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Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy
Open accessAbstract
The study of gender differences in academic achievement has been one of the core topics in education, especially because it may uncover possible gaps and inequalities in certain domains. Whereas these differences have largely been examined in traditional domains, such as mathematics, reading, and science, the existing body of empirical studies in the domain of ICT literacy is considerably smaller, yet abounds in diverse findings. One of the persistent findings however is that boys consider their ICT literacy to be higher than that of girls. This meta-analysis tests whether the same pattern holds for students’ actual performance on ICT literacy tasks, as measured by performance-based assessments. In total, 46 effect sizes were extracted from 23 empirical studies using a random-effects model. Overall, the gender differences in ICT literacy were significant, positive, and favored girls (g = + 0.12, 95 % CI = [0.08, 0.16]). This effect varied between studies, and moderation analyses indicated that the grade level students were taught at moderated its magnitude—effect sizes were larger in primary school as compared to secondary school. In conclusion, our findings contrast those obtained from previous meta-analyses that were based on self-reported ICT literacy and suggest that the ICT gender gap may not be as severe as it had been claimed to be.
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TL;DR
This meta-analysis synthesizes 23 studies and 46 effect sizes on gender differences in K-12 students' performance-based ICT literacy. It finds a small but significant overall advantage for girls (Hedges' g = +0.12), moderated only by educational level, with larger effects in primary than secondary school.
Key findings
- Overall random-effects model: girls outperformed boys, g = +0.124, 95% CI [0.084, 0.160], k = 46, z = 6.8, p < .001; fixed-effects model was similar, g = +0.131, 95% CI [0.120, 0.142]. Significant heterogeneity was present, Q(45) = 407.3, p < .001, I² = 89.0%, τ² = 0.012.
- Educational level was the only significant moderator: primary school g = +0.201 vs. secondary school g = +0.113, p < .10, explaining 7.5% of between-study variance. Task interactivity, skills assessed, test fairness, sampling, region, and publication status did not significantly moderate effects.
- Publication-bias and sensitivity checks: trim-and-fill adjusted effect was g = +0.142, 95% CI [0.104, 0.180], k = 50; Egger's test was non-significant, t(44) = -0.79, p = .43; fail-safe N was 7898 at p = .05. Correcting for unreliability gave random-effects g = +0.135, 95% CI [0.097, 0.174]; aggregating ICILS 2013 as one effect gave g = +0.118, 95% CI [0.056, 0.180], k = 26.
- The overall sample was N = 121,614 students (girls n = 59,489; boys n = 62,125); 87% of effect sizes came from secondary school and 13% from primary school, with average score reliability 0.86.
Methods
- Meta-analysis of performance-based ICT literacy assessments in K-12 education, extending Siddiq et al.'s (2016) systematic review and updating the search from November 2014 to August 2017; 23 studies yielded 46 effect sizes.
- Effect sizes were transformed into Hedges' g from means/SDs, t-values, or F-values; a random-effects model used the DerSimonian-Laird estimator, with moderator analyses for study, sample, and publication characteristics.
- Publication bias was assessed via funnel plot, trim-and-fill, Egger's regression, fail-safe N, and p-curve; sensitivity analyses compared uncorrected vs. reliability-corrected effects and different treatments of ICILS 2013 effect sizes.
Limitations
- Stated: the broad, unidimensional conceptualization of ICT literacy produced only one overall effect size; the small number of studies reporting sub-dimensions limited finer-grained analyses. Primary school students' digital competence is less often assessed.
- Stated: between-study variation may be caused by assessment design features not captured by coding (e.g., time on tasks, test-taking effort, prior experience) and by varying methodologies/models; motivational constructs and ICT stereotype beliefs were not examined.
- Evident: heterogeneity remained largely unexplained (I² = 89.0%; educational level explained only 7.5%), and the primary-school moderation estimate rests on only 6 effect sizes (13.0%), so it is fragile; most effect sizes came from secondary school, limiting generalizability to primary education.
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Summarizing the overall effects including the single effect obtained from ICILS 2013 resulted in g = +0.118(95% CI = [0.056,0.180], k = 26, z = 3.7, p < .001)for uncorrected and g = +0.133(95% CI = [0.066,0.200], k = 26, z = 3.9, p < .001)for corrected effect sizes under random-effects models.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > Effects of aggregating effect sizes from large-scale studies.
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“After correcting the original effect sizes for unreliability, the overall effect obtained from a fixed-effects model was g = +0.141,95% CI = [0.130,0.152], k = 46, z = 25.0,p < .001.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.5. Sensitivity analyses
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As mentioned earlier, the status of publication (i.e., published vs. grey literature) did not moderate the gender differences.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.3. Moderator analyses (RQ 2)
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Neither study characteristics that referred to the interactivity of assessment tasks nor the type of skills assessed (i.e., the application of digital skills in certain contexts vs. more knowledge-lean and theoretical skills) moderated the gender differences.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.3. Moderator analyses (RQ 2)
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In the paper
“Moreover, whether researchers made an attempt to examine the fairness of the assessment, often manifested by the invariance of the measures used to indicate ICT literacy across gender, did not affect the overall gender differences.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.3. Moderator analyses (RQ 2)
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In the paper
“The LRT suggested that the random-effects model fitted the data significantly better than the fixed-effects model, χ 2 (1) = 255.3,p < .001.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.2. Overall effect size and between-study variation (RQ 1)
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In the paper
“Adding publication status as an explanatory variable to the random-effects model did not provide evidence for significant differences in effect sizes, Q M (1) = 1.67, p = .20.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.4. Publication bias
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In the paper
“The resultant overall effect size after adding these studies was g = +0.142,95% CI = [0.104,0.180], k = 50, z = 7.4, p < .001.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.4. Publication bias
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In the paper
“Egger's linear regression test of funnel plot asymmetry indicated the symmetry of the plot, t(44) = -0.79,p = .43,bias = -0.83,SE = 1.04.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.4. Publication bias
Strength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Neither study characteristics that referred to the interactivity of assessment tasks nor the type of skills assessed (i.e., the application of digital skills in certain contexts vs. more knowledge-lean and theoretical skills) moderated the gender differences.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.3. Moderator analyses (RQ 2)
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A random-effects model resulted in g = +0.135,95% CI = [0.097,0.174], k = 46, z = 6.9, p < .001.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.5. Sensitivity analyses
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Apart from the educational level the assessments were administered in, neither the sampling procedure nor the geographical region the study was conducted in explained the between-study variation significantly.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.3. Moderator analyses (RQ 2)
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Comparing the fixed-and random-effects models, we found that the random-effects model fitted that data significantly better.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.1. Summary of results
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In the paper
“Apart from the educational level the assessments were administered in, neither the sampling procedure nor the geographical region the study was conducted in explained the between-study variation significantly.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.3. Moderator analyses (RQ 2)
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Hence, published (g = +0.160,95% CI = [0.095,0.224], k = 17) and grey literature (g = +0.109,95% CI = [0.066,0.151], k = 29) did not differ in the overall effects reported as gender differences.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.4. Publication bias
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In the paper
“The corresponding between-study variances were τ 2 = 0.020 (SE = 0.009) and τ 2 = 0.023 (SE = 0.010) respectively.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > Effects of aggregating effect sizes from large-scale studies.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Unexpectedly, test content (i.e., the competences measured in the tests) did not moderate the gender effect.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.3. Explaining between-study variation (RQ 2)
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In the paper
“The results displayed gender differences favoring girls across K-12 education across all regions included in the primary studies.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 6. Conclusion
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- The authors state this as an assumption: ICT literacy can be treated as a unidimensional construct for the purpose of estimating an overall gender difference.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Considering this and the small differences in both effect sizes and between-study variances between uncorrected and corrected effects, we conclude that our findings on the overall gender differences were not sensitive toward the correction for unreliability.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.5. Sensitivity analyses
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In the paper
“These numbers are large in comparison to the available effect sizes.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.4. Publication bias
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In the paper
“Moreover, the moderation effects were largely unaffected.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.5. Sensitivity analyses
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIn the paper
“Even though self-reports of one's competence might be predictive of performance to a certain extent, they do not represent actual performance (Honicke & Broadbent, 2016).”
- Also stated in: § 2.4. Gender and ICT literacy performance · plain
“Self-reported skills only provide rough indicators of performance (Honicke & Broadbent, 2016).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 1. Introduction
What the sources say
- Not checked yetcites Honicke & Broadbent, 2016 source
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Also stated in: § 2.4. Gender and ICT literacy performance · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Once again, these values did not differ substantially from those obtained from the randomeffects models with multiple independent effect sizes from ICILS 2013.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > Effects of aggregating effect sizes from large-scale studies.
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesWhat the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Moreover, the analysis of influential cases did not flag any effect size to be influential in the sample of effect sizes (see Supplementary Material S2).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > Effects of aggregating effect sizes from large-scale studies.
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In the paper
“Hence, the decision for the random-effects model was not affected by the unreliability correction.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.5. Sensitivity analyses
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesWhat the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The extracted effect sizes fulfilled the independence assumption-although some studies reported multiple effect sizes, these effects were obtained from different samples (e.g., of different countries, gender, or age groups).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 3.2. Statistical analyses
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In the paper
“Our meta-analysis, however, suggests a significant effect.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIn the paper
“For instance, synthesizing the findings from the PISA 2015 study in science, Stoet and Geary (2018) could not find evidence for a significant, overall effect of students' gender on scientific literacy in a large sample of students from 67 countries (d = -0.01).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
What the sources say
- Not checked yetcites Stoet and Geary (2018) source
Strength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIn the paper
“In all conditions, the power to detect meaningful effect sizes, given the overall sample sizes, was 100% (for a more detailed discussion of power in meta-analyses, please review Valentine, Pigott, & Rothstein, 2010).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > Effects of aggregating effect sizes from large-scale studies.
What the sources say
- Not checked yetcites Valentine, Pigott, & Rothstein, 2010 source
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In the paper
“Despite this observation, the moderation effects were not sensitive toward the handling of the ICILS 2013 effect sizes.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > Effects of aggregating effect sizes from large-scale studies.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIn the paper
“Similarly, Lindberg, Hyde, Petersen, and Linn (2010), who reviewed 242 studies that reported gender differences in mathematics performance between 1990 and 2007, could not find evidence for a significant gender effect either (d = 0.05).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
What the sources say
- Not checked yetcites Lindberg, Hyde, Petersen, and Linn (2010)
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In the paper
“Overall, the positive and significant effect size suggested that girls outperformed boys in performance measures of digital competence.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.2. Overall effect size and between-study variation (RQ 1)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Moreover, the magnitude of the effect, although in a different direction, is similar to that reported by Cai et al. (2017) for ICT attitudes and selfefficacy (g = -0.17).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Our findings further testify to the fact that the gender gap may not be as strong as expected in the domain of ICT.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 6. Conclusion
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- The authors state this as an assumption: ICT literacy can be treated as a unidimensional construct for the purpose of estimating an overall gender difference.
In the paper
“In contrast to the claims surrounding strong disadvantages of girls in performance in technological domains (King & Winthrop, 2015), our meta-analysis suggests that the gender gap may not be as practically critical as these claims suggest.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
What the sources say
- Not checked yetcites King & Winthrop, 2015
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In the paper
“While boys performed significantly better than girls on scales that required more technical knowledge (e.g., basic operations, information networks, programming, and database operations; Aesaert & van Braak, 2015;Christoph, Goldhammer, Zylka, & Hartig, 2015;Lau & Yuen, 2014;Meri-Tuulia et al., 2017).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.3. Explaining between-study variation (RQ 2)
What the sources say
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesThe paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“For instance, girls were identified to outperform boys on scales related to using learningrelated software and tools (e.g., word processing, spreadsheets, presentation software, image processing, and measures related to communication, social networking, and security issues).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.3. Explaining between-study variation (RQ 2)
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIn the paper
“It seems obvious that self-reported performance and actual performance may not necessarily go together (Honicke & Broadbent, 2016).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
What the sources say
- Not checked yetcites Honicke & Broadbent, 2016 source
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIn the paper
“We believe that our meta-analysis lays the foundation to establish the existence of a generalized, female advantage in the domain of ICT, next to other domains (Voyer & Voyer, 2014).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 6. Conclusion
What the sources say
- Not checked yetcites Voyer & Voyer, 2014
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- The authors state this as an assumption: ICT literacy can be treated as a unidimensional construct for the purpose of estimating an overall gender difference.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This knowledge is critical because if school interventions developed to correct for the gender gap are based on self-report measures, they might work counterproductively.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
Tests✓ Asserted: passes? Checkable: unclear✓ Load-bearing: passes✓ Based: passesIn the paper
“Machin and Pekkarinen (2008) also found extreme differences in gender effects between achievement in reading (d = +0.30)and mathematics (d = -0.10).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
What the sources say
- Not checked yetcites Machin and Pekkarinen (2008)
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes
- It may state two separate claims as one. 38
- Probably not a substantial claim. 15
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In the paper
“Fourth, the p-curve was right-skewed (see Fig. 3) and thus suggested that the primary studies had evidential value.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.4. Publication bias
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This effect was associated with significant heterogeneity (Q [49] = 490.5,p < .001,I 2 = 90.0%)and a positive between-study variance (τ 2 = 0.014), both of which were close to the original estimates based on k = 46 primary studies.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.4. Publication bias
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Third, the fail-safe N analyses based on Rosenthal's method showed that 7898 effect sizes would be needed to turn the observed effects into insignificant effects for the target significance level of 0.05.For a significance level of 0.01, the fail-safe N was 3926, and 2205 for 0.001 respectively.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.4. Publication bias
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Given the smaller sample size of studies when an overall ICILS 2013 effect is used, some moderator effects became more pronounced.For instance, the moderation effects for primary and secondary school students were larger, and moderation by publication status became statistically significant (p < .10),yet with small effects explaining up to 3.6% of between-study variance.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > Effects of aggregating effect sizes from large-scale studies.
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As for the uncorrected effect sizes, the random-effects model (AIC = -24.1,BIC = -20.4,cAIC = -23.8)was statistically preferred over the fixed-effects model (AIC = 285.4,BIC = 287.2,cAIC = 285.5),as indicated by smaller values of information criteria and the LRT, χ 2 (1) = 311.4,p < .001.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.5. Sensitivity analyses
Strength:plain· not yet calibratedTests✗ Asserted: fails✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The authors may not put it forward as true. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Notably, there was a tendency toward higher effect sizes after correcting for unreliability, leading to more pronounced differences in effect sizes between primary and secondary school students.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.5. Sensitivity analyses
Strength:hedged· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This model uncovered significant heterogeneity in the effect sizes (Q[45] = 407.3,p < .001,I 2 = 89.0%)and a positive between-study variance (τ 2 = 0.012, SE = 0.004).”
- Also stated in: § Abstract · plain
“This effect varied between studies”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.2. Overall effect size and between-study variation (RQ 1)
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- Also stated in: § Abstract · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“First, a graphical inspection of the funnel plot suggested some degree of asymmetry (see Fig. 2), and the corresponding trim-and-fill analyses indicated that four studies should be added to adjust for this asymmetry.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.4. Publication bias
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This model revealed a positive and significant effect size, favoring girls (g = +0.13)and significant between-study variation of these gender differences.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.1. Summary of results
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Based on a random-effects model, our research synthesis showed an overall effect size of g = +0.124,95 % CI = [0.084,0.160], representing gender differences in favor of girls.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- The authors state this as an assumption: ICT literacy can be treated as a unidimensional construct for the purpose of estimating an overall gender difference.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Overall, the gender differences in ICT literacy were significant, positive, and favored girls (g = + 0.12, 95 % CI = [0.08,0.16]).”
- Also stated in: § 4.2. Overall effect size and between-study variation (RQ 1) · plain
“The overall effect size was again positive and significant and differed only marginally from that of the fixed-effects model, g = +0.124,95% CI = [0.084,0.160], k = 46, z = 6.8, p < .001.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > Abstract
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- Also stated in: § 4.2. Overall effect size and between-study variation (RQ 1) · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For uncorrected effect sizes, the overall ICILS effect was g = +0.132(95% CI = [0.098,0.165], k = 21, z = 7.6, p < .001)and g = +0.139(95% CI = [0.104,0.175], k = 21, z = 7.6, p < .001)for corrected effect sizes.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > Effects of aggregating effect sizes from large-scale studies.
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In primary schools, the gender differences were slightly higher than in secondary schools (primary: g = +0.201,secondary: g = +0.113;p < .10)-thisdifference explained 7.5% of the between-study variation.”
- Also stated in: § Abstract · hedged
“This effect varied between studies, and moderation analyses indicated that the grade level students were taught at moderated its magnitude-effect sizes were larger in primary school as compared to secondary school.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.3. Moderator analyses (RQ 2)
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
- Also stated in: § Abstract · hedged
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Further moderator analyses showed that only the students' educational level (i.e., primary vs. secondary education) explained this variation significantly; the gender differences were slightly higher in primary schools.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.1. Summary of results
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The corresponding between-study variance was τ 2 = 0.014 (SE = 0.006), and the heterogeneity test indicated significant between-study heterogeneity (Q[45] = 475.5,p < .001,I 2 = 90.5%).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.5. Sensitivity analyses
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Our data did not reveal any further moderation effects of region, sampling procedure, or task mode (i.e., whether the task required interactivity within the test environment).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.3. Explaining between-study variation (RQ 2)
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“(4) The effect shows significant variation between studies: Primary studies abounded in different findings that comprised significantly negative gender effects in favor of boys, insignificant effects, and significantly positive effects in favor of girls.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Interestingly, our findings showed that only students' educational level moderated gender differences, with higher effects for primary school students.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.3. Explaining between-study variation (RQ 2)
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None of the sources cited for this claim have been checked yet.
In the paper
“Many researchers concluded that most of the terms are interchangeable and largely reflect the same content (Law et al., 2009;Søby, 2013).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 2. Theoretical framework
What the sources say
- Not checked yetcites Law et al., 2009
- Not checked yetcites Søby, 2013
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Moreover, our analyses indicated little risk of publication bias in the data, and the sensitivity analyses supported the robustness of the overall effect size against the treatment of a large-scale data set (i.e., that of ICILS 2013).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.1. Summary of results
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“(1) The effect is statistically significant: The fact that the overall effect size differs significantly from zero testifies to the existence of gender differences or, in terms of equity and diversity, to a gender gap.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Along the same lines, further sensitivity analyses showed that the overall gender differences were not sensitive toward the correction for unreliability, neither did the analysis of influential cases flag any effect sizes.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.1. Summary of results
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In the paper
“Moreover, their review revealed that the reporting of the reliability and validity of the assessments in the primary studies was insufficient.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 2.3. Assessment of ICT literacy
What the sources say
- Not checked yetcites Siddiq et al. (2016) source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In sum, these analyses did not provide strong evidence for publication bias-in fact, they indicated only a small risk of publication bias in the data.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.4. Publication bias
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Overall, these variables moderated the gender differences in digital competence to only a limited extent, leaving the significant between-study variance largely unexplained.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.3. Moderator analyses (RQ 2)
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In the paper
“Although these frameworks are diverse and structured differently, they converge to a great extent to a set of core knowledge domains and skills of ICT literacy (Voogt & Roblin, 2012).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 2.2. Frameworks of ICT literacy
What the sources say
- Not checked yetcites Voogt & Roblin, 2012 source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Considering that the extant literature reports considerable variation of gender effects across domains (Voyer & Voyer, 2014), we suspect that the existence of gender differences may be domain-specific or specific to certain assessment domains.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
What the sources say
- Not checked yetcites Voyer & Voyer, 2014
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In conclusion, our findings contrast those obtained from previous meta-analyses that were based on self-reported ICT literacy and suggest that the ICT gender gap may not be as severe as it had been claimed to be.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > Abstract
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What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The average score reliability was 0.86 (SD = 0.08, Mdn = 0.89, range = 0.61-0.95),providing an acceptable measurement precision.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 4.1. Description of primary studies
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In the paper
“Hyde (2005) supported this observation and reported a broad range of effect sizes for different measures of mathematics achievement (d = -0.14-0.16).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
What the sources say
- Not checked yetcites Hyde (2005) source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Siddiq et al. (2016) conclude that most tests measure the knowledge and skills in the area of Information, whereas few tests measure knowledge and skills in the areas of Communication, Collaboration, Safety, and Problem solving.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 2.3. Assessment of ICT literacy
What the sources say
- Not checked yetcites Siddiq et al. (2016) source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“A recently published meta-analysis on gender and attitudes toward technology partly confirms this view by revealing that there is a small but significant positive effect towards boys, suggesting that boys have higher ICT self-efficacy and hold more favorable attitudes toward technology than girls (Cai, Fan, & Du, 2017).”
- Also stated in: § 2.4. Gender and ICT literacy performance · plain
“A meta-analysis based on studies using self-reports of ICT literacy and attitudes found that there was a small but significant positive effect favoring boys.In other words, boys held more favorable attitudes toward technology and considered themselves more competent than girls did (Cai et al., 2017).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 1. Introduction
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
- Also stated in: § 2.4. Gender and ICT literacy performance · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“(3) The effect is small.In comparison to gender differences in other domains, the effect for ICT literacy is relatively small and comparable to those found in some of the above-mentioned studies in social sciences, science, and mathematics.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
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In the paper
“This might be due to the fact that primary school students have less access to and therefore experience with technology at school, and are to a lesser degree taught digital competence (Aasen et al., 2012).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.3. Explaining between-study variation (RQ 2)
What the sources say
- Not checked yetcites Aasen et al., 2012
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In any case, the gender effect on ICT literacy is evident and deviates from those reported for mathematics in some of the recent research syntheses.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“(2) The effect is positive: This observation uncovers higher average performance of girls on ICT literacy tasks and aligns with the effects identified in verbal domains.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This variation may have been caused by certain design features of the ICT literacy assessments that were not captured by the coding of possible moderators in our meta-analysis (e.g., the time students spent on assessment tasks, their test-taking effort, or prior experience with similar tasks).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“Recent research has shown that, within the ICT literacy framework, boys and girls tend to score differently in different competence areas.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.3. Explaining between-study variation (RQ 2)
Strength:hedged· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“We believe that this contrast may be explained by a common observation: Boys tend to overestimate their ICT knowledge and skills, while girls tend to underestimate themselves, irrespective of their actual knowledge and skills (Aesaert, Voogt, Kuiper, & van Braak, 2017).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
What the sources say
- Not checked yetcites Aesaert, Voogt, Kuiper, & van Braak, 2017
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Despite the fact that the overall effect aligns with others, it also indicates that ICT literacy may represent a domain in which equity can be achieved to a certain extent.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This is quite a surprising result as it seems that the gender gap is higher among younger children.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.3. Explaining between-study variation (RQ 2)
Strength:hedged· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The effect size was generally small in magnitude, but its consistency suggests that it should not be ignored.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 6. Conclusion
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- The authors state this as an assumption: ICT literacy can be treated as a unidimensional construct for the purpose of estimating an overall gender difference.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“An explanation for this might be that the studies included in this meta-analysis mostly reported ICT literacy as one composite measure and not for specific knowledge domains or skills-in fact, gender differences for the areas outlined in the DIGCOMP framework were reported to a very limited extent.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.3. Explaining between-study variation (RQ 2)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Moreover, our findings contradict the claims that boys have higher ICT literacy-claims that were merely based on self-efficacy rather than performance measures (Aesaert & van Braak, 2015).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 6. Conclusion
What the sources say
- Not checked yetcites Aesaert & van Braak, 2015 source
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- The authors state this as an assumption: ICT literacy can be treated as a unidimensional construct for the purpose of estimating an overall gender difference.
In the paper
“Interestingly, Cai et al. (2017) meta-analyzed the gender differences in ICT attitudes and self-efficacy and found a significant effect favoring boys (g = -0.17).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
What the sources say
- Not checked yetcites Cai et al. (2017) source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Moreover, the varying methodologies and models used to report the gender differences may have also contributed to this variation (e.g., Hohlfeld et al., 2013).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
What the sources say
- Not checked yetcites Hohlfeld et al., 2013 source
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although their meta-analysis examined somehow similar concepts around ICT, it contrasts the finding obtained from our meta-analysis.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“More specifically, in their recent meta-analysis on gender differences in academic achievement, Voyer and Voyer (2014) found effects in favor of girls, especially in language learning (d = +0.37),science (d = +0.15),and social sciences (d = +0.17),whereas those in mathematics were closer to zero (d = +0.07).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
What the sources say
- Not checked yetcites Voyer and Voyer (2014)
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Assessments of ICT literacy oftentimes rely on verbal skills, such as communication-this may explain the direction of gender effects in ICT literacy as compared to more verbal domains.”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.2. Gender differences in ICT literacy and their between-study variation (RQ1)
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Moreover, one limitation might be that primary school students' digital competence is less often assessed compared to secondary school students (Siddiq et al., 2016).”
§ Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy > 5.3. Explaining between-study variation (RQ 2)
What the sources say
- Not checked yetcites Siddiq et al., 2016 source
Strength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
The paper relies on this without support.
No prior meta-analysis has addressed inconsistent findings on gender differences in students' performance-based ICT literacy.
“To our knowledge, this issue of inconsistent research findings concerning possible gender differences in students' ICT literacy performance has not yet been addressed.”
The paper relies on this without support.
A synthesis of gender differences in students' ICT literacy in K-12 education is lacking.
“To our best knowledge, a synthesis of this kind is still lacking in the existing body of research-this is surprising because such a synthesis could provide more detailed insights into the magnitude and direction of a digital divide that otherwise would neither be available nor obvious based on individual studies (Fan & Chen, 2001).”
The paper relies on this without support.
The diversity in findings of primary empirical studies has not yet been explained by study, sample, or publication characteristics.
“It should be noted that this diversity in the findings of primary, empirical studies have not yet been explained by study, sample, or publication characteristics.”
The authors state this as an assumption.
ICT literacy can be treated as a unidimensional construct for the purpose of estimating an overall gender difference.
“Our unidimensional view on ICT literacy provided us with only one overall effect size.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“However, there are some discrepancies when considering performance-based evidence (especially when using ICT literacy assessments) where it has been found that girls perform better than boys (Reinking & Martin, 2018;Siddiq & Scherer, 2019).”
From Fostering students’ motivation and self-efficacy in science, technology, engineering, and design through design thinking and making in project-based learning: a gender-perspective study in primary education (2025) · cites this paper as Siddiq & Scherer, 2019
Statistics recomputed
Every reported test result, recomputed from its test statistic and degrees of freedom. A result shows as not adding up only once an independent check has confirmed it.
- Consistentz = 23.2reported p < .001 · recomputed p < .001
“z = 23.2,p < .001”
- Consistentz = 6.8reported p < .001 · recomputed p < .001
“z = 6.8, p < .001”
- Consistentχ²(1) = 255.3reported p < .001 · recomputed p < .001
“χ 2 (1) = 255.3,p < .001”
- Consistentz = 7.4reported p < .001 · recomputed p < .001
“z = 7.4, p < .001”
- Consistentt(44) = -0.79reported p = .43 · recomputed p = .434
“t(44) = -0.79,p = .43”
- Consistentz = 25reported p < .001 · recomputed p < .001
“z = 25.0,p < .001”
- Consistentz = 6.9reported p < .001 · recomputed p < .001
“z = 6.9, p < .001”
- Consistentχ²(1) = 311.4reported p < .001 · recomputed p < .001
“χ 2 (1) = 311.4,p < .001”
- Consistentz = 7.6reported p < .001 · recomputed p < .001
“z = 7.6, p < .001”
- Consistentz = 3.7reported p < .001 · recomputed p < .001
“z = 3.7, p < .001”
- Consistentz = 3.9reported p < .001 · recomputed p < .001
“z = 3.9, p < .001”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Sampling counts differ between Tables 1 and 2
MinorTable 1 assigns 7 effect sizes to convenience samples and 39 to randomized or stratified samples; Table 2 assigns 9 and 37, respectively. Both tables describe the same 46 effect sizes.
“| Convenience sample | 7 | 15.2% | | Randomized and/or stratified sample | 39 | 84.8% |”
“| Convenience sample | 9 | +0.151 | [0.050, 0.251] | 0.31 (1) | .58 | 401.30 (44) | < .001 | 0.0% | | Randomized and/or stratified sample | 37 | +0.120 | [0.081, 0.159] | | | | | |”
The 2007 publication-year percentage is misrounded
MinorOne of 46 effect sizes is 2.17%, which rounds to 2.2% at one decimal place, not the reported 2.3%.
Reported 2.3 · recomputed 2.173913
“| 2007 | 1 | 2.3% |”
Citations
Cites
Bias in meta-analysis detected by a simple, graphical test
Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997) · BMJ · doi:10.1136/bmj.315.7109.629 · Cited by 56,722
A new look at the statistical model identification
Akaike, H. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100705 · Cited by 51,879
Estimating the Dimension of a Model
Schwarz, G. (1978) · The Annals of Statistics · doi:10.1214/aos/1176344136 · Cited by 47,033
Meta-analysis in clinical trials
DerSimonian, R., & Laird, N. (1986) · Controlled Clinical Trials · doi:10.1016/0197-2456(86)90046-2 · Cited by 39,552
Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009) · doi:10.1002/9780470743386 · Cited by 14,225
Duval, S., & Tweedie, R. (2000) · Biometrics · doi:10.1111/j.0006-341x.2000.00455.x · Cited by 14,099
Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2021) · doi:10.1002/9781119558378 · Cited by 9,799
(2000) · Cited by 9,198
Cohen, J. (1992) · Psychological Bulletin · doi:10.1037//0033-2909.112.1.155 · Cited by 8,771
Methods of Meta-Analysis: Correcting Error and Bias in Research Findings
Schmidt, F. L., & Hunter, J. E. (2015) · doi:10.4135/9781483398105 · Cited by 5,542
Flagged first, then by citations
1 of the 71 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- Chu, 2012, Vol. 15
Cited by
Sorted by citations
Cattáneo, A., Antonietti, C., & Rauseo, M. (2021) · Computers & Education · doi:10.1016/j.compedu.2021.104358 · Cited by 454
Jin, K.-Y., Reichert, F., Cagasan, L. P., de la Torre, J., & Law, N. (2020) · Computers & Education · doi:10.1016/j.compedu.2020.103968 · Cited by 178
Qazi, A., Hasan, N., Abayomi‐Alli, O., Hardaker, G., Scherer, R., Sarker, Y., Paul, S. K., & Maitama, J. Z. (2021) · Education and Information Technologies · doi:10.1007/s10639-021-10775-x · Cited by 193
Self-citationGnambs, T. (2020) · Computers in Human Behavior · doi:10.1016/j.chb.2020.106533 · Cited by 156
Almenara, J. C., Guillén‐Gámez, F. D., Ruiz‐Palmero, J., & Palacios‐Rodríguez, A. (2021) · Education and Information Technologies · doi:10.1007/s10639-021-10476-5 · Cited by 141
Metadata
- Authors
- Siddiq, F., & Scherer, R.
- Affiliations
- University of South-Eastern Norway (NO)
- University of Oslo (NO)
- Corresponding author
- Siddiq, Fazilat
- Venue
- Educational Research Review
- Publisher
- Elsevier BV
- Published
- 2019-06
- Volume
- 27
- Pages
- 205-217
- ISSN
- 1747-938X (ISSN-L)
- OpenAlex
- W2930535595
- Semantic Scholar
- 32b83048a91f6f1c67bcbb80f3292a4fe6d7a6f6
- Cited by
- 297
- References
- 71
- Citations by year
- 2026: 40 · 2025: 58 · 2024: 38 · 2023: 55 · 2022: 43 · 2021: 39 · 2020: 24
- FWCI
- 5.61
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Educational Research Review (publishedVersion, cc-by)
- NORA - Norwegian Open Research Archives (submittedVersion, cc-by-nc-nd)
- NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
- Topics
- Social Sciences › Gender Studies › Gender and Technology in Education
- Social Sciences › Education › Digital literacy in education
- Social Sciences › Psychology › Developmental and Educational Psychology › Educational Strategies and Epistemologies
- Keywords
- gender differences, ICT literacy, gender gap, students, performance-based assessment, grade level, elementary school, secondary schools, educational inequality
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-08, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-08 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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