CAPÍTULO 6. RESULTADOS
6.2. Valor explicativo de las variables estudiadas sobre el rendimiento de
6.2.3. Análisis del efecto de la edad cronológica, edad lingüística y
The purpose of factor analysis is to reduce a large number of variables to a smaller number of factors (Hartas, 2010; Rogerson, 2010) which are believed to “reflect underlying processes that have created the correlations among variables” (Tabachnick & Fidell, 2001, p.582). Factor analysis, according to Kline (1994), “is a statistical technique widely used in psychology and the social sciences. Indeed, in some branches of psychology, especially those in which tests or questionnaires have been administered, it is a necessity” (p.1) In general, it allows researchers to identify the relationships amongst a large number of variables by defining a set of common dimensions.
Factor analysis was utilised in the current study in order to determine the number of factors and how the variables were grouped; consequently, exploratory factor analysis was appropriate, since the research questionnaire consisted of many varied items. While the selection of these items (i.e. the variables) had been carefully based on a comprehensive review of the literature, any which did not load on a factor were disqualified from the study.
The analysis was conducted by means of SPSS v19. This software was applied to two sections of the questionnaire: part two, comprising 48 items measuring teachers’ satisfaction with a variety of aspects of their jobs, and part four, consisting of 9 items designed to measure their motivation.
5.6 Job Satisfaction Factors
Principal component analysis (PCA) was first employed to identify the number of job satisfaction factors to be extracted. Table 5.12 summarizes the results for the extraction of component factors and the percentage of variance explained by each of these factors.
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For ten factors the total value exceeded 1.0. The percentage of variance ranged from 2.5%, for factor 10, to 11.4%, for factor 1. The extraction of these ten factors together accounts for 59.2% of the variance.
Table 5.12: Total variance explained
F
a
ct
o
rs
Initial eigenvalues Extraction sums of squared loadings Rotation sums of squared loadings Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative % 1 13.584 28.299 28.299 13.584 28.299 28.299 5.477 11.411 11.411 2 3.195 6.656 34.955 3.195 6.656 34.955 4.642 9.670 21.081 3 2.245 4.677 39.632 2.245 4.677 39.632 4.272 8.901 29.982 4 1.862 3.880 43.512 1.862 3.880 43.512 2.962 6.171 36.153 5 1.606 3.345 46.857 1.606 3.345 46.857 2.675 5.572 41.726 6 1.451 3.022 49.880 1.451 3.022 49.880 2.351 4.898 46.624 7 1.230 2.562 52.442 1.230 2.562 52.442 1.841 3.835 50.459 8 1.121 2.336 54.778 1.121 2.336 54.778 1.594 3.321 53.780 9 1.073 2.236 57.014 1.073 2.236 57.014 1.362 2.837 56.617 10 1.026 2.137 59.151 1.026 2.137 59.151 1.216 2.534 59.151 11 .952 1.984 61.135
Extraction method: PCA
5.6.1 Varimax rotation of job satisfaction factors
The new eigenvalues and percentages of variance explained are also shown in Table 5.12. The next step in interpreting the ten factors was to rotate them.Table 5.13 presents the factor pattern matrix for the job satisfaction items using varimax with the Kaiser normalization rotation (KNR) method, which is commonly used to maximize the variance of squared loadings on a factor by producing some high and some low loadings for each factor (Everitt & Hothorn, 2011; Kline, 1994). In order to identify the highest loading for each variable, the interpretation begins with the first item on the first factor, moving from left to right and selecting the highest loading for that item on any factor. If it is significantly high, it loads onto this factor. The same technique is then applied to the remaining variables(Appendix F).
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Table 5.13: Results of PCA with varimax rotation for job satisfaction
Statements Components/Factor loadings
1 2 3 4 5 6 7 8 9 10
28 ICT facilities .791
26 Support to improve your teaching
.749
27 Classroom facilities and resources
.742
22 New ICT opportunities .735 24 Professional development and
self-growth
.709
23 Training opportunities .703 25 Opportunity to pursue advanced
degree
.680
33 Financial support to conduct educational development programmes
.574
2 The principal .785
32 School policy and administration .775
29 School management .700
35 Recognition and reward for good work from your principle
.686
3 Evaluation by the principal .634
31 School bureaucracy .559
30 Schools staff meetings in general .558 44 Opportunity to contribute to
school decision-making
.528
41 Autonomy over teaching .677
42 Responsibilities .674 39 Classroom discipline .641 36 Classroom teaching .596 43 Job security .537 45 Job variety .533 40 Supervising extracurricular activities outside classroom
.506
47 Intellectual challenge .474
37 Administrative paperwork you have to do
.389
11 Student achievement .809
10 Students’ motivation to learn .751
12 Student behaviour .670
14 Pressure from students about examinations
.504
13 Relationships with parents .493
15 Workload .717
16 Classroom teaching load .650
19 Length of the working day .615
17 School working environment .462
48 The level of stress .407
6 Job grade system .825
5 Promotion opportunities .821
1 Your Salary .585
7 Relationships with colleagues .746
8 Social activities with colleagues .711
9 Relationships with students .492
20 Length of school holidays .709
21 The curriculum .452
46 Regulations and educational systems
.450
38 Marking pupils’ work .419 .548
18 Doing school work at home .526
4 Educational supervisor -.565
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Table 5.13 shows that all items had loadings greater than 0.5, with the exception of seven items (Q47, Q17, Q13, Q17, Q18, Q 21 and Q48) whose loadings were greater than 0.4 and two (Q34 and Q37) greater than 0.3. Kline (1994) regards factor loadings as high if they are greater than 0.6 (regardless of the sign) and acceptably high above 0.3, while Tabachnick and Fidell (2001) state that “a criterion for meaningful correlation is usually 0.3 or larger” (p.625). Furthermore, the results reveal that only one of the items had a loading of greater than 0.4 on more than one factor: Q38 (Marking pupils’ work) loaded .548 on factor 9 and .419 on factor 3.
5.6.2 Interpretation and labelling of job satisfaction factors
The last step was to label each of the ten job satisfaction factors. The labels and the loading of variables using varimax with KNR on each factor are presented in Tables 5.14 to 5.23.
5.6.2.1 Factor 1
Table 5.14: Loading of variables on factor 1 using varimax with KNR
N Variables (Items) Loading Factor name
28 ICT facilities .791
Staff development
26 Support to improve your teaching .749
27 Classroom facilities and resources .742
22 New ICT opportunities .735
24 Professional development and self-growth .709
23 Training opportunities .703
25 Opportunity to pursue advanced degree .680
33 Financial support to conduct educational development programmes
.574
Table 5.14 shows that factor 1 consisted of eight items, whose loading ranged between .574 for item 33 and .791 for item 28. Five of these items (Support to improve your teaching, Professional development and self-growth, Training opportunities, Opportunity to pursue advanced degree and Financial support to conduct educational development programmes) can be seen to relate to work development, while the other three (ICT facilities, New ICT opportunities and Classroom facilities and resources) are concerned with available facilities. Accordingly, this factor was named ‘Staff development’.
151 5.6.2.2 Factor 2
Table 5.15: Loading of variables on factor 2 using varimax with KNR
N Variables (Items) Loading Factor name
2 The principal .785
Administration
32 School policy and administration .775
29 School management .700
35 Recognition and reward for good work from your principal
.686
3 Evaluation by the principal .634
31 School bureaucracy .559
30 School staff meetings in general .558
44 Opportunity to contribute to school decision-making .528
Factor 2, as shown in Table 5.15, consisted of eight items whose loading ranged from .528 (item 44) to .785 (item 2). It can be seen that they were all concerned with the school principal or with school policy, administration and decision-making. Therefore, this factor was named ‘Administration’.
5.6.2.3 Factor 3
Table 5.16: Loading of variables on factor 3 using varimax with KNR
N Variables (Items) Loading Factor name
41 Autonomy over teaching .677
Nature of the work 42 Responsibilities .674 39 Classroom discipline .641 36 Classroom teaching .596 43 Job security .537 45 Job variety .533
40 Supervising extracurricular activities outside classroom .506
47 Intellectual challenge .474
37 Administrative paperwork you have to do .389
Factor 3 comprised nine items, as shown in Table 5.16, with loadings ranging from .389 (item 37) to .677 (item 41). As they were all concerned with features of the teachers’ work itself, this factor was named ‘Nature of the work’.
152 5.6.2.4 Factor 4
Table 5.17: Loading of variables on factor 4 using varimax with KNR
N Variables (Items) Loading Factor name
11 Student achievement .809
Student progress
10 Students’ motivation to learn .751
12 Student behaviour .670
14 Pressure from students about examinations .504
13 Relationships with parents .493
Table 5.1.7 shows that factor 4 comprised five items whose loading ranged between .809 (item 11) and .493 (item 13). It can be seen that all but one of these items were related to the achievement of the students, their motivation, behaviour and pressure on teachers regarding examinations, while item 13, on teachers’ relationships with the parents, was included because in Saudi Arabia such relationships tend to be concerned with communication regarding their children’s progress. Therefore this factor was named ‘Student progress’.
5.6.2.5 Factor 5
Table 5.18: Loading of variables on factor 5 using varimax with KNR
N Variables (Items) Loading Factor name
15 Workload .717
Workload
16 Classroom teaching load .650
19 Length of the working day .615
17 School working environment .462
48 Level of stress .407
Factor five, as Table 5.18 shows, consisted of five items whose loading ranged between .407 (item 48) and .717 (item 15). As the component item entitled Workload had the highest loading, followed by Teaching load and Length of the working day, while the related variables of School working environment and Stress had lower loadings, the obvious name for the factor was Workload.
153 5.6.2.6 Factor 6
Table 5.19: Loading of variables on factor 6 using varimax with KNR
N Variables (Items) Loading Factor name
6 Job grade system .825 Salary and
promotion
5 Promotion opportunities .821
1 Your salary .585
Table 5.19 shows that factor 6 consisted of three items with loadings of .585 (item 1) to .825 (item 6), all related to salaries and promotion. One explanation of their grouping under one factor is that in the Saudi education system, there is a very strong link between salary and promotion in the sense that when a teacher is promoted to a higher grade, there is no advantage or benefit other than a salary increase. Therefore, this factor was named ‘Salary and promotion’.
5.6.2.7 Factor 7
Table 5.20: Loading of variables on factor 7 using varimax with KNR
N Variables (Items) Loading Factor name
7 Relationships with colleagues .746 Interpersonal relationships
8 Social activities with colleagues .711
9 Relationships with students .492
As Table 5.20 shows, factor 7 consisted of three items, with loadings from .492 (item 9) to .746 (item 7). As all of these items concern relationships, this factor was named ‘Interpersonal relationships’.
5.6.2.8 Factor 8
Table 5.21: Loading of variables on factor 8 using varimax with KNR
N Variables (Items) Loading Factor name
20 Length of school holidays .709 Educational system
21 The curriculum .452
46 Regulations and educational systems .450
Factor eight, as Table 5.21 shows, comprised three items whose loading ranged between .450 (item 46) and .709 (item 21), related to rather disparate matters: school holidays, the curriculum, and regulations and educational systems. Therefore, this factor was named ‘Educational system’.
154 5.6.2.9 Factor 9
Table 5.22: Loading of variables on factor 9 using varimax with KNR
N Variables (Items) Loading Factor name
38 Marking pupils’ work .548 Marking pupils’ work
18 Doing school work at home .526
Table 5.22 shows that factor 9 consisted of only two items, loading .548 (item 38) and .526 (item 18). Given that work at home would include marking, it was named ‘Marking pupils’ work’.
5.6.2.10 Factor 10
Table 5.23: Loading of variables on factor 10 using varimax with KNR
N Variables (Items) Loading Factor name
4 Educational supervisor -.565 Educational supervision
34 Status of teachers in society .329
As Table 5.23 shows, factor 10 also consisted of two items, loading -.565 (item 4) and .329 (item 34). The factor was named ‘Educational supervision’ because the more strongly loaded of its two variables was ‘Educational supervisor’.
5.7 Motivation Factors
For the motivation section of the questionnaire, as with job satisfaction, PCA was employed to identify the number of factors to be extracted from the nine questionnaire items. Table 5.24 summarizes the results for the extraction of component factors and the percentage of variance explained by each of them. Two factors can be seen to have total values over 1.0, their extraction accounting for 38.1% (factor 1) and 24.7% (factor 2) of variance, a total of 62.9%.
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Table 5.24: Total variance explained
F
a
ct
o
rs Initial Eigenvalues
Extraction Sums of Squared Loadings
Rotation Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative % 1 4.351 48.350 48.350 4.351 48.350 48.350 3.437 38.186 38.186 2 1.312 14.578 62.928 1.312 14.578 62.928 2.227 24.742 62.928 3 .746 8.285 71.213
Extraction method: PCA
5.7.1 Varimax rotation of motivation factors
In order to interpret the two factors, the next step was to rotate them, using varimax with KNR to identify the highest loading for each variable. The results are listed in Table 5.25.
Table 5.25: Result of PCA with varimax rotation for motivation
Items
Components/ Factor loadings
1 2
Q 3 Contributing to a better society .816 Q 2 Wanting to help students to succeed .814
Q 4 Working with students .809
Q 5 Using my professional knowledge and expertise .785
Q 6 Classroom teaching .607
Q 1 Doing a worthwhile job .546
Q 9 Recognition and status in society .811
Q 8 Working condition .773
Q 7 Your salary .722
Table 5.25 shows that all items had high loadings on one factor or the other, greater than .06, except for item 1, whose loading on factor 1 was greater than 0.5, and that no variable had a loading greater than 0.5 on both factors. Therefore, no item was disqualified.
It is clear that factor 1 consisted of six variables and factor 2 of three variables, identified by the method explained in section 5.6.
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5.7.2 Interpretation and labelling of motivation factors
The last step in factor analysis was to label each of the two motivation factors. The resulting labels and the loading of the variables on each factor using varimax with KNR are presented in Tables 5.26 and 5.27.
5.7.2.1 Factor 1
Table 5.26: Loading of variables on factor 1 using varimax with KNR
N Variables (Items) Loading Factor name
3 Contributing to a better society .816
Intrinsic and altruistic motivation
2 Wanting to help students to succeed .814
4 Working with students .809
5 Using my professional knowledge and expertise .785
6 Classroom teaching .607
1 Doing a worthwhile job .546
Factor 1, as Table 5.26 shows, consisted of six items with loadings from .546 (item 1) to .816 (item 3). Variables 4, 5 and 6 can be seen as intrinsic to teaching, while items 1, 2 and 3 are altruistic in nature, so this factor was named ‘Intrinsic and altruistic motivation’.
5.7.2.2 Factor 2
Table 5.27: Loading of variables on factor 2 using varimax with KNR
N Variables (Items) Loading Factor name
9 Recognition and status in society .811 Extrinsic motivation
8 Working conditions .773
7 Your salary .722
Factor 2 consisted of three items with loadings which ranged between .722 (item 7) and .811 (item 9) (Table 5.27). All can be seen to be extrinsic to teaching, so this factor was named ‘Extrinsic motivation’.