The sample

Sampling techniques are divided into two types: “probability sampling and purposive sampling” (Tashakkori and Teddlie, 2003, p. 277; Creswell, 2012, p. 206). Probability sampling is common in quantitative studies in which the researcher utilises large samples and identifies the participants and the site randomly; whereas purposive sampling is more common in qualitative inquiry (Patton, 2002, p. 46; Tashakkori and Teddlie, 2003, p. 277). Purposive sampling is “hand-picked for the topic” (Denscombe, 2010, p. 34), and, for the current study, purposive sampling was utilised because the researcher selected a small number of participants deliberately and consciously to get in depth. The sample

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was selected according to the following criteria: full-time Libyan students, studying master’s taught courses at the Yorkshire UK university in different disciplines (Education, Computing and Engineering, Applied Science, and Business) in order to compare and contrast any differences that might emerge in their perspectives or perceptions. They had all obtained Bachelor’s degrees from their home country before coming to the UK, and this was their first time studying in the West. They were from different cities in Libya; and they also all volunteered to participate in this study. However, they differed in terms of age, gender, starting dates of their master’s courses and their attendance at pre-sessional courses.

According to King and Horrocks, snowball sampling is a particular type of purposive sampling in which:

The researcher uses the initial few interviewees to recommend other participants who fit the inclusion criteria for the study. They in turn will be asked to suggest further contacts, and so the sample builds up.

(King and Horrocks, 2010, p. 34) In this study, snowball sampling was utilised because Libyan students as a specific group were initially hard to access, and snowball sampling provided an opportunity to identify participants quickly and efficiently because each participant recommended two or more who met the criteria. Since it was via recommendation, it is a type of snowball sampling of which the researcher still keeps some control.

It was difficult to determine the number of the participants that would be appropriate for this study. Adler and Adler suggest that “our best bet is to advise in the broad range of between a dozen and 60, with 30 being the mean” (Adler and Adler, 2012, p. 10). For the questionnaire sample in this study, 30 Libyan students: fifteen male and fifteen female aged 25-45 years old were selected intentionally to obtain demographic data to inform the interviews. However, it is important to consider Mason (2002), Baker and Edwards (2012); Adler and Adler (2012); and Ragin (2012), who suggest “saturation” is crucial to any qualitative

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sampling. In addition, Seidman (2006, p. 55) suggests two criteria for enough: sufficiency and saturation. In this study, of the total sample who participated in the questionnaire, thirteen participants: four males and nine females were each interviewed three times and observed in their classrooms. The number was reviewed after the first phase of the research process in order to ensure sufficiency and appropriately rich data. When I heard the same information and no new data emerged from the latest interview; that was a time when I said enough.

The participants in the sample were all given pseudonyms. Utilising pseudonyms rather than numbers was intended to give a kind of life to the account and a sense of the person to the reader. The pseudonyms have been selected on an arbitrary basis (see the next section ethical issues 4.5). Because this study is about the perceptions of students in different disciplines and since it includes three interviews with each participant, at the end of each quotation in the data analysis and interpretation chapters, these details are designated (e.g. Ali, Education, interview 2). Information is explicit for the reader and for transparency purposes. The following table provides a description of the questionnaire sample:

Table 4.1: A profile of the students in the questionnaire

Name Code

Sex Age Status Subject area Name of School Starting

date 1. Amina F 39 Single Bio-medical

Science

Applied Science 9/2012 2. Khoula F 29 Single Management Business School 1/2013 3. Majed M 40 Married Information

Technology

Computing and Engineering

1/2013 4. Laila F 27 Single Advanced

Computing

Computing and Engineering

1/2013 5. Nahla F 32 Married Pharmaceutical and

analytical Science

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6. Mahmod M 31 Married Biology Applied Science 9/2012

7. Khaled M 45 Single TESOL Education 1/2013

8. Fatima F 25 Single TESOL Education 9/2012

9. Sara F 32 Married TESOL Education 1/2013

10. Omar M 35 Married Advanced Computer

Computing and Engineering

1/2013 11. Eman F 28 Married Banking and

Finance

Business School 9/2012 12. Jameel M 33 Single Marketing

management

Business School 9/2012 13. Aziza F 41 Married Banking and

Finance

Business School 1/2013 14. Najmi M 45 Married Telecommunication Computing and

Engineering

9/2012 15. Nora F 25 Married Analytical

Chemistry

Applied Science 1/2013 16. Ghada F 27 Single Analytical

Chemistry

Applied Science 1/2013 17. Baqir M 48 Married Risk management Business school 9/2012

18. Maryam F 33 Married TESOL Education 9/2012

19. Husam M 26 Single Accounting Business School 9/2012 20. Emad M 34 Married Risk management Business School 9/2012 21. Ayman M 26 Single Management Business School 1/2013 22. Amira F 29 Married Modern English Humanities 1/2013 23. Manal F 27 Married Modern English Humanities 1/2013

24. Ali M 26 Single TESOL Education 1/2013

25. Ashraf M 43 Married Business Business School 9/2012 26. Ahmed M 28 Married English Literature Humanities 9/2012

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28. Thuria F 38 Married Engineering Computing and Engineering

1/2013 29. Aisha F 45 Single Modern English Humanities 1/2013 30. Hussain M 41 Married Information

Technology

Computing and Engineering

1/2013

As is clear from the table above, the numbers of males and females were equal in the questionnaire sample. Some participants were enrolled in different disciplines within the same school. Some of the participants were married and others were single.

Table 4.2: A profile of the student interviewees

Name code

Sex Age Status Subject area School City in Libya

1. Amina F 39 Single Bio-medical science Applied Science Tripoli 2. Khoula F 29 Single Management Business School Zawia 3. Majed M 40 Married Information

Technology

Computing and Engineering

Garian 4. Laila F 27 Single Advanced

Computer

Computing and Engineering

Baida 5. Nahla F 32 Married Pharmaceutical

and analytical Science

Applied Science Misrata

6. Khaled M 45 Single TESOL Education Ban-Walid

7. Fatima F 25 Single TESOL Education Zintan

8. Sara F 32 Married TESOL Education Ban-Walid

9. Omar M 35 Married Advanced Computer

Computing and Engineering

Benghazi 10. Aziza F 41 Married Banking and

Finance

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11. Nora F 25 Married Analytical Chemistry Applied Science Sabha 12. Ghada F 27 Single Analytical Chemistry Applied Science Jofra

13. Ali M 26 Single TESOL Education Darna

The above table illustrates that there was difference in the number of males and females in the interview sample. The number of females who opted to participate in this phase was higher than males. This may be because, traditionally, Libyan males feel less comfortable talking to a female for cultural reasons.