Univariate Analysis

In order to test whether any difference in the answers to Q1 to Q35 occurred as a result of the respondents’ characteristics such as gender, age, marital status, and parenthood, non-parametric tests (Mann Whitney, and Kruskal-Wallis) were used where appropriate.

Kruskal-Wallis Test: is the analogue to the F-test used in analysis of variance. While analysis of variance tests depend on the assumption that all populations under comparison are normally distributed, the Kruskal-Wallis test places no such restriction on the comparison.

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The Kruskal-Wallis test at a significance level of 0.05 may be used to determine whether evidence exists to conclude that the answers tend to differ as a result of the respondents.

In our study a Kruskal-Wallis Test is conducted to explore whether any difference in the answers to some questions from our questionnaire.

5.6.2.2.1 Gender

The Kruskal-Wallis test revealed a significant effect of gender in the answers to some of the questions (bolded values P<.05) as shown in Table 5.5.

Table 5.5: Effect of Gender (Kruskal-Wallis Test)

Question Q1 Q2 Q3 Q4 Q5 P-VALUE 0.150 0.018 0.359 0.055 0.905 Question Q6 Q7 Q8 Q9 Q10 P-VALUE 0.905 0.009 0.009 0.308 0.853 Question Q11 Q12 Q13 Q14 Q15 P-VALUE 0.556 0.398 0.064 0.086 0.021 Question Q16 Q17 Q18 Q19 Q20 P-VALUE 0.370 0.229 0.219 0.433 0.492 Question Q21 Q22 Q23 Q24 Q25 P-VALUE 0.496 0.198 0.914 0.488 0.354 Question Q26 Q27 Q28 Q29 Q30 P-VALUE 0.062 0.55 0.715 0.358 0.881 Question Q31 Q32 Q33 Q34 Q35 P-VALUE 0.773 0.035 0.3 0.138 0.186 Key:

Q2: (Q9 in the questionnaire): I speak English with my family

Q7: (Q13 in the questionnaire): Did you take a Special English Language course in Libya before you come to the UK for your PhD programme?

Q8: (Q14 in the questionnaire): Did you take Special English Language course in the UK before you began your PhD studies?

Q15: (Q17 in the questionnaire): Have you ever done any serious prolonged reading of academic articles in English?

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Q32: (Q34 in the questionnaire): I will finish my PhD studies on time.

5.6.2.2.2 Age

The Kruskal-Wallis test also revealed a significant effect according to the respondent’s age on the answers to certain questions (bolded values P<.05), as shown in Table 5.6.

Table 5.6: Effect of Age (Kruskal-Wallis Test)

Question Q1 Q2 Q3 Q4 Q5 P-VALUE 0.156 0.016 0.169 0.834 0.234 Question Q6 Q7 Q8 Q9 Q10 P-VALUE 0.25 0.00 0.00 0.871 0.065 Question Q11 Q12 Q13 Q14 Q15 P-VALUE 0.049 0.064 0.129 0.112 0.643 Question Q16 Q17 Q18 Q19 Q20 P-VALUE 0.65 0.509 0.623 0.883 0.941 Question Q21 Q22 Q23 Q24 Q25 P-VALUE 0.939 0.12 0.198 0.314 0.162 Question Q26 Q27 Q28 Q29 Q30 P-VALUE 0.893 0.364 0.485 0.346 0.389 Question Q31 Q32 Q33 Q34 Q35 P-VALUE 0.427 0.026 0.433 0.990 0.36 Key:

Q2: (Q9 in the questionnaire): I speak English with my family

Q7: (Q13 in the questionnaire): Did you take Special English Language course in Libya before you come to the UK for your PhD programme?

Q8: (Q14 in the questionnaire): Did you take Special English Language course in the UK before you began your PhD studies?

Q15: (Q17 in the questionnaire): Have you ever done any serious prolonged reading of academic articles in English?

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5.6.2.2.3 Marital Status

Again, the Kruskal-Wallis test showed a significant influence by the respondent’s marital status on some of the questions (bolded values P<.05) as revealed in Table 5.7.

Table 5.7: Effect of Marital Status (Kruskal-Wallis Test)

Question Q1 Q2 Q3 Q4 Q5 P-VALUE 0.257 .000 0.001 0.939 0.284 Question Q6 Q7 Q8 Q9 Q10 P-VALUE 0.284 0.00 0.00 0.284 0.017 Question Q11 Q12 Q13 Q14 Q15 P-VALUE 0.836 0.508 0.889 0.809 0.72 Question Q16 Q17 Q18 Q19 Q20 P-VALUE 0.126 0.098 0.15 0.44 0.924 Question Q21 Q22 Q23 Q24 Q25 P-VALUE 0.937 0.586 0.321 0.658 0.369 Question Q26 Q27 Q28 Q29 Q30 P-VALUE 0.448 0.367 0.565 0.746 0.453 Question Q31 Q32 Q33 Q34 Q35 P-VALUE 0.121 0.00 0.019 0.223 0.662 Key:

Q2: (Q9 in the questionnaire): I speak English with my family

Q3: (Q11 in the questionnaire): Did you begin your PhD course in the UK immediately after completing Master’ degree in another English speaking country?

Q7: (Q13 in the questionnaire): Did you take Special English Language course in Libya before you come to the UK for your PhD programme?

Q8: (Q14 in the questionnaire): Did you take Special English Language course in the UK before you began your PhD studies?

Q10: (Q16 in the questionnaire): Did you take any special course in study and research skills before you began your PhD studies?

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Q33: (Q41 in the questionnaire): I found the teaching methods are problematic for me as they differ from how I learnt previously.

5.6.2.2.4 Parenthood

The Kruskal-Wallis test also revealed a significant effect upon the answers according to parenthood (bolded values P<.05) as indicated in Table 5.8.

Table 5.8: Effect of Parenthood (Kruskal-Wallis Test)

Question Q1 Q2 Q3 Q4 Q5 P-VALUE 0.323 0.00 0.002 0.801 0.411 Question Q6 Q7 Q8 Q9 Q10 P-VALUE 0.411 0.00 0.00 0.411 0.011 Question Q11 Q12 Q13 Q14 Q15 P-VALUE 0.627 0.658 0.702 0.648 0.932 Question Q16 Q17 Q18 Q19 Q20 P-VALUE 0.123 0.119 0.074 0.198 0.757 Question Q21 Q22 Q23 Q24 Q25 P-VALUE 0.760 0.702 0.392 0.826 0.479 Question Q26 Q27 Q28 Q29 Q30 P-VALUE 0.087 0.604 0.782 0.936 0.606 Question Q31 Q32 Q33 Q34 Q35 P-VALUE 0.124 0.001 0.044 0.474 0.727 Key:

Q2: (Q9 in the questionnaire): I speak English with my family.

Q3: (Q11 in the questionnaire): Did you begin your PhD course in the UK immediately after completing Master’ degree in another English speaking country?

Q7: (Q13 in the questionnaire): Did you take Special English Language course in Libya before you come to the UK for your PhD programme?

Q8: (Q14 in the questionnaire): Did you take Special English Language course in the UK before you began your PhD studies?

Q10: (Q16 in the questionnaire): Did you take any special course in study and research skills before you began your PhD studies?

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Q32: (Q34 in the questionnaire): I will finish my PhD studies on time.

Q33: (Q41 in the questionnaire): I found the teaching methods are problematic for me as they differ from how I learnt previously

5.6.2.3Factor Analysis

As already indicated, Factor Analysis (FA) is a data reduction technique used to condense large data sets into smaller ones by subsuming certain characteristics under a larger umbrella heading (West, 1991). It is a statistical approach that performs such an action with the minimum loss of information, and it was used with the data gathered from this study as a means of reducing the large amount of highly correlated variables into a smaller number of latent uncorrelated variables (factors), and thus to determine the factors affecting Libyan PhD students. The steps in FA are to select and measure a set of variables, prepare the correlation matrix, extract a set of factors (latent variables), rotate the factors (if necessary) to increase the interpretability, and ultimately interpret the results. It is worth noting that a factor is more easily interpreted when several observed variables correlate highly with it and do not correlate with other factors. The FA starts by displaying the correlation matrix, which is a square matrix symmetrical 22 by 22. Because of its size only a portion is displayed here in Table 5.9.

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This table shows the top half of the R-matrix, which contains the Pearson correlation coefficient between all pairs of questions.

In deciding how many factors are to be extracted using Kaiser’s criterions, researchers use latent roots or Eigen values, and scree test criteria. Latent roots or Eigen values are in fact the most popular methods in this respect. In this study, only those components carrying an Eigen value of 1 or more than 1 and half were regarded as significant, and all those below were ignored.

The Scree test is used to identify the optimum number of factors that can be extracted before the amount of unique variance begins to dominate the common variance structure. The scree test is obtained by plotting the Eigen values against the number of factors in their order of extraction, and the shape of the resulting curve is used to evaluate the cut-off point.

In factor analysis, a principal component approach is used with varimax rotation. The results of the analysis were in the form of 4 components, each component consists of many factors; the researcher chose only those factors with factor loadings of 0.4 or higher, based on the sample size and the criteria of the Significance of factor loadings (Hair et aI., 1998).