significant variable, the direction of the influence of gender was different for the two subjects, being a positive relationship for girls in English, and a negative relationship in mathematics." Similarly, for home language, although insignificant, the coefficient for the regression on English was negative, as would be expected, unlike that for the regression on mathematics. Seventy-five percent of the pupils in the sample reported that their mothers had no education, so the lack of s-gnificance of mother's education can best be understood by the lack of discrimination of this variable, rather than its being counterintuitive.

44. _Class Level Variables._ The best set of class level explanatory variables consisted of the teacher's gender, the teacher's age, the teacher's qualifications, the availability of texts in the classroom, and for mathematics, additionally, the amount of instructional time devoted to mathematics (Table 9).

45. On first inspection, female teachers seem to have a strong influence on achievement in both English and mathematics, raising achievement by between .56 and .66 points. It is important to note that in this sample 82% of female teachers are in urban schools, however, urban being defined as Bulawayo and Harare, and not including those small towns which were also sampled. The strength of the regression of teacher's gender on achievement disappears when regressed together with the urban/rural variable.

46. Older teachers seem to have a positive influence on pupils' Grade 7 achievement. The log transformations of this variable only marginally improved the fit, so the natural metric was retained. Ten percent of between school differences were explained by this variable. Teachers at the low-fee-paying and district council schools were younger than the average teacher's age of 33 years. No doubt some of these differences are being captured by this variable. Not surprisingly, teacher's qualifications influenced pupil achievement in English and maCiematics. Reported in Table 9 are both the regressions of the dummy variables for all the qualification bands, using 'standard trained' as the reference point, as well as the dummy variable for 'standard trained' vs. all the other categories. It is clear that teacher's qualifications have a stronger influence on mathematics achievement than on English. The differentiation of the 'untrained' qualification band from 'standard trained' is most notable for mathematics achievement.

47. The final significant class level variable uncovered in the individual regressions for both subjects was the availability of textbooks. This influence was stronger for mathematics than for English, accounting for 57% of between school variation in mathematics, 40% in English. The log transformation of this variable was tested, but did not fit better than the natural metric.'<sup>6</sup> 48. As already pointed out, there was much variation in the number of hours of instructional time devoted to mathematics between schooltypes. Not surprisingly, therefore, this variable added a further dimension to the explanation of achievement differences, whereas it was not significant in the regression on English achievement.

- **I5** While such tests of significance are relevant for average, fixed relationships across classes and schools, further inve.;-gation is merited to determine whether a gender gap exists in individual schools (entailing modelling gender as a random variabie at least between schools). Prelimiry investigations of gender as a random variable at the school level regressed on mathematics achievement, point to the existence of varying slopes between schools, with the gender gap smaller, the higher the achievement of boys in the school.

- **16** Raudenbush and Bhumirat (1992) illustrate the use of the logs of various physical resource variables in a school effectiveness study of Thailand, enabling investigation of diminishing returns to resources. This was attempted here.

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