CHAPTER 3 CHAPTER 3
METHODS AND PROCEDURES METHODS AND PROCEDURES
This chapter briefly presents the different methods and procedures used by the This chapter briefly presents the different methods and procedures used by the resea
researcher in doing his investircher in doing his investigatigation. on. It consisIt consists of the research design, the reseats of the research design, the researchrch loc
localeale, , and the subjeand the subjectscts. . It also incluIt also includes the instrdes the instrumeuments used in nts used in the collthe collectection andion and gathering of data, as well as the statistical tools used in processing and analyzing the data. gathering of data, as well as the statistical tools used in processing and analyzing the data.
Research Method Research Method
This study uti
This study utilized the descrilized the descriptive correptive correlatilational design. onal design. SancheSanchez (1998) statedz (1998) stated that descriptive research includes all studies that purport to present facts concerning the that descriptive research includes all studies that purport to present facts concerning the nature and status of anything – a group of persons, a number of objects, a set of nature and status of anything – a group of persons, a number of objects, a set of conditions, a class of events, a system of thought or any other kind of phenomena which conditions, a class of events, a system of thought or any other kind of phenomena which one may wish to study
one may wish to study. . In this studIn this study, the nature and staty, the nature and status of the Medical Technus of the Medical Technologyology graduates were determined.
graduates were determined.
The study also employed a correlational design in order to determine the extent to The study also employed a correlational design in order to determine the extent to which the different variables are related to each other in the population of interest. which the different variables are related to each other in the population of interest. Through this method, the researcher was able to ascertain how much variation is caused Through this method, the researcher was able to ascertain how much variation is caused by each of
by each of the indethe independpendent varient variablables to es to the depenthe dependendent t varvariabiable. le. The magniThe magnitudtude e andand direction of the relationship was determined and was used for further computations to direction of the relationship was determined and was used for further computations to predict the value of the dependent variable.
predict the value of the dependent variable. Th
The e imimpapact ct of of ththe e acacadadememicic, , clclininicical al anand d sesemiminanar r raratitingngs, s, as as inindepdepenendendentt variables, on the dependent variable, board examination performance of the Medical variables, on the dependent variable, board examination performance of the Medical Technology graduates, was measured and
Subjects and Locale of the Study Subjects and Locale of the Study
The subjects of the study were the medical technology graduates of Angeles The subjects of the study were the medical technology graduates of Angeles University Foundation who graduated from 1995 – 2000. Each of the subjects should University Foundation who graduated from 1995 – 2000. Each of the subjects should have taken the licensure examination on the same year as their graduation, that is, they have taken the licensure examination on the same year as their graduation, that is, they should have graduated March and have taken the board examination on September of the should have graduated March and have taken the board examination on September of the year they gradua
year they graduated regardlted regardless of whether the former passeess of whether the former passed or d or not. not. All graduatAll graduates whoes who have re-enrolled a failed subject from a school other than Angeles University Foundation have re-enrolled a failed subject from a school other than Angeles University Foundation were disqualified. There were a total of one hundred sixty nine (169) medical technology were disqualified. There were a total of one hundred sixty nine (169) medical technology graduates who were considered in the study.
graduates who were considered in the study.
The study was conducted at Angeles University Foundation particularly at the The study was conducted at Angeles University Foundation particularly at the Dean’s Office of College of Allied Medical Professions, the Office of the University Dean’s Office of College of Allied Medical Professions, the Office of the University Reg
Regististrar rar and and at at the the RecRecordords s SecSectition on of of the the ProProfesfessiosional nal ReguRegulatlation ion ComCommismissiosion,n, Morayta, Manila.
Morayta, Manila.
The College of Allied Medical Professions opened its doors to the first batch of The College of Allied Medical Professions opened its doors to the first batch of students for both Medical Technology and Physical Therapy on June 1990 and has since students for both Medical Technology and Physical Therapy on June 1990 and has since been in the pursuit of
been in the pursuit of academic excellence. academic excellence. The academic programs cited were given The academic programs cited were given thethe stamp of approval by the Professional Regulation Commission and were later granted stamp of approval by the Professional Regulation Commission and were later granted government recognition on June 15, 1992 and August 25, 1993 respectively.
government recognition on June 15, 1992 and August 25, 1993 respectively. At
At prpresesent ent ththe e twtwo o coucoursrses es arare e rerecogcogninized zed by by ththe e PrProfofesessisiononal al ReRegugulalatitionon Commission as the college ranked 3
Commission as the college ranked 3rdrdamong 68 schools offering Medical Technology 8among 68 schools offering Medical Technology 8thth
out of 112 schools which
Research Instruments Research Instruments
The researcher gathered data
The researcher gathered data by examining, verifyby examining, verifying and ing and analyanalyzing the zing the gradingradingg sheets from the Coll
sheets from the College of Allied Medical Prege of Allied Medical Professions and of the ofessions and of the Registrar’s Office. Registrar’s Office. TheThe off
officiicial al priprintontout ut of of the the boaboard rd exaexaminminatiation on perperforformanmance ce of of the the medmedicaical l tectechnolhnologyogy graduates had also undergone the same process.
graduates had also undergone the same process.
Upon approval of the request letter, the researcher gathered the grading sheets of Upon approval of the request letter, the researcher gathered the grading sheets of th
the e fofollllowowining g susubjbjecectsts: : ClClininicical al ChChememisistrtry y 1 1 & & 2, 2, MiMicrcrobiobiolologyogy, , PaPararasisitotolologygy,, Hematology, Serology, Blood Banking, Histopathology, and Medical Technology Laws Hematology, Serology, Blood Banking, Histopathology, and Medical Technology Laws and
and Ethics. Ethics. TheThe
A data matrix table
A data matrix table was prepared to encode all the was prepared to encode all the data needed in the study. data needed in the study. TheThe dat
data a matmatrix was used togetrix was used together with a her with a datdata-ca-codioding manualng manual. . The data encodThe data encoded on ed on thethe matrix table included the year the students graduated, their names, academic ratings in matrix table included the year the students graduated, their names, academic ratings in the different subject areas, their internship grades, seminar grades, and board examination the different subject areas, their internship grades, seminar grades, and board examination performance which is inclusive of all ratings per subject taken and the general weighted performance which is inclusive of all ratings per subject taken and the general weighted
average. average.
Data Collection Data Collection
The initial phase of the study was the gathering of data pertaining to the medical The initial phase of the study was the gathering of data pertaining to the medical tec
technolhnology ogy gragraduatduates es of of AngeAngeles les UniUniverversitsity y FouFoundatndationion, , ColColleglege e of of AllAllied ied MedMedicaicall Professions from academi
Professions from academic year 1995 – 2000. c year 1995 – 2000. A letter was sent to tA letter was sent to the Dean of CAMP tohe Dean of CAMP to seek permi
seek permission to revission to review the records of the 1995 to 2000 graduatew the records of the 1995 to 2000 graduates. es. The researThe researcher cher likewise requested for an endorsement letter to be presented to the Professional regulation likewise requested for an endorsement letter to be presented to the Professional regulation Commission and to the Registrar so that records of the medical technology graduates’ Commission and to the Registrar so that records of the medical technology graduates’
board examination performance as well as the academic, clinical and seminar ratings can board examination performance as well as the academic, clinical and seminar ratings can be availed of respectively.
be availed of respectively.
An endorsement letter from the Dean of CAMP presented to the Registrar enabled An endorsement letter from the Dean of CAMP presented to the Registrar enabled the researcher to access the grading sheets of the subjects for their grades in the different the researcher to access the grading sheets of the subjects for their grades in the different Medica
Medical Technologl Technology subject areay subject areas. s. ComparComparison was made betweeison was made between the data obtainedn the data obtained from the Registrar’s Office and CAMP.
from the Registrar’s Office and CAMP.
For the medical technology graduates’ board examination ratings, the researcher For the medical technology graduates’ board examination ratings, the researcher presented the endorsement letter of the Dean of CAMP to the section chief of the presented the endorsement letter of the Dean of CAMP to the section chief of the
Educational Task Force of
Educational Task Force of the Professional the Professional Regulation Commission. Regulation Commission. All data collectedAll data collected were encoded using a data matrix table prepared by the researcher.
were encoded using a data matrix table prepared by the researcher.
Data Processing and Analysis Data Processing and Analysis A.
A. The data gatherThe data gathered were talled were tallied, tabulied, tabulated, analyated, analyzed and interzed and interpretedpreted. The data for the. The data for the academic, clinical and seminar ratings were grouped based on the following (CAMP academic, clinical and seminar ratings were grouped based on the following (CAMP Bulletin 2000): Bulletin 2000): 97 97 – – ExcellentExcellent 9 91 1 – – 996 6 –– VVeerry y GGoooodd 8 82 2 – – 990 0 –– GGoooodd 7 77 7 – – 881 1 –– SSaattiissffaaccttoorryy 7 75 5 – – 776 6 –– PPaasssseedd b beelloow w 7755 –– FFaaiilleedd
To analyze and describe the data obtained, the researcher made use of a computer To analyze and describe the data obtained, the researcher made use of a computer progr
program called Statam called Statistiistical Package for the Social Scical Package for the Social Sciences (SPSences (SPSS version 9.05). S version 9.05). TheThe statistical tools that were employed are as follows:
1.
1. FrFreqequenuency Dicy Diststriribubutitionon
A frequency distribution is a grouping of data into categories showing the A frequency distribution is a grouping of data into categories showing the number of observat
number of observations in each category (Utzuions in each category (Utzurrum, 1997). rrum, 1997). This statThis statistiistical toolcal tool was employed to describe the board examination ratings and scores in each of the was employed to describe the board examination ratings and scores in each of the subjec
subject t areas given during areas given during the licensure examinatthe licensure examination ion which includewhich includes s CliniClinicalcal Chemi
Chemistrystry, , MicroMicrobiolobiology-Pagy-Parasitrasitologyology, , HematHematologyology, , SerolSerology-Bogy-Blood lood BankiBanking,ng, and Histop
and Histopatholathology-Meogy-Medical Techdical Technology Lawnology Laws and Ethicss and Ethics. . The academiThe academic andc and clinical ratings were not described using this statistical tool since the CAMP clinical ratings were not described using this statistical tool since the CAMP Bulletin provided the categories for classification of the data.
Bulletin provided the categories for classification of the data.
2.
2. PePercrcententagage Dise Distrtribibututioionn
Percentage distribution was used in the analysis of frequency distribution Percentage distribution was used in the analysis of frequency distribution data. This
data. This statistatisticastical l tool charactertool characterized ized all variables under all variables under studystudy, , which includeswhich includes the academic, clinical, and seminar ratings as well as the board examination the academic, clinical, and seminar ratings as well as the board examination performance of the
performance of the subjects. subjects. The percentage distriThe percentage distribution is computed bution is computed by dividingby dividing the number of responses by the
the number of responses by the total number of responses multiplied by 100.total number of responses multiplied by 100. The formula for percentage is as follows:
The formula for percentage is as follows: %
% = = number number of of responses responses X X 100100 total number of respondents
total number of respondents
3
3.. MMeeaann
Mean is defined as a measure of central tendency wherein it is the point on Mean is defined as a measure of central tendency wherein it is the point on the score scale which is equal to the sum of scores divided by the number of the score scale which is equal to the sum of scores divided by the number of
respondents (Cassens, 1987).
respondents (Cassens, 1987). Subjected to these tSubjected to these tests were the academiests were the academic, seminar c, seminar and clinical ratings as well as the board examination performance of the Medical and clinical ratings as well as the board examination performance of the Medical Technology graduates.
Technology graduates.
The mean, for grouped data, may be computed as (Downie, 1983): The mean, for grouped data, may be computed as (Downie, 1983):
X = X = ΣΣ XifiXifi N N Where: Where: X = mean X = mean Xi = midpoint Xi = midpoint fi = frequency fi = frequency N = number of cases N = number of cases 3. Standard Deviation 3. Standard Deviation
The standard deviati
The standard deviation on is the is the positpositive square root ive square root of the of the variavariance nce (Reye(Reyes,s, 1996).
1996). It is the most It is the most useful measure of useful measure of dispersion (Cassens, 1987) dispersion (Cassens, 1987) and was usedand was used to describe the variation and scatter of values of the variables academic, clinical, to describe the variation and scatter of values of the variables academic, clinical, and seminar ratings.
and seminar ratings. This statistThis statistical tool also descrical tool also described the degree of disibed the degree of dispersionpersion of the board examination ratings.
of the board examination ratings. The
The stastandarndard d devideviatiation on for for grogroupeuped d datdata a was was detdetermermineined d as as (Do(Downiwnie,e, 1983): 1983): s = s = NNΣΣ XX22– (– (ΣΣ X)X)22 √ √ N (N-1)N (N-1) Where: Where: s = standard deviation s = standard deviation N = number of cases N = number of cases
X = value for the observation X = value for the observation Σ
B.
B. To test the null hypTo test the null hypothesiothesis, the follows, the following infering inferential stential statisatistics were emptics were employedloyed::
1.
1. Pearson r Pearson r
To determine the relationship between two quantitative variables, the Pearson To determine the relationship between two quantitative variables, the Pearson Produc
Product Moment Correlt Moment Correlation Coeffation Coefficienicient was used. t was used. The relatiThe relationship betweonship betweenen ea
each ch of of ththe e fofollllowiowing ng vavaririabableles s anand d ththe e boboarard d exexamamininatatioion n raratitingngs s wewerere determined using this statistical tool.
determined using this statistical tool. A.
A. AcAcadeademimic Rac Ratitingngss B.
B. SeSemiminar nar RaRatitingngss C.
C. ClClininicical al RaRatitingsngs
Formula: Formula: N NΣΣ XY – (XY – (ΣΣ X) (X) (ΣΣ Y)Y) r = r = √√ [N[NΣΣ XX22 – (– (ΣΣ X)X)22] [N] [NΣΣ YY22 -- ΣΣ Y)Y)22]] Where: Where:
N = number of cases or observations N = number of cases or observations
X = value of the independent or predictor variable X = value of the independent or predictor variable Y = value of the dependent or criterion variable Y = value of the dependent or criterion variable r = Pearson product moment correlation coefficient r = Pearson product moment correlation coefficient
The Guilford Coefficient values were used to determine the degree of The Guilford Coefficient values were used to determine the degree of rel
relatiationsonship hip betbetweeween n the the varvariabiables les as as refrefleclected ted by by the the PeaPearsorson n r r corcorrelrelatiationon coefficient.
V
Vaalluue e IInntteerrpprreettaattiioonn 0
0 NNo o ccoorrrreellaattiioonn 0
0..221 1 – – 00..4400 -- Weeaak W k oor r lloow w ccoorrrreellaattiioonn 0
0..441 1 – – 00..6600 -- MMooddeerraatte e ccoorrrreellaattiioonn 0
0..661 1 – – 00..8800 SSttrroonng g oor r hhiiggh h ccoorrrreellaattiioonn 0
0..881 1 – – 00..9999 -- VVeerry y ssttrroonng g oor r vveerry y hhiiggh h ccoorrrreellaattiioonn 1
1..00 -- PPeerrffeecct t rreellaattiioonnsshhiipp
After the correlation coefficients are computed, the algebraic signs, either After the correlation coefficients are computed, the algebraic signs, either positive or negative, were interpreted as follows:
positive or negative, were interpreted as follows: (+)
(+) = Direct relationship which indicates a parallel increase or decrease in values.= Direct relationship which indicates a parallel increase or decrease in values. The variables follow the same rhythm or direction of
The variables follow the same rhythm or direction of movements.movements. (-)
(-) = Inverse relationship where the variables move in opposite direction. When= Inverse relationship where the variables move in opposite direction. When one increases in value, the other variable decreases.
one increases in value, the other variable decreases.
2.
2. PrPrededicictitive ve VaValuluee
The predictive value is defined as the variation caused by the independent The predictive value is defined as the variation caused by the independent varia
variables, on the board exables, on the board examinatimination performon performance. ance. It is compuIt is computed gettited getting theng the sq
squauarered d vavalulue e of of ththe e PePeararsoson n prprododucuct t momomement nt corcorrerelalatition on coecoefffficicieient nt anandd multiplying it by 100.
multiplying it by 100.
The formula is as follows: The formula is as follows:
Predictive value = r
3.
3. Linear Regression Analysis.Linear Regression Analysis.
This is a statistical tool employed in order to discover the effect of one This is a statistical tool employed in order to discover the effect of one variable on another variable (Parel, 1986).
variable on another variable (Parel, 1986).
The test also performs correlational analysis (Pearson r) and is similar to The test also performs correlational analysis (Pearson r) and is similar to simple correlational analysis, but whilst correlation analysis allows us to conclude simple correlational analysis, but whilst correlation analysis allows us to conclude how strongly two variables relate to each other (both magnitude and direction), how strongly two variables relate to each other (both magnitude and direction), lin
linear ear regregresressiosion n wilwill l ansanswer the wer the quesquestition on by by how how mucmuch h wilwill l y y (de(depenpendentdent var
variabiable) changle) change, if e, if x x (pr(prediedictoctor r or indepeor independenndent t varvariabiable) changle) changes. es. LinLinear ear regres
regression gives a sion gives a measumeasure of re of the effect x has the effect x has on y, on y, or it allows the or it allows the researesearcher torcher to predict y from x (Dancey, 1999).
predict y from x (Dancey, 1999). Whe
When n lilinear near regregresressiosion n anaanalyslysis is is is perperforformedmed, , a a regregresressiosion n equaequatiotion n isis obtained, which shows the way in which y changes as a result of change in x. The obtained, which shows the way in which y changes as a result of change in x. The general formula is as follows (Dancey, 1999):
general formula is as follows (Dancey, 1999):
Y = a + bx Y = a + bx
where:
where: Y = is the variabY = is the variable to be predicle to be predictedted x = is the score on the variable x x = is the score on the variable x b = is the value for
b = is the value for the slope of the linethe slope of the line a = is the value
a = is the value of the constant or interceptof the constant or intercept
The value for the intercept or constant, which is a, may be computed as follows The value for the intercept or constant, which is a, may be computed as follows (Reyes, 1996): (Reyes, 1996): a = X – bY a = X – bY where: where:
a = value for the constant or intercept and makes the mean of the a = value for the constant or intercept and makes the mean of the
actual or observed values equal to the predicted values of Y actual or observed values equal to the predicted values of Y b = value for the slope of the line and indicates the amount of b = value for the slope of the line and indicates the amount of
change in Y per unit change in X. change in Y per unit change in X. X = mean of the
X = mean of the observation for the predictor variableobservation for the predictor variable Y = mean of the observation for the dependent variable Y = mean of the observation for the dependent variable
The value for b was determined as: The value for b was determined as:
b b = = nnΣΣ XY -XY - ΣΣ XXΣΣ YY n nΣΣ XX22– (– (ΣΣ X)X)22 Where: Where:
b = value for the slope of the line b = value for the slope of the line
n = total number of observations or c n = total number of observations or casesases X = observation or values for the
X = observation or values for the predictor variablepredictor variable Y = observation or values for the dependent variable Y = observation or values for the dependent variable
4.
4. MuMultltipiple le RegRegreressssioion.n. Mul
Multiptiple regrele regressission on is an is an extextensension of ion of lilinear regrnear regressessionion. . In order toIn order to discover the ways in which several variables (called independent or predictor discover the ways in which several variables (called independent or predictor varia
variables) are bles) are relarelated ted to another to another (call(called ed the dependent or the dependent or critcriterion variableerion variable), ), thisthis method is made use of.
method is made use of. This technique is able tThis technique is able to give information on o give information on the ways inthe ways in which the independent variables combined relate to the dependent variable, and which the independent variables combined relate to the dependent variable, and how each of the variables relate to the dependent variable, separately (Dancey, how each of the variables relate to the dependent variable, separately (Dancey, 1999).
The regression equation is just an extension of the linear regression and is The regression equation is just an extension of the linear regression and is as follows:
as follows: y = a + b
y = a + b11xx11+ b+ b22xx22+ b+ b33xx33
w
whheerree:: y y iis s tthhe e vvaarriiaabblle e tto o bbe e pprreeddiicctteedd x
x11is the score on the variable xis the score on the variable x11
x
x22is the score on the variable xis the score on the variable x22
x
x33is the score on the variable xis the score on the variable x33
b is the value for the
b is the value for the slope of the lineslope of the line a is the value of the constant or intercept a is the value of the constant or intercept
The independent variables academic, clinical and seminar ratings were the The independent variables academic, clinical and seminar ratings were the predictor variables and board examination rating as the dependent or criterion predictor variables and board examination rating as the dependent or criterion
variable. variable.
Upon measurement of the significance of the result, the following basis Upon measurement of the significance of the result, the following basis was used to determi
was used to determine the rejectine the rejection or acceptance of the null hypotheson or acceptance of the null hypotheses. es. ThisThis basis was used in all of the
basis was used in all of the hypotheses formulated in this study.hypotheses formulated in this study. Rejecti
Rejection on of null of null hypotheshypothesisis – reject the null hypothesis if the computed– reject the null hypothesis if the computed significance level
significance level is lower is lower than 0.05. than 0.05. (Dancey, 1999)(Dancey, 1999) Acceptance of the null hypothesis
Acceptance of the null hypothesis – accept the null hypothesis if the– accept the null hypothesis if the computed significance level is higher than 0. 05. (Dancey, 1999)
