Three demographic variables related to the students themselves:

• Gender: boys and girls
• Ethnicity: Mäori, Pasifika and Pakeha (this term was used for all other students)
• Language used predominantly at home: English and other.

During the previous cycle of the Project (1999-2002), special supplementary samples of students from schools with at least 15 percent Pasifika students enrolled were included. These allowed the results of Pasifika students to be compared with those of Mäori and Pakeha students attending these schools. By 2002, with Pasifika enrolments having increased nationally, it was decided that from 2003 onwards a better approach would be to compare the results of Pasifika students in the main NEMP samples with the corresponding results for Mäori and Pakeha students. This gives a nationally representative picture, with the results more stable because the numbers of Mäori and Pakeha students in the main samples are much larger than their numbers previously in the special samples.

The analyses reported compare the performances of boys and girls, Pakeha and Mäori students, Pakeha and Pasifika students, and students from predominantly English-speaking and non-English-speaking homes.

For each of these three comparisons, differences in task performance between the two subgroups are described using “effect sizes” and statistical significance.

For each task and each year level, the analyses began with a t-test comparing the performance of the two selected subgroups and checking for statistical significance of the differences. Then the mean score obtained by students in one subgroup was subtracted from the mean score obtained by students in the other subgroup, and the difference in means was divided by the pooled standard deviation of the scores obtained by the two groups of students. This computed effect size describes the magnitude of the difference between the two subgroups in a way that indicates the strength of the difference and is not affected by the sample size. An effect size of +.30, for instance, indicates that students in the first subgroup scored, on average, three tenths of a standard deviation higher than students in the second subgroup.

For each pair of subgroups at each year level, the effect sizes of all available tasks were averaged to produce a mean effect size for the curriculum area and year level, giving an overall indication of the typical performance difference between the two subgroups.

Results achieved by students who reported that English was the predominant language spoken at home were compared, using the effect size procedures, with the results of students who reported predominant use of another language at home (most commonly an Asian or Pasifika language). Because of the relatively small numbers in the “other language” group, p = .05 has been used here as the critical level for statistical significance.

For year 4 students, the mean effect size across the 21 tasks was +.24 (students for whom English was the predominant language at home averaged 0.24 standard deviations higher than the other students). This is a moderate difference. There were statistically significant differences on 10 of the 21 tasks, with students for whom English was the predominant language spoken at home scoring higher on all 10 tasks: Mowers (p19), Ngä Pätaka (p21), Link Task 2 (p23), Link Task 3 (p23), Jar Opener (p25), Computer Chair (p26), Pet Mouse (p29), Link Task 9 (p36), Biscuits (p38) and Link Task 12 (p43). There were also differences on three questions of the year 4 Technology Survey (p45): students whose predominant language at home was not English reported that their class more frequently did really good things in technology (question 4), made visits or had visitors to help learn about technology (question 6c) and made things (question 6g).

For year 8 students, the mean effect size across the 26 tasks was +.33 (students for whom English was the predominant language at home averaged 0.33 standard deviations higher than the other students). This is a moderate difference. There were statistically significant differences favouring those whose home language was English on 17 of the 26 tasks: all of the Chapter 5 tasks, two-thirds of the Chapter 3 tasks and one-third of the Chapter 4 tasks. Because of the number of tasks involved, they will not be listed here. There were also differences on 10 questions of the year 8 Technology Survey (p46): students whose predominant language at home was not English were more enthusiastic about doing technology at school (question 1), about how much they learned in technology at school (question 2), about how often their class did really good things in technology (question 4) and about how good they were in technology (question 5). They also reported more frequent opportunities in technology at schools to engage in six of the nine aspects mentioned in question 6 (6a, 6b, 6c, 6d, 6e and 6h).