1. Can't Count, Won't Count? Some Results From A National Survey Of Student Attitudes To Quantitative Methods Malcolm Williams, Liz Hodgkinson, Geoff Payne, Donna Poade, University of Plymouth Contact: malcolm.williams@plymouth.ac.uk

2. Stages of the Research Series of small scale projects: i) Content analysis of quantitative output of leading British sociology journals ii) Baseline study of taught quantitative methods in UK HEIs & consultation with methods teachers (CSAP/ BSA funded) iii)Study of student attitudes to quantitative methods (undergraduates in English & Welsh HEIs (ESRC Funded)

3. Results - Journals 14.3% of content quantitative & 40.6% qualitative 5.3% used bivariate analysis 6.1% multivariate Junior staff over twice as likely to employ qualitative than quantitative methods. Conclusion: quantitative methods underepresented in UK academic sociological output

4. Results – Sociology Units 68% of units said quants comprised between 5 & 15% of sociology curriculum. Only 5% taught no quants Survey methods compulsory in 19% of units Data analysis compulsory in 15% Conclusion: Quants central to virtually all programmes, but consultations revealed problems in quantitative culture, teaching and learning.

5. HEI Study Survey of sociology students across HEIs in England and Wales (n= 738). Focus groups in 4 institutions. Conducted November – March 2005/6 Aimed to description of student perceptions of and attitudes towards quantitative methods in political science and sociology.

6. Views of Sociology Nearly two-thirds thought sociology had less status than the natural sciences. ten point semantic differential scale: 71% scored toward the arts humanities end of the scale,14.5 % the science end of the scale chose 15.5% the middle category two sociologies in the focus groups

7. Table 1 Topics Studied during degree (multiple response)

8. All students in the sample had studied some quantitative methods by Stage 3 Just under 80% had studied statistics in some form. Quantitative secondary analysis and qualitative analysis probably being interpreted quite broadly.

9. Table 2 Student Experience of Research Methods

10. Student Experience of Research Methods. Some indication that students mostly regard quantitative methods as a necessary evil. Less than half of students enjoyed learning about surveys. 65% would rather write an essay than analyse data. A sizeable proportion have concern about their numeric ability and nearly half claim to have had a bad experience of maths at school. 76.6% of all those who had a bad experience of maths at school were anxious about statistics (not shown here).

11. Table 3 Student Attitude by Performance

12. With the exception of the final attitude statement about trusting statistics there is a clear association between a positive attitude toward quantitative methods and achievement in methods modules. Students who viewed number and quantitative methods more positively more likely to obtain 2.1 / 1st and less likely to fail or obtain a 3rd. Opposite true for those who expressed a negative attitude, or fear of number (though maybe issue of causality).

13. Table 4. Performance in Research Methods marks by Course entry requirements

14. Relationship between achievement and UCAS entry points. Courses requiring 340-260 more likely to have students achieving 1st / 2.1 and less likely to have students failing methods modules than those HEIs with a lower entry tariff for sociology. Lowest band had the highest percentage of Fails, but those in the lower band were more likely to achieve Firsts or Upper Seconds than those in the middle band. By-product of recruitment policies geared to mature students? Cross-tab (not shown here) of tariff points by attitude statements showed a significant positive relationship between the highest point band and positive view of number.

15. Table 5 Difficulty of Statistical Technique

16. Yellow Group: intuitively understandable topics requiring little arithmetic skill and to some extent largely visual (charts, means, frequencies, histograms). Green Group: topics that require greater conceptualisation/logic and perhaps more confidence with number (correlation, hypothesis testing, standard deviation): Blue Group: topics that form a more conventional core of basic statistics techniques requiring more grasp of number and the internal logic of statistical reasoning (Chi-sq, Pearson's, V, t test, z test, Spearmans rho, regression)

17. Provisional Conclusions All students study some quantitative methods Less than 50% enjoy learning about quantitative methods and majority would rather write an essay Evidence of concern about number and bad experiences of number at school These latter associated with poorer marks as is a negative attitude to quantitative methods. Some evidence of an underlying anti-science/ pro- humanities attitudes.