4.2.1. The Pilot Study

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4.2.1.1 The Internal Reliability of the Latent Constructs (Pilot2RQ1). The pilot phase of the instructors’ questionnaire was to test if the scales of the questionnaire managed to produce reliable results. For this, Cronbach’s alpha values were calculated along with principal component analysis. The values are shown in Table 30. It was desired that constructs reach a minimum 0.6 Cronbach’s alpha value (Dörnyei & Csizér, 2012), as well as items of the constructs load to the same dimension.
 

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Table 30 The First Round of Construct Reliability Analysis of the Instructors’ Pilot Questionnaire
Construct’s name
Cronbach’s alpha of construct
N = 268
Number of components extracted by principal component analysis
Number of items in the construct
  1. Acceptance of ICT
.768
1
5
  1. Availability of ICT
.622
1
5
  1. Reasons for using ICT
.884
1
5
  1. Willingness to use ICT
.960
1
4
  1. Devoted time
.907
1
4
  1. Opportunities for ICT skills development
.971
1
7
  1. Substitution
.839
1
5
  1. Using ICT for instruction
.827
1
4
  1. Digital competences 1: Creating and sharing content
.893
1
5
  1. Digital competences 2: Keeping up with development
.907
1
5
  1. Digital competences 3: Reliability of digital sources
.899
1
5
  1. Digital competences 4: Using search engines
.797
1
4
  1. Transitioning to online education
.864
1
4
  1. Effectiveness of online education
.863
1
4
  1. Offline versus online self-image
.668
1
5
 

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As a final construct reliability measure, the scales’ skewness and kurtosis values were calculated (Table 31). As the values skewness and kurtosis do not reach the skewness = 2 and kurtosis = 7 cut-off margins proposed by Ryu (2011), parametric statistical tests can be used to analyse the results of the questionnaire. It must also have contributed to the reliability of the scales of the instructors’ pilot survey that constructs one to 12 had undergone multiple rounds of reliability analysis as part of the learners’ questionnaire (Study 1) and constructs 13 to 15 were adopted from another validated instrument (Fekete, 2020a).
 

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Table 31 Skewness and Kurtosis of the Scales of the Instructors’ Pilot Questionnaire
Descriptive Statistics
N
Skewness
Kurtosis
Statistic
Statistic
Std. Error
Statistic
Std. Error
  1. Acceptance of ICT
48
–.720
.343
–.254
.674
  1. Availability of ICT
48
–.680
.343
–.125
.674
  1. Reasons for using ICT
48
–1.780
.343
2.922
.674
  1. Willingness to use ICT
48
–1.851
.343
3.316
.674
  1. Devoted time
48
–.128
.343
–.700
.674
  1. Opportunities for ICT skills development
48
–.514
.343
–.659
.674
  1. Substitution
48
–2.039
.343
6.042
.674
  1. Using ICT for instruction
48
–.487
.343
–.633
.674
  1. Digital competences 1: Creating and sharing content
48
–1.931
.343
5.130
.674
  1. Digital competences 2: Keeping up with development
48
–.927
.343
.203
.674
  1. Digital competences 3: Reliability of digital sources
48
–1.859
.343
3.999
.674
  1. Digital competences 4: Using search engines
48
–1.425
.343
1.586
.674
  1. Transitioning to online education
48
–.255
.343
.216
.674
  1. Effectiveness of online education
48
.291
.343
–.937
.674
  1. Offline versus online self-image
48
–.055
.343
–.806
.674
Valid N (listwise)
48
 

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4.2.1.2 Willingness and Ability to use ICT Devices, and Their Connections with Digital Competence Levels (Pilot2RQs 2-3). The descriptive statistics of the pilot instructors’ questionnaire (Table 32) show that the Willingness to use ICT devices (M = 4.27; SD = 0.97), Acceptance of ICT devices (M = 4.20; SD = 0.63) as well as the Availability of ICT devices (M = 4.31; SD = 0.54) are rather high, and instructors are routinely Substituting students’ hard essay copies as well as provide feedback on them using digital devices (M = 4.60; SD = 0.52). As per digital competences, instructors perceived that they were competent in content creation (M = 4.43; SD = 0.69) and using search engines – including online databases (M = 4.40; SD = 0.72). The value for judging the reliability of digital sources is also high (M = 4.38; SD = 0.67), which signals criticality and awareness, but the mean average of Keeping up with development is below the rather similar means of the other three digital competences (M = 3.76; SD = 0.94) and could signal that some instructors in the sample prefer using digital devices routinely as opposed to experimenting with ever new technologies.
 

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Table 32 Descriptive Statistics of the Scales of the Instructors’ Pilot Study
Descriptive Statistics
N = 48
Mean
Std. Deviation
  1. Acceptance of ICT
4.20
.63
  1. Availability of ICT
4.31
.54
  1. Reasons for using ICT
4.71
.47
  1. Willingness to use ICT
4.27
.97
  1. Devoted time
3.45
.99
  1. Opportunities for ICT skills development
3.53
1.11
  1. Substitution
4.60
.52
  1. Using ICT for instruction
3.94
.81
  1. Digital competences 1: Creating and sharing content
4.43
.69
  1. Digital competences 2: Keeping up with development
3.76
.94
  1. Digital competences 3: Reliability of digital sources
4.38
.67
  1. Digital competences 4: Using search engines
4.40
.72
  1. Transitioning to online education
3.46
.88
  1. Effectiveness of online education
3.56
.80
  1. Offline versus online self-image
3.64
.69
 

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Paired sample t-tests (Table 33) revealed that the highest mean values belong to the construct Reasons for using ICT devices (M = 4.71; SD = 0.47), followed by Substitution (M = 4.60; SD = 0.52). Among the Digital competences, participants’ perceived mean of DigComp2: Keeping up with development (M = 3.76; SD = 0.94) is significantly lower than the other three digital competences, DigComp3 (M = 4.38; SD = 0.67); DigComp4 (M = 4.40; SD = 0.72) and DigComp1 (M = 4.43; SD = 0.69).
 

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Table 33 Paired Sample t-tests of the Scales of the Instructors’ Pilot Study
95% Confidence Interval of the Difference
Mean
St. Deviation
Std. Error mean
Lower
Upper
t
df
Sig. (2-tailed)
Pair 1: Reasons – DigComp1
0.283
0.705
0.102
0.079
0.488
2.785
47
= 0.008
Pair 2: Reasons – DigComp4
0.307
0.608
0.088
0.131
0.484
3.504
47
= 0.001
Pair 3: Reasons – DigComp3
0.329
0.649
0.141
0.141
0.518
3.514
47
= 0.001
Pair 4: Reasons – Willingness
0.438
0.802
0.205
0.205
0.671
3.777
47
< 0.001
Pair 5: Reasons – Acceptance
0.508
0.483
0.368
0.368
0.649
7.294
47
< 0.001
Pair 6: Substitution – DigComp3
0.225
0.740
0.102
0.010
0.440
2.107
47
= 0.040
Pair 7: Substitution – Willingness
0.333
0.760
0.113
0.113
0.554
3.038
47
= 0.004
Pair 8: Substitution – Acceptance
0.404
0.540
0.247
0.247
0.561
5.183
47
< 0.001
Pair 9: DigComp1 – DigComp2
0.667
0.633
0.483
0.483
0.850
7.298
47
< 0.001
Pair 10: DigComp3 – DigComp2
0.621
0.654
0.431
0.431
0.811
6.577
47
< 0.001
Pair 11: DigComp4 – DigComp2
0.643
0.702
0.439
0.439
0.847
6.343
47
< 0.001
 

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The two highest mean values (Reasons for using ICT devices and Substitution) emerge as the two most important functions of ICT devices in current university programmes of the target population. Instructors mainly use ICT devices because they are essential parts of 21st century skills, and substitution of assigning, collecting, and providing feedback on students’ written productions has also become a customary, time-consuming advantage of modern university life.
 

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4.2.1.3 The Connections Between Digital Competences, Availability, and Acceptance Towards the use of ICT Devices (Pilot2RQ4). Running bivariate Pearson correlational analyses (Table 34) on the scales for preliminary results showed a slightly different picture than the correlations of the learners’ study (Study 1). There are statistically significant strong correlations between the scales Availability and Opportunities for development (r = 0.622; Sig. (2-tailed): p < 0.001); Acceptance and Instructional use (r = 0.659; Sig. (2-tailed): p < 0.001); and DigComp 3: Reliability of online sources and Willingness (r = 0.612; Sig. (2-tailed): p < 0.001).
 

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Table 34 Statistically Significant Correlations between the digital Competences and Other Scales of the Learners’ Main Questionnaire Study
1. Acceptance of ICT
2. Availability of ICT
3. Reasons for using ICT
4. Willingness to use ICT
5. Devoted time
6. Opportunities for ICT skills development
7. Substitution
8. Using ICT for instruction
13. Transitioning to online education
14. Effectiveness of online education
15. Offline versus online self-image
9. Digital competences 1: Creating and sharing content
.470
.206
.303
.507
.533
.441
.345
.421
.382
–.322
10. Digital competences 2: Keeping up with development
.675
.432
.356
.727
.602
.604
.418
.510
.516
–.321
11. Digital competences 3: Reliability of digital sources
.462
.399
.612
.425
.354
.329
–.118
12. Digital competences 4: Using search engines
.483
.368
.549
.557
.427
.405
.358
.426
 

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As these correlations only signal relationships, no cause-and-effect implications can be drawn from them, but they might contribute towards an understanding of instructors’ dimensions of ICT use. Availability of devices is linked to development possibilities, and the lack of devices are the main, first order barriers of inclusion in the teaching processes (Lowther et al., 2008; Tsai & Chai, 2012). Similar to the findings of Kler (2014), institutional, leadership and technical support are all enablers of ICT use. However, availability of devices does not inherently mean that the necessary software is available on them (Ananiadou & Rizza, 2010).

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There is also a strong link between the acceptance of ICT devices and their instructional use, which point toward how much the use of technology is part of instruction. The strong correlation between participants’ self-reported ability to judge the reliability of online sources and their willingness to use ICT devices point towards the importance of being able to critically assess online content. This link might also suggest that university instructors, most of whom are conducting research, find the abundance of online materials to be strong enough to trigger their willingness to use the devices. Looking at teachers as role models is a recurring finding in the literature when it comes to enablers of ICT use (Aşık et al., 2020; Goktas et al., 2009; Graham et al., 2012; Tezci, 2011), if this link is explicitly, or implicitly visible for their students, instructors can contribute towards making their learners aware of the importance of criticality and the abundance of quality materials available online.

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A final important finding at this phase was the several weak, but negative correlations found between Offline versus online self-image and Acceptance (r = -0.305; Sig. (2-tailed): p = 0.035), DigComp1: Creating and sharing content (r = -0.322; Sig. (2-tailed): p = 0.026), DigComp2: Keeping up with development (r = -0.321; Sig. (2-tailed): p = 0.026), Transitioning to online education (r = -0.318; Sig. (2-tailed): p = 0.028), and Effectiveness of online education (r = 0.393; Sig. (2-tailed): p = 0.006). These negative correlations might suggest the interconnectedness of ICT devices in the instructors’ regular, in-class teaching practices and that acceptance or skills development occurs for on-site teaching reasons.
 

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4.2.1.4 Conclusions of the Instructors’ Pilot Study. An important outcome of the pilot study was that the questionnaire proved to be suitable for large-scale data collection following the scales’ reliability analyses (Dörnyei & Csizér, 2012). Interestingly, compared to the learners’ pilot (4.1.1) and main studies (4.1.2), the fourth Digital competence, Using search engines, proved to be a reliable construct in the instructors’ pilot questionnaire, signalling that perhaps search engine use is rather mastered by professional purposes. It was also found that instructors’ Reasons for using ICT devices (M = 4.71; SD = 0.47), and Substitution (M = 4.60; SD = 0.52) were the two highest rated constructs in the questionnaire study, signalling that it was the very teaching environment that prompts and necessitates the usage most. The construct of Availability of digital devices only reached a 0.62 Cronbach’s alpha value, which is albeit acceptable (Dörnyei & Csizér, 2012), would be ideal to reach a higher value as part of the main instrument.
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