7.8.3 Student survey analysis
The data were cleaned, and some open text responses were coded, and missing records eliminated. The total sample after cleaning was 437 responses with 430 complete or near complete responses.
Initially, descriptive statistics generated directly from the BOS tool were examined by the
research team to indicate any interesting trends. The response rates of particular choice responses for the questionnaire were then inspected and, where these were low, some choice responses were concatenated. A Pearson chi squared cross-tabulation analysis was then undertaken. This is a statistical test which evaluates how likely it is that any observed difference between two sets of data arose by chance – for example if the proportion of people who report that they like a particular soft drink (variable A) differs significantly between people of different ages (variable B). This test produces a measure of that difference such as p = 0.05 which indicates that the likelihood of the pattern of relationship found between A and B would happen by chance – in this case as 1 in 20 (0.05).
A. Based on the research questions and the inspection of descriptive statistics, items of interest were identified for the rows in the analysis. These items are the demographic, background and school experience elements of the survey.
1. Provider (Where are you studying)* 2. Undergraduate or Postgraduate 3. Primary or PostPrimary
4. Chosen Subject Specialism* 5. Age*
6. Gender
7. What is your experience of working in schools generally prior to the course? 8. What type of school(s) have you worked in prior to starting the course*
9. What is the total length of time that you have worked in schools prior to starting the course*
10. What is your experience of working specifically with children with special needs, in a school or other setting, prior to starting the course?*
11. What is the total length of time that you have worked with children with special needs prior to starting the course?*
12. Have you had significant interactions with a friend or relative who has a special educational need or disability?
13. Do you consider that you yourself have a special educational need or disability? 14. Which of the following types of schools have you had placements in during your
course?*
15. Thinking across all your placement classes, did you have involvement with small groups and 1:1 classes as well as your main class?
16. Thinking across all your placement classes, did you have involvement with team teaching?
17. Were all your school placements (i.e. which schools you would go to) decided upon by you?
20. Extent of experience on school placement with:
20.1a Children from diverse cultural and ethnic backgrounds 20.2a Children with different levels of social disadvantage 20.3a Children with English as an Additional Language 20.4a Children with Special Educational Needs 23.1a Inclusive education was covered well in my course.
24. 2 Please rank which part of the course helped you understand about inclusive education the most, by ranking them 1, 2 or 3 where 1 is most and 3 is least
24a. In terms of what you learned from the college elements of the course, was the most useful input from
Opportunities to work with children with a range of abilities and needs* Opportunities to work with children with mild or moderate learning needs* Opportunities to work with children with severe learning needs*
Level of support from my school in helping me develop inclusive practice whilst on school placement
Level of support from my co-operating teacher in helping me develop inclusive practice whilst on school placement
Q25/26 Improvements to the course:
More input on attitudes and understanding in relation to inclusive education*
More input on specific strategies and approaches for working with children with a range of learning needs*
More input on subject specific strategies for inclusion
More emphasis on inclusion across different areas of my taught programme rather than in just one or two modules
Level of support around dealing with challenging behaviour and meeting children’s emotional needs*
More input on dealing with challenging behaviour and meeting children’s emotional needs*
* Indicates items where some content elements were concatenated.
B. The items identified for the columns in the analysis were those elements of the survey which focused on the student’s understanding of knowledge, attitude and skills as indicated by their responses on the survey for questions Q21 – “Understanding of Inclusion Section 1” and Q22 “Understanding of Inclusion Question 2” (Please refer to appendix 5).
The following Q21 and Q22 sub elements were specifically identified, based on a review of the descriptive statistics that highlighted areas of particular interest:
21.2; 21.3; 21.5; 21.6; 21.7; 21.8; 21.9; 21.10; 21.11; 21.12; 21.13; 21.14; 21.15; 22.4; 22.6; 22.7; 22.8; 22.10; 22.11
For example, Q21.2 – “Most children with special educational needs can be included successfully in mainstream schools”, and Q21.3 – “I understand that there are debates about the use of language to label or categorise learners”.
Please refer to appendix 5 for a description of each item.
For items with multiple response possibilities, cross-tabulations were undertaken independently for each response. For example, for Q10, type of experience working with children with special needs – the possible answers were a. None, b. I have worked in a mainstream school with a child/ group of children with special needs; c. I have worked in a special school; d. I have worked in a summer scheme with children with special needs; e. Other.
As each respondent can choose one or more of these answers, it would not make sense to compare them against each other in a simple cross tabulation. Rather, each response item is compared independently. Thus b. – I have worked in a mainstream school with a child/group of children with special needs – is treated as a dichotomous variable with values “yes” has had such experience and “no”, has not had such experience. In other words, a separate comparison is performed for each element a–d, and for each of these comparisons those respondents who ticked this item are compared to those who did not tick this item.
Overall, therefore, the analysis aimed to identify where demographic details and experience prior and during the course was significantly associated with any variation of perception of attitude, skills and knowledge as related to the EASNIE profile.
From this initial Pearson chi square analysis, cross-tabulations which were significant at p <0.05 were identified and listed. For these cross-tabulations, correlation analysis was then individually undertaken. Correlation analysis gives a measure of the strength of the relationship between two variables. Using the example given above, the p value indicates the likelihood that the relationship would happen by chance. The correlation statistic gives the strength of the relationship, i.e. to what extent people who are older are more or less likely to like the soft drink product. This is expressed usually as a value between 0 and 1 with a value of 1 indicating that as variable a increases, variable b directly increases.
Various types of correlation statistic were used, depending on the survey item configuration as follows:
•
For cross-tabulations where both items were for ranked (ordinal) data – i.e. Likert type scale items or other rankings such as extent of experience working with children with SEN in placement classes – the Spearman’s rank correlation statistic was used.•
For cross-tabulations where one item was for ranked data and one was for dichotomous nominal data (e.g. Gender or Primary vs Postprimary) then the Cramer’s V correlation statistic was used.•
For cross-tabulations where one item was for ranked data and one was for multiple nominal data (e.g. type of provider) then a linear regression analysis was used to identify variations in correlation.Cramer’s V gives a measure of association between 0 and 1 (i.e. the extent to which there is a variation in the trend between the two dichotomous items and the dependent variable). Spearman’s gives a measure of how well the items match to a monotonic relationship (i.e. the extent to which as one item increases so does the other), and gives a value between 0 and 1. Statistical tests were undertaken using the STATA data analysis package. The significant cross- tabulation tables and the appropriate statistics are available on request. The UCL Institute of Education Social Science Research Unit advised on the use of the appropriate tests and on the analytic approach in general.