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Family Factors

4. Exploring the Effects of School, Teaching Processes and Students’ Views of Themselves on Later KS3 Attainment

4.3. Students’ Views of Themselves

Based on the ‘All about me’ questionnaire, the following indicators were created (see Sammons et al., 2011b report for the technical details of obtaining these factors):

 Maths Academic Self-Concept

 English Academic Self-Concept

 Enjoyment of School

 Popularity

 Citizen Values

 Anxiety Behaviours

These factors were entered separately as predictors of the Year 9 academic outcomes in multilevel models that also included individual student, familial and HLE characteristics. For each academic outcome, different school factors were significant. Lower scores on these factors indicate higher degrees of agreement with the items that entered in the composition of the specific factor. Similarly with the indicators of the teaching and school processes, these factors were also 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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4.3.1. Maths and English Academic Self-Concepts

Students own perceptions of their abilities in maths and English were highly predictive of academic attainment in Year 9. As expected, the academic self-concept in maths was the strongest predictor of the maths TA levels (ESOrig=1.15; ESImputed=1.02). This was also a strong predictor of science

(ESOrig=0.76; ESImputed=0.68) and English TA levels (ESOrig=0.47; ESImputed=0.51). Similarly, the

English academic self-concept was the strongest predictor of the English TA levels (ESOrig=0.74;

ESImputed=0.66).

In interpreting these findings, it should be noted that academic self-concept is likely to be strongly influenced by earlier and current attainment and the links are reciprocal (Marsh & O’Mara, 2008). The maths academic self concept was a better predictor of English TA levels (ESOrig=0.47;

ESImputed=0.51 than the English academic self-concept predicting maths TA levels (ESOrig=0.23;

ESImputed=0.31). Moreover, the academic self-concept in maths was a stronger predictor of the

science TA levels (ESOrig=0.76; ESImputed=0.68) than the academic self-concept in English predicting

the same academic outcome - science (ESOrig=0.38; ESImputed=0.39).

These findings are in line with previous research that showed that self-concept effects on academic achievement tended to be greater and more systematic for maths than for science and, particularly, English (Marsh & Yeung, 1997).

Table 4.19: Contextualised Models for English Teacher Assessment Levels in Year 9: Maths Academic Self-Concept (Original Data vs. Imputed Data)

Year 9 English TA Original Data

Year 9 English TA Imputed Data STATA ICE

Number of students 1458 2632

Number of schools 388 567

Fixed Effects Coef SE ES Sig Coef SE ES Sig

Maths Academic Self-Concept (continuous) 0.30 0.04 0.47 * 0.34 0.04 0.51 *

% Reduction school variance 85% 83%

% Reduction student variance 32% 26%

% Reduction total variance 45% 40% * p <0.05

Table 4.20: Contextualised Models for Maths Teacher Assessment Levels in Year 9: Maths Academic Self-Concept (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 388 567

Fixed Effects Coef SE ES Sig Coef SE ES Sig

Maths Academic Self-Concept (continuous) 0.91 0.04 1.15 * 0.86 0.04 1.02 *

% Reduction school variance 85% 85%

% Reduction student variance 40% 30%

% Reduction total variance 49% 42% * p <0.05

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Table 4.21: Contextualised Models for Science Teacher Assessment Levels in Year 9: Maths Academic Self-Concept (Original Data vs. Imputed Data)

Year 9 Science TA Original Data

Year 9 Science TA Imputed Data STATA ICE

Number of students 1461 2632

Number of schools 388 567

Fixed Effects Coef SE ES Sig Coef SE ES Sig

Maths Academic Self-Concept (continuous) 0.51 0.04 0.76 * 0.48 0.03 0.68 *

% Reduction school variance 87% 90%

% Reduction student variance 31% 22%

% Reduction total variance 44% 38% * p <0.05

Table 4.22: Contextualised Models for English Teacher Assessment Levels in Year 9: English Academic Self-Concept (Original Data vs. Imputed Data)

Year 9 English TA Original Data

Year 9 English TA Imputed Data STATA ICE

Number of students 1458 2632

Number of schools 388 567

Fixed Effects Coef SE ES Sig Coef SE ES Sig

English Academic Self-Concept (continuous) 0.55 0.04 0.74 * 0.51 0.04 0.66 *

% Reduction school variance 88% 85%

% Reduction student variance 36% 28%

% Reduction total variance 49% 43% * p <0.05

Table 4.23: Contextualised Models for Maths Teacher Assessment Levels in Year 9: English Academic Self-Concept (Original Data vs. Imputed Data)

Year 9 Maths TA Original Data

Year 9 Maths TA Imputed Data STATA ICE

Number of students 1474 2632

Number of schools 388 567

Fixed Effects Coef SE ES Sig Coef SE ES Sig

English Academic Self-Concept (continuous) 0.24 0.06 0.23 * 0.34 0.05 0.31 *

% Reduction school variance 87% 84%

% Reduction student variance 22% 15%

% Reduction total variance 34% 29% * p <0.05

Table 4.24: Contextualised Models for Science Teacher Assessment Levels in Year 9: English Academic Self-Concept (Original Data vs. Imputed Data)

Year 9 Science TA Original Data

Year 9 Science TA Imputed Data STATA ICE

Number of students 1460 2632

Number of schools 388 567

Fixed Effects Coef SE ES Sig Coef SE ES Sig

English Academic Self-Concept (continuous) 0.32 0.05 0.38 * 0.34 0.04 0.39 *

% Reduction school variance 83% 88%

% Reduction student variance 25% 17%

% Reduction total variance 39% 33% * p <0.05

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4.3.2. Enjoyment of School

The degree to which students enjoyed their school was a statistically significant predictor of their attainment in Year 9. Students who liked being at school or found the school as a friendly place were also more likely to obtain higher TA levels in English (ESOrig=0.29; ESImputed=0.22), maths

(ESOrig=0.38; ESImputed=0.28) and science (ESOrig=0.31; ESImputed=0.23).

Again in interpreting these results, it should be noted that these relationships are reciprocal. Enjoyment may be influenced by academic success and vice versa.

Table 4.25: Contextualised Models for English Teacher Assessment Levels in Year 9: Enjoyment of School (Original Data vs. Imputed Data)

Year 9 English TA Original Data

Year 9 English TA Imputed Data STATA ICE

Number of students 1468 2632

Number of schools 388 567

Fixed Effects Coef SE ES Sig Coef SE ES Sig

Enjoyment of School (continuous) 0.47 0.09 0.29 * 0.39 0.08 0.22 *

% Reduction school variance 87% 83%

% Reduction student variance 30% 22%

% Reduction total variance 43% 38% * p <0.05

Table 4.26: Contextualised Models for Maths Teacher Assessment Levels in Year 9: Enjoyment of School (Original Data vs. Imputed Data)

Year 9 Maths TA Original Data

Year 9 Maths TA Imputed Data STATA ICE

Number of students 1484 2632

Number of schools 388 567

Fixed Effects Coef SE ES Sig Coef SE ES Sig

Enjoyment of School (continuous) 0.85 0.12 0.38 * 0.67 0.11 0.28 *

% Reduction school variance 89% 84%

% Reduction student variance 23% 15%

% Reduction total variance 36% 29% * p <0.05

Table 4.27: Contextualised Models for Science Teacher Assessment Levels in Year 9: Enjoyment of School (Original Data vs. Imputed Data)

Year 9 Science TA Original Data

Year 9 Science TA Imputed Data STATA ICE

Number of students 1471 2632

Number of schools 388 567

Fixed Effects Coef SE ES Sig Coef SE ES Sig

Enjoyment of School (continuous) 0.56 0.10 0.31 * 0.43 0.09 0.23 *

% Reduction school variance 87% 88%

% Reduction student variance 22% 15%

% Reduction total variance 38% 32% * p <0.05

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4.3.3. Anxiety Behaviours

Anxious behaviour was a negative predictor of academic outcome. As might be anticipated, students who rated themselves more highly in terms of anxiety had poorer attainment levels (see Table 4.28 and Table 4.30). Anxiety had its strongest negative effect on attainment in maths (ESOrig=-0.29; ESImputed=-0.16), more anxious students losing almost half of TA level when compared

to less anxious students.

Table 4.28: Contextualised Models for English Teacher Assessment Levels in Year 9: Anxiety (Original Data vs. Imputed Data)

Year 9 English TA Original Data

Year 9 English TA Imputed Data STATA ICE

Number of students 1460 2632

Number of schools 388 567

Fixed Effects Coef SE ES Sig Coef SE ES Sig

Anxiety (continuous) -0.18 0.07 -0.15 * -0.09 0.06 -0.07

% Reduction school variance 86% 81%

% Reduction student variance 29% 21%

% Reduction total variance 43% 37% * p <0.05

Table 4.29: Contextualised Models for Maths Teacher Assessment Levels in Year 9: Anxiety (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 388 567

Fixed Effects Coef SE ES Sig Coef SE ES Sig

Anxiety (continuous) -0.48 0.09 -0.29 * -0.28 0.08 -0.16 *

% Reduction school variance 90% 85%

% Reduction student variance 22% 14%

% Reduction total variance 35% 28% * p <0.05

Table 4.30: Contextualised Models for Science Teacher Assessment Levels in Year 9: Anxiety (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 388 567

Fixed Effects Coef SE ES Sig Coef SE ES Sig

Anxiety (continuous) -0.30 0.07 -0.23 * -0.19 0.07 -0.14 *

% Reduction school variance 86% 88%

% Reduction student variance 23% 15%

% Reduction total variance 38% 31% * p <0.05

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