Melbourne Graduate School of Education - Theses

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    The effects of schools on achievement in science
    Owen, John M (1943-) ( 1975)
    The study sought to identify factors which were based in schools which affected the performance of sixth form students in science in Victorian schools, In order to identify school effects, allowance was made using multiple regression analysis for factors which were shown to contribute to academic performance but were those over which the school had no control. Use was made of information collected during a. study of science achievement by the International Association for the Evaluation of Educational Achievement (IEA). A sample of 37 schools was used the probability of selection of the school was proportional to its enrolment. Within each school, a random sample of students in the sixth form was made to select the students to take part in the testing program. Information collected enabled a predicted score for each school to be made and this was compared with the actual score obtained by averaging the scores of each student in the sample. Two groups of five schools were then selected for comparative study; one group which had performed better than expected and the other which had performed below expectations. The comparison of the two groups of schools to identify school factors was achieved by the study of the responses of teachers, students and school principals on survey instruments. In addition a visit was made to each school to gather further information. These procedures enabled the identification of school characteristics which were seen as contributing factors to the performance of students on tests of science achievement.
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    Distinguishing the science content taken by grade 12 students
    Cross, R. J. ( 1977)
    The population of grade 12 students in Australian secondary schools has been steadily increasing over the past two decades. For most of this period the percentage of students at this level choosing science-type courses has been decreasing, and recently the actual number taking physics and chemistry has declined in some states. This study aimed to find a set of variables that would maximize the prediction of grade 12 student science content. Emphasis was directed toward identification of science talented students not opting for high science content in grade 12, and, equally as important, those of low science ability who select predominantly science courses at this level. It was proposed that the variables could be measures of any area likely to be related to the criterion. For example, factors associated with the home, the school, and personal measures were all included. The variable set was then searched for that combination returning optimal criterion prediction. Attention was focussed on six main units of analysis viz males, males of higher science ability, males of lower science ability, females, females of higher science ability, females of lower science ability. The data in each unit was subjected to both discriminant (stepwise and direct) analysis and a process similar to a stepwise regression procedure called the Automatic Interaction Detector (AID). AID employs a branching process using variance analysis to subdivide the sample into subgroups which maximize dependent variable value prediction. The International Association for the Evaluation of Educational Achievement (IEA) conducted a series of tests on a stratified random sample of grade 12 students throughout Australia in 1970. The results, held at ACER, included measures of some 418 variables thirty four of which were selected for this investigation. Included in this group were the results of the four Commonwealth Secondary Scholarship Examination (CSSE) ability tests taken two years earlier. Analysis units were formed on the basis of sex and CSSE - Science score. The results indicate successful science content prediction is possible with the personal or internal variables of science interest, attitudes and abilities, consistently being of greatest importance. The participating external variables vary depending on the unit of analysis. The non-monotonic "State" and "Type of School" factors are predominant in AID analyses.
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    A comparison of the educational set of students in two introductory physics courses
    Blazely, Lloyd David ( 1972)
    The P.S.S.C. physics course and a traditional physics course taught in Tasmania were examined for differences in aims that might lead to differences in the educational set developed in students taking the two courses. A six-category model of educational set in physics involving recall of specifics, practical applications, mathematical generalizations, verbal generalizations, constructive criticism and destructive criticism was developed and a 24 item test instrument (Test E.S. (Physics)) constructed, subsequent to two different trials. Test E.S. (Physics), the Educational Set Scale of Siegal and Siegal and tests AL and AQ were administered to a sample of 389 students made up as follows:- Form IV - 97 in Tasmania and 58 in Victoria Form V - 49 in Tasmania and 82 in Victoria Form VI - 51 in Tasmania and 50 in Victoria Classes from two schools were included in each sub-sample. AL plus AQ was used as the covariate and the appropriate corrections were made before the technique of planned comparisons was used in a variety of within-state and between-state comparisons. The only significant between-state difference detected was in the categories of mathematical generalization. Within each state the comparison between Form IV students and students in later years resulted in significant differences in all comparison except for category 1 (specific facts). A number of correlations were investigated without any clear pattern emerging although category 3 (mathematical generalizations) was involved in several significant correlations. An off-shoot of the major study lead to the development of an Education Set Test based on Bloom's Taxonomy of Educational Objectives. The administration of the test gave results consistent with the order between categories suggested by the Bloom model. The major finding of the study was that both physics courses probably produced significant changes in students' educational set but these changes did not seem to be consistent with the differences between their aims.