Appendix A

 

ZIS Documentation (Excerpt)

Schauffel, N., Schmidt, I., Peiffer, H., & Ellwart, T. (2021). ICT Self-Concept Scale (ICT-SC25). Zusammenstellung sozialwissenschaftlicher Items und Skalen (ZIS). https://doi.org/10.6102/zis308_exz

Terms of use This work is an excerpt of the article ‘Schauffel, N., Schmidt, I., Peiffer, H., & Ellwart, T. (2021). Self-concept related to information and communication technology: Scale development and validation. Computers in Human Behavior Reports, 4, 1100149., Article 1. https://doi.org/10.1016/j.chbr.2021.100149 licensed under a Creative Commons Attribution 4.0 International License.
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


Table A 1

Fit indices of alternative structural models of the ICT-SC25g/e within the three quota samples (S2/S3/S5)

Model

χ²

df

χ²/df

CFI

TLI

RMSEA

 SRMR

         AIC

BIC

Adj. BIC

German quota sample (S2, N = 485)

M1

2994.355***

275

10.889

.750

.728

.143

.074

27264.874

27578.685

27340.640

M2

767.418***

260

2.952

.953

.946

.063

.036

24071.696

24448.270

24162.615

M3

1080.840***

269

4.018

.925

.917

.079

.062

24498.392

24837.308

24580.219

M4

660.902***

245

2.698

.962

.953

.059

.023

23941.268

24380.603

24047.340

German quota sample (S3, N = 369)

M1

1733.554***

275

6.304

.774

.754

.120

.073

21480.383

21773.693

21535.744

M2

578.786***

260

2.226

.951

.943

.058

.033

19413.130

19765.102

19479.563

M3

733.782***

269

2.728

.922

.913

.071

.057

19729.853

20046.628

19789.643

M4

521.155***

245

2.127

.957

.948

.055

.025

19343.975

19754.609

19421.481

English quota sample (S5, N = 483)

M1

3547.927***

275

12.902

.716

.690

.157

.076

26649.409

26962.910

26724.866

M2

709.729***

260

2.730

.961

.955

.060

.028

22255.949

22632.150

22346.498

M3

1090.599***

269

4.054

.929

.920

.080

.066

22799.279

23137.861

22880.773

M4

638.603***

245

2.607

.966

.958

.058

.022

22167.801

22606.703

22273.441

Note. Analyses with the retest samples in S2/S3/S5 came to comparable results. Analysis within S4 also showed good model fit for the FOCF model. For the NMS no convergence occured due to the small sample size (N = 204). In bold = cut of criteria reached or best fit index compared to alternative models. CFI = comparative fit index; TLI = Tucker-Lewis index; RMSEA = root-mean-square-error-of-approximation; SRMR = standardized root-mean-square-residual; AIC = Akaike information criterion; BIC = Bayesian information criterion; Adj. BIC = sample-adjusted BIC; M1 = g-factor model; M2 = first-order-correlated-factor model; M3 = second-order model; M4 = nested Marsh/Shavelson model (NMS, incomplete bifactor model).

***p < .001.

Table A 2

Standardized model results within the NMS model and the FOCF model in the three quota samples (S2/S3/S5) divided by a slash

Nested Marsh/Shavelson model (NMS)

First-order-correlated-factor model (FOCF)

Item

R2

First-order loading

Loading on the

g-factor

R2

First-order loading

SCGL1

.75/.78/.70

-

.87/.88/.84

.74/.78/.70

.86/.88/.84

SCGL2

.83/.85/.87

-

.91/.92/.93

.83/.85/.87

.91/.92/.93

SCGL3

.84/.80/.93

-

.92/.89/.96

.85/.80/.93

.92/.89/.96

SCGL4

.85/.77/.88

-

.92/.88/.94

.86/.77/.88

.93/.88/.94

SCGL5

.77/.76/.76

-

.88/.87/.87

.78/.77/.77

.88/.88/.88

SCCO1

.69/.74/.76

.19/.27/.31

.81/.82/.81

.70/.74/.76

.84/.86/.87

SCCO2

.79/.82/.86

.31/.38/.35

.83/.82/.86

.80/.83/.86

.90/.91/.93

SCCO3

.80/.85/.88

.31/.44/.41

.84/.81/.85

.81/.84/.88

.90/.91/.94

SCCO4

.79/.83/.90

.45/.44/.40

.76/.80/.86

.74/.82/.90

.86/.90/.95

SCPS1

.84/.82/.92

.51/.46/.49

.76/.78/.83

.81/.81/.91

.90/.90/.95

SCPS2

.85/.88/.93

.53/.52/.48

.76/.78/.83

.82/.84/.91

.91/.92/.95

SCPS3

.83/.80/.88

.40/.37/.43

.82/.82/.84

.84/.82/.89

.92/.90/.95

SCPS4

.84/.81/.89

.42/.40/.36

.81/.81/.87

.86/.83/.89

.93/.91/.95

SCGE1

.73/.78/.86

.57/.49/.62

.64/.73/.69

.73/.77/.85

.86/.88/.92

SCGE2

.82/.79/.91

.71/.65/.67

.56/.61/.68

.78/.77/.90

.88/.87/.95

SCGE3

.81/.83/.84

.56/.58/.57

.70/.71/.71

.81/.84/.84

.90/.92/.92

SCGE4

.86/.84/.89

.67/.64/.63

.64/.65/.70

.85/.83/.89

.92/.91/.94

SCSA1

.82/.77/.85

.72/.65/.71

.55/.58/.58

.80/.73/.82

.89/.86/.90

SCSA2

.86/.75/.86

.72/.63/.73

.59/.60/.57

.85/.73/.82

.92/.85/.91

SCSA3

.85/.77/.84

.65/.56/.62

.65/.67/.67

.85/.78/.86

.92/.88/.93

SCSA4

.67/.70/.77

.47/.46/.55

.67/.70/.68

.65/.70/.78

.81/.84/.88

SCSP1

.83/.83/.88

.63/.67/.65

.66/.62/.68

.83/.83/.88

.91/.91/.94

SCSP2

.88/.85/.92

.62/.68/.65

.70/.62/.71

.88/.85/.92

.94/.92/.96

SCSP3

.90/.88/.92

.63/.67/.63

.71/.62/.72

.90/.88/.92

.95/.94/.96

SCSP4

.87/.81/.91

.63/.64/.65

.69/.63/.70

.88/.81/.92

.94/.90/.96

Note. Analyses with the retest samples in S2/S3/S5 came to comparable results. Analysis within S4 (N = 204) also showed comparable results for the FOCF model. N2 = 485, N3 = 369, N5 = 483. All λ, p < .001 except SCCO1 in S2 in the NMS (λ= .19, p = .001), all R2 p < .001. SCGL1-5 = items that refer to the general ICT self-concept (ICT-SC); SCCO1-4 = items that refer to the domain-specific ICT-SC communicate; SCPS1-4 = items that refer to the domain-specific ICT-SC process and store; SCGE1-4 = items that refer to the domain-specific ICT-SC generate content; SCSA1-4 = items that refer to the domain-specific ICT-SC safe application; SCSP1-4 = items that refer to the domain-specific ICT-SC solve problems. The nested Marsh/Shavelson model specifies an incomplete bifactor model, therefore items SCGL1-5 load only on the higher-order g-factor.


Table A 3

Latent intercorrelations within the NMS model (below the diagonal) and the FOCF model (above the diagonal) in the three quota samples (S2/S3/S5) divided by a slash

Facet

SCCO

SCPS

SCGE

SCSA

SCSP

SCGL

SCCO

1

.93/.94/.94

.79/.83/.81

.70/.79/.75

.77/.74/.78

.93/.90/.91

SCPS

.74/74/.70

1

.83/.84/.82

.77/.83/.78

.80/.76/.80

.86/.87/.89

SCGE

.52/.54/.48

.59/.54/.52

1

.83/.94/.90

86/.87/.91

.71/.76/.74

SCSA

.31/.41/.41

.48/.53/.47

.66/.86/.78

1

91/.91/.91

.68/.74/.69

SCSP

.35/.41/.39

.45/.45/.46

.70/.75/.80

.82/.82/.81

1

.74/.68/.73

SCGL

-

-

-

-

-

1

ICTSCg

.00/.00/.00

.00/.00/.00

.00/.00/.00

.00/.00/.00

.00/.00/./.00

 

Note. Analyses with the retest samples in S2/S3/S5 came to comparable results. Analysis within S4 (N = 204) also showed comparable results for the FOCF. N2 = 485, N3 = 369, N5 = 483. All correlations p < .001 except for the last line (ICTSCg). NMS model = Nested Marsh/Shavelson model; FOCF model = first-order-correlated-factor model. SCCO = domain-specific ICT self-concept (ICT-SC) communicate; SCPS = domain-specific ICT-SC process and store; SCGE = domain-specific ICT-SC generate content; SCSA = domain-specific ICT-SC safe application; SCSP = domain-specific ICT-SC solve problems; SCGL = first-order factor general ICT-SC; ICTSCg = g-factor general ICT-S