The development and validation process of the university instructor questionnaire was largely informed by the pilot and large-scale data collection experiences of the learner questionnaire (3.1). Thus, the tested and validated questionnaire constructs of the learners’ questionnaire was used to develop the instructors’ study because both Study 1 and Study 2 are concerned with the technology use, but with a focus on two different perspectives, the learners’, and the instructors’, respectively.

 

3.2.1.1 Research Questions. The main goal of this pilot study was to test whether the instrument produces reliable results (Pilot2RQ1) as well as to yield some preliminary results (Pilot2RQs2-5). Thus, the pilot study sought answers to the following research questions:

 

3.2.1.2 Developing the Data Collection Instrument. The questionnaire used in this study was partly developed based on the learner questionnaire (3.1), and as per the Covid-19-related scales, it was informed by a different study in the Hungarian K12 educational context (Fekete, 2022). Development of the pilot instrument was preceded by extensive reading in the literature because a focal question was whether the dual nature of the learner questionnaire should be preserved for this project or not; that is, whether informants should rate certain constructs from two different perspectives: general use and teaching/instructional use. Finally, it was decided to abandon the idea of insisting on the dual questionnaire for several reasons:

 

To describe the 15 final constructs of the questionnaire used in the pilot, a list of them follows with the number of items they consisted, the definition of the constructs and the sources already discussed in the Theoretical and empirical background that rationalise their presence in the questionnaire. All the items and scales of the questionnaire are reproduced in Appendix C.

 

3.2.1.3 Participants. The study was carried out in the Hungarian university context throughout the spring semester of 2021 involving 48 participants from nine Hungarian universities forming a non-probability convenience sample ideal in size to test the reliability of the questionnaire scales (Dörnyei & Csizér, 2012). 27 (56%) respondents were instructors in both English Studies and EFL Teacher Education programmes, 11 (23%) in English Studies, seven (15%) in EFL Teacher Education, two (4%) taught English for specific purposes (ESP) apart from teaching in English Studies and EFL Teacher Education programmes, while one (2%) respondent taught ESP. The sample consisted of 32 females (67%), 15 males (31%), and one informant wished not to disclose their gender (2%). The overall teaching experience of the participants ranged from five to 55 years (M = 26.58; SD = 11.68), and their university teaching experience spanned from one to 45 years (M = 21.21; SD = 11.75).

3.2.1.4 Methods of Data Collection. Data collection took place in the form of an L1 (Hungarian) Google Forms online questionnaire. Participants were sought by circulating a call for participation via two national email lists: the list of the Hungarian Society for the Study of English (HUSSE) and that of the Association of Hungarian Applied Linguists and Language Teachers (MANYE). Additional call for participation emails were spread through some personal collegial contacts of the researcher. As universities were closed in the Spring of 2021, online data collection was the only feasible solution to reach participants nationwide. For time limit constraints, collecting data could not have been postponed even further, and later data collection could have resulted in unreliable answers regarding the 2020 Covid-19 situation because as time passes, it is more difficult to recall the details of certain past events for most individuals. In addition to the questionnaire constructs, some additional background variables were collected to ensure the integrity of the sample such as place of work, programmes where the instructor taught classes, teaching experience and teaching methods used during Covid-19.

3.2.1.5 Methods of Data Analysis. Data was analysed using Statistical Package for Social Sciences (SPSS) version 22. To answer the first, technical research question, the individual items were reorganised into constructs and construct reliability was tested. To accept a construct as reliable, it had to reach a minimum 0.6 Cronbach’s alpha value and each individual item of the construct needed to load to the same dimension using principal component analysis (Dörnyei & Csizér, 2012). Furthermore, the scales were also tested for skewness and kurtosis following Curran et al.’s (1996 as cited by Ryu, 2011, p. 1073) cut-off margins of maximum level of skewness = 3 and kurtosis = 21. These values are justified because “Curran et al. (1996) examined a wider range of skewness and kurtosis values; they found that the inflation of the ML [maximum likelihood] test statistic was more severe with skewness = 3, kurtosis = 21 than with skewness = 2, kurtosis = 7” (Ryu, 2011, p, 1073). Thus, these cut-off values were accepted as normal distribution that allows for running parametric statistical tests on the dataset (Dörnyei & Csizér, 2012; O’Leary, 2017).