Digital Self-efficacy measurement and gender differences between 52 countries in PISA

Daniel Miranda, Juan Carlos Castillo, Nicolas Tobar, Tomás Urzúa e Ismael Aguayo

University of Chile & Millennium Nucleus on Digital Inequalities and Opportunities (nudos.cl)

5th ISA Forum of Sociology; Rabat, 6-11 July

NUDOS

More information: nudos.cl

Starting point

Digital self-efficacy and gender

“… expectations about one’s capabilities to learn and accomplish tasks in digital technologies and digital environments, is one of the principal components to promote the formation of digital competences” (Ulffert-Blank & Schmidt, 2022).

Bidimensional digital self-efficacy?

  • Digital Self-efficacy have been understood as a unidimensional concept

  • In the last years it has been proposed a distinction between two types of self-efficacy: general and specialized.

  • Cross-country studies operationalize digital self-efficacy in a one-dimensional and two-dimensional manner

Country differences

It is possible to identify two dimensions on PISA Digital Self-efficacy measurement?

Is the bidimensional model of Digital Self-efficacy equivalent by gender and across countries?

Which gender differences exist on Digital Self-efficacy across countries?

Methods

  • Measurement validation of the scale

  • Stability of the scale across countries and gender

Data

  • Programme for International Student Assessment

  • ICT familiarity questionnaire.

  • 2022 cycle: 393607 students, 14038 schools and 52 countries

Digital self-efficacy variables

¿To what extent are you able to do the following tasks when using ?

General self-efficacy

  • Assess the quality of information you found online.

  • Share practical information with a group of students.

  • Collaborate with other students on a group assignment.

  • Explain to other students how to share digital content online or on a school platform

  • Write or edit text for a school assignment.

Specializated self-efficacy

  • Create a computer program .

  • Identify the source of an error in a software after considering a list of potential causes

  • Break down a problem and represent a solution as a series of logical steps, such as an algorithm

Answers: I cannot do this (1), I struggle to do this on my own (2), I can do with a bit of effort (3), I can easily do this (4).

Hypothesis

Results

  1. Measurement model
  2. Invariance test
  3. Mean distribution across country
  4. Gender differences across country

Global CFA model

CFI: 0.999 RMSEA: 0.054 χ²: 15107.60

Metrical and Scalar Invariance across countries and by gender

Digital Self-efficacy across countries

Gender differences across country

Discusion

  • It is possible to identify two dimensions on PISA Digital Self-efficacy measurement?

    • Yes, we can identify both basic and specialized Digital Self-efficacy on PISA 2022.

  • Is the bidimensional model of Digital Self-efficacy equivalent by gender and across countries?

    • Yes, but with less items PISA propose in their own battery.

  • Which gender differences exist on Digital Self-efficacy across countires?

    • Girls takes advantage in General DSE and boys on Specialized DSE.

Next steps

What factors could explain these differences between countries and genders in relation to digital self-efficacy?

Thank!

Appendices

Invariance Analysis

Cross-Country
Model χ² df CFI TLI RMSEA SRMR Δχ² Δdf ΔCFI ΔRMSEA p-value (Δχ²)
Configural 15107.60 988 0.999 0.998 0.054 0.035
Metrical 18502.76 1294 0.999 0.999 0.052 0.037 3395.16 306 0 -0.002 0
Scalar 24944.79 2008 0.998 0.999 0.048 0.035 6442.03 714 0 -0.004 0


By Gender
Model χ² df CFI TLI RMSEA SRMR Δχ² Δdf ΔCFI ΔRMSEA p-value (Δχ²)
Configural 10154.70 38 0.999 0.999 0.046 0.029
Metrical 10796.98 44 0.999 0.999 0.044 0.029 642.28 6 0 -0.002 0
Scalar 11634.72 58 0.999 0.999 0.040 0.029 837.74 14 0 -0.004 0