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Table 1 SNSME component extraction

From: “How is social media used for learning?”: relationships between social media use by medical students with their self-regulated learning skills

Component

Initial Eigenvalues

Extraction Sums of Squared Loadings

 

% of Variance

Cumulative %

Total

% of Variance

Cumulative %

 

1

8.783

46.226

46.226

8.783

46.226

46.226

 

2

2.308

12.147

58.373

2.308

12.147

58.373

 

3

1.168

6.146

64.520

1.168

6.146

64.520

 

4

0.867

4.564

69.083

    

5

0.719

3.783

72.866

    

6

0.684

3.599

76.465

    

7

0.627

3.301

79.767

    

8

0.507

2.666

82.433

    

9

0.446

2.350

84.783

    

10

0.421

2.216

86.999

    

11

0.396

2.085

89.083

    

12

0.350

1.840

90.924

    

13

0.314

1.653

92.576

    

14

0.301

1.586

94.162

    

15

0.283

1.488

95.650

    

16

0.235

1.235

96.884

    

17

0.226

1.188

98.072

    

18

0.201

1.057

99.129

    

19

0.165

0.871

100.000

    
  1. Extraction Method: Principal Component Analysis. The bold values are those with Eigenvalue more than 1