 1.85 2.01 1.99

Verbal Interpretation Highly Satisfactory Highly Satisfactory Outstanding Highly Satisfactory Satisfactory Highly Satisfactory Satisfactory Highly Satisfactory Outstanding Satisfactory Satisfactory Highly Satisfactory Satisfactory Satisfactory Highly Satisfactory Highly Satisfactory Satisfactory Satisfactory Satisfactory Satisfactory Highly Satisfactory Satisfactory Average Highly Satisfactory Satisfactory Satisfactory Satisfactory Highly Satisfactory Satisfactory Satisfactory Satisfactory Satisfactory Average Highly Satisfactory Satisfactory Highly Satisfactory Satisfactory Highly Satisfactory

Responde nt 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77

Math 11 2.25 3.00 3.00 2.75 3.00 2.50 2.75 2.75 2.75 2.50 3.00 2.75 2.50 2.25 2.25 2.75 1.75 2.50 1.75 3.00 2.75 1.50 3.00 2.00 2.25 1.75 2.75 2.25 1.25 1.75 1.75 3.00 2.00 2.75 2.50 2.75 2.50 3.00 2.25

Eng 11 1.50 2.00 1.50 1.75 1.25 1.75 1.50 1.75 1.75 1.75 2.25 1.75 1.50 1.75 1.50 2.00 1.50 1.50 2.00 1.75 1.75 1.75 1.75 1.75 2.25 1.50 2.00 2.00 2.00 1.75 1.50 2.50 2.00 2.00 2.00 2.50 2.00 2.25 2.00

Eng 12 1.50 2.75 1.75 2.00 1.50 2.25 1.75 2.75 1.75 2.25 2.75 2.00 1.75 2.25 1.75 2.50 2.00 1.75 1.75 1.25 2.00 1.50 2.50 1.75 2.25 1.75 2.25 2.50 2.00 2.00 1.50 2.50 1.75 2.00 2.25 1.50 2.25 2.75 2.25

Eng 3 1.75 2.25 2.25 2.00 1.75 2.00 2.25 2.25 2.00 2.00 2.25 2.25 1.75 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.25 2.25 2.50 2.25 2.25 2.75 2.25 2.50 2.00 1.50 2.50 2.00 2.25 2.25 2.00 2.75 2.50 1.75

Bio Sci 13 2.50 2.75 2.25 2.75 1.75 2.25 2.50 3.00 2.75 2.50 2.75 2.75 2.00 3.00 2.25 2.50 1.75 2.25 2.00 2.25 2.25 2.25 2.75 2.50 3.00 2.25 2.75 2.00 3.00 2.50 1.75 2.00 1.75 2.25 2.25 2.50 2.75 2.00 2.75

61

Bio Sci 14/L 1.75 2.25 2.50 2.00 1.50 1.50 2.00 2.25 2.00 1.75 2.50 1.75 1.75 2.25 1.75 2.00 1.75 1.75 2.50 2.00 1.75 1.50 2.50 2.25 2.25 1.75 2.25 2.25 2.75 2.50 1.75 2.25 2.00 1.75 2.50 2.50 2.00 2.00 2.00

GW A 1.93 2.51 2.23 2.25 1.77 2.04 2.15 2.50 2.21 2.14 2.60 2.24 1.88 2.32 1.94 2.30 1.79 1.98 2.02 2.06 2.08 1.82 2.49 2.17 2.43 1.90 2.48 2.19 2.35 2.14 1.64 2.40 1.90 2.15 2.30 2.32 2.39 2.36 2.21

Verbal Interpretation Highly Satisfactory Average Satisfactory Average Highly Satisfactory Satisfactory Satisfactory Average Satisfactory Satisfactory Average Satisfactory Highly Satisfactory Average Highly Satisfactory Average Highly Satisfactory Highly Satisfactory Satisfactory Satisfactory Satisfactory Highly Satisfactory Average Satisfactory Average Highly Satisfactory Average Satisfactory Average Satisfactory Outstanding Average Highly Satisfactory Satisfactory Average Average Average Average Satisfactory

Respondent

PHC 11

PHC 11

PHC 12 Did

PHC 12

NCM 100

NCM 100

NCM 101

NCM 101

NCM 102

NCM 102

NCM 103

NCM 104

NCM 104

NCM 105

NCM 105

GWA

Interpretation

Nursing Core Subjects

1

2.25

1.75

1.75

1.75

1.75

1.75

2.50

2.25

2.25

2.25

2.25

2.00

2.00

2.00

2.00

2.09

S

2

1.75

1.75

1.75

1.75

2.00

2.00

2.25

2.25

2.25

2.25

2.00

2.25

2.00

2.00

2.00

2.06

S

3

2.00

2.00

1.75

1.75

1.75

1.75

1.50

2.00

2.00

1.75

2.00

1.75

2.00

1.25

2.00

1.79

HS

2.23

S

4

2.25

2.25

2.00

2.00

2.00

2.00

2.50

2.25

2.75

2.00

2.25

2.25

2.25

2.25

2.00

5

2.50

2.50

2.25

2.25

2.00

2.00

1.75

2.00

2.50

2.25

2.25

2.25

2.00

2.00

2.00

2.12

S

6

2.00

2.00

2.00

2.00

1.75

1.75

2.50

2.00

2.50

2.00

2.25

2.25

2.00

2.25

1.75

2.10

S

7

2.25

2.25

2.00

2.00

2.00

2.00

2.00

2.00

2.50

2.00

2.75

2.25

2.00

2.25

1.75

2.11

S

2.06

S

8

2.00

2.00

1.75

1.75

1.75

1.75

2.25

2.25

2.25

2.00

2.25

2.00

2.25

2.00

2.00

9

1.75

1.75

1.50

1.50

2.00

2.00

2.00

2.00

2.25

2.25

1.75

2.00

2.00

2.00

1.75

1.94

HS

10

2.50

2.50

1.75

1.75

2.00

2.00

2.50

2.25

2.50

2.25

2.00

2.00

2.25

2.25

2.00

2.20

S

2.00

1.75

2.13

S

2.11

S

11

2.25

2.25

2.00

2.00

2.00

2.00

2.50

2.25

2.75

2.00

2.25

2.00

2.00

12

2.25

2.25

1.75

1.75

1.75

1.75

2.25

2.25

2.25

2.25

2.25

2.00

2.00

2.25

2.00

13

2.25

2.25

2.00

2.00

2.25

2.25

1.75

2.00

2.25

2.25

2.25

2.25

2.25

2.25

2.25

2.14

S

14

2.25

2.25

2.00

2.00

2.00

2.00

2.50

2.25

2.25

2.00

2.25

2.00

2.25

2.25

2.00

2.15

S

2.01

S

15

2.00

2.00

1.75

1.75

2.00

2.00

2.25

2.25

2.25

1.75

2.00

2.00

2.00

2.00

2.00

16

2.25

2.25

2.00

2.00

2.00

2.00

2.50

2.00

2.25

2.00

2.00

2.00

2.00

2.25

3.00

2.19

S

17

2.25

2.25

2.00

2.00

2.00

2.00

2.50

2.25

2.50

2.00

2.25

2.25

2.00

2.00

2.00

2.15

S

18

2.50

2.50

2.00

2.00

2.00

2.00

2.25

2.25

2.25

2.00

2.25

2.00

2.25

2.00

2.25

2.15

S

2.21

S A

19

2.50

2.50

2.25

2.25

2.25

2.25

2.25

2.00

2.50

2.25

2.00

2.25

2.25

2.25

2.00

20

2.75

2.75

2.25

2.25

2.25

2.25

2.00

2.25

2.75

2.50

2.25

2.50

2.50

2.25

2.25

2.36

21

2.25

2.25

2.00

2.00

2.00

2.00

2.50

2.25

2.25

2.25

2.00

2.25

2.00

2.00

1.75

2.12

S

1.88

HS

22

2.00

2.00

1.75

1.75

1.75

1.75

1.75

1.75

2.00

2.00

2.00

2.00

2.00

1.75

2.00

23

2.00

2.00

2.25

2.25

2.25

2.25

2.50

2.50

2.75

2.75

2.25

2.50

2.50

2.50

3.00

2.49

A

24

2.00

2.00

1.50

1.50

1.75

1.75

1.50

2.00

1.75

2.00

2.25

1.75

2.00

1.75

1.75

1.81

HS

25

2.25

2.25

2.25

2.25

2.50

2.50

2.00

2.25

2.50

2.25

2.25

2.25

2.00

2.25

2.00

2.18

S

1.98

HS

26

2.00

1.75

1.75

1.50

2.50

2.50

2.25

2.00

2.50

1.75

2.00

2.50

1.75

2.00

1.50

27

2.25

1.75

1.75

1.75

2.25

2.25

2.00

2.00

2.25

2.00

2.25

2.50

2.00

2.00

2.00

2.05

S

28

2.00

1.75

1.75

2.00

2.00

2.00

2.25

2.00

2.75

2.00

2.25

2.00

2.50

2.00

2.00

2.11

S

29

2.25

1.75

1.75

1.75

2.25

2.25

2.25

2.00

2.50

2.00

2.25

2.00

2.00

2.00

2.00

2.05

S

2.07

S

30

2.00

1.75

1.75

1.50

2.25

2.25

2.25

2.00

2.75

2.00

2.00

2.25

2.00

2.25

1.75

31

2.00

2.00

2.00

1.75

2.50

2.50

2.25

2.25

3.00

2.00

2.25

2.00

2.00

2.25

1.75

2.14

S

32

2.00

1.75

1.50

1.50

2.25

2.25

2.25

2.00

2.75

2.00

2.25

2.25

2.00

2.00

2.00

2.08

S

2.16

S

33

2.25

2.00

2.00

2.00

2.25

2.25

2.50

2.00

2.50

2.00

2.00

2.50

2.00

2.00

2.25

34

2.00

1.75

1.75

1.75

2.25

2.25

2.25

1.75

2.25

2.00

2.25

2.25

2.00

2.00

1.75

1.99

HS

35

2.00

2.00

1.75

1.50

2.00

2.00

2.50

2.00

2.50

2.00

2.00

2.50

2.00

2.00

1.75

2.08

S

36

1.75

1.50

1.50

1.50

2.00

2.00

2.25

2.00

2.50

2.00

2.00

2.00

2.00

1.75

1.75

1.94

HS

2.10

S

1.87

HS

37

2.00

1.50

1.75

1.50

2.25

2.25

2.25

2.25

2.75

2.00

2.25

2.50

2.00

2.00

1.75

38

2.25

1.75

1.75

1.75

1.75

1.75

2.00

1.75

2.00

1.75

1.75

2.25

2.00

1.75

1.75

62

Respondent

PHC 11

PHC 11

PHC 12 Did

PHC 12

NCM 100

NCM 100

NCM 101

NCM 101

NCM 102

NCM 102

NCM 103

NCM 104

NCM 104

NCM 105

NCM 105

GWA

Interpretation

39

2.25

1.75

2.00

1.50

2.00

2.00

2.25

2.00

2.25

3.00

2.25

2.50

2.00

2.00

1.75

2.15

S

40

2.25

1.75

2.00

1.75

2.25

2.25

2.25

2.00

2.50

3.00

2.00

2.50

2.00

2.25

2.00

2.22

S

41

1.75

1.75

1.75

1.50

2.00

2.00

2.25

2.00

2.50

2.00

2.00

2.50

2.00

3.00

2.00

2.15

S

42

1.75

1.50

3.00

1.75

2.25

2.25

2.50

2.00

2.75

2.00

2.25

2.00

2.00

2.00

1.75

2.09

S

1.79

HS

43

1.50

1.50

1.25

1.25

1.75

1.75

2.00

2.00

2.00

1.75

2.00

1.75

2.00

1.75

1.75

44

2.25

1.50

1.50

1.50

2.00

2.00

2.00

1.75

2.00

1.75

2.00

2.25

2.00

1.75

1.75

1.87

HS

45

2.00

1.75

1.75

1.25

2.00

2.00

2.25

2.00

2.75

2.00

2.00

2.00

2.00

2.00

1.75

2.01

S

2.18

S

46

2.25

2.00

2.00

2.00

2.50

2.50

2.50

2.00

2.75

2.00

2.25

2.25

2.25

2.25

1.75

47

2.50

2.00

2.00

2.00

2.00

2.00

2.25

2.00

3.00

2.00

2.25

2.00

2.00

2.25

2.00

2.16

S

48

2.25

2.00

2.00

1.75

2.50

2.50

2.50

2.00

2.50

2.00

2.25

2.50

2.00

2.00

1.75

2.13

S

49

2.25

1.75

1.75

2.00

2.25

2.25

2.25

2.00

2.75

2.00

2.25

2.25

2.00

2.25

1.75

2.11

S S

50

2.25

1.75

1.75

1.75

2.25

2.25

2.00

2.00

2.25

1.75

2.25

2.50

2.00

2.00

1.75

2.01

51

1.75

1.75

1.75

1.50

2.00

2.00

2.25

1.75

2.25

1.75

2.00

2.25

2.00

2.00

1.75

1.93

HS

52

2.50

2.00

1.75

1.75

2.25

2.25

2.50

2.00

2.75

2.00

2.25

2.50

2.00

2.50

1.75

2.20

S

2.25

1.75

2.05

S

2.18

S

53

2.00

1.75

1.75

1.75

2.25

2.25

2.25

1.75

2.50

2.00

2.00

2.50

2.00

54

2.25

1.75

2.00

1.75

2.25

2.25

2.25

3.00

2.50

2.00

2.25

2.50

2.00

2.00

1.75

55

1.25

1.25

1.50

1.25

2.00

2.00

2.00

1.75

2.00

1.75

2.00

1.75

1.75

1.75

1.75

1.73

O

56

1.75

1.50

1.75

1.25

2.00

2.00

2.00

1.75

2.25

2.00

2.00

1.75

2.00

1.75

1.75

1.85

HS

2.10

S

57

2.25

2.25

2.00

2.00

2.25

2.50

2.25

2.00

2.50

2.00

2.00

2.25

2.00

2.00

2.00

58

2.25

1.75

1.75

1.50

2.25

2.25

2.00

2.00

2.25

1.75

2.00

2.50

2.00

2.00

1.50

1.96

HS

59

1.75

1.75

1.75

2.00

2.00

2.00

2.00

1.75

2.50

1.75

2.00

2.00

2.00

1.75

2.00

1.92

HS

60

2.00

1.75

1.75

1.75

2.00

2.00

2.25

2.00

2.50

1.75

2.00

2.00

2.00

2.00

1.75

1.98

HS

2.17

HS

61

2.25

1.75

1.75

1.75

2.25

2.25

2.25

2.25

2.00

2.75

2.25

2.50

2.00

2.25

2.00

62

2.00

1.75

1.75

1.75

2.00

2.00

2.00

1.75

2.50

2.00

2.00

2.25

1.75

2.00

1.50

1.93

HS

63

1.75

1.50

1.75

2.00

2.25

2.25

2.25

1.75

2.50

1.75

2.00

2.00

2.00

2.00

1.75

1.94

HS

2.03

S

64

2.00

1.75

1.75

1.75

2.25

2.25

2.25

2.00

2.50

1.75

2.00

2.50

2.00

2.00

1.75

65

2.00

1.75

1.75

1.50

2.50

1.50

2.25

2.00

2.25

2.00

2.00

2.25

2.25

1.75

2.00

2.02

S

66

2.00

2.00

2.50

1.75

2.25

1.75

2.00

2.25

2.00

2.00

2.00

2.25

2.00

2.25

1.75

2.04

S

67

2.75

2.00

2.50

1.50

2.25

1.75

2.25

2.25

2.25

2.25

2.00

2.25

2.25

2.50

2.25

2.23

S

2.01

S

68

2.00

1.75

2.25

1.50

2.00

1.75

2.00

2.00

2.25

1.75

2.00

2.25

2.25

2.00

2.00

69

1.75

1.50

1.75

1.50

2.00

1.50

1.75

2.00

1.75

2.00

2.00

1.75

2.25

1.25

1.75

1.77

HS

70

1.75

2.00

2.25

1.75

2.25

1.75

2.25

2.00

2.25

2.25

2.00

2.25

2.25

2.25

2.00

2.11

S

71

2.00

1.25

2.00

1.50

2.00

1.75

2.25

2.00

2.00

2.25

2.00

2.25

2.25

1.75

1.75

1.98

HS

2.06

S HS

72

2.00

2.00

2.00

1.75

2.25

1.50

2.25

2.25

2.00

2.25

2.00

2.25

2.00

2.00

2.00

73

2.00

1.75

2.00

1.75

2.00

1.75

1.75

2.25

1.50

2.00

2.00

2.00

2.25

1.75

1.75

1.89

74

2.25

2.00

2.00

1.75

2.50

2.50

2.25

2.00

2.25

2.00

2.00

2.00

2.25

2.00

2.00

2.07

S

1.97

HS

75

2.00

1.75

2.25

1.75

2.50

1.75

2.25

2.00

2.00

2.00

2.00

2.00

2.25

1.75

1.75

76

2.25

1.75

2.75

2.00

2.00

1.50

2.25

2.25

2.25

1.75

2.00

2.25

2.25

2.00

1.75

2.07

S

77

2.00

2.00

2.00

2.25

2.25

1.75

2.25

2.25

2.25

2.25

2.00

2.00

2.25

2.00

2.00

2.10

S

63

Respondent

Sub 1

Sub 2

Sub 3

Sub 4

Sub 5

Ave

Remarks

Nursing Board Rating Per Subject

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

81 81 86 83 81 81 82 79 79 81 83 83 78 88 83 82 79 85 65 75 88 80 77 83 75 82 86 83 83 82 82 84 80 88 88 83

81 85 83 69 78 78 76 77 74 76 81 83 77 81 78 79 78 81 82 78 81 78 80 85 77 80 77 86 77 80 77 75 77 84 80 83

78 81 79 73 77 78 76 79 81 78 79 76 75 79 79 77 77 77 81 65 77 76 79 80 75 78 78 78 81 80 69 77 81 78 78 82

80 86 84 78 75 78 72 84 79 80 82 84 76 79 80 78 82 89 81 72 78 83 80 82 66 75 77 80 75 79 63 75 77 83 84 72

83 85 83 72 77 82 79 83 82 85 83 82 76 81 79 76 79 86 76 74 83 87 81 82 77 82 80 82 76 80 74 78 85 89 83 81

80.6 83.6 83 75 77.6 79.4 77 80 79 80 81.6 81.6 76.4 80.8 79.8 78.4 79 83.6 77 72.8 81.4 80.8 79.4 82.4 74 79.4 79.6 81.8 78.4 80.2 73 77 80 84.4 82.6 80.2

p p p p p p p p p p p p p p p p p p p f p p p p f p p p p p f p p p p p

64

Respondent

Sub 1

Sub 2

Sub 3

Sub 4

Sub 5

Ave

Remarks

37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74

79 85 86 85 80 80 88 86 83 80 78 83 82 86 86 76 82 83 85 80 86 85 86 83 82 85 78 86 76 76 76 80 84 82 81 79 82 81

83 85 87 74 78 78 86 86 82 77 81 82 83 85 85 72 81 80 83 80 81 82 85 80 78 88 78 81 77 77 77 77 86 63 82 69 81 77

76 80 83 78 69 79 80 79 78 73 78 80 79 80 79 76 80 80 82 79 79 76 81 79 76 80 77 78 74 78 71 80 82 76 72 81 79 77

71 84 78 80 68 71 81 84 76 64 76 76 78 74 80 83 75 79 77 83 78 76 76 69 79 81 75 82 66 56 77 68 78 58 69 75 78 56

77 82 86 78 80 80 83 89 83 81 83 78 81 85 85 76 76 79 86 79 82 81 85 85 80 83 84 79 59 77 77 77 80 68 75 74 82 76

77.2 83.2 84 79 75 77.6 83.6 84.8 80.4 75 79.2 79.8 80.6 82 83 68.6 78.8 80.2 82.6 80.2 81.2 80 82.6 79.2 79 82.6 78.4 81.2 70.4 72.8 75.6 76.4 82 69.4 75.8 75.6 80.4 73.4

p p p p p p p p p p p p p p p f p p p p p p p p p p p p F F P P P F P P P F

65

Respondent

Sub 1

Sub 2

Sub 3

Sub 4

Sub 5

Ave

Remarks

75 76 77

79 76 79

77 76 79

76 77 78

74 77 79

74 78 78

76 76.8 78.6

P P P

66

CURRICULUM VITAE

CURRICULUM VITAE Name: Birthday: Civil Status: Address: Email address: Cell number:

HERMANITO B. CONSAD II December 02, 1979 Married Tiniguiban, Puerto Princesa City [email protected] 09192977736

License/s: Eligibility:

Registered Nurse (2008) Civil Service Professional (2006)

Occupation: Employer:

Clinical Instructor Palawan State University College of Nursing and Health Sciences

Post-Graduate:

Palawan State University-Puerto Princesa Master of Science in Nursing 2015

Tertiary:

Palawan State University-Puerto Princesa Bachelor of Science in Nursing April 2007

Secondary:

Saint Mary Academy Guindulman, Bohol March 1997

Elementary:

Candijay Central Elementary School Candijay, Bohol March 1993

68