Sampling

This study sought to investigate the characteristics and effectiveness of current in-sessional provision at the British universities recorded by the Higher Education Statistics Agency (HESA) as being fit to award degrees. The target population at the time of data collection (i.e. the 2015/2016 and 2016/2017 academic years) was 167 HE institutions. Three groups of participants from all these institutions were sent the online survey. The participant groups were as follows:

• Participant group 1 (P1): Students (any student who has used in-sessional provision at some point during their university education)

• Participant group 2 (P2): Other subject (non-EAP) university lecturers (i.e. subject specialists)

• Participant group 3 (P3): In-sessional academic English staff (i.e. tutors and DOSs/coordinators)

Both probability and non-probability sampling procedures were used in this mixed- method study. As with Phase One, both study foci (i.e. in-sessional characteristics and the guiding principles informing them, and the perceptions of the stakeholders regarding the effectiveness of in-sessional programmes and the factors determining those perceptions) were addressed via an online survey. According to Teddlie and Tashakkori (2009, p.171), probability sampling involves ‘randomly selecting specific units or cases so that the probability of inclusion is determinable’. According to this technique, an equal chance of being involved will be given to ‘each sampling unit in a clearly defined population’ (ibid, 2009, p. 171). This technique was used in order to give an equal opportunity to all participants at each of the 167 higher education institutions. Given that it was not feasible to access participants from all three groups through similar methods of communication, different methods were employed to reach a sample population from each group. These methods are sum- marised below:

The first method was to send an ‘invitation to participate’ email to administra- tive staff whose email addresses were available on the English language support or services units’ web pages of each university, requesting that they share the survey link with their in-sessional staff and students (P1 and P3). To this end, all 167 university websites were recorded in a spreadsheet in alphabetical order. This list was used to check each website, using certain keywords (e.g. ‘academic English’, ‘in-sessional classes’, ‘English language support’, ‘international student support’) in order to locate the relevant pages on which such email addresses could be found. As

well as academic English programme administrators, any contact information for in-sessional teaching and management staff was also collated where available. An Excel file was used to create contact lists for in-sessional staff. The spreadsheets were also used to monitor and track contacting in-sessional administrators, tutors and managers in each institution. Once these contact lists were created, an invi- tation email was sent, along with a link to the online survey. The email sent to the administrators requested that they forward the email to in-sessional staff and students. The email sent to the in-sessional staff also included a request to share the email with their current and previous in-sessional students, wherever feasible.

In addition to this method, the BALEAP email list of 1,026 members (at the time of conducting this research) was also used to reach a wider sample population for P3, as well as those in-sessional staff who were on this email list but whose contact information was unavailable online via their universities’ in-sessional course links.

As for the subject specialists participant group (P2), the list of universities’ web- page links was used to find the relevant email addresses. Since the probability sampling did not allow control over the number of participants in order to deter- mine the exact sample population who received an invitation to participate, non- probability sampling was also used to determine the exact number of the sample population for each participant group. Consequently, convenience sampling − a form of non-probability sampling− was used with potential participants based on the accessibility of their email addresses. For example, in the case of the group 2 participants (i.e. subject specialists), using the list of universities webpage links alphabetically ordered, those email addresses which took a shorter time to access online were selected and entered into a spreadsheet to create a contact list. This meant that only those online resources which did not use spam filters and, there- fore, allowed the copying of bulk email lists (for subject specialists), were used for creating the sample population. This process continued until the first target sample population was met (calculated based on the desired margin of error and 20 per cent response rate, as explained in detail in the next section). Similarly, as mentioned above, for participant group 3 (in-sessional staff), any email addresses of in-sessional tutors and managers/coordinators available on university webpages were inputted in the contact list spreadsheet. The only difference between the convenience techniques used for P2 was that, in the case of P3 email addresses, instead of using only those pages that allowed bulk copying of email addresses, all email addresses provided for in-sessional staff on academic English programme pages were collected, regardless of whether they were available for bulk copying or via an individual click. Since there is no official source (e.g. Higher Education Statistics Agency) indicating the

exact population of this participant group, the survey link was sent to all potential participants whose email addresses were available online.

A timeframe was created against which each group’s main invitation email and follow-up (reminder) emails could be tracked. Following the compilation of initial email lists, email templates for each group were created, including the main in- vitation and a reminder email. Emails were sent to each institution individually in order to address them directly and personalise the message, and to avoid the message being treated as spam and, therefore, being ignored.