La ropa del personal del establecimiento debe de ser lavada y desinfectada dentro del perímetro interno del establecimiento

In order to enhance the integrity of qualitative data, it is important to address four areas of concern: internal validity, construct validity, bias, and objectivity (Mariotto, Zanni, & Moraes, 2014). In order to enhance internal validity, this research established a research framework while triangulation was addressed through the collection of multiple sources of data investigated using pattern matching. Where the data uncovered a questionable or unique phenomenon, other data sources were examined to investigate the phenomenon further, including from differing perspectives. For instance, when the participants showed a

reluctance to engage with the online activities outside of the scheduled class time, an analysis of the entire range of available data was undertaken in order to provide a holistic overview of the behaviours and attitudes of the participants, thereby enhancing internal validity. Construct validity refers to how much the study investigates what it is designed to investigate and

should be addressed in the data collection phase (Gibbert, Ruigrok, & Wicki, 2008). In order to address construct validity, a clear chain of evidence was recorded in the research log book and every effort was made to ensure triangulation of findings by collecting data from a range of sources. Internal validity refers to the data analysis phase and relates to whether there is “a plausible causal argument [and] logical reasoning that is powerful and compelling enough to defend the research conclusions” (Gibbert et al., 2008, p. 1466). Several data sources were analysed at different times. For instance, upon receiving the entrance and exit surveys, an analysis was performed in order to search for outlying data and to assist in modifying the next survey to address or more deeply investigate phenomena. Writing in the research log after an investigation of the exit survey results, the follow-up online survey was modified to gather data to investigate the effect of the BL environment, including the atmosphere, classroom and classmates. An overall examination of the data, including coding, was performed on the study’s conclusion in order to avoid coding data that does not fit

(Oppenheim, 2004). However, a real time ongoing sensitivity to phenomena during the BL intervention was important in ensuring that data could be collected in subsequent surveys that would help to answer questions that arose during the study. External validity was addressed by providing “a clear rationale for the study” (Gibbert et al., 2008, p. 1468), consisting of a mix of extensive experience of the culture and a thorough investigation of the available literature. The researcher was aware of governmental and local institutional objectives for improving graduates’ English language skills while this researcher’s experience in this context helped to inform the scope of the intervention as well as the study’s rationale. Although an investigation of the recent literature did not locate studies that shared a similar context, through transparency, honesty and careful reporting of the research process, findings from this study might be combined with those from future cases to form “replication logic” (Yin, 2013, p. 37) which may be more generalizable to larger populations.

Gibbert et al. (2008) suggest that, to enhance reliability, the researcher should outline the research procedures clearly and organise and store results to allow replication at a later date. To this end, data was organised in a spreadsheet and will be made available as

appropriate while protecting the identities of participants and the data’s fidelity. While this research was based on a small sample group over a relatively short period of time, the measures adopted in research design and data collection were reported as transparently as possible to ensure that validity and reliability can be assessed by readers and that similar interventions can test the study’s findings.

The researcher’s colleagues, due to their experience and differing perspectives, were also consulted to seek out alternative perspectives and these were taken into consideration in the process of designing and revising the research tools. During the preparation for the pilot study, the second instructor provided input into lesson content, timing and the way the

activities should be explained to students. The Dean of the department needed to be informed on progress, helped to maintain ethical regulations and offered perspective and assistance with respect to translation of the surveys and the respondents’ comments.

The collection and handling of data was based on Yin’s (2013) three principles: using multiple sources, creating a database, and maintaining a chain of evidence, all in order to enhance “truth, applicability, consistency, and neutrality” (p. 11). Qualitative and quantitative data were collected using three surveys; paper-based entrance and exit surveys and a follow- up online survey. Quantitative data was derived from logs on a Moodle website consisting of data such as login times, duration, frequency of visits, user location, and when participants engaged with the online activities. A database was created using a spreadsheet, which allowed data to be combined and viewed from a range of perspectives. After the data was integrated on the study’s completion, a holistic approach was undertaken to search for patterns that could be used to provide an overview of the phenomenon under investigation.

The research log served as a record for qualitative observations throughout the study

including during the design and execution of both the pilot and main study as well as the data collection and analysis. It also served to track the data handling and the chain of evidence in terms of how the data was stored and protected.