Scientific Literacy and School Characteristics

Scientific Literacy and School CharacteristicsJohn B. Leake

University of Missouri-Columbia, Columbia, Missouri 65201

Charles 0. HinermanCentral Missouri State College, Warrensburg, Missouri 64093

INTRODUCTIONIn the past decade a growing number of people representing many

diverse professions have become concerned with the need for whathas been termed a scientifically literate citizenry.More than half the citizens of this country get no formal education *

beyond high school. These same people will make direct decisionsconcerning scientific matters on a personal basis and indirect decisionson a national basis at the ballot box. It seemed imperative that somemeasure of their scientific literacy be made, and that school charac-teristics associated with scientific literacy be identified.

THE PROBLEMThe purpose of this study was to determine the level of achievement

attained on two referents of scientific literacy by graduating seniorsfrom Missouri Public High Schools as indicated by scores on theSequential Tests of Educational Progress: Science, and the WisconsinInventory of Science Processes.Subproblems investigated,

1. The degree of relationship between student scores earned on the STEP instrument,and;a. total school enrollment in grades 10-12.b. percent of seniors of each school going on to higher education.c. average salary of science teachers.d. annual budget for science per student enrolled.e. number of science credits required for graduation.f. average size of science class.

2. The degree of relationship between student scores earned on the WISP instrument,and;a. total school enrollment in grades 10-12.b. percent of seniors of each school going on to higher education.c. the average salary of science teachers.d. annual budget for science per student enrolled.e. number of science credits required for graduation.f. average size of science class.

3. To determine whether a significant difference exists among:a. the mean WISP scores from various geographic areas.b. the mean STEP scores from various geographic areas.

Harvard Project Physics, Newsletter 7 (Cambridge: Harvard University, 1968).

772

Scientific Literacy and School Characteristics 773

DESIGN AND EXPERIMENTAL PROCEDURES

A sample of graduating high school seniors was obtained by randomlyselecting small, medium, and large high schools from each of thefive state college districts. The schools were designated as small ifthey graduated less than 100 seniors per year, medium if they graduatedat least 100 but less than 300, and large if the number of graduatingseniors was 300 or over.

INSTRUMENTS USED IN THE STUDYTwo instruments were selected for assessing the level of achievement

on the two referents of scientific literacy investigated in this study.The Sequential Tests of Educational Progress (STEP) is a series ofachievement tests designed to appraise the development of generalcomprehension and reasoning abilities in the major subject matterareas2. The science sections of this series, Science Forms 4A, 3A,2A, and 1A purport not to measure facts but the ability to use scientificknowledge3. The questions are for the most part based on "real life’problem situations. The subject matter content is drawn from all theconventional branches of natural science. The highest possible scoreis 60.The Wisconsin Inventory of Science Processes is itself an experi-

mental instrument4. In its various developmental forms it has beenadministered to high school students, elementary teachers, high schoolscience teachers and research scientists. The instrument satisfactorilydiscriminates in the expected direction. The items of the instrumentwere validated by submitting them to 56 University of Wisconsinprofessors who participated in the National Science Foundationsponsored Research Participation Program5.The instrument purportsnot to measure science subject matter knowledge but a knowledgeof the processes of science. The highest possible score on thisinstrument is 93.A school questionnaire was utilized to obtain information on factors

associated with scores earned on the STEP and WISP instruments.This questionnaire provided information about the variables of totalschool enrollment grades 10-12, percent of seniors going on to highereducation, average salary of science teachers, annual budget for science

2. Arthur E. Traxler and Robert D. North, "The Selection and Use of Tests in a School Testing Programin the Impact and Improvement of School Testing Programs," 62nd Yearbook of the National Society for theStudy of Education (Chicago: The University of Chicago Press, 1963).

3. William D. Hedges and Mary MacDougal, "Teaching Fourth Grade Science by Means of Programmed ScienceMaterials with Laboratory Experiences Phase III," Science Education, 49 (1965), 348-358.

4. Frank A. Wittwer, "An Evaluation of the National Science Foundation Research Participation Program forHigh School Teachers at the University of Wisconsin," (unpublished Ph.D. dissertation, University of Wisconsin,1967).

5. Wittwer. loc. cit.

774 School Science and Mathematics

per student enrolled, number of science credits required for graduation,average science class size, and other school characteristics not utilizedin this study.

ANALYTICAL PROCEDURES

The degree of relationship between WISP scores and total schoolenrollment grades 10-12, percent of seniors going on to highereducation, average salary of science teachers, annual budget for scienceper student enrolled, number of science credits required for graduation,average size of science classes, and STEP scores and the same variableswas examined by utilizing product moment correlations and regressionanalysis.

In order to determine whether STEP scores are more closelycorrelated with the six school variables than the WISP scores, thefollowing hypothesis was tested:There is no significant difference between correlation coefficients

of STEP and WISP scores with any of the six school variables studied.This hypothesis was tested by means of a ( test for correlation

coefficients described by Walker and Lev6.The total amount of variance of STEP scores and WISP scores

accounted for by the six variables was ascertained by utilizingregression analysis methods7.Comparisons of the contributions of the six variables studied to

the variance of STEP and WISP scores were also made by rankingthem in descending order of the amount of variance contributed toeach of the criterion measures.

In order to avoid the error of regarding a variable as insignificantwhen it might indeed be associated with STEP or WISP scores, amultiple regression analysis was performed. This statistical modelenables one to assess the amount of variation in criterion scoresassociated with these variables, and also to determine which of thevariables probably make a unique contribution to predicting thecriterion measure8. The STEP and WISP scores were utilized ascriterion measures.

Results

STEP scores were obtained for each student in the sample. Themean was computed to be 28.93 and the school mean of the nationalnorms is 27.509.

6. Helen Walker and Joseph Lev, Statistical Inference (New York: Henry Holt and Company, 1953).7. Francis Kelly, Donald Beggs, Keith McNeil, Tony Eichelberger and Judy Lyon, Multiple Regression Approach

(Carbondale: Southern Illinois University Press, 1969).8. William Cooley, "Project Talent Implications for Science Education." Journal of Research in Science Teaching,

3(1965), 211-215.9. Educational Testing Service, Sequential Tests of Educational Programs, Manual for Interpreting Scores, Science

(Princeton: New Jersey, 1957).


It is possible to statistically determine whether the differencebetween two sample means is significant, however, when the numberof cases is as large as the number (4693) in this study a very smalldifference in means becomes statistically significant, primarily dueto the large number of degrees of freedom used in tests of significance.It is therefore doubtful if the difference has any practical value10.A more realistic comparison of means can be made by regardingthe national norm mean as the true population mean.The standard error of the mean for the sample is

0 7.9725SE^ = �� = �� = .117

VN V4693"

In a sampling distribution of means 99.73% will fall within –3^.The confidence interval is computed to be .117 x 3 = .35; 28.93– .35 or 28.58 to 29.28.

Since the population mean would be expected to fall within theinterval 28.58 - 29.28, 99.73% of the time; and since the populationmean, 27.5, clearly does not fall in the 99.73% confidence interval,it is concluded that the mean STEP score for the sample is significantlyhigher than the national norm mean.

ACHIEVEMENT AS MEASURED BY THE WISP INSTRUMENT

The WISP instrument is an experimental instrument and no nationalnorms are available. Jaffarian11, however, utilized the instrument tomeasure the level of achievement attained on the processes andassumptions of science by a sample of twelfth grade students inWisconsin.A comparison was made between the Jaffarian-Wisconsin data and

the Missouri data utilized in this study.It was noted that the mean score of the Missouri sample was 2.60

points below the Wisconsin sample and that the standard deviationof the Missouri data was 1.96 greater than the Wisconsin data.A comparison of significant differences was made by calculating

a two tailed t test according to Garrett12. The critical ratio exceeds2.58 (critical value for t at a .01) and the difference in mean scoresin favor of Wisconsin is therefore significant at the .01 level.The mean STEP scores earned by students in schools with a mean

10. Willard North, Personal conversation. Research and Testing Center, Central Missouri State College, Warrens-burg, Missouri 64093.

11. William Armand Jaffarian, "An Evaluation of the Relative Levels of Scientific Literacy Possessed by TwelfthGrade Students," (Unpublished Ph.D. Thesis, Madison: Wiscon, University of Wisconsin, 1968).

12. Garrett, Henry E. Statistics in Psychology and Education. New York: David McKay Co., Inc., 1966.


science class size of less than 10 were slightly higher than thoseof students in schools where the mean science class size was 10or greater. It is interesting to note that 86.67% of the sample attendedschools where the mean science class size ranged from 20 to 29.There seems to be little or no relationship between mean STEP

scores and mean annual science teachers salaries. Nearly half (48.51%)of the students in the sample attended schools in which the meanannual science teachers salary ranged from $6000.00 to $6999.00.The highest mean STEP score was earned by students in schools

with the highest total enrollment included in the sample, however,the lowest mean STEP was not earned by students in schools withthe smallest total enrollment. In fact there seems to be little or norelationship between total enrollment and mean STEP scores.Over half the students (52%) in the sample attended schools which

spend less than $2.00 annually per student enrolled for science.Teachers salaries and textbooks are excluded. It was noted that thelowest mean STEP scores were earned by students in schools whoseannual expenditures for science were in excess of $22.00.There is little difference in the mean STEP scores earned by students

in other annual expenditure categories.Students attending schools in which over 50% or less than 10%

of the seniors go to college earned the highest mean STEP scores.The lowest mean STEP score was earned by students attending schoolsin which 10 to 20% of the seniors go to college. Approximately 27%of the students attend schools in which 10 to 20% of the seniorsgo to college.Approximately 97% of the sample attended schools requiring only

1 credit in science for graduation. No students attended a schoolrequiring more than two credits in science, and there is essentiallyno difference in mean STEP scores between the schools with the1 and 2 credit requirements.The degree of linear association of STEP scores with values of

the 6 variables of the study was ascertained by computing the productmoment correlation coefficients according to Ostle13. These correlationcoefficients are noted in Table 1 along with the means and standarddeviations of the variables.

In order to decide whether a given correlation coefficient indicateda significant linear relationship, the hypothesis that the sample waschosen from a population for which the correlation coefficient p =

0, was tested utilizing Student’s t test according to Alder and Roessler14.

13. Ostle, Barnard. Statistics in Research. Ames: The Iowa State University Press, 1963.14. Henry L. Alder and Edward B. Roessler, Introduction to Probability and Statistics (New York: W. H.

Freeman and Company, 1968).


TABLE 1: CORRELATIONS OF SELECTED VARIABLES WITH STEP SCORESa

Standard CorrelationVariable Mean Deviation Coefficient t^

Mean science class size 23.82 3.93 -.02 1.4015Mean annual science teachers

salary 7045.70 1285.60 .00 .OO1’Enrollment grades 10-12 1020.90 734.10 .09 6.26Annual expenditures for

science per student $ 3.08 3.40 .00 .OO1’Percent of seniors going to

college 31.00 18.00 .13 9.04Credits of science required

for graduation 1.03 .16 .00 .OO11

a. N = 4693b. These values are not significant at the .05 levelc. Critical value for t at a = .05 is 2.58

The results of these t tests indicate no significant linear correlationsbetween STEP scores and (a) mean science class size, (b) mean annualsalary of science teachers, (c) credits in science required for graduation,and (d) annual expenditure for science per student. The variablesof enrollment grades 10-12 and percent of seniors going on to collegeare correlated with STEP scores, however, the correlation is verylow.

TABLE 2: PERCENT OF VARIANCE OF STEP SCORES CONTRIBUTED BY SELECTED VARIABLES

Variable (B x r Percent

Mean science class sizeMean annual salary of science teachersEnrollment grades 10-12Annual expenditures for science per studentPercent of seniors going on to collegeCredits of science required for graduation

.00000.0

.00050.0

.00400.4

.00010.1

.00790.7

.00000.0

It is noted from Table 2 that the variables of mean science classsize, mean annual salary of science teachers, and credits of sciencerequired for graduation make no contribution to the variance of theSTEP scores. The variables of enrollment grades 10-12, annualexpenditures for science per student and percent of seniors goingon to college collectively can account for only 1.2% of the variance.

Students who earned the highest mean WISP scores attended schoolswhere the mean science class size was 20-29 and students who earnedthe lowest mean WISP scores attended schools where the mean scienceclass size was 9 or less.


The data seem to indicate no regular relationship between meanWISP scores and the mean annual salary of the science teachers.It was noted however, that the highest mean WISP scores were earnedby students in schools where the mean annual salary of the scienceteacher was $7000-7999 and the lowest mean WISP scores were earnedby students in schools where the mean annual salary of the scienceteacher was $4000-4999.

It was interesting to note that the mean WISP scores earned bystudents in all the schools were about the same except for thosein the 1200-1399 enrollment group.The absence of relationship between the annual expenditures for

science per student and the mean WISP scores of students wasobserved. The highest mean WISP score was earned in schools withan annual expenditure for science per student enrolled of $10.00-11.99and the lowest score was earned in schools with an annual expenditurefor science per student enrolled of $22.00-23.99. Slightly less than10% of the students in the sample attended schools with annualexpenditures for science per student enrolled of more than $6.00.

Analysis of the data indicates little or no relationship between meanWISP scores and percent of seniors going to college. It is notedthat those students in which 0-9% and 50-59% of the seniors goto college earned the highest mean WISP scores.

Students who attended schools that required only 1 credit of sciencefor graduation earned a higher mean score (51.53) than students inschools that required 2 credits of science for graduation. It was notedhowever, that the latter group of students constitute only 2.59% ofthe sample.

TABLE 3: CORRELATIONS OF SELECTED VARIABLES WITH WISP SCORES

Standard CorrelationVariable Mean Deviation Coefficient t°

Mean science class size 23.82 3.93 .08 5.26Mean annual science teachers

salary 7045.70 1285.60 -.03 2.2815Enrollment grades 10-12 1020.90 734.10 .07 4.79Annual expenditures for

science per student 3.08 3.40 -.07 4.79Percent of seniors going to

college 31.00 18.00 .04 2.86Credits of science required

for graduation 1.03 .16 -.05 3.32

a. Critical value for t at a.05 is 2.58b. Not significant at .05 level

It is noted from Table 3 that there is no significant linear correlationbetween WISP scores and mean annual salary of science teachers.


The coefficient of multiple correlation (R) for the 6 variables andWISP scores is .078. The contribution of these variables to the varianceof the WISP scores is therefore 2.8%. The total variance contributedby each variable is summarized in Table 3.

TABLE 4: PERCENT OF VARIANCE OF WISP SCORES CONTRIBUTED BY SELECTED VARIABLES

Variable (S x r Percent

Mean science class sizeMean annual salary salary of science teachersEnrollment grades 10-12Annual expenditures for science per studentPercent of seniors going to collegeCredits of science required for graduation

.01021.0

.00600.6

.00000.0

.00790.8

.00230.2

.00170.2

Of the 2.8% variance contributed by the six variables, one percentmay be attributed to mean science class size. Mean annual salaryof science teachers, enrollment in grades 10-12, annual expendituresfor science per student, percent of seniors going on to college andcredits of science required for graduation each contributed less than1% of the variance in WISP scores.

STEP SCORES AND WISP SCORES AS RELATED TO GEOGRAPHIC AREASFrom the STEP and WISP scores listed for the five state college

districts shown in Table 5, it is noted that the mean WISP scoresrange from 49.95 in District 5 to 54.00 in District 3 and that theSTEP scores range from 27.97 in District 4 to 30.67 in District 3.

TABLE 5: MEAN STEP AND WISP SCORES BY COLLEGE DISTRICT

College DistrictMeanSTEPMean WISP

1. Northeast2. Central3. Northwest4. Southwest5. Southeast

Total Sample

29.6229.6030.6727.9728.3228.93

51.0952.8654.0051.8249.9551.44

In order to determine whether any of these differences betweendistricts were significant one way analyses of variances were per-formed, which revealed variations in both STEP and WISP scorestoo great to be attributed to chance.The sources of variation were identified by utilizing Scheffe’s

procedure15 as a post hoc test.

15. John T. Roscoe, Fundamental Research Statistics for the Behavioral Science (New York: Holt, Rinehart,and Winston, 1969).


TABLE 6: SUMMARY TABLE FOR THE ANALYSIS OF VARIANCE OF STEP SCORES�ALPHA .01

Sourcessdfms F F(critical)

Between districts3958.904989.73 15.76 13.46Within294268.01468762.78

TABLE 7: SUMMARY TABLE FOR THE ANALYSIS OF VARIANCE OF WISP SCORES�ALPHA .01

Source ss df ms F F(critical)

Between districts 8801.30 4 2200.31 16.10 13.46Within 640447.61 4687 136.64

TABLE 8: COMPARISON OF MEAN STEP SCORES OF COLLEGE DISTRICTS

College District Southwest Southeast Central Northeast Northwest

Mean STEPScore 27.97 28.32 29.60 29.62 30.67

TABLE 9: COMPARISON OF MEAN WISP SCORES OF COLLEGE DISTRICTS

College District Southeast Northeast Southwest Central Northwest

Mean WISPScore 49.95 51.09 51.82 52.86 54.00

The results of the Scheffe’ procedure are summarized in Tables8 and 9. Any two means underscored by the same line are notsignificantly different and conversely any two means not underscoredby the same line are significantly different.

Table 8 indicates that the mean STEP scores earned by studentsin the Central, Northwest, and Northeast college districts do not differsignificantly and that the mean STEP scores of these students dodiffer significantly from the mean STEP scores earned by studentsin the Southwest and Southeast college districts.An examination of Table 9 reveals that the mean WISP score earned

by students in the Northwest college district differs significantly fromthe mean WISP scores earned by students in any of the other Missouricollege districts except Central. This table also indicates that the mean


WISP score earned by students in the Southeast district is significantlylower than the mean WISP scores earned by students in all otherdistricts except Northwest.

SUMMARY AND CONCLUSIONSThis study was undertaken primarily to determine the level of

achievement attained on two referents of scientific literacy by graduat-ing seniors from Missouri Public High Schools.

Scores on the science section of the Sequential Tests of EducationalProgress (STEP) were regarded as indicators of achievement on theconceptual knowledge referent. Scores on the Wisconsin Inventoryof Science Processes (WISP) were regarded as indicators of achieve-ment on the process of science referent.A number of school factors which could conceivably be associated

with achievement as measured by STEP and WISP scores wereinvestigated. The factors were (a) total school enrollment in grades10-12, (b) percent of seniors going to college, (c) mean annual salaryof science teachers, (d) annual expenditures for science per studentenrolled, (e) credits of science required for graduation, and (f) meanscience class size.

Since the State of Missouri varies widely in topography and inthe socio-economic development of certain areas, the relationshipbetween the geographic areas served by the five state colleges andachievement as measured by STEP and WISP scores was investigated.On the basis of this research and subject to the assumptions and

limitations of the study the following statements appear to be warrent-ed.The level of achievement attained in the conceptual knowledge

referent of scientific literacy as indicated by STEP scores is signifi-cantly greater for the students in the sample utilized in this studythan the national norm.The level of achievement attained on the processes of science

referent of scientific literacy as indicated by WISP scores is signifi-cantly lower for the students utilized in this study than a sampleof Wisconsin students studied by Jaffarian.There is a significant positive correlation between the level of

scientific literacy attained by students as indicated by STEP scoresand percent of seniors going on to college, and enrollment in grades10-12.There is a significant positive correlation between the level of

scientific literacy as indicated by WISP scores and mean scienceclass size, enrollment in grades 10-12, and percent of seniors goingon to college. There is a significant negative correlation between the


level of scientific literacy as measured by WISP scores and creditsin science required for graduation and annual expenditures for scienceper student. No apparent explanation for the negative correlationsis available.The variance of STEP and WISP scores with respect to geographic

area is too great to be attributed to chance. The sources of thisvariance were identified: The mean STEP score of the Southwestand Southeast districts are significantly lower than the Central,Northeast and Northwest districts and the mean WISP scores of theNorthwest district is significantly higher than all other districts exceptCentral.The six variables studied can account for a very small portion

of the variance in STEP and WISP scores. Studies to identify otherfactors associated with a knowledge of science processes and conceptsshould be performed. Controlled experiments designed to indicatecausual relationships cannot be performed efficiently until such factorscan be identified.

REFERENCES

ALDER, HENRY L., AND EDWARD B. ROESSLER. Introduction to Probability and Statistics.San Francisco: W. H. Freeman and Company, 1968.

COOLEY, WILLIAM. "Project Talent Implications for Science Education.^Journal ofResearch in Science Teaching, 3, 1965, 211-215.

EDUCATIONAL TESTING SERVICE. Sequential Tests of Educational Program, Manual forInterpreting Scores, Science. Princeton, New Jersey: Educational Testing Service,1957.

GARRETT, HANRY E. Statistics in Psychology and Education. New York: David McKayCo., Inc., 1966.

HARVARD PROJECT PHYSICS. Newsletter 7. Cambridge: Harvard University, 1968.HEDGES, WILLIAM D. AND MARY MACDOUGAL. ’Teaching Fourth Grade Science by Means

of Programmed Science Materials with Laboratory Experiences Phase III," ScienceEducation, 49, 1965, 348-358.

JAFFARIAN, WILLIAM ARMAND. ’ ’An Evaluation of the Relative Levels of Scientific LiteracyPossessed by Twelfth Grade Students." Unpublished Ph.D. Thesis, Madison, Wis-consin: University of Wisconsin, 1968.

KELLY, FRANCIS, DONALD BEGGS, KEITH MCNEIL, TONY EICHELBERGER, AND JUDY LYON.Multiple Regression Approach. Carbondale: Southern Illinois University Press, 1969.

NORTH, WILLARD. Personal conversation. Research and Testing Center, Central MissouriState College, Warrensburg, Missouri, 1970.

OSTLE, BERNARD. Statistics in Research. Ames: The Iowa State University Press, 1963.ROSCOE, JOHN T. Fundamental Research Statistics for the Behavioral Science. NewYork: Holt, Rinehart and Winston, 1969.

TRAXLER, ARTHUR E. AND ROBERT D. NORTH. "The Selection and Use of Tests in a SchoolTesting Program in the Impact and Improvement of School Testing Programs,"62nd Yearbook of the National Society for the Study of Education. Chicago: TheUniversity of Chicago Press, 1963.

WALKER, HELEN AND JOSEPH LEV. Statistical Inference. New York: Henry Holt andCompany, 1953.

WITTWER, FRANK A. "An Evaluation of the National Science Foundation ResearchParticipation Program for High School Teachers at the University of Wisconsin,"Unpublished Ph.D. Thesis, Madison, Wisconsin: The University of Wisconsin, 1967.

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Scientific Literacy and School Characteristics