Family Factors
4. Exploring the Effects of School, Teaching Processes and Students’ Views of Themselves on Later KS3 Attainment
4.1. Teaching and School Processes
First, we explored the students’ school related perceptions and experiences. Using Exploratory and Confirmatory Factor Analysis (EFA & CFA) several factors related to teaching and school processes were created (see Sammons et al., 2011b). These factors included:
Emphasis on learning Behaviour climate Headteacher School environment Valuing pupils School/Learning resources
Teacher behavioural management
Teacher support
These factors were tested as separate predictors of the Year 9 academic outcomes in multilevel models that also included various individual student, familial and HLE characteristics (described as important in Sections 2 and 3). For each academic outcome a number of school factors were found to be statistically significant. Originally, the items that entered in the composition of any of the factors were Likert type scale that went from (1) strongly agree to (4) strongly disagree. These were reversed in order to make the interpretation easier. The factors were treated as continuous measures and were centred to the grand mean. Only the factors that were significant predictors of Year 9 academic attainment are presented.
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4.1.1. Emphasis on Learning
Emphasis on learning describes the perceived expectations that teachers have regarding their students’ learning, but also the students’ expectations regarding their own attainment. A higher emphasis on learning was a significant predictor of better attainment measured by TA levels in English (ESOrig=0.21; ESImputed=0.21), maths (ESOrig=0.22; ESImputed=0.21) and science (ESOrig=0.20; ESImputed=0.16). In terms of gain in academic attainment, higher emphasis on learning was associated with an increase of half of a TA level in English and science and more than three quarters of a TA level in maths.
Table 4.1: Contextualised Models for English Teacher Assessment Levels in Year 9: Emphasis on Learning (Original Data vs. Imputed Data)
Year 9 English TA Original Data
Year 9 English TA Imputed Data STATA ICE28
Number of students 1460 2632
Number of schools 387 567
Fixed Effects Coef SE ES Sig Coef SE ES Sig
Emphasis on Learning (continuous) 0.51 0.14 0.21 * 0.55 0.16 0.21 *
% Reduction school variance 85% 83%
% Reduction student variance 29% 22%
% Reduction total variance 43% 38%
* p <0.05
Table 4.2: Contextualised Models for Maths Teacher Assessment Levels in Year 9: Emphasis on Learning (Original Data vs. Imputed Data)
Year 9 Maths TA Original Data
Year 9 Maths TA Imputed Data STATA ICE
Number of students 1475 2632
Number of schools 387 567
Fixed Effects Coef SE ES Sig Coef SE ES Sig
Emphasis on Learning (continuous) 0.77 0.19 0.22 * 0.76 0.19 0.21 *
% Reduction school variance 89% 85%
% Reduction student variance 21% 14%
% Reduction total variance 34% 29%
* p <0.05
Table 4.3: Contextualised Models for Science Teacher Assessment Levels in Year 9: Emphasis on Learning (Original Data vs. Imputed Data)
Year 9 Science TA Original Data
Year 9 Science TA Imputed Data STATA ICE
Number of students 1463 2632
Number of schools 387 567
Fixed Effects Coef SE ES Sig Coef SE ES Sig
Emphasis on Learning (continuous) 0.54 0.15 0.20 * 0.46 0.17 0.16 *
% Reduction school variance 87% 88%
% Reduction student variance 22% 15%
% Reduction total variance 37% 32%
* p <0.05
28These analyses are based on a further imputation model that incorporated additional measures of students’
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4.1.2. Behaviour Climate
Behaviour climate refers to the specific (disruptive) behaviours that students notice around the school (e.g., obeying rules, fighting, bringing into schools knives or weapons). Higher scores on this factor reflect a more positive behaviour climate29. The results of the multilevel models predicting academic attainment indicated that the TA levels in English, maths and science were higher for students who perceived their secondary schools’ behaviour climate as more positive than those who rated the behaviour climate of their schools less favourably (see Table 4.4 and Table 4.6). The ES for maths and science were larger than for English.
These results are in accord with previous school effectiveness research that points to the importance of the school’s overall behaviour climate (see Creemers & Kyriakides, 2008; Rutter et al., 1979; Sammons, Thomas, & Mortimore, 1997; Scheerens & Bosker, 1997).
Table 4.4: Contextualised Models for English Teacher Assessment Levels in Year 9: Behaviour Climate (Original Data vs. Imputed Data)
Year 9 English TA Original Data
Year 9 English TA Imputed Data STATA ICE
Number of students 1461 2632
Number of schools 387 567
Fixed Effects Coef SE ES Sig Coef SE ES Sig
Behaviour Climate (continuous) 0.31 0.07 0.28 * 0.37 0.07 0.32 *
% Reduction school variance 86% 84%
% Reduction student variance 29% 23%
% Reduction total variance 43% 38%
* p <0.05
Table 4.5: Contextualised Models for Maths Teacher Assessment Levels in Year 9: Behaviour Climate (Original Data vs. Imputed Data)
Year 9 Maths TA Original Data
Year 9 Maths TA Imputed Data STATA ICE
Number of students 1476 2632
Number of schools 387 567
Fixed Effects Coef SE ES Sig Coef SE ES Sig
Behaviour Climate (continuous) 0.72 0.09 0.46 * 0.79 0.09 0.50 *
% Reduction school variance 89% 87%
% Reduction student variance 21% 17%
% Reduction total variance 34% 32%
* p <0.05
Table 4.6: Contextualised Models for Science Teacher Assessment Levels in Year 9: Behaviour Climate (Original Data vs. Imputed Data)
Year 9 Science TA Original Data
Year 9 Science TA Imputed Data STATA ICE
Number of students 1464 2632
Number of schools 387 567
Fixed Effects Coef SE ES Sig Coef SE ES Sig
Behaviour Climate (continuous) 0.45 0.08 0.37 * 0.52 0.08 0.41 *
% Reduction school variance 89% 89%
% Reduction student variance 23% 17%
% Reduction total variance 38% 33%
* p <0.05
29
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4.1.3. School Environment
The school environment measure represents the perceived quality of the physical environment of the secondary school (i.e., attractive building, decoration of the classroom, level of cleanness of the toilets) but also the level of organisation. The environment in which teaching and learning take place is found to predict the students’ academic attainment. Thus, students who perceived their school’s environment as pleasant and attractive achieved better TA levels than those who did not. The school environment was found to be a statistically significant predictor of TA levels in both maths and science but it was not significantly related to the English TA levels (see Table 4.7-Table 4.8).
Table 4.7: Contextualised Models for Maths Teacher Assessment Levels in Year 9: School Environment (Original Data vs. Imputed Data)
Year 9 Maths TA Original Data
Year 9 Maths TA Imputed Data STATA ICE
Number of students 1476 2632
Number of schools 387 567
Fixed Effects Coef SE ES Sig Coef SE ES Sig
School Environment (continuous) 0.29 0.13 0.13 * 0.13 0.14 0.06
% Reduction school variance 89% 84%
% Reduction student variance 21% 13%
% Reduction total variance 34% 38%
* p <0.05
Table 4.8: Contextualised Models for Science Teacher Assessment Levels in Year 9: School Environment (Original Data vs. Imputed Data)
Year 9 Science TA Original Data
Year 9 Science TA Imputed Data STATA ICE
Number of students 1464 2632
Number of schools 387 567
Fixed Effects Coef SE ES Sig Coef SE ES Sig
School Environment (continuous) 0.23 0.10 0.13 * 0.12 0.11 0.07
% Reduction school variance 86% 88%
% Reduction student variance 21% 14%
% Reduction total variance 37% 31%
* p <0.05
4.1.4. Valuing Pupils
Another domain that predicted the academic outcome was students’ perceptions of the degree in which their teachers valued and respected them. Higher scores on this factor reflect higher perceived levels of respect and friendliness from the teachers. The more the teachers were perceived as valuing pupils’ views and opinions, the higher the academic outcome in maths (ESOrig=0.12; ESImputed=0.09ns) and science (ESOrig=0.14; ESImputed=0.09ns), although positive, the ES were small. As with all self-perception measures, it is not possible to make causal connections since the directionality of relationships may be reciprocal. Students with higher attainment may have more positive perceptions of their teachers. Additionally, teachers who value their students could also put more effort in the teaching and learning and therefore increase academic attainment. Regardless of the specific directionality, it is important for the teachers to recognise that the way they relate and present themselves to the students may influence their academic outcome.
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Table 4.9: Contextualised Models for Maths Teacher Assessment Levels in Year 9: Valuing pupils (Original Data vs. Imputed Data)
Year 9 Maths TA Original Data
Year 9 Maths TA Imputed Data STATA ICE
Number of students 1477 2632
Number of schools 387 567
Fixed Effects Coef SE ES Sig Coef SE ES Sig
Valuing pupils(continuous) 0.24 0.11 0.12 * 0.20 0.11 0.09
% Reduction school variance 89% 84%
% Reduction student variance 21% 14%
% Reduction total variance 34% 28%
* p <0.05
Table 4.10: Contextualised Models for Science Teacher Assessment Levels in Year 9: Valuing pupils (Original Data vs. Imputed Data)
Year 9 Science TA Original Data
Year 9 Science TA Imputed Data STATA ICE
Number of students 1465 2632
Number of schools 387 567
Fixed Effects Coef SE ES Sig Coef SE ES Sig
Valuing pupils(continuous) 0.22 0.09 0.14 * 0.16 0.09 0.09
% Reduction school variance 86% 88%
% Reduction student variance 21% 14%
% Reduction total variance 37% 31%
* p <0.05
4.1.5. School/Learning Resources
The schools’ capacity to offer good learning resources is likely to influence the way students learn and acquire new information. Amenities like good science labs, libraries and computer rooms were directly associated with academic outcome, especially in maths and science. Again, higher scores on learning resources meant that the students perceived that the school was well equipped with computers and technology and that there was enough time in using these facilities. Students’ perceptions of available learning resources significantly predicted higher TA levels in maths and science (see Table 4.11and Table 4.12), although the ES were small and significantly only in the original data. Thus, students’ academic attainment in maths and science increased with half of a
level when more learning resources were available.
Table 4.11: Contextualised Models for Maths Teacher Assessment Levels in Year 9: Learning Resources (Original Data vs. Imputed Data)
Year 9 Maths TA Original Data
Year 9 Maths TA Imputed Data STATA ICE
Number of students 1477 2632
Number of schools 387 567
Fixed Effects Coef SE ES Sig Coef SE ES Sig
Learning Resources (continuous) 0.50 0.21 0.13 * 0.23 0.23 0.06
% Reduction school variance 90% 83%
% Reduction student variance 20% 20%
% Reduction total variance 34% 36%
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Table 4.12: Contextualised Models for Science Teacher Assessment Levels in Year 9: Learning Resources (Original Data vs. Imputed Data)
Year 9 Science TA Original Data
Year 9 Science TA Imputed Data STATA ICE
Number of students 1464 2632
Number of schools 387 567
Fixed Effects Coef SE ES Sig Coef SE ES Sig
Learning Resources (continuous) 0.46 0.17 0.15 * 0.25 0.17 0.08
% Reduction school variance 88% 88%
% Reduction student variance 21% 14%
% Reduction total variance 37% 31%
* p <0.05
4.1.6. Emphasis on Learning and Behaviour Climate
After testing each of the eight factors derived from the Year 9 student survey separately as predictors of attainment, we also tested them together to investigate which ones are the most important in predicting academic outcomes in Year 9 when still controlling for individual student, familial and HLE characteristics. Because the factors were correlated the question of multicolliniarity arises. For all three core curriculum subjects, it was found that the two factors ‘emphasis on learning’ and ‘behaviour climate’ together significantly predicted Year 9 academic attainment. Additionally, it when tested together the factor ‘behaviour climate’ is found to be the stronger predictor of academic attainment. Also, for maths, the ES is slightly larger than the ES found in the equivalent analyses for English and science TA levels (ESOrig=0.43; ESImputed=0.47) as can be seen in Table 4.14. For attainment in all areas a stronger ‘emphasis on learning’ and a more positive rating of their school’s ‘behaviour climate’ – as they were perceived by students – significantly predicted better attainment in all three subjects.
Table 4.13: Contextualised Models for English Teacher Assessment Levels in Year 9: Emphasis on Learning and Behaviour Climate (Original Data vs. Imputed Data)
Year 9 English TA Original Data
Year 9 English TA Imputed Data STATA ICE
Number of students 1459 2632
Number of schools 387 567
Fixed Effects Coef SE ES Sig Coef SE ES Sig
Emphasis on Learning (continuous) 0.39 0.14 0.16 * 0.44 0.16 0.17 *
Behaviour Climate (continuous) 0.26 0.07 0.23 * 0.34 0.07 0.29 *
% Reduction school variance 85% 84%
% Reduction student variance 30% 23%
% Reduction total variance 43% 39%
* p <0.05
Table 4.14: Contextualised Models for Maths Teacher Assessment Levels in Year 9: Emphasis on Learning and Behaviour Climate (Original Data vs. Imputed Data)
Year 9 Maths TA Original Data
Year 9 Maths TA Imputed Data STATA ICE
Number of students 1477 2632
Number of schools 387 567
Fixed Effects Coef SE ES Sig Coef SE ES Sig
Emphasis on Learning (continuous) 0.45 0.19 0.13 * 0.52 0.19 0.15 *
Behaviour Climate (continuous) 0.66 0.10 0.43 * 0.75 0.09 0.47 *
% Reduction school variance 92% 88%
% Reduction student variance 23% 18%
% Reduction total variance 36% 33%
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Table 4.15: Contextualised Models for Science Teacher Assessment Levels in Year 9: Emphasis on Learning and Behaviour Climate (Original Data vs. Imputed Data)
Year 9 Science TA Original Data
Year 9 Science TA Imputed Data STATA ICE
Number of students 1462 2632
Number of schools 387 567
Fixed Effects Coef SE ES Sig Coef SE ES Sig
Emphasis on Learning (continuous) 0.33 0.15 0.12 * 0.31 0.16 0.11
Behaviour Climate (continuous) 0.41 0.08 0.33 * 0.50 0.08 0.39 *
% Reduction school variance 88% 89%
% Reduction student variance 23% 17%
% Reduction total variance 38% 34%
* p <0.05
These results again point to the importance of the secondary school’s behaviour climate as an important feature of effectiveness, and this supports the findings of previous research on secondary schools (e.g., Rutter et al., 1979; Sammons, Thomas & Mortimore, 1997).