# _IV. Conclusions_

78. We are now at the stage where it is possible to answer some of the questions raised in this research. We have found that schooltype differences in English achievement go considerably beyond differences in student intake, whereas for mathematics achievement, once one has controlled for student background variables, schooltype is not a significant discriminating factor. We can account for schooltype differences in English, however, with either class or school level variables. We have found that for mathematics achievement, focussing at the class level is likely to be more productive in influencing achievement, whereas the broader school level focus for English achievement may be more appropriate. We are able to account entirely for between school differences in mathematics on the basis of the variables included in our model. Differences between schools in English achievement, however, remain, after our best attempts at modelling with the variables at hand.

79. What are the handles at our disposal for influencing achievement in either of these two subjects? Not surprisingly, textbooks and trained teachers come up as highly significant variables across both subjects, at both the class and school levels.<sup>2</sup> ' Both trained teachers and the availability of textbooks for mathematics instruction are more important than for English, however, in equalizing disparities across schools, as can be seen first in the individual regressions on achievement and subsequently in the further modelling carried out. More of the variance in mathematics achievement between schools is explained by these variables. In addition, older teachers seem to achieve better results with their charges than new recruits across both subjects. Also, teacher's gender seemed to be a promising variable at first, the pupils of female teachers outperforming those of male teachers. However, once we understood that the variable was describing in fact the urbanicity of the school, further concentration on this variable proved futile, particularly outside the introduction of additional classroom practice variables (not available in this study).

80. Two addit:onal class level variables proved of importance in explaining achievement differences in mathematics, but not in English. The amount of instructional time devoted to mathematics and the number of hours of supervised study given by the teacher were significant. Clearly these are both areas meriting attention by the responsible authorities of the different schooltypes. In particular, supervised study, which has also proved to be a successful non-formal type of education in Zimbabwe through 'study groups"'5, may hold out an inexpensive, supplementary means of raising students' mathematics performance.

81. At the school level, the three variables, the pupil-teacher ratio, the availability of textbooks, and the percentage of trained teachers, proved highly significant across both subjects, explaining more between school differences in mathematics, but accounting for more of the total variance in English.

82. What is of interest in examining the interaction of these different variables with the schooltype variables is the intractable disadvantage of the low-fee-paying and district council schools, the poor

> **_24_** The average academic qualifications of the teachers at the schools surveyed in a 1992 survey of Zimbabwe's primary schools was the most important factor distinguishing its group of 'most effective' schools, also. In addition to the physical resources which also distinguished this group, the pupil-teacher ratio and those schools with more full-time female teachers as well as tbose with more teaching experience who lived on their own were the notable factors. (Ross and Postlethwaite 1992)

- **25** Study groups consist of groups of students brought together in registered study centers with a mentor, provided at government expense.

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