Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy

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The p-curve was right-skewed and suggested that the primary studies had evidential value.

“Fourth, the p-curve was right-skewed (see Fig. 3) and thus suggested that the primary studies had evidential value.”

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The trim-and-fill overall effect was associated with significant heterogeneity (Q[49] = 490.5, p < .001, I2 = 90.0%) and positive between-study variance (τ2 = 0.014), both close to the original estimates based on k = 46 primary studies.

“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.”

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Rosenthal's fail-safe N analyses showed that 7898 effect sizes would be needed to turn the observed effects insignificant at α = .05, 3926 at α = .01, and 2205 at α = .001.

“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.”

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With the smaller sample size when an overall ICILS 2013 effect is used, some moderator effects became more pronounced; moderation for primary and secondary school students was larger, and moderation by publication status became statistically significant (p < .10), explaining up to 3.6% of between-study variance.

“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.”

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After correcting for unreliability, the random-effects model was statistically preferred over the fixed-effects model, with AIC = -24.1, BIC = -20.4, cAIC = -23.8 versus AIC = 285.4, BIC = 287.2, cAIC = 285.5, and LRT χ2(1) = 311.4, p < .001.

“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.”

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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.

“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.”

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The effect sizes showed significant between-study heterogeneity (Q[45] = 407.3, p < .001, I2 = 89.0%) and positive between-study variance (τ2 = 0.012, SE = 0.004).

“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”

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Graphical inspection of the funnel plot suggested some degree of asymmetry, and trim-and-fill analyses indicated that four studies should be added to adjust for this asymmetry.

“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.”

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The random-effects model revealed a positive and significant effect size favoring girls (g = +0.13) and significant between-study variation of these gender differences.

“This model revealed a positive and significant effect size, favoring girls (g = +0.13)and significant between-study variation of these gender differences.”

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Based on a random-effects model, the research synthesis showed an overall effect size of g = +0.124, 95% CI [0.084, 0.160], representing gender differences in favor of girls.

“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.”

• AssumptionThe authors state this as an assumption: ICT literacy can be treated as a unidimensional construct for the purpose of estimating an overall gender difference.

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In a random-effects model, the overall gender difference in students' ICT literacy performance was statistically significant, positive, and favored girls (g = +0.124, 95% CI [0.084, 0.160], k = 46).

“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.”

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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 for corrected effect sizes it was g = +0.139 (95% CI [0.104, 0.175], k = 21, z = 7.6, p < .001).

“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.”

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In primary school, gender differences in ICT literacy were larger than in secondary school (primary g = +0.201 vs secondary g = +0.113; p < .10), explaining 7.5% of between-study variation.

“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.”

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Further moderator analyses showed that only students' educational level (primary vs. secondary education) explained the variation significantly; gender differences were slightly higher in primary schools.

“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.”

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After correcting for unreliability, the between-study variance was τ2 = 0.014 (SE = 0.006), and the heterogeneity test indicated significant between-study heterogeneity (Q[45] = 475.5, p < .001, I2 = 90.5%).

“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%).”

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The data did not reveal any further moderation effects of region, sampling procedure, or task mode.

“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).”

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The effect shows significant variation between studies: primary studies comprised significantly negative gender effects in favor of boys, insignificant effects, and significantly positive effects in favor of girls.

“(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.”

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The findings showed that only students' educational level moderated gender differences, with higher effects for primary school students.

“Interestingly, our findings showed that only students' educational level moderated gender differences, with higher effects for primary school students.”

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Many researchers concluded that most terms for ICT-related concepts are interchangeable and largely reflect the same content.

“Many researchers concluded that most of the terms are interchangeable and largely reflect the same content (Law et al., 2009;Søby, 2013).”

• cites Law et al., 2009Not checked yet

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• cites Søby, 2013Not checked yet

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The analyses indicated little risk of publication bias, and the sensitivity analyses supported the robustness of the overall effect size against the treatment of the ICILS 2013 data set.

“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).”

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The overall effect size differs significantly from zero, testifying to the existence of gender differences or a gender gap.

“(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.”

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Further sensitivity analyses showed that the overall gender differences were not sensitive toward the correction for unreliability, and the analysis of influential cases did not flag any effect sizes.

“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.”

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The prior systematic review revealed that reporting of reliability and validity of assessments in primary studies was insufficient.

“Moreover, their review revealed that the reporting of the reliability and validity of the assessments in the primary studies was insufficient.”

• cites Siddiq et al. (2016) sourceNot checked yet

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The publication-bias analyses did not provide strong evidence for publication bias and indicated only a small risk of publication bias in the data.

“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.”

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Overall, the study, sample, and publication variables moderated gender differences in digital competence only to a limited extent, leaving the significant between-study variance largely unexplained.

“Overall, these variables moderated the gender differences in digital competence to only a limited extent, leaving the significant between-study variance largely unexplained.”

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Existing frameworks of ICT literacy converge to a great extent to a set of core knowledge domains and skills.

“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).”

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Considering that the extant literature reports considerable variation of gender effects across domains, the existence of gender differences may be domain-specific or specific to certain assessment domains.

“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.”

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The findings contrast previous meta-analyses 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.

“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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The average score reliability across primary studies was 0.86 (SD = 0.08, Mdn = 0.89, range = 0.61-0.95), providing acceptable measurement precision.

“The average score reliability was 0.86 (SD = 0.08, Mdn = 0.89, range = 0.61-0.95),providing an acceptable measurement precision.”

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Hyde (2005) reported a broad range of effect sizes for different measures of mathematics achievement (d = -0.14 to 0.16).

“Hyde (2005) supported this observation and reported a broad range of effect sizes for different measures of mathematics achievement (d = -0.14-0.16).”

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The prior systematic review by Siddiq et al. (2016) concluded that most tests measure knowledge and skills in the area of Information, whereas few measure Communication, Collaboration, Safety, and Problem solving.

“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.”

• cites Siddiq et al. (2016) sourceNot checked yet

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A prior meta-analysis based on self-reports found a small but significant positive effect favoring boys, indicating boys had higher ICT self-efficacy and more favorable attitudes toward technology than girls.

“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).”

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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 social sciences, science, and mathematics.

“(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.”

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The higher gender gap among younger children might be due to primary school students having less access to and therefore experience with technology at school, and being to a lesser degree taught digital competence.

“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).”

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The gender effect on ICT literacy is evident and deviates from those reported for mathematics in some recent research syntheses.

“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.”

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The effect is positive, uncovering higher average performance of girls on ICT literacy tasks and aligning with effects identified in verbal domains.

“(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.”

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The 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 the meta-analysis (e.g., time spent on assessment tasks, test-taking effort, or prior experience with similar tasks).

“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).”

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Recent research has shown that, within the ICT literacy framework, boys and girls tend to score differently in different competence areas.

“Recent research has shown that, within the ICT literacy framework, boys and girls tend to score differently in different competence areas.”

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Boys tend to overestimate their ICT knowledge and skills, while girls tend to underestimate themselves, irrespective of their actual knowledge and skills.

“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).”

• cites Aesaert, Voogt, Kuiper, & van Braak, 2017Not checked yet

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The overall effect aligns with others, but it also indicates that ICT literacy may represent a domain in which equity can be achieved to a certain extent.

“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.”

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This is a surprising result as it seems that the gender gap is higher among younger children.

“This is quite a surprising result as it seems that the gender gap is higher among younger children.”

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The effect size was generally small in magnitude, but its consistency suggests that it should not be ignored.

“The effect size was generally small in magnitude, but its consistency suggests that it should not be ignored.”

• AssumptionThe authors state this as an assumption: ICT literacy can be treated as a unidimensional construct for the purpose of estimating an overall gender difference.

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An explanation for the lack of moderation by test content 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; gender differences for DIGCOMP areas were reported to a very limited extent.

“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.”

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The findings contradict the claims that boys have higher ICT literacy, claims that were merely based on self-efficacy rather than performance measures.

“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).”

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• AssumptionThe authors state this as an assumption: ICT literacy can be treated as a unidimensional construct for the purpose of estimating an overall gender difference.

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Cai et al. (2017) meta-analyzed gender differences in ICT attitudes and self-efficacy and found a significant effect favoring boys (g = -0.17).

“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).”

• cites Cai et al. (2017) sourceNot checked yet

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The varying methodologies and models used to report the gender differences may have also contributed to this variation.

“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).”

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The Cai et al. (2017) meta-analysis contrasts the finding obtained from our meta-analysis.

“Although their meta-analysis examined somehow similar concepts around ICT, it contrasts the finding obtained from our meta-analysis.”

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Voyer and Voyer (2014) found effects in favor of girls in language learning (d = +0.37), science (d = +0.15), and social sciences (d = +0.17), whereas mathematics effects were closer to zero (d = +0.07).

“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).”

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Assessments of ICT literacy often rely on verbal skills such as communication, which may explain the direction of gender effects in ICT literacy compared to more verbal domains.

“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.”

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One limitation might be that primary school students' digital competence is less often assessed compared to secondary school students.

“Moreover, one limitation might be that primary school students' digital competence is less often assessed compared to secondary school students (Siddiq et al., 2016).”

• cites Siddiq et al., 2016 sourceNot checked yet

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