DOCUMENT RESUME

ED 322 369 CE 055 505

AUTHOR Jyung, Chyul-Young; Miller, Larry E.TITLE Predictors of Students' Career Maturity in Central

Ohio High Schools. Summary of Research 55.INSTITUTION Ohio State Univ., Columbus. Dept. of Agricultural

Education.PUB DATE 90NOTE 17p.

PUB TYPE Reports - Research/Technical (143)

EDRS PRICE MF01/PC01 Plus Postage.DESCRIPTORS *Academic Achievement; College Preparation; Grade 10:

Grade 12; High Schools; *Place of Residence; *RuralUrban Differences; *Sex Differences; VocationalEducation; *Vocational Maturity

IDENTIFIERS Career Development Inventory; *Ohio

ABSTRACT

A study was conducted to determine the relationshipof curriculum, gender, and location of residence to career maturityof high school students. Two schools (one urban, on, rural) incentral Ohio provided 320 participating students. A stratified randomsampling techique was then used to select equal numbers of 10th and12th grade vocational-male, vocational-female, college

preparatory-male, college preparatory-female students from each ofthe rural and urban schools. Data -4ere collected in the classroomsusing the Career Development Inventory (CDI) and a demographic dataquestionnaire. Grade point averages and test scores were provided bythe schools. Among the findings were the following: (1) collegepreparatory students were higher in career maturity than vocationalstudents at both the 10th- and 12th-grade levels; (2) female studentswere higher than male students in career maturity at both the 10th-and 12th-grade levels; (3) no significant difference in careermaturity was found between rural and urban students; and (4)scholastic achievement was significantly related to career maturity.(34 references) (CML)

Reproductions supplied by EDRS are the best that can be madefrom the original document.

II DEPARTMENT Of EDUCATIONO4ti9 of Educational Research and Improvement

E noNAL RESOURCES INFORMATIONCENTER (ERIC)

This doCument has been reproduced asrCeived from the person or OrganizationOriginating it

CI Minor changes have been made to improvereproduction Qualify

Points of view or opinions stated in this doc ff-ment do not necessarily represert officialOEM position or policy

Departmeat of digticaltursi EducationThe Oido State University, Cotambus, Ohio 43210

RS OFSTUDENTS CAREER MATURITY

IN CENTRAL OHIO HIGH SCHOOLS

SR SS

"PERMISSION TO REPRODUCE THISMATERIAL HAS BEEN GRANTED BY

.

111"rTO THE EDUCATIONAL RESOURCESINFORMATION CENTER (ERIC)"

Chyul-Young Jyung and Larry E. Mier

Teachers of agriculture have many op-Portunie Br career guidance because theyreceive many requests tbrhelp from individu-slain thaircommunitise. Theyalso frequentlyhave cePortunities to col:taut* intimationvaluabletootherpersons in the school who areprtniidingr ddanceservicabecause they visitthehonseofstudents and because they workwith their students intensively. Therefore,iiiricultitrill educators' attention to career

-need to 1hr exceed the attentiongiven *teachers of other content areas, andteachers ofagriculture are the key individualsin a school's careerguidance program (PhipPet1980).

turity ofindividuals in the Inas that arecritical to realistic career decision-mak-ing developed as a result of this realize-don.

Reflecting this trend, career ma-turity has come to be used as a prerequi-site to the ability to make a wise occupa-tional choice. Moreover, as boys and girlsprogress through school and the educe-tional level increases, the occupationalimplications of career decisions becomedear. Therefore, cducators ask questionssuch ac (1) When shonld instruction inthe Various vocational fields begint (2)When between courses should studentsbe expected to choose leading to differenttypes of education and thus to differentfields ofworkand occupationst (a) Is thisstudent or group of students ready tomate such a choice; and (4) Does taldnga certain imme, studying a certain unit,

in at certain extracunicular &-Ws lark experience

by a prof**.in any way affect the

_students to make these deci-sions? ritre 1974).

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In many states, the policy for enroll-ing in a vocational program is that studentscan be enrolled in vocational education atthe start of their junior year in high school.Further, the philosophy and goals ofvoca-tional education are to have students pre-pared to enter the world of work upon com-pleting high school. The problem is: "Arestudents ready to make these career deci-sions at this point of their life?" In a mono-graph based on a thorough survey of theliterature, Mitchell (1979) emphasized theneed to be able to answer such questions.Other researchers in career education, ca-reer counseling, and career development(Hoyt, 1980; McCaslin, Gross and Walker,1977) also reported the widespread need toaddress these concerns.

REVIEW OF LITERATURE

According to the literature (Achebe,1982; Jordaan and Heyde, 1979; Khan andAlvi, 1983; McNair and Brown, 1983;Osipow, 1983; Thompson, Lindeman, Su-per, Jordaan, and Myers, 1981; Trebilco,1984; Westbrook, Cutts, Madison, and Ar-cia, 1980), many variables are related tocareer maturity. They can be classified as:(1) biological variables (gender, race); (2)psychological variables (mental ability, self-concept, locus of control); (3) social variables(social economic status, location of resi-dence); (4) educational variables (curricu-lum, grade, scholastic achievement, educa-tional aspiration, career development pro-gram); and (5) vocational variables (workvalue, work salience, work axperience, ca-reer decision, vocational aspiration, congru-ence, decision making style). Among thesevariables, some variables can be classifiedas main independent variables, and somevariables can be classified as rival inde-pendent variables. That is, according to theliterature, curriculum, gender, and locationof residence are found to affect career ma-

turity indirectly: the rival variables tocurriculum are mental ability, scholasticachievement, s3cial economic status, educa-tional aspiration, and vocational aspiration(Esslinger, 1976; Fetters, 1975; Herr andEnderlein, 1976; Super and Overstreet,1960); the rival variable to gender is scho-lastic achievement (Omvig, 1976; Omvigand Thomas, 1977; Thompson et al., 1981);and the rival variables to location are scho-lastic achievement, social economic status,educational aspiration, and vocational aspi-ration (Burchinal, 1961; Carmichael, 1982;Hanson, 1980).

Based on the literature, the theoreti-cal framework can be depicted as shown onpage 3.

PURPOSE

The purpose of this study was tomeasure the career maturity of senior highschool students, and to determine the rela-tionship between selected variables and thecareer maturity. This study was specifi-cally conducted to determine the relation-ship of curriculum, gender and location ofresidence to career maturity of senior highschool students, and to determine the inter-vening variables moderating each of thesethree main independent variables.

RESEARCH QUESTIONS

The following research questionswere developed to guide this study.

1 What is the level of career maturity ofsenior high school students?

2. What is the relationship between themain independent variables (cur-riculum, gender and location of resi-dence) and career maturity in seniorhigh school students?

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Main I.V.s Rival I.V.s

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D.V.

SthOISSt1c:ithi0014041t

I Location',Educational ASpiration

Vocational Aspiration

3. What is the relationship between therival independent variables (level ofmental ability, scholastic achieve-ment, social economic status, educa-tional aspiration and vocational aspi-ration) and career maturity?

4. What is (are) the interveningvariable(s) of each of the three mainindependent variables?

5. How much of the variance in careermaturity is explained by each of thepredictor variables?

METHODOLOGY

The relational research method wasused for the study. The end sought byrelational studies is to investigate relation-ships between variables in order to explainand predict (Miller, 1986, p.13).

Population and Sample

The target population in the studywas all senior high schools of eight countieswithin a 50 miles radius of Columbus, Ohio,during 1988-89 school year. The totalnumber of students in the populationatotal of 80 senior high schoolsin the eightcounties was taken from the Ohio Educa-tional Directory 1988-89 (N=32,069), withan accessible population of 983 students.

Using the formula to determine a samplesize with 95% confidence (Krejcie & Mor-gan, 1970), 278 students were needed.Considering the needed number, the num-ber of sample was set at 320 students. Acluster sampling technique was used, whereschools were the sampling units, and 1urban school and 1 rural school were pur-posely selected as an accessible population.A stratified random sampling techniquewas then used to select equal numbers of10th and 12th grade vocational-male, voca-tional-female, college preparatory-male,college preparatory-female students fromeach of the rural and urban schools.

Data Collection

In each of the urban and ruralschools, two vocational tenth grade classes,two college preparatory tenth grade classes,two vocational twelfth grade classes, andtwo college preparatory twelfth gradeclasses were purposely selected. For eachclass, two envelopes were prepared: One forfemale students, and the other for malestudents. Each envelope contained tenoriginal answer sheets and extra copies ofthe answer sheet. In each classroom, the tenoriginal answer sheets and the extra copieswere randomly handed to each of male andfemale students. The data were collected inApril, 1989. Only the original answer sheets

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were used for data analysis, but extras weresupplied to meet the wishes ofthe schools toexamine all students in the classes at thesame time.

Instrument

The instrument used to measure ca-reer maturity was the Career DevelopmentInventory (CDI) School Form Part I(Thompson et al., 1981). Internal consis-tency reliability coefficients for the CDIrange from .79 to .88 with a median of .86(Thompson et al., 1981). Test-retest relia-bilities from previous forms of the CDI sug-gest that the current version has sufficientstability over periods of up to six months(Thompson et aL, 1981). Content validityhas been demonstrated by the relationshipbetween the CDI items and the theoreticalcomponents of vocational maturity thathave been described by Super and his col-leagues in the Career Pattern Study (Super,1984; Thompson et al., 1981). Constructvalidity is evident from the connection be-tween CDI scores and differences in grade,gender, and curriculum; with each of thesevariables, CDI scores correlated in a waythat was consistent with career develop-ment theory. Furthermore, factor analysesof the CDI rovealed a statistical structurethat confirmed the existence of two identifi-able factors of vocational maturity.

The subjects were administered thisCDI-Part I instrument. The subjects werealso administered a questionnaire as ameans of obtaining demographic data suchas curriculum, gender, grade, location ofresidence, educational aspiration, voca-tional aspiration, and parents' or guardi-ans' occupation. Level of mental ability andgrade point average scores were providedby school counselors.

Data Analysis

Data were analyzed using the SAS atthe Instructional and Research ComputingCenter of The Ohio State University. Cor-relations, t-tests, two way analyses of vari-ance, and multiple regression analyses wereused to develop a further understanding ofthe relationship of curriculum, gender, andlocation to career maturity. An alpht levelof .05 was established prior to data treat-ment.

FINDINGS

Large differences in the career ma-turity existed among the subgroups classi-fied, based on curriculum, gender, and loca-tion. The means for affective, cognitive, andtotal career maturity of tenth grade stu-dents (90.34, 94.61 and 89.98 respectively),and cognitive career maturity of twelfthgrade students (99.65) were under 100which was the mean of the norm group of theinstrument.

In order to examine the relationshipamong the main and rival independentvariables, and dependent variables, correla-tions, t-tests, and two way analysis of vari-ance were used. The magnitude of the rela-tionships investigated in this stildy wasdescribed based on the scale delineated byDavis (1971).

A. Relationship between main inde-pendent variables and depend-ent variable

1. Both in the tenth and the twelfthgrade, college preparatory studentswere significantly higher in affective,cognitive and total career maturitythan vocational students. The rela-tionship between curriculum and af-fective and total career maturity was

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higher in the tenth grade (.79 and .75rebpectively) than in the twelfthgrade (.57 and .63 respectively). Onthe contrary, the relationship be-tween curriculum and cognitive ca-reer maturity was higher in thetwelfth grade (.52) than in the thetenth grade (.44). The difference inaffective career maturity and totalcareer maturity between college pre-paratory students and vocationalstudents were significantly less inthe twelfth graders than in the tenthgraders.

2. Both in the tenth and the twelfthgrade, female students were higherin affective, cognitive and total careermaturity than male students, andalmost all of the relationships werestatistically significant. The rela-tionship of gender to affective andtotal career maturity was higher inthe twelfth grade (.20 and .52 respec-tively) than in the tenth grade (.13and .31 respectively). On the con-trary, the relationship between gen-der and cognitive career maturitywas higher in the tenth grade (.42)than in the twelfth grade (.35). Gen-der was more highly correlated withthe cognitive domain of career matur-ity than the affective domain of ca-reer maturity, and the relationshipbetween gender and cognitive careermaturity was higher in the tenthgrade than in the twelfth grade.

3. Both in the tenth and twelfth grade,rural students were negligibly higherthan urban students in career matur-ity and the relationship was not sta-tistically significant. Also, no signifi-cant difference in affective, cognitive,and total career maturity meanscores between rural students andurban students was found.

B.

1.

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Relationship between rival inde-pendent variables and depend-ent variable

Mental ability was moderately orsubstantially related to career ma-turity, and the relationship was sta-tistically significant. Also, mentalability, which is assumed to be ameasure of the cognitive domain, wasmore highly related to the cognitivedomain of career maturity than theaffective domain cf career maturity.From the developmental point ofview, mental ability was more highlyrelated to career maturity in thetenth grade than in the twelfth grade.

2. Scholastic achievement was substan-tially or very highly related to careermaturity, and the relationship wasstatistically significant. Also, scho-lastic achievement, which is as-sumed to be a measure of the cogni-tive domain, was more highly relatedto the cognitive domain of careermaturity than the affective domain ofcareer maturity.

3. Social economic status waP low ormoderately related to career matur-ity, and the most of the relationshipswere statistically significant. Also,social economic status was morehighly related to the cognitive do-main of career maturity than theaffective domain of career maturity.As grades increased from the tenth tothe twelfth, the strength of the rela-tionship decreased. That is, from thedevelopmental point of view, socialeconomic status was more highly re-lated to career maturity in the tenthgrade than in the twelfth grade.

4. Educational aspiration was moder-ately related to career maturity, and

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the relationships were statisticallysignificant. Also, educational aspira-tion was more highly related to theaffective domain of career maturitythan the cognitive domain of careermaturity. As grades increased fromtenth to twelfth, the relationship de-creased. That is, from the develop-mental point of view, educationalaspiration was more highly related tocareer maturity in the tenth gradethan in the twelfth grade.

5. Vocational aspiration was low ormoderately related to career matur-ity, and the relationships were statis-tically significant. Also, vocationalaspiration was more highly related tothe cognitive domain ofcareer matur-ity than the affective domain of ca-reer maturity. As grades increasedfrom tenth to twelfth, the relation-ship increased. That is, from the de-velopmental point of view, vocationalaspiration was more highly related tocareer maturity in the twelfth gradethan in the tenth grade.

C. Relationship between rival inde-pendent variables and main in-dependent variables

1. Both in the tenth and the twelfthgraders, substantial relationshipsexisted between mental ability andcurriculum ( 50 and .58 respectively),and the relationships were statisti-cally significant. A t-test showed thatcollege preparatory students weresignificantly higher in mental abilitythan vocational students. Mentalability was more highly related tocurriculum in the twelfth grade thanin the tenth grade.

2. Both in the tenth and the twelfthgraders, substantial relationships

existed between scholastic achieve-ment and curriculum (.51 and .59respectively), and the relationshipswere statistically significant. A t-testshowed that college preparatory stu-dents were significantly higher inscholastic achievement than voca-tional students. Scholastic achieve-ment was more highly related to cur-riculum in the twelfth grade than inthe tenth grade.

3. Both in the tenth and the twelfthgraders, moderate relationships ex-isted between social economic statusand curriculum (.39 and .38 respec-tively), and the relationships werestatistically significant. A t-testshowed that college preparatory stu-dents were significantly higher insocial economic status than voca-tional students. The relationshipwas almost the same in the tenth andthe twelfth grade.

4. Both in the tenth and the twelfthgraders, substantial relationshipsexisted between educational aspira-tion and curriculum (.55 and .63 re-spectively), and the relationshipswere statistically significant. A t-testshowed that college preparatory stu-dents were significantly higher ineducational aspiration than voca-tional students. Educational aspira-tion was more highly related to cur-riculum in the twelfth grade than inthe tenth grade.

5. In the tenth graders, a substantial re-lationship existed between voca-tional aspiration and curriculum(.51), and in twelfth graders, a veryhigh relationship existed between vo-cational aspiration and curriculum(.71). Both of the relationships werestatistically significant. A t-test

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showed that college preparatory stu-dents were sigiaificantly higher invocational aspiration than vocationalstudents. Vocational aspiration wasmuch more highly related to curricu-lum in the twelfth grade than in thetenth grade.

6. Both in the tenth and the twelfthgraders, moderate relationships ex-isted between scholastic achieve-ment and gender (.44 and .42 respec-tively), and the relationships werestatistically significant. A t-testshowed that female students weresignificantly higher in scholasticachievement than male students.Scholastic achievement was morehighly related to gender in the tenthgrade than in the twelfth grade.

7. Both in the tenth and the twelfthgraders, negligible relationships ex-isted between scholastic achieve.ment and location (-.01 and -.02 re-spectively), and th e. relationghipswere not statistically significant.That is, rural students were negligi-bly higher in scholastic achievementthan urban students, and it was notsignificant. Scholastic achievementwas more highly related in the nega-tive direction to location in thetwelfth grade than in the tenth grade.

8. Both in the tenth and the twelfthgraders, negligible relationships ex-isted between social economic statusand location (.07 and .10 respec-tively), and the relationships werenot statistically significant. That is,urban students were negligiblyhigher than rural students, and itwas not significant. Social economicstatus was more highly related tolocation in the twelfth grade than inthe tenth grade.

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9. In the tenth graders, a negligiblenegative relaiionship existed be-tween educational aspiration andlocation (-.08). On the contrary, intwelfth graders, a low positive rela-tionship existed between educationalaspiration and location (.11). That is,in the tenth graders, rural studentswere negligibly higher in educationalaspiration than urban students, andin the twelfth graders, urban stu-dents were higher in educational as-piration than rural students. Both ofthe relationships were not statisti-cally significant.

10. In the tenth graders, a negligiblenegative relationship existed be-tween vocational aspiration and loca-tion (- .06). On the contrary, intwelfth graders, a low positive rela-tionship existed between vocationalaspiration and location (.13). That is,in the tenth graders, rural studentswere negligibly higher in vocationalaspiration than urban students, andin the twelfth graders, urban stu-dents were higher in vocational aspi-ration than rural students. Both ofthe relationships were not statisti-cally significant.

D. Relationship between main inde-pendent variables and depend-ent variables while holding rivalindependent variables constant

1. Both in the tenth and the twelfthgraders, when mental ability, scho-lastic achievement, social economicstatus, educational aspiration, andvocational aspiration were statisti-cally controlled, no significant rela-tionship existed between curric .11=1and cognitive career maturity (SeeTables 1 & 2).

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Table 1

Regression of Cvnitive Career Maturityon Rival Independent Variables(Mental Ability, Scholastic Achievement, Social Economic Status, EducationalAspiration and Vocational Aspiration) and Main Independent Variable(Curriculum) in 10th Graders (n=160) (Hierarchical Entry)

Variables R2 R2th.p b Beta tSet of Rival Independent Variables .641 .641

o Mental Ability .424 .259 4.26'o Scholastic Achievement 14.549 .631 10.37'o Social Economic Status .031 .032 .59o Educational Aspiration 1.744 .124 1.95o Vocational Aspiration -.020 -.026 -.42

Main Independent Variable .644 .003o Curriculum' -2.816 -.083 -1.21

(Constant) 33.771*p.05Adjusted R2=.630For Model: F=46.13; p<.0001a: 0=Vocational; 1=College Preparatory

Table 2

Regression of Cognitive Career Maturity on Rival Independent Variables(Mental Ability, Scholastic Achievement, Social Economic Status, EducationalAspiration and Vocational Aspiration) and Main Independent Variable(Curriculum) in 12th Graders (n=160) (Hierarchical Entry)

Variables R2 R2e... b Beta tSet of Rival Independent Variables .528 .528

o Mental Ability .463 .260 3.60'o Scholastic Achievement 11.241 .493 6.87'o Social Economic Status .075 .087 1.41o Educational Aspiration -.342 -.024 -.32o Vocational Aspiration .006 .008 .09

Main Independent Variable .329 .001o Curriculum' 1.898 .056 .60

(Constant) 45.002*p<.05Adjusted R2=.511For Model: F=28.65; p<.0001a: 0=Vocational; 1=College Preparatory

2. Both in the tenth and the twelfthgraders, when scholastic achieve-ment was statistically controlled, nosignificant relationship existed be-tween gender and affective, cogni-tive, and total career maturity with-out exception (See Tables 3 & 4).

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3. Both in the tenth and the twelfthgraders, no significant relationshipexisted between location, and affec-

ve, cognitive, and total career ma-turity. That is, the assumption forthe hypothesisSignificant rela-tionship will exist between location,

Table 3

Regression of Total Career Maturity on Rival Independent Variable(Scholastic Achievement) and Main Independent Variable (Gender)in 10th Graders (n=160) (Hierarchical Entry)

Variables R2 R2 e b Beta tchang

Rival Independent Variable .554 .554

o Scholastic AchievementMain Independent Variable .555 .001

o Gender -1.047 -.025 -.42(Cons:ant) 39.519

21.427 .756 12.72'

*p<.05Adjusted R2=.549For Model: F=97.90; p<.0001a: 0=Male; 1=Female

Table 4

Regression of Total Clreer Maturity on Rival Independent Variable(Scholastic Achievement) and Main IniependentVariable (Gender)in 12th Graders (n=160) (Hierarchical Entry)

Variables R2 R2 b BetaRival Independent Variable .559 .559

o Scholastic Achievement 19.322 .748 12.78'Main Independent Variable .559 .000

o Gender' -.022 -.001 -.01(Constant) 61.870*p<.05Adjusted R2=.553For Model: F=99.40; p<.0001a: 0=Male; 1=Female

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and affective, cognitive, and totalcareer maturitywas not true.Therefore, no further regressionsanalysis to test the hypothsisIfscholastic achievement, social eco-nomic status, educational aspira-tion, and vocational aspiration arestatistically controlled, no relation-ship will mdst between location andcareer maturitywere conducted.

E. Relationship between inde-pendent variables and depend-ent variable

1. In the tenth grade, the variance ofthe affective, cognitive, and totalcareer maturity explained by thelinear combination of curriculum,gender, location, mental ability,scholastic achievement, social eco-nomic status, educational aspira-tion and vocational aspiration were67.7%, 68.1%, and 78.0%, and whichwere statistically significant. In thetwelfth grade, the variance ofthe af-fective, cognitive, and total careermaturity explained by the linearcombination of curriculum, gender,location, mental ability, scholasticachievement, social economicstatus, educational aspiration andvocational aspiration were 46.6%,56.0%, and 63.9%, and which werestatistically significant.

2. When the dependent variable wasaffective career maturity, in thetenth grade, curriculum, and voca-tional aspiration, and, in thetwelfth grade, c irriculum and scho-lastic achievement contributed sig-nificantly to the regression whenthe other independent variableswere controlled. When the depend-ent variable was cognitive careermaturity; in both tenth grade and

twelfth grade, gender, mental abilityand scholastic achievement contrib-uted significantly to the regressionwhen the other independent vari-ables were controlled. When thedependent variable was total careermaturity; in the tenth grade, curricu-lum, gender, mental ability, scholas-tic achievement and vocational aspi-ration, and, in the twelfth grade, cur-riculum, gender, mental ability andscholastic achievement contributedsignificantly to the regression whenthe other independent var: bles werecontrolled.

SUMMARY, DISCUSSION,IMPLICATIONS AND

RECOMMENDATIONS

Large differences in the career ma-turity existed among the subgroups classi-fied based on curriculum, gender, and loca-tion. The means for affective, cognitive, andtotal career maturity of tenth grade stu-dents, and cognitive career maturity oftwelfth grade students were under 100which was the mean ofthe norm group of theinstrument.

Two of the three main independentvariablescurriculum and genderweresignificantly related to career maturity, andall of the rival independent variablesmental ability, scholastic achievement, so-cial economic status, educational aspira-tion, and vocational aspirationwere sig-nificantly related to career maturity. Sig-nificant relationships existed between cur-riculum and rival independent variablesmental ability, scholastic achievement, so-cial economic status, educational aspira-tion, and vocational aspiration. When therival independent variables were con-trolled, no significant relationship existedbetween curriculum and career maturity.

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Also, significant relationships existed be-tween gender and a rival independent vari-ablescholastic achievement. When therival independent variable was controlled,no significant relationship existed betweengender and career maturity.

In this study, based on the findingsthat urban students were higher in scholas-tic achievement, social economic status,educational aspiration, and vocational aspi-ration (Burchinal, 1961; Hanson 1980;Carmichael, 1982), hypothesis was estab-lished as follows: Urban students will behigher in career maturity than rural stu-dents. However, the result showed thatrural students were negligibly higher incareer maturity than urban students. Theresult was in accordance with the studies ofSuper and Overstreet (1960), Dillard(1976), and Holland (1981). There are threepossible reasons why, in this study, urbanstudents were not higher in career maturitythan rural student. First, uthan studentsmight be lower in career maturity thanrural students because of the ethnicity ofstudents included in the sample of urbanstudents. In this study, the selected urbanschool had 10% black students of the totalenrolling students, whereas, the selectedrural school had no black students. That is,there were some black students in thesample of the urban school used in thisstudy, and, on the contrary, there was noblack student in the sample of the ruralschool. Most researchers (Karayanni, 1981;Lawrence and Brown, 1976; McNair andBrown, 1983) agreed that whites are higherin career maturity than blacks. Second, thevillage where the rural school was located,had a very peculiar characteristic comparedto other rural areas: A large auto plant waslocated there, and new large plants werebeing establishing there. Third, rural stu-dents were higher than urban students incareer 'maturity possibly because the ruralstudents had work experience on farms and

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were likely to follow family farming pat-terns which were already clear to them(Osipow, 1:183).

Implications

1. A significant difference in the rate ofcareer development existed amongthe subgroups based on curriculumand gender. Also, career maturityvaried depending on each student'scharacteristics such as mental abil-ity, scholastic achievement, socialeconomic status, educational aspira-tion, and vocational aspiration. Themeans for affective, cognitive, andtotal career maturity of tenth gradestudents (90.34, 94.61, and 89.98, re-spectively) were under 100 whichwas the mean ofthe norm group of theinstrument. Many students werevocationally immature at the comple-tion of tenth grade when they wereencouraged to decide their curricu-lum. In accordance with this finding,in 1983, when asked how certainstudents were about their occupa-tional preferences, 27 percent of the .

eleventh grade students answered, "Iam not sure at all" (Herr and Cram-mer, 1988, p. 269). In short, at thecompletion of tenth grade whenmany students are too immature todecide career choices, students areforced to finalize their curricularchoice. Therefore, educational ad-ministrators and teachers are recom-mended to provide support for facili-tating students' career maturity sothat as students approach the end ofthe tenth grade they should havereached a stage of career develop-ment where they can make curricularchoice wisely. Clearly, it would be anadvantage if the first year of highschool could be an exploratory period,when students were able to sample

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and react to a variety of courses in themanner cnce envisaged for juniorhigh schools. If this is not feasible,school policies should be flexibleenough to facilitate studelt transferfrom one curricular track to anotherwith as little penalty as possible.That is, more avenues must be cre-ated for all students to move freelyamong the curricula with the criteriafar such movement being individualneed, readiness, interest, motivation,and the blend of academic and voca-tional experiences to meet these cri-teria.

2. Female students were significantlyhigher in career maturity than malestudents. This finding is apparentlya manifestation of girls maturingearlier than boys and needing spe-cialized guidance and counselingabout their plans and goals in thehigh school. Like gender difference incareer maturity, college preparatorystudents were significantly higher incareer maturity than vocational stu-dents. Therefore, present career de-velopment practices need to be re-vised to reflect the experiences of theparticular subgroup. Also, whenpredicting career maturity, differentpredictors may be employed depend-ing on the subgroup of the subjects.

3. Gender difference and curriculi-indifference in career maturity were afunction ofintervening variables: thegender difference was a function ofscholastic achievement; and the cur-riculum difference ...las a function ofmental ability, scholastic achieve-ment, social economic status, voca-tional aspiration and educationalaspiration. Therefore, career guid-ance and counseling based solely ongender or curriculum is not appropri-

ate. Teachers and school counselorsneed to help students utilize multiplesources of information about them-selves (interests, abilities, careermaturity, values) and consider avariety of career options when mak-ing educational and career decisions.

4. Individuals who had higher level of'mental ability, scholastic achieve-ment and social economic status, andwho set higher educational and voca-tional aspirations exhibited greatercareer maturity. In other words,career maturity was related to bio-logical, social, psychological, educa-tional and vocational variables. Thatis, this study, like many others,pointed to the fact that career matur-ity should be viewed as a function oftotal human development. An impor-tant implication of this finding is thatany program designed to facilitatecareer development must be con-ceived as part of a total educationalexperience aimed at developing apositive self-concept, higher level ofmental ability and scholasticachievement, realistic levels of edu-cational aspiration and vocationalaspiration, an understanding of one'sstrengths and weaknesses, skills indecision making and problem solv-ing, and appreciations of appropriatework values. Therefore, as propo-nents of the career education move-ment would say, career educationmust not be simply considered anextra course in the curriculum but aninstructional strategy that relates es-tablished subject matter to careerconcepts, and career education ac-tivities must be integrated into thetotal school curriculum in order to beoptimally effective in terms of achiev-ing the outcomes listed.

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Recommendations forFurther Study

1. The data utilized in this study wereobtained from urban and rural tenth-and twelfth-grade students. The cri-teria used to identify urban and ruralschools and the size of the sampleused in this study were identified aslimitations. The generalization ofthe results was limited on that basisto tenth- and twelfth-grade studentsin the two schools studied. In addi-tion, subjects for the study wereobtained from available intactgroups since random sampling proce-dureta were not feasibly applied to theavailable populations. Therefore, fo -greater generalizability, replicationis needed.

2. In this study, statistically significantdifferences in career maturity as wellas scholastic achievement, socialeconomic status, educational aspira-tion, and vocational aspiration werenot found between the urban schooland the rural school. One possiblereason for the finding may be due tothe definition of urban and ruralschools used in this study. Urban andrural schools have been defined inmany different and diverse ways (i.e.,McCracken and Miller, 1988; U.S.Bureau of the Census, 1983). There-fore, additional attempts should bemade in defining the nature of urbanand rural schools. Based on the clas-sification, the State Department ofEducation should identify schools asurban, suburban, or rural, and keeprecords according to this classifica-tion so that researchers can studyusing this unified classification.

3. Because of the inherent difficulties ofthe longitudinal methoddemand-

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ing an extended commitment from anindividual or institution willing tospend time, money, and other re-Rources for several years before com-pleting the project the cross-sec-tional method was used in this study.Since career maturity was stemmedfrom developmental concepts devel-oped by Super, what students are likeat various ages, how they vary fromone another within age levels, andhow they grow and develop are veryimportant questions in the study ofcareer maturity. To nnswer thesequestions effectively, the longitudi-nal method is the most suited.

4. Especially, this study was conductedto determine the relationship of cur-riculum, gender, and location to ca-reer maturity of senior high schoolstudents, and to determine the inter-vening variables of each of thesethree variables. Thus, this study wassuccessful in determining the inter-vening variables of each of the threemain independent variables. How-ever, this study did not determi, e thecausal relationships among the rivalvariables. Therefore, further re-searches to determine the causal re-lationships among the rival variablesare needed.

5. The result showed that rural stu-dents were negligibly higher thanurban student, and the relationshipwas not statistically significant. Onepossible reason for the non-signifi-cance is that urban students mightbe lower than rural students becauseof the ethnicity included in thesample of urban students. That is,there were some black students in thesample of the urban school used inthis study, and, on the contrary, therewas no black student in the sample of

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the rural school. Therefore, othervariables including race should beincluded in future studies.

6. This study was relational in nature.A relational study cannot establishcause-and-effect relationships be-tween variables; the investigatorsought only to describe and explainrelationships between characteris-tics (Miller, 1986). To overcome theshortcominp a causal approach isneeded. 1 .ysis of covariance struc-ture is a combination of factor analy-sis and multiple regression analysis.Kerlinger (1986) stated that analysisof covariance structure is the mostsuited to the study and analysis ofcomplex structural theoretical mod-els in which complex chains of rea-soning are used to tie theory to em-pirical research, and under certainconditions and limitations, the ap-proach is a powerful means of testingalternative explanations of behaviorphenomena. Therefore, the covari-ance structure modeling is needed inthe future study of career maturity.

REFERENCES

Achebe, C. (1982). Assessing the vocationalmaturity of students in the eastcentral state of Nigeria. Journal ofVocational Behavior, 20, 153-161.

Burchinal, L.G. (1961). Differences ineducational and occupational aspi-rations of farm, small town and cityboys. Rural Sociology, 26, 107-121.

Carmichael, D. (1982). The challenge ofrural education. The Rural Educa-tor, 4, 5-10.

Davis, J.A. (1971). Elementary surveyanalysis. Englewood, New Jersey:Prentice-Hall.

Dillard, J. M. (1976). Relationship betweencareer maturity and self-concept ofsuburban and urban middle- andurban lower-class preadolescentblack males. Journal of VocationalBehavior, 9, 311-320.

Esslinger, C.W. (1976). Educational andcccupational aspirations and expec-taions and the educational, per-sonal, and family characteristics ofselected twelfth grade female stu-dents. Dissertation Abstracts Inter-national, 37, 255A.

Fetters, W. B. (1975). National longitudi-nal study of the high school class of1972: Student questionnaire and testresults by high school program, eth-nic category, and father's education.Washington, D. C.: U.S. Govern-ment Printing Office.

Hanson, J.T. (1980). Vocational educationin a rural setting . Paper presented atthe Annual Kansas State UniversityRural and Small School Conference.Manhattan, Kansas. (ERIC Docu-ment Reproduction Service No. ED198 176).

Herr, E.L., & Cramer, S.H. (1988). Careerguidance and counseling through thelife span (32d Ed.). Boston: Little,Brown & Company.

Herr, E.L., & Enderlein, T.E. (1976). Voca-tional maturity: The effects ofschool, grade, curriculum and sex.Journal of Vocational Behavior, 8,227-238.

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Holland, M. (1981). Relationships betweenvocational development and self-concept in sixth grade students.Journal of Vocational Behavior, 18,228-236.

Hoyt, K.B. (1980). Evaluation of K-12 ca-reer education: A status report.Washington, D.C.: U.S. GovernmentPrinting Office.

Jordaan, J.P., & Heyde, M. (1979). Voca-tional maturity during the highschool years, New York: TeachersCollege Press.

Karayanni, M. (1981). Career maturity ofemotionally maladjusted high schoolstudents. Vocational GuidanceQuarterly, 29, 213-220.

Kerlinger, F.N. (1986). Foundations ofbehavioral research (3rd Ed.). NewYork: Holt, Rinehart and Winston.

Khan, S.B., & AM, S.A. 1;1983). Educa-tional, social, Rad psychological cor-relates of vocational maturity. Jour-nal of Vocativigal Behavkr, 22, 357-364.

Krejcie, R. V., & Morgan D. W. (1970).Determining sample site for re-search activities. Educational Psy-chology Measurement, 30, 607-610.

Lawrence, W., & Brown, D. (1976). An in-vestigation of intelligence, self-con-cept, socioeconomic status, race, andsex as predictors of career maturity.Journal of Vocational Behavior, 9,45-52.

McCracken, J.D., & Minor, C. (1988). Ruralteachers' perceptions oftheir schoolsand communities. Research in RuralEducation, 5, 23-26.

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McCaslin, N.L., Gross, C.J., & Walker, J.P.(1977). Career education measures.Columbus, Ohio: Center for Voca-tional Education,The Ohio StateUniversity..

McNair, D., & Brown, D. (1983). Predictingthe occupational aspirations, occu-pational expectations, and careermaturity of black and white maleand female 10th graders. VocationalGuidance Quarterly, 32, 29-36.

Miller, L.E. (1986). Lecture note of Ag. Ed.885 Research Methods. Columbus,Ohio: The Ohio State University.

Mitchell, A.M. (1979). Evaluating careereducation. Salt Lake City, Utah:Olympus.

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Omvig, C.P., & Thomas, E.D. (1977). Rela-tionship between career, education,sex, and career maturity ofsixth andeighth grade pupils. Journal ofVocational Behavior, 11, 322-331.

Osipow, S.H. (1983). Theories of careerdevelopment (3rd Ed.). EnglewoodCliffs, New Jersey: Prentice-Hall,Inc.

Phipps, L.J. (1980). Handbook on agricul-tural education in public schools(4th Ed.). Danville, Illinois: kter-state Printers & Publishers.

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Super, D.E. (1974). Measuring vocationalmaturity for counseling and evalu-ation. Washington, D.C.: NationalVocational Guidance Association.

Super, D.E. (1984). Work role salience as adeterminent of career maturity inhigh school students. Journal ofVocational Behavior, 25, 30-44.

Super, D.E., & Overstreet, P.L. (1960). Thevocational maturity of ninth-grade boys.New York: Teachers College, ColumbiaUniversity.

Thompson, A.S., Lindeman, R.H., Super,D.E., Jordaan, J.P., & Myers, R.A.(1981). Career Development Inventory

Volume 1: User's Manual. Palo Alto,California: Consulting PsychologistsPress.

Trebilco, G.R. (1984). Career educhtionand career maturity. Journal of Voca-tional Behavior, 25, 191-202.

U.S.Bureau of the Census. (1983). Censusof population: 1980, Vol. 1. Character-istic of the population. Washington,D.C.: U.S. Government Printing Office.

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SUMMARY OF RESEARCH SERIES

Teachers of agriculture have many opportunities for career guidance because they receivemany requests for help from individuals in their community. The current emphasis on vocationalagriculture and career development theory has brought to light a common focus on the emergingreadiness and competence of individuals to not enter, but find satisfaction in the world of work.This study reports research conducted in Ohio that examines the relationship of curriculum,gender, and location of residence to career maturity of senior high school studer It should beof interest to vocational education teachers, guidance counselors, and school awninistrators.

This summary is based on a dissertation by Chyul-Young Jyung under the direction ofLarry E. Miller. Chyul-Young Jyung was a graduate student in the Comprehensi /e VocationalEducation Program, The Ohio State University. He is currently a Visiting &holar for theDepartment of Agricultural Education. Dr. Larry E. Miller is a Professor, Department ofAgricultural Education, The Ohio State University. Special appreciation is due to William H.Hamilton, Purdue University; and Oren L. Christmas, Michigan State Department ofEducation;for their critical review of this manuscript prior to its publication.

Research has been an important function of the Department of Agricultural Educationsince it was established in 1917. Research conducted by the Department has generally been inthe form of graduate theses, staff studies, and funded research. It is the purpose of this seriesto make useful knowledge from such research available to practitioners in the profession.Individuals desiring additional information on this topic should examine the references cited.

Wesley E. Budke, Associate ProfessorDepartment of Agricultural Education

SR 55 1990

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