This was a closed ended question with three possible answers. It was decided that not enough times of the day were covered and that weekends (when students are generally more alone, with people returning home) had been dismissed entirely. Other general feedback about the pilot survey included the complaint that the finance questions were in fact, too personal. This is what we had been concerned about from the onset so the questions would have to be re worded so that people were not offended and wouldn’t refuse to complete the questionnaire. If this were to happen, it could disrupt the sample that would be represented.

Other feedback included reports that a minority of international students had become confused over the questions about tuition fees and student loans because their systems work slightly differently. Another complaint was that there was no room for comments and suggestions-i. e. the questions should have been more open ended. Overall, during the piloting process, I have learned that as straight forward as you think a question is, it can still have some level of ambiguity in it and careful thinking about how explicit you want a question to be must be undergone.

After completing the pilot study, the final survey emerged as we revised the questions, added and removes things and organised the structure. The questions were whittled down from 31 in the pilot study to 27. The sub topics remained the same because we felt that they were relevant to the different questions everyone wished to answer. The question wording had been revised so that ambiguous questions had been completely removed, changed entirely or slightly adjusted so that they were more comprehendible.

In our final survey, we used the quota sampling technique in order to collect a representative sample so that each faculty within the University would be represented evenly. However looking at age, this was not taken into account as a representative sample and as a result, a higher percentage of eighteen year olds completed the survey compared to the other age groups. Gender was another factor. In our sample, there were 10. 9 %more females represented than males.

Within the faculty departments themselves, the highest percentage of students represented were studying for degree in arts subjects. The advantage of this kind of sample is that every department of the university is represented so that bias is less likely to occur. The results are more reliable rather than valid. The disadvantage is that bias can occur in other areas that have not been taken into consideration such as gender bias etc. Also different groups such as again, gender can end up being over represented.

To collect the data, everyone was assigned to two departments of the University with figures of how many subjects needed to fill in surveys from each department. I was assigned to medicine and dentistry and engineering. To avoid problems finding subjects to obtain the quota, I decided it would be more effective to look for Students to fill in the surveys in the actual departments that they were representing instead of going to a more neutral place like the Student union (As I probably would have done if I were looking to collect a more random sample).

On the whole, I had few problems actually achieving the quota, although it was harder to find female engineers because there are less females studying for this degree. The results The sample achieved generally represents the student population at Manchester as a whole. The only bias was age as 18 year olds were over represented, this may mean that the mature student population were under represented.