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Smith, Stuart F.Strong Vocational Interest Blank Scores for JuniorCollege Students in Five Curricula.Alfred Univ., N.Y.Mar 7018p.: Paper presented at the 1970 American Personneland Guidance Association Convention, New Orleans,March 1970

EPPS Price MF-$0.25 HC-$1.00*College Curriculum, College Stueients, GuidanceCounseling, * Interest Scales, Interest Tests,*Junior Colleges, Student Characteristics, *StudentInterests, *Vocational Interests*Strong Vocational Interest Blank, SVIB

ABSTRACTAn irvestiaation was conducted to determine if

students in five junior college curricula could be differentiated bythe Stronci Vocational Interest Blank (1VIB) scores and if suchdifferentiation could be improved by using several scores incombination rather Phan single scores separately. The SVIB wasadministered to 130 students at Alfred Agricultural & TechnicalSchool and the resulting means and standard deviations were submittedto analysis. The conventional overlap method of scaling wassubsequently compared to the non-conventional multi-scale method toascertain the latter's differentiating power. However, furtherstudies based on a larger simple are necessary to adequatelydetermine the effectiveness of the multi-scale approach. (Figures1/4--SVIB Profilesmay not reproduce well due to marginal legibilityof the original copy.) (PR)

a

1970 APGA Convention

STRONG VOCATIONAL INTEREST BLANK SCORES FORJUNIOR COLLEGE STUDENTS IN FIVE CURRICULA

..S. DEPARTMENT OF HEALTH, ED UCATIOII WELFARE

OFFICE OF EDUCATIONTHIS DOCUMENT HAS BEEN REPRODUCE0EXACTLY AS RECEIVED FPOM THE PERSON OFORGANIZATION ORIGINATING IT. POINTS 01VIEW OR OPINIONS STATED DO NOT FAECESSARAN, REPRESENT OFFICIAL OFFICE OF tOUCATION POSITION OR POLICY

Stuart E. Smith, Alfred University

CO The major objective of the study was to determine if Btu-

13 dents in five different junior college curricula could be differ-pr\

entiated by their Strong VocationalInterest Blank (SVIB) scores.

CD A second objeotive me to asoertain if differentiation between

LLJ curriculum groups could be improved by the use of several scales

in combination as opposed to differentiation by single scales

C) separately.

C)It is assumed that the majority of the readers are familiar

C) with the SVIB literature to the extent that they know that many

studies have demonstrated the effectiveness of the SV/B.(N).to

differentiate fairly wisll adult groups of employed men, and to

a lesser extent, students in various four-year college ourriou-

luma. The effeotiveneet, of the SVIB (W) to differentiate adult

and student groups of Roman has not been so well demonstrated.

Although there is a fairly extensive literature, aommulated over

the past 30 years or 30, concerning the interests of students in

four-year oollegee, e. e,, the well known studies by Strong (1955),

and by Darley and Hagonall (1955), only a few studies have been

published whioh provide data oonoerning the measured interests

of junior college students, Stewart (1966) found that students

in one junior college lcold be differentiated in terms of their

0 interests as measured hi the Interest Assessment Scales. Although0

two reoent studies (Ta;#:or & Bondy, 1966; Taylor & Hooker, 1967)

of the interests of junler college students have been published,

p, 2

differentiation by specific curriculum was not attempted. So

far as the writer can determine, no studies have been published,

other than Stewart's, whioh compare the measorsd interests of

students in various junior college ourrioula.

Inasmuch as the enrollments in the nation's junior colleges

are inoreasing, and in absolute Lerma already constitute a sub-

stantial number of post-high school studentelit would seem desir-

able to describe the characteristics, inoluding measured interests,

of junior college students as well as senior oollege students.

Beoause junior college students have less time than their 4 year

counterparts in which to make decisions about their curriculum

choices, it oan be argued that the need for better information

about curriculum choices is greater for the junior college than

for the typioal senior college.

PROCEDURE

Sample: The total sample wss comprised of 130 junior col-

lege students in five different curricula at Alfred Agricultural

and Technical College, Alfred, New York.* Men students in three

curricula were tested on the SVIB (1966 revision), and women

students in two curricula were tested on the SVIB (q). The

three men's ourrioula were (a) Design and Drafting (N = 20), (h)

Engineering Science (N = 14) and (o) "Agriculture" (Ii = 22). The

two women's 'curricula were (a) Pursing (N = 39) and (b) Medical

Laboratory Teohnioian (N = 35). The students were in the second

year (1968-69) of a two-year program. No attempt was made to

*Acknowledgment is hereby made of the assistance provided by Dr.

George Herrick, Director and Dr. Joan Blankenship, Counselor ofAlfred State College in making this study possible.

P. 3

give the BVIB to those students who had entered these ourrioula

as freshmen in 1967-68 but had dropped out of school or trans-

ferred to other ourrioula.

Analysis of the data: For each of the five groups, means

and standard deviations for each of the oocupational scales of

the BVIB were computed. Tilton's (1937) index of overlap was

used to determine the percentage of overlap for each occupational

scale for each of the three comparisons between men's groups,

and for the two women's groups. Also, on the basis of inspeotion

of the mean profiles, various combinations of several different

scales were selected for multi-scale analyses as opposed to a

single scale, "one-at-a-time" approach.

Results: The means and standard deviations for eaoh of the

three men's groups are presented in Table 1; the means and stand-

ard deviations for the two women's groups are presented in Table

2. The mean profiles for each of the four sets of scores are

presented graphically In Figures 1, 2, 3, and 4. The percentages

of overlap for the men's groups are presented in Table 3; for

the two women's groups, overlap percentages are presented in

Table 4.

The extent to which the three men's groups and the two

women's groups are differentiated by their measured interests

is discussed below.

DISCUSSION

Campbell 0960 has stated that "the statistic usually used

to measure the differentiation of groups by an interest sofas

is Tilton's overlap, which given the percentage of scores in

AMA - 1970TABLE 1

.1.1

SVIB (1966 revision) Means and Standard Deviations for ThreeDifferent Curriculum Groups of Junior College Students (Nen)

--------.-.

SVIBOccupational

Scales

:'agriculture

(N . 22)Mean S.D.

Dentist 37 9Osteopath 33 7Veterinarian 50 5Physician 33 10Psychiatrist 13 7Psychologist 16 6Biologist 25 11Architect 31 10Mathematician 19 10Physicist 21 10Chemist 25 11Engineer 30 10Production Manager 36 10Army Officer 26 11Air Porce Officer 28 8Carpenter. 38 7Forest Service Man 37 9Farmer 52 6Math-Science Teacher 27 9Printer 42 7Policeman 29Personnel Director 13 122Public Wministrater 24 12Rehabilitation Cowes, 18 9YMCA Seeretary 25 12Social Worker 14 12Social Science Teacher 28 9School Superintendent 9 9Minister 1 10Librarian 17 8Artist 33 10Musician Performer 34 8Music Teacher 21 9C.P.A. Owner 15 8Senior C.P,A.Accountant

2219

910

Office Worker 24 8Purchasing Agent 37 8Banker 32 7Pharmacist 35 5Mortician 3.Sales Manager 28 5Real Estate Salesman 39 7Life Ins, SalesmanAdvertising Nan

3028

88

LawyerAuthor-JournalistPresident - Mfg,Credit ManagerChamber of Comp Exec,

3132242472

9,

81 1

9

Physical Therapist 35 11Computer IrogrammerBusiness Ed, Teacher

2527

89

Community Rec. Admin. 25 13.* ....... . 46. 16. .-

Design and EngineeringDrafting Science

20) (N . 14)Mean S.D, Mean S.D.

34 1429 932 1029 1218 824 728 938 1426 1231 1140 1042 1142 934 1542 1242 1223 1340 1235 1039 102 8185

1424 1322 13

1414 1318 8

...11133 1133 1434 1233 1523 1525 930 1429 1023 929 1139 1238 1038 1139 1445 1034 1730112

141;

33 1224 118 1228 1223 1227 5

171514

19 94 1 122 12

0 84 14

21 9 19 1035 13 28 73.) 9 32 820 9 16 101832 11 3 10

21 10

27 7 25 1127 7 25 1159 7 33 1127 8 229 7 32

588

28 6 25 824 8 23 833 6 30 620 5 19 926 9 19 822 7 23 829 10 24 626 9 20 8

215

2729 11

10 103 13 40 1143 10 49 11

21 1229 11

16 24 15

- - --- . Alb

S. E. Smith p.APO,: - 1970

TABLI3 2

SVIB 6) Neanc and Standard Deviationc for TwoDifferent Curriculwa Groups of Junior College Students (Women)

Nursing

(N x 39)ean S.D.

MedicalTechnician(N m

Mean

Lab.

35)S.D.

am. a

SVIBOccupational

Scale

Lusic Teacher 24 13 16 11Nusic Performer 36 11 29 9Artist 33 9 33 9Author 30 11 28 9Librarian 23 9 24 8English Teacher 14 12 12 12Social-Science Teacher 10 11 11 13YWC.:. Staff Member 9 10 8 12Social 'orker 31 9 27 11neychologist 16 11 23 10Ikwyer 13 8 17 10Life ins. Sal:iswoman 13 8 12 9BuyeV 23 7 18 9Bus. Education Teacher 22 9 21 7Stenographer-Secretary 36 7 32 5Office \ ?orker 33 9 33 7elementary Teacher 32 10 27 10Housewife 38 8 33 8Home Econ. Teacher 26 13 26 11

Dietician 28 10 31 8

Phys. 2d, Teacher 30 10 30 9p.G.)Phys. Ed, Teacher Coll,) 14 13 21 13

Occupational Therapist 37 10 33 12Physical Therapist 3? 8 41 9Nurse 34 9 31 12Physician 26 9 34 7

Dentist 26 3 32 6

Laboratory Technician 31 10 41 8

Math-Science Teacher 20 10 30 11

Engineer 13 9 26 10

Sister Teacher 24 10 24 9

Speech Pathologist 30 13 31 11

Computer Programmer 23 10 34 8

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L_J E.= L-2-3 ED,Neon Profiles for 35 Medleal Laboratory taobnioions andStudents

39 Horsing

S. E. Smith p. 10APGA - 1970

.111

TABLE 3

PERCENTAGES OF OVERLAP BETWEEN THE THREE MEWS GROUPS

SVIBOccupational

Scales

Agriculturevs

EngineeringScience

Design andDrafting

vsEngineering

Science

Agriculturevs

Design andDrafting

Dentist 84 97 89Osteopath 100 85 81Veterinarian 33 93 28Physician 100 88 86Psychiatrist 65 78 76Psychologist 59 95 68Biologist 84 92 88Architect 92 71 78Mathematician 83 89 75Physicist 69 93 65

Chemist 53 96 44Engineer 69 84 54

Production Manager 91 84 74

Army Officer 59 87 76

Air Force Officer 35 89 48Carpenter 87 84 83

Forest Service Man 70 80 53Farmer 47 97 51Math-Science Teacher 45 64 66

Printer 62 78 86policeman 80 96 81

Personnel Director 84 100 85

Public Administrator 87 87 100

Rehabilitation Couns. 81 97 83

YMCA Secretary 100 89 87Social Worker 91 91 100

Social Science Teacher 62 95 55School Superintendent 96 86 80

Minister 91 94 96

Librarian 91 91 86

Artist 77 73 93Musician Performer 90 81 91Music Teacher 78 83 96

C.P.A. Owner 74 87 86

Senior C.P.A. 52 88 62

Accountant 76 91 62

Office Worker 96 91 87

Purchasing Agent 85 74 90

Banker 62 90 80

Pharmacist 83 83 62

Mortician 36 92 43

Sales Manager 67 92 73Real Estate Salesman 46 80 62

Life Ins. Salesman 5 94 74

Adverti..,!ng Man 66 67 91

Lawyer 62 94 54

Author-Journalist 61 76 87

President - Mfg. 80 72 90

Credit Manager 78 88 97

Chamber of Com. Exec. 100 92 91Physical Therapist 78 81 97

Computer Programmer 23 76 32

Business Ed. Teacher 92 93 100

Community Rec. Admin. 97 91 78

S. E. Smith. APGA - 1970

TABLE 4

PERCENTAGES OF OVERLAP BETWEEN THE TWO WOMEN'S GROUPS

p. 11

SVIBOccupational

Scales

Medical Lab.technician

vs

Nursing

Music Teacher 74Music Performer 73Artist 100Author 92Librarian 95English Teacher 93Social-Science Teacher 97YWCA Staff Member 96Social Worker 84Psychologist 71Lawyer 83Life Ins. Saleswoman 95Buyer 75Bus. Education Teacher 95Stenographer-Secretary 75Office Worker 100Elementary Teacher 80Housewife 75Home Econ. Teacher 100Dietician 87Phys. Ed. Teacher (H.S.) 100Phys. Ed. Teacher (Coll.) 79Occupational Therapist 66Physical Therapist 80Nurse 87Physician 62Dentist 67Laboratory Technician 58Math-Science Teacher 63Engineer 50Sister Teacher 100Speech Pathologist 97Computer Programmer 55

p. 12

one distribution which can be matched scores in the other

distribution." Although Strong (1959) used the percentage of

overlap measure in reporting on the validity of his scales,

and Campbell (1968) has used it to compare the effectiveness of

two recently developed scales, there does not seem to be a fixed

percentage of overlap which is accepted as the criterion of

"good separation." In one discussion of overlap, Campbell (1966,

p. 34) states that the Physicist scale separates "rather well"

chemists from physicists on the basis of a percentage of overlap

of "roughly 55 percent." This percentage of overlap (55%) has

been used in this study to indicate "the criterion for good sepa-

ration." In other words, if on a given scale, Group A's scores

overlap Group B's by 55% or less, Group A is said to have dif-

ferent measured interests than Group B.

The Agriculture students have different measured interests

from the Design and Drafting students, and from Engineering

students. The Agriculture students' scores overlap the Design

and Drafting students' scores 55% or less on the following ten

scales: Veterinarian, Chemist, Engineer, Air Force Officer,

Forest Service Man, Farmer, Social Science Teacher, Mortician,

Lawyer, and Computer Programmer. The Agriculture students over-

lap the Engineering Science students 55% or less on the follow-

ing ten scales: Veterinarian, Chemist, Air Force Officer,

Farmer, Math-Science Teacher,Senior C.P.A., Mortician, Real

Estate Salesman, Life Insurance Salesman, and Computer Programmer.

On the basis of percentage of overlap, the Design and Draft-

ing studensts and the Engineering Science students have similar

P. 13

measured interests. As ocm, be seen in Table 3, 23 of the 54 scales

overlap 904 or more. Thq scale with the least overlap (64%) is Math-

Science Teacher.

The Medical laboratory Technician and Nursing students have

similar measured interests on 32 of the 34 scales. On the Engineer

scale, the overlap is 504; nn Computer Programmer the amount of overlap

is 554 (see Table 4).

At this point, it should be noted that the sample sizes, especially

for the three men's groups. are small. Many of the differences presumably

are the result of considerable chance factors. On the other hand, there

is some evidenoe that sugg$sts that the mean scores for these samples

are quite stable. The Agriculture and the Design and Drafting means

were compared with mean scores obtained for Agriculture and Design and

Drafting students who were 'ested under comparable conditions the

previous year (1968). For the two Agriculture groups, on 48 of the 54

scales, the difference betroan means was 3 points or less; the largest

difference was 7 points. In a like fashion, the 1969 Design and Drafting

(N = 20) means were compare0 to a 1968 sample (N = 44). For 48 scales

the mean difference was 3 points or less; the largest difference was 6

points,

For the women, no comparison sample of Alfred students was avail-

able. A comparison with another two-year college sample of nursing

students indicated that the profiles were very similar.

The overlap method of comparison, as used in this study,

compares one scale at a time versus a multi -scale or Alonfigural"

approach. A multi scale approach was used with several combinations

of scales to ascertain if this method could "differentiate

ID. 14

better" than the conventional overlap method between the respec-

tive pairs of groups. The results of a study by Dunnette (1957)

suggested that scoring keys based upon an inspection of mean

differences (versus scoring keys developed by item-analysis)

could be developed.

In the present study, the multi-scale analysis was applied

only to the Design and Drafting and Engineering Science compar-

isons. Based essentially upon percentages of overlap, several

different combinations of scales were tried. Two such combina-

tions are reported in this paper. A "Design and Drafting key,"

based upon the differences between the Architect and Biologist

scores, was used. For the "Engineering Science key," President,

Mfg., and Computer Programmer scales were used.

The Design and Drafting key, developed upon the 1969 sam-

ple (N = 20), "correctly identified" 15 (75%) of the 20 Design

and Drafting students. The same key, when applied to the Engi-

neering Science scores, "incorrectly identified" 4 of the 14

Engineering Science students as Design and Drafting students.

The Engineering Science key was not as effective; 9 (64%) of

the 14 Engineering Science students were correctly identified.

When the Engineering Science key was applied to the Design and

Drafting students, it incorrectly identified 5 of the 15 as

Engineering Science students.

The Design and Drafting key was cross-validated on the 1968

sample of Design and Drafting students (N = 44). Twenty-nine

(66%) of the 44 students were correctly identified. The Engi-

neering Science key was also applied to the 1968 Design and

P. 15

Drafting sample. Eleven of the 44 students were incorreotly identified

as Engineering Science students. No sample of Engineering Science students

was available for cross-validation.

In the writer's view, the differentiation resulting from the applica-

tion of the two spools' keys, each based upon only two soales, was fairly

good, In other words, although the Design and Drafting students were not

differentiated from Engineering Science students on the basis of conventional

scale by scale comparisons, a multi-scale, or "oonfigural, approach pro-

duced fairly good differentiation. Obviously, studies based on larger

samples are needed to determine tho effectiveness of the multi-scale

approach.

SUMMARY

Means and standard deviations for students in five different junior

college curricula were presented. Measures of overlap were also presented.

A non-conventional multi-scale approach was discussed.

REFERENCES

Harmon, L. E. & Campbell. D. P. Use of interest inventories with non-professional women: stewardesses versus dental assistants.aurzaloljaunielingayeliology, 1968; 15, 17-22.

Campbell, D. P. lignualgotnng Vocational Tnterest Blanks.Stanford: Stanford University Press, 1966.

Darley, J. G. & Hagenah, T. bratianalWarStALEMBSV92111Minneapolis: University of Minnesota Press, 1955.

Dunnette, M. D. Vocational interest differences among engineers employedin different functions, gPurnal of Applied Psvoboloav, 1957, 41,273-278.

p. 16

Stewart, L. H. Characteristics of junior college students inoccupationally orientediqurricula. Journal of CounselingtayshRlom, 1966, 13, 46-52,.

Strong, E. K., Jr. Manual - Stronj Vocational Interest Blank.Palo Alto: Consulting Psychologists Press, 1959.

Strong, E. K., Jr. Vocational interests 18 yearsafter college.Minneapolis: University of Minnesota Press, 1955.

Taylor, R. G. and Hecker, D.L. Interest and intellectual indioearelated to successful and non-successful male collem stu-dents in technical and associate degree programs. UnitedStates Department of Health, Education and Welfare, 1967.

Taylor, R. G. and Bondy, S. B. Interest patterns of male tradeand industrial and collegiate technical graduates. Voca-tional Guidance_auarLarly, 1966, 14, 57-60.

Tilton, J. W. Measurement of overlapping. Journal of EducationalPsychology, 1937, 28, 656-662.