Imre Fekete: Technology in English teaching • The Hungarian university context
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3. Research Methods
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3.1. Study 1: The Learners’ Questionnaire Study
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3.1.2. The Main Study

3.1.2. The Main Study

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Largely informed by the learners’ questionnaire validation study, this subchapter details the methods of data collection and analysis of the large-scale questionnaire. Parts of the results have already been published on data gained from a sub-sample (Fekete, 2020b). This section introduces the data collection and analysis steps of the main learner questionnaire study.
 

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3.1.2.1 Research Questions. The study sought answers to the following research questions:

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  • Study1RQ1. To what extent are ICT devices accepted by Hungarian English Studies / EFL teacher education majors?
  • Study1RQ2. To what extent are ICT devices available for Hungarian English Studies / EFL teacher education majors?
  • Study1RQ3. For what purposes do Hungarian English Studies / EFL teacher education majors use ICT devices?
  • Study1RQ4. What are the perceptions of Hungarian English Studies / EFL teacher education majors about their digital competences?
  • Study1RQ5. How willing are Hungarian English Studies / EFL teacher education majors to develop their digital competences?
  • Study1RQ6. What characterises the relationship between the general and the learning use of ICT devices regarding the constructs Reasons for using ICT devices, Willingness to use ICT devices, Willingness to develop in the use of ICT devices, and Substitution?
  • Study1RQ7. What statistically significant differences do age and gender as individual variables show in the ICT use of Hungarian English Studies / EFL teacher education majors?
  • Study1RQ8. What characterises the relationship between Hungarian English Studies / EFL teacher education majors’ digital competences and the other surveyed dimensions of ICT use such as acceptance and availability of ICT devices, willingness to use and develop in using ICT devices?
 

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3.1.2.2 The Data Collection Instrument. The data collection instrument was an online Google Forms questionnaire that had been designed based on the piloted instrument (Fekete, 2021). Although the pilot used a paper and pencil questionnaire method, nationwide data collection was more feasible to be implemented online. Respondents were asked to rate the questionnaire items on 5-point Likert-scales depending on the extent to which they feel that the items represent them (1: not true for me at all, 5: absolutely true for me). To describe the constructs of the final questionnaire, a list of them follows with the number of items they consist of, a sample item, a definition and the sources introduced in the Theoretical and empirical background chapter of this monograph that serve as rationale for the inclusion of each construct (O’Leary, 2017). The complete questionnaire is included as Appendix B.

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  1. Acceptance of ICT devices (5 items). Sample item: I think using ICT devices confidently is part of one’s basic skills nowadays. Definition: The extent to which participants hold positive attitudes and are accepting of ICT devices (Ham & Cha, 2009; Kozma, 2008; Tondeur et al., 2007a; Voogt & Pelgrum, 2005).
  2. Availability of ICT devices (5 items). Sample item: An ICT device is usually available for me to use. Definition: The extent to which ICT devices are available for the participants in their daily lives, and what features (e.g., Internet connection) do the available devices have (Kárpáti, 2012; MDOS, 2016).
  3. Reasons for using ICT devices (5 items). Sample item: I think nowadays one can be expected to be able to use ICT devices. Definition: The extent to which participants regard the use of ICT devices part of the basic skills of the 21st century (Davies, 2011; Drent & Meelissen, 2008; EU, 2018; Tongori, 2012).
  4. Willingness to use ICT devices (4 items). Sample item: I feel that it is important to get to know new ICT devices. Definition: The extent to which participants feel that they are willing to develop their ICT skills (EU, 2016; ICTLP, 2007; Vuorikari et al., 2016).
  5. Devoted time to develop in using ICT devices (4 items). Sample item: I feel that I devote enough time to develop my knowledge on ICT devices. Definition: The extent to which participants feel that they need to invest time into learning more and staying up to date about technology (Bayne & Ross, 2011; Drent & Meelissen, 2008; Mossberger et al., 2008).
  6. Opportunities for ICT skills development (7 items). Sample item: I feel that I have every possibility to be up to date in using ICT devices. Definition: The extent to which informants feel that they have the necessary opportunities to develop their ICT knowledge (EU, 2018; Kler et al., 2013; Selinger, 2001).
  7. Substitution: ICT use over personal contact (3 items). Sample item: I think it is evident nowadays to share most of the information using ICT devices. Definition: The extent to which participants feel that technology can substitute personal contacts in the form of, e.g., online meetings or online assignment handling, such as turning in and receiving feedback on assignments (Kozma, 2008; Venezky & Davis, 2002).
  8. Using ICT devices for language learning (4 items). Sample item: ICT devices make it possible to access practice activities quickly. Definition: The extent to which participants use ICT devices for language learning, and how much they feel that using technology for language learning processes (including software, applications, webpages) contribute to a more convenient language learning process (BECTA, 2003; Lei et al., 2021).
  9. Digital competences 1: Creating and sharing content (5 items). Sample item: I can use content created by others for my personal needs using ICT devices. Definition: The extent to which participants perceive that they can create, edit, and share digital content created by themselves or others using technology (EU, 2015; 2016; ICTLP, 2007; Vuorikari et al., 2016).
  10. Digital competences 2: Keeping up with development (5 items). Sample item: I understand how the latest ICT devices work without much difficulty. Definition: The extent to which participants keep up with the development of technology, and how much they feel that they are able to follow and remain up to date about constant updates (EU, 2015; 2016; ICTLP, 2007; Vuorikari et al., 2016).
  11. Digital competences 3: Reliability of digital sources (5 items). Sample item: I can assess the reliability of online sources. Definition: The extent to which informants perceive that they can identify reliable and unreliable, biased, low quality and fake online content (EU, 2015; 2016; ICTLP, 2007; Vuorikari et al., 2016).
  12. Digital competences 4: Using search engines (4 items). Sample item: I can use online scholarly databases easily, for example Google Scholar. Definition: The extent to which participants perceive that they can use online search engines such as Google or other common booking engines, e.g., booking accommodation, tickets (EU, 2015; 2016; Vuorikari et al., 2016).
 

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To explore if there were any differences between general and learning use of ICT devices, respondents were asked to rate items of four constructs from two different perspectives, one that represents general free time, and another that represents learning use. These constructs were Reasons for using ICT devices, Willingness to use ICT devices, Opportunities for ICT skills development and Substitution – ICT use over personal contact. Before the large-scale data collection was launched, the proposed instrument underwent further expert reviews to ensure content and – following the analysis of the pilot questionnaire – criterion validity (Dörnyei, 2007). Table 9 illustrates the changes that were administered to the instrument based on the pilot study detailed in 3.1.
 

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Table 9 A Comparison of the Learners’ Pilot and Main Questionnaire Constructs
Pilot study
Main study
Explanation of the difference
1. Acceptance of ICT devices (general and learning use) – 4 items
1. Acceptance of ICT devices (general use) – 5 items
Dimension reduction confirmed that Constructs 1 and 2 cannot be separated into two distinct uses (general and learning use). Additionally, extra items were added for enhanced internal consistency.
2. Availability of ICT devices (general and learning use) – 3 items
2. Availability of ICT devices (general use) – 5 items
3. Reasons for using ICT devices (general and learning use) – 4 items
3. Reasons for using ICT devices (general and learning use) – 5 items
4. Willingness to use ICT devices (general and learning use) – 3 items
4. Willingness to use ICT devices (general and learning use) – 4 items
–
5. Devoted time (general use) – 4 items
This extra construct emerged as a latent dimension during the principal component analysis of the 4th pilot construct (Willingness for ICT skills development).
5. Opportunities for ICT skills development (general and learning use) – 4 items
6. Opportunities for ICT skills development (general and learning use) – 7 items
Extra items were added for enhanced internal consistency.
6. Perceived ability to use ICT devices (general and learning use) – 4 items
–
This scale was removed because its items greatly resembled the items measured by the Digital competences constructs (Constructs 9 to 12).
7. Substitution: ICT use over personal contact (general and learning use) – 5 items
7. Substitution: ICT use over personal contact (general and learning use) – 3 items
Principal component analysis resulted in deleting two items from the construct.
8. Using ICT devices for language learning (learning use only) – 5 items
8. Using ICT devices for language learning (learning use only) – 4 items
Principal component analysis resulted in deleting an item from the construct.
9. Digital competences (general use only) – 18 items
9. Digital competences 1: Creating and sharing content (general use only) – 5 items
Rotated factor analysis (varimax rotation) confirmed the presence of four latent dimensions in the original 18 item pool that were separated for the large-scale data collection.
10. Digital competences 2: Keeping up with development (general use only) – 5 items
11. Digital competences 3: Reliability of digital sources (general use only) – 5 items
12. Digital competences 4: Using search engines (general use only) – 4 items
 

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3.1.2.3 Participants. The study was carried out in the Hungarian university context in the autumn semester of 2019 and the spring semester of 2020 involving 320 participants (234 females and 77 males). The participants were from 10 Hungarian universities that offer English Studies BA, MA or undivided one-tier EFL teacher education MA programmes; thus, forming a non-probability convenience sample (Dörnyei, 2007). This means that there was only one university that was not included in the sample according to the data available on the official website of the Hungarian Educational Authority (https://www.felvi.hu/felveteli/szakok_kepzesek) at the time because despite all the efforts taken, I was unable to reach any participants from that particular institution. Participants were between the ages of 18 and 63, the mean of which was 22.27 (SD = 5.75). Altogether 243 females and 77 males formed the sample, which suggests that females greatly outnumber males in Hungarian English Studies programmes, which, as mentioned before, keys in with the observations of Csizér and Tankó, (2017) conducted in a very similar context.

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The current educational status of the 320 informants was also surveyed. 289 (90%) participants were full-time, while 31 (10%) were part-time students. 171 informants were enrolled in English Studies BA, 143 in one-tier EFL teacher education MA and six in English Studies MA programmes. Participants were between their first and sixth year of their studies, the mean was 2.21 (SD = 1.35) with almost half of the participants (N = 140, 43.8%) in their first year of studies. Table 10 provides an overview of the respondents respective of their universities and their university programmes; however, to ensure anonymity of the participants, I decided not to reveal the specific universities they were studying at the time of data collection; instead, references to the location of the university were used in a random order.
 

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Table 10 An Overview of the Participants of The Main Learner Questionnaire
University’s location
Total number of participants
English Studies BA student
EFL Teacher Education student
English Studies MA student
East 1
17
6
9
2
Budapest 1
98
36
62
–
Northeast 1
28
8
20
–
Budapest 2
13
10
3
–
Budapest 3
19
19
–
–
Northeast 2
11
4
4
3
East 2
2
–
2
–
Budapest 4
59
51
7
1
Southwest 1
11
–
11
–
Southeast 1
62
37
25
–
Total
320
171
143
6
 

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The 320 informants surveyed owned a total number of 1,206 digital devices. The most frequently owned digital device was the smartphone (N = 318, 99.4%) followed by laptops (N = 301, 94.1%), tablets (N = 116, 36.3%), personal desktop computers (N = 102, 31.9%) and e-book readers (N = 60, 19%). The most frequently owned digital devices that are not typically used for studying purposes were TVs (N = 149) and smart TVs (N = 94). Additionally, some participants reported ownership of smart watches (N = 33) non-smart mobile phones (N = 21), games consoles (N = 10) and MP3/MP4 players/iPods (N = 2).
 

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3.1.2.4 Methods of Data Collection. Data was collected through an (L1 – Hungarian) online Google Forms questionnaire to reach as many participants as possible. Data collection took place by distributing the link to the questionnaire through personal collegial contacts and the e-mail list of the Hungarian Society for the Study of English (HUSSE), where instructors were asked to share the URL of the questionnaire with their students. Although online data collection had its limitations, this method was chosen because it seemed to be most feasible to reach a larger sample, especially in the spring of 2020 as news of the appearance of a novel coronavirus sparked speculations over forthcoming strict quarantine measures worldwide. The integrity of the sample was ensured by collecting background variables regarding learners’ place of studies, type of programmes and years of studies.

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The questionnaire started with a brief Hungarian introduction addressed to the informants, who were asked to participate voluntarily and anonymously in a study targeting the digital device use of Hungarian English majors. They were reassured that the instrument was not a test, there were no good or bad answers, and they were encouraged to answer honestly. To maximise response potential, participants were informed that filling in the questionnaire only requires clicks; no long elaborate answers were needed to be keyed in.
 

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3.1.2.5 Methods of Data Analysis. Data was analysed using the Statistical Package for Social Sciences (SPSS) version 22. Before answering the research questions, construct reliability was tested. Constructs were only accepted as reliable if their Cronbach’s alpha value reached the minimum 0.60 cut-off value as well as if all individual items of the construct loaded to the same dimension applying principal component analysis (Dörnyei & Csizér, 2012). Furthermore, the scales were also tested for skewness and kurtosis. “Curran et al. (1996) […] 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).

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Research questions one to five were answered using descriptive statistics, while the highest and lowest mean values were calculated using paired sample t-tests. Paired sample t-tests were also used to investigate if there are statistically significant differences between participants’ perceptions regarding the constructs that were rated from two different perspectives: learning use and free-time use of ICT. To answer research question six, bivariate Pearson correlations were run. In all cases, the statistical significance level was set to p = 0.05 (APA, 2019; O’Leary, 2017). Reporting of the data follows the standards proposed by the American Psychological Association (APA, 2019).
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