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Cited by 225Cognitive Abilities and TestingCognitive and developmental aspects of mathematical skillsDevelopmental and Educational Neuropsychology

Working memory training in typically developing children: A meta-analysis of the available evidence.

Open access
Sala, Giovanni, Gobet, Fernand·2017·Developmental Psychology
DOI 10.1037/dev0000265
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Abstract

The putative effectiveness of working memory (WM) training at enhancing cognitive and academic skills is still ardently debated. Several researchers have claimed that WM training fosters not only skills such as visuospatial WM and short-term memory (STM), but also abilities outside the domain of WM, such as fluid intelligence and mathematics. Other researchers, while acknowledging the positive effect of WM training on WM-related cognitive skills, are much more pessimistic about the ability of WM training to improve other cognitive and academic skills. In other words, the idea that far-transfer-that is, the generalization of a set of skills across two domains only loosely related to each other-may take place in WM training is still controversial. In this meta-analysis, the authors focused on the effects of WM training on cognitive and academic skills (e.g., fluid intelligence, attention/inhibition, mathematics, and literacy) in typically developing (TD) children (aged 3 to 16). Whereas WM training exerted a significant effect on cognitive skills related to WM training (g = 0.46), little evidence was found regarding far-transfer effects (g = 0.12). Moreover, the size of the effects was inversely related to the quality of the design (i.e., random allocation to the groups and presence of an active control group). Results suggest that WM training is ineffective at enhancing TD children's cognitive or academic skills and that, when positive effects are observed, they are modest at best. Thus, in line with other types of training, far-transfer rarely occurs and its effects are minimal. (PsycINFO Database Record

AI snapshot

Written from the paper’s full text.

TL;DR

This meta-analysis of working memory (WM) training in typically developing children found reliable near-transfer to WM-related skills but little evidence of far-transfer to cognitive or academic skills. The authors conclude WM training is ineffective for improving children’s broader cognitive or academic abilities, with positive effects being modest at best and linked to weaker designs.

Key findings

  • WM training significantly improved near-transfer measures (WM/STM-related outcomes): Hedges’ g = 0.46, 95% CI [0.35, 0.57], k = 30, p < .001; follow-up near-transfer effect was g = 0.33, 95% CI [0.00, 0.65], k = 6, p = .049.
  • Far-transfer effects were small: g = 0.12, 95% CI [0.06, 0.18], k = 74, p < .001; follow-up far-transfer was not significant: g = 0.09, 95% CI [−0.02, 0.20], k = 24, p = .122.
  • Far-transfer effects were smaller in randomized samples (g = 0.07, p = .046) than non-randomized samples (g = 0.27, p < .001), and smaller with active control groups (g = 0.05, p = .311) than passive control groups (g = 0.18, p < .001); randomized samples with active controls had g = 0.03, p = .521.
  • Only mathematics showed a significant domain-specific far-transfer effect (g = 0.20, 95% CI [0.03, 0.36], k = 17, p = .018), but it was not significant in randomized samples (g = 0.10, p = .193) or with active controls (g = −0.11, p = .426).

Methods

  • Systematic search through April 1, 2016, in Scopus, ERIC, PsycInfo, ProQuest Dissertations & Theses, and Google Scholar; inclusion required an intervention training WM, a control group, a non-WM cognitive/academic outcome, participants aged 3–16, typically developing children without specific learning disability or borderline cognitive ability, and sufficient data for effect sizes.
  • Included 25 studies, 26 independent samples, 104 effect sizes (30 near-transfer, 74 far-transfer), total N = 1,601; follow-up subsample n = 6 studies, 30 effect sizes, total N = 249.
  • Random-effects meta-analysis using Hedges’ g, with moderator analyses for random allocation, active/passive control, training duration, age, and domain; publication bias assessed with funnel plots, Egger’s test, trim-and-fill, and p-curve.

Limitations

  • The paper states that follow-up conclusions are limited by few studies/effect sizes: near-transfer follow-up had n = 4 studies and k = 6 effect sizes, and far-transfer follow-up had n = 6 studies and k = 24 effect sizes.
  • The paper states that other potential moderators, such as type of training program, were not considered because of the limited number of effect sizes; it also notes that the small degree of heterogeneity discourages expecting other moderators to change the overall results.
  • Evident from the text: the significant mathematics effect was driven by non-randomized and passive-control comparisons, and the authors caution that near-transfer improvements may reflect task-specific learning rather than genuine WM capacity enhancement.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1037/dev0000265

Cites

80 of 80 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 12 cited sources checked · 0 supported · 0 flagged

  • Findingown data
    § Moderators analysis

    Age was not a significant moderator of far-transfer effects.

    “No other moderator was significant: Age, Z(1) = -1.60,b = -0.03,p = .110;and Domain, p = .703.”
    Quote in the paperNot a substantial claim
  • Findingown data
    § Additional meta-analytic models

    Cognitive control had no significant overall far-transfer effect (g = 0.09, 95% CI [-0.08, 0.26], k = 14, p = .302).

    “= 0.09, 95% CI [-0.08; 0.26], k = 14, p = .302for cognitive control”
    Quote in the paperNot a substantial claim
  • Findingown data
    § Additional meta-analytic models

    For mathematics, random allocation significantly moderated the effect: randomized samples had a smaller effect (g = 0.10, 95% CI [-0.05, 0.25], k = 12, p = .193) than nonrandomized samples (g = 0.49, 95% CI [0.11, 0.88], k = 5, p = .012).

    “Random Allocation was a significant moderator, Z(1) = -2.01,b = -0.35,p = .045.The overall effect sizes in randomized and non-randomized samples were = 0.10, 95% CI [-0.05; 0.25], k = 12, p = .193,and = 0.49, 95% CI [0.11; 0.88], k = 5, p = .012,respectively.”
    Quote in the paperSubstantial claim
  • Findingown data
    § Moderators analysis

    In randomized samples with active control groups, the far-transfer overall effect was not significant (g = 0.03, 95% CI [-0.07, 0.14], k = 34, p = .521).

    “Also, the overall effect size in randomized samples with active control groups was = 0.03, CI [-0.07; 0.14], k = 34, p = .521.”
    Quote in the paperSubstantial claim
  • Findingown data
    § Abstract

    In typically developing children aged 3 to 16, working memory training produced a significant positive overall effect on near-transfer working-memory-related cognitive skills (g = 0.46, 95% CI [0.35, 0.57], k = 30, p < .001).

    “While WM training exerted a significant effect on cognitive skills related to WM training ( = 0.46)”
    • Also stated in: § Near-Transfer Effects · plain
      “The random-effects meta-analytic overall effect size was = 0.46, 95% CI [0.35; 0.57], k = 30, p < .001.”
    Quote in the paperSubstantial claim
  • May combine two claims. 22
  • The quote only partly states this claim. 1
  • Classified as probably not a substantial claim. 16

  • May combine two claims.

    Findingown data
    § Publication bias analysis

    In the fluid intelligence model, trim-and-fill imputed five studies and reduced the point estimate to g = 0.03, 95% CI [-0.09, 0.15].

    “In the fluid intelligence model, five studies were filled in, and the point estimate was = 0.03, 95% CI [-0.09; 0.15].”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § Additional meta-analytic models

    For mathematics, type of control group significantly moderated the effect: active control comparisons had a smaller effect (g = -0.11, 95% CI [-0.38, 0.16], k = 6, p = .426) than passive control comparisons (g = 0.31, 95% CI [0.13, 0.49], k = 11, p = .001).

    “Type of control group was significant, Z(1) = -2.41,b = -0.43,p = .016.The overall effect sizes when WM training was compared to active and passive control groups were = -0.11,95% CI [-0.38; 0.16], k = 6, p = .426,and = 0.31, 95% CI [0.13; 0.49], k = 11, p = .001,respectively.”
    Quote in the paperNot a substantial claim

  • The quote only partly states this claim.

    Findingown data
    § Follow-Up Effects

    Near-transfer follow-up effect sizes showed moderate heterogeneity (I2 = 40.50).

    “The degree of heterogeneity between effect sizes was I 2 = 40.50.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § Publication bias analysis

    In the literacy/word decoding model, trim-and-fill imputed two studies and reduced the point estimate to g = 0.08, 95% CI [-0.03, 0.19].

    “In the literacy/word decoding model, two studies were filled in, and the point estimate was = 0.08, 95% CI [-0.03; 0.19].”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data
    § Inclusion/Exclusion Criteria

    A subsample of 6 included studies reported follow-up effects, yielding 30 follow-up effect sizes and 249 participants.

    “Finally, a subsample of the included studies (n = 6) reported follow-up effects.A total of 30 follow-up effect sizes were computed (6 for WM-related measures, see Table 3; 24 for non-WM-related measures, see Table 4), with a total of 249 participants.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § Inclusion/Exclusion Criteria

    The meta-analysis included 25 studies, 26 independent samples, 104 effect sizes, and 1,601 participants.

    “We found 25 studies, conducted from 2007 to 2016, that met all the inclusion criteria.These studies included 26 independent samples and 104 effect sizes (30 for WM-related measures, see Table 1; 74 for non-WM-related measures, see Table 2), with a total of 1,601 participants.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § Moderators analysis

    Type of control group was a marginally significant moderator of far-transfer effects: comparisons with active control groups had a smaller effect (g = 0.05, 95% CI [-0.05, 0.15], k = 40, p = .311) than comparisons with passive control groups (g = 0.18, 95% CI [0.09, 0.26], k = 34, p < .001).

    “Type of control group was marginally significant, Z(1) = -1.83,b = -0.12,p = .067.The overall effect sizes when WM training was compared to active and passive control groups were = 0.05, 95% CI [-0.05; 0.15], k = 40, p = .311,and = 0.18, 95% CI [0.09; 0.26], k = 34, p < .001,respectively.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § Additional meta-analytic models

    Among the six far-transfer domains, only mathematics had a significant overall effect, which was modest (g = 0.20, 95% CI [0.03, 0.36], k = 17, p = .018).

    “The only significant overall effect size was = 0.20, 95% CI [0.03; 0.36], k = 17, p = .018,for mathematics.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Findingnone given
    § Limitations of the Present Meta-Analysis

    Near-transfer effects seem to remain even a few months after the end of training.

    “Near-transfer effects seem to remain even a few months after the end of the training.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingreasoning
    § Limitations of the Present Meta-Analysis

    The far-transfer follow-up findings are consistent with the immediate post-test outcomes, showing modest or null effects in both measures.

    “In this case, however, the findings are consistent with the immediate post-test outcomes: modest or null effects in both the measures.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data
    § Discussion

    Training duration showed a slight inverse relationship with effect size (b = -0.02).

    “the duration of training seems to be slightly inversely related to the size of the effects (b = -0.02).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § Discussion

    In the meta-analysis, the pooled effect size was smaller for comparisons against active control groups (g = 0.05, p = .311) than for comparisons against passive control groups (g = 0.18, p < .001).

    “the overall effect size was smaller when the experimental group was compared to an active control group ( = 0.05, p = .311)than a passive control group ( = 0.18, p < .001).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § Theoretical and Practical Implications

    In the general population of children, working memory training produces improvements in working-memory-related outcomes but not in other cognitive and academic measures.

    “in the general population of children, WM training induces improvements in WM-related outcomes but not in other types of cognitive and academic measures”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § Moderator analyses

    Random allocation, type of control group, and duration of training were not significant moderators of near-transfer effects.

    “None of the other three moderators were significant: Random allocation, Z(1) = -0.58,b = -0.08,p = .562;Type of control group, Z(1) = -0.31,b = -0.04,p = .760;and Duration of training, Z(1) = 0.42, b = 0.01, p = .678.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data
    § Theoretical and Practical Implications

    Participants showed improvements on a large variety of tasks different from the trained working memory tasks.

    “The fact that the participants showed improvements in a large variety of tasks different from the WM trained tasks (see Table S1.1 in the Supplemental Material available online) might suggest that WM capacity was actually boosted.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Table S1.1 in the Supplemental Material

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data
    § Method Literature Search

    The systematic search followed PRISMA and searched multiple databases, reference lists, and contacted scholars.

    “In accordance with the PRISMA statement (Moher, Liberati, Tetzlaff, & Altman, 2009), a systematic search strategy was used to find the pertinent studies.”
    • Also stated in: § Method Literature Search · plain
      “we searched Scopus, ERIC, Psyc-Info, ProQuest Dissertation & Theses, and Google Scholar databases to identify all the potentially relevant studies.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Moher, Liberati, Tetzlaff, & Altman, 2009

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data
    § Moderators

    The authors coded effect sizes for moderators independently; agreement was complete for random allocation, type of control group, and age; 87% for duration; and Cohen's kappa was .95 for domain.

    “The two authors coded each effect size for moderator variables independently.There was no disagreement with respect to Random allocation, Type of control group, and Age.”
    • Also stated in: § Moderators · plain
      “Regarding the moderator Duration of training, 87% agreement was obtained.For the moderator Domain, the Cohen's kappa was κ = .95.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data
    § Abstract

    Working memory training is ineffective at enhancing typically developing children's cognitive or academic skills, and any positive effects are modest at best.

    “The results suggest that WM training is ineffective at enhancing TD children's cognitive or academic skills and that, when positive effects are observed, they are modest at best.”
    • Also stated in: § Discussion · plain
      “Thus, the results of the meta-analysis do not support the hypothesis according to which WM training benefits cognitive or academic abilities in TD children.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning
    § Theoretical and Practical Implications

    If near-transfer improvements reflect task-specific learning rather than capacity enhancement, then nothing can be inferred about the relationship between fluid intelligence (or any other far-transfer measure) and working memory capacity.

    “If this is the case, nothing can be inferred about the relationship between fluid intelligence (or any other far-transfer measure) and WM capacity.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data
    § Moderator analyses

    No moderator analysis was run for the near-transfer follow-up model because of the small number of effect sizes.

    “Due to the small number of effect sizes, no moderator analysis was run for the near-transfer effects model.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data
    § Discussion

    In typically developing children, working memory training has little or no effect on fluid intelligence, cognitive control, literacy, or science.

    “However, we found little or no evidence that WM training enhances fluid intelligence or domaingeneral processes such as cognitive control.The same applied to academic abilities such as literacy or science.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning
    § Limitations of the Present Meta-Analysis

    The same limitation applies, to a lesser degree, to the far-transfer follow-up effects (n = 6, k = 24).

    “The same limitation applies, to a lesser degree, to the far-transfer follow-up effects (n = 6, k = 24).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning
    § Theoretical and Practical Implications

    The absence of fluid intelligence enhancement could be interpreted as a failed improvement in working memory capacity after training.

    “the absence of fluid intelligence enhancement could be interpreted as a failed improvement in WM capacity after the training (see also the discussion in Melby-Lervag & Hulme, 2013).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Melby-Lervag & Hulme, 2013

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Interpretationreasoning
    § Limitations of the Present Meta-Analysis

    It is hard to see why negligible effects immediately after training should become significantly larger several months after the end of training.

    “In fact, it is hard to see why negligible effects immediately after training, such as those reported in this meta-analysis, should become significantly larger several months after the end of training.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationcitation
    § Discussion

    The moderator analyses may have detected effects caused by random error rather than true heterogeneity between effect sizes.

    “the moderator analyses may have detected effects due to random error rather than true heterogeneity between-effect sizes (see footnote 7).”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Interpretationreasoning
    § Theoretical and Practical Implications

    If the required conditions can be met in a well-powered single study, then it can be convincingly claimed that working memory capacity has been enhanced.

    “If such conditions can be met in a well-powered single study, then it can be convincingly claimed that WM capacity has been enhanced.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data
    § Publication bias analysis

    No p-curve analysis was carried out for the far-transfer follow-up model because none of its effect sizes reached statistical significance.

    “No p-curve analysis was carried out because none of the effect sizes in the model reached statistical significance.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data
    § Discussion

    Self-selection in experimental groups or baseline differences between groups may have inflated effect sizes in nonrandomized samples.

    “This outcome suggests that episodes of selfselection in the experimental groups or differences at baseline level between experimental and control groups may have inflated the effect sizes in samples with no random allocation.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning
    § Abstract

    Far-transfer from working memory training rarely occurs and its effects are minimal.

    “Thus, in line with other types of training, far-transfer rarely occurs and its effects are minimal.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data
    § Limitations of the Present Meta-Analysis

    Other potential moderators, such as the type of training program, were not considered in the meta-analytic models because of the limited number of effect sizes.

    “Finally, other potential moderators -such as the type of training program -were not considered in the meta-analytic models because of the limited number of the effect sizes.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data
    § Publication bias analysis

    No publication bias analysis was run for the science and crystallized intelligence models because of too few effect sizes.

    “Due to the scarcity of effect sizes, no publication bias analysis was run for the science and crystallized intelligence models.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning
    § Theoretical and Practical Implications

    If transfer to untrained domains is more probable in children than in adults during the development of cognitive and academic skills, then the findings cast serious doubt on the idea that training a general mechanism like working memory boosts fluid intelligence, cognitive control, or academic achievement.

    “if far-transfer is more likely to occur in children than adults when cognitive and academic skills are developing, then our findings cast serious doubts on the idea that training a domain-general mechanism such as WM improves fluid intelligence, cognitive control, or academic achievement.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning
    § Inclusion/Exclusion Criteria

    The meta-analysis excluded measures of performance on the trained working memory task to assess genuine near-transfer.

    “importantly, to assess a genuine near-transfer effect, all the measures of performance in the trained WM intervention task were excluded”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning
    § Discussion

    The between-group difference decreased at post-test, suggesting the positive effect size is probably due to a statistical artefact such as regression to the mean or a ceiling effect.

    “The difference between the groups decreased at the post-test, suggesting that the positive effect size is probably due to some statistical artefact (e.g., regression to the mean, ceiling effect).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning
    § Theoretical and Practical Implications

    Testing whether working memory training enhances working memory capacity requires multivariate measures of working memory capacity and that task-related improvements occur through a common factor that is measurement invariant across treatment and control groups.

    “testing whether WM training enhances WM capacity requires not only a set of multivariate measures of WM capacity, but also that task-related improvements occur through a common factor that is measurement invariant across treatment and control groups (i.e., training effects that are proportional to the factor loadings in a structural equation model).”
    Quote in the paperSubstantial claim
35 of 35

  • The paper relies on this without support.

    Publication bias is unlikely when the overall effect size is close to zero.

    “However, it must be kept in mind that the occurrence of publication bias is quite unlikely when the overall effect size is close to zero.”
1 of 1

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?

  • Sala and Gobet (2017) found a modest far-transfer effect (g=0.12) in typically developing children.

    “With TD children (aged 3 to 16), Sala and Gobet (2017) found a medium effect (𝑔̅ = 0.46) with near transfer and a modest effect with far transfer (𝑔̅ = 0.12), with the qualification that the better the quality of the design (use of an active control group), the smaller the effect sizes.”

    From Working memory training in typically developing children: A multilevel meta-analysis (2020) · cites this paper as Sala & Gobet, 2017

  • Sala and Gobet (2017) found a medium near-transfer effect (g=0.46) in typically developing children.

    “With TD children (aged 3 to 16), Sala and Gobet (2017) found a medium effect (𝑔̅ = 0.46) with near transfer and a modest effect with far transfer (𝑔̅ = 0.12), with the qualification that the better the quality of the design (use of an active control group), the smaller the effect sizes.”

    From Working memory training in typically developing children: A multilevel meta-analysis (2020) · cites this paper as Sala & Gobet, 2017

  • In Sala and Gobet (2017), better design quality (active control) was associated with smaller effect sizes.

    “With TD children (aged 3 to 16), Sala and Gobet (2017) found a medium effect (𝑔̅ = 0.46) with near transfer and a modest effect with far transfer (𝑔̅ = 0.12), with the qualification that the better the quality of the design (use of an active control group), the smaller the effect sizes.”

    From Working memory training in typically developing children: A multilevel meta-analysis (2020) · cites this paper as Sala & Gobet, 2017

  • The results are in line with and corroborate Sala and Gobet (2017) and previous meta-analytic syntheses on working memory training in the general population.

    “These results are also in line with Sala and Gobet (2017; a re-analysis with RVE of the data used in that study yields similar results; for the details, see the supplemental materials) and, more broadly, the conclusions of previous meta-analytic syntheses concerning WM training in the general population (Aksayli et al., 2019;Melby-Lervåg et al., 2016;Sala et al., 2019a).”

    From Working memory training in typically developing children: A multilevel meta-analysis (2020) · cites this paper as Sala & Gobet, 2017

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.

  • Table 4 mislabels far-transfer effects as near-transfer

    Minor

    The Table 4 heading calls its 24 follow-up effect sizes near-transfer effects, but the methods identify the 24 effects in Table 4 as non-WM-related (far-transfer) effects. The six WM-related follow-up effects are assigned to Table 3.

1 of 1

Cites

Flagged first, then by citations

1 of the 81 references couldn’t be matched to a known paper.

Research works printed but not linked: 5

  1. Gobet, F. (2015). Understanding expertise: A multi-disciplinary approach. London: Palgrave/Macmillan.
  2. Kun, Y. (2007). Impact of computerized cognitive training on working memory, fluid intelligence, science achievement. Doctoral dissertation, Stanford University, CA: Stanford.
  3. Lindsay, J. R. (2012). Everything I need to know I learned before elementary school: The relationships between phoneme awareness, letter knowledge, and working memory. Doctoral dissertation, University of California, CA: Irvine.
  4. Perkins, D. N., & Salomon, G. (1994). Transfer of learning. In T. N. Postlethwaite & T. Husen (Eds.), International Encyclopedia of Education (pp. 6452-6457). Oxford: Elsevier.
  5. Shavelson, R. J., Yuan, K., Alonzo, A. C., Klingberg, T., & Andersson, M. (2008). On the impact of computerized cognitive training on working memory and fluid intelligence. In D. C. Berliner & H. Kuppermintz (Eds.), Contributions of educational psychology to changing institutions, environments, and people (pp. 1-11). New York, NY: Routledge.

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Related

Authors
Sala, G., & Gobet, F.
Affiliations
University of Liverpool (GB)
ORCID
Venue
Developmental Psychology
Publisher
American Psychological Association (APA)
Published
2017
Volume
53
Issue
4
Pages
671-685
ISSN
  • 0012-1649 (ISSN-L)
  • 1939-0599
DOI
10.1037/dev0000265
OpenAlex
W2586089211
Semantic Scholar
36e34376d9eeaf18b8a18e3e58fbbfd380a6ec95
Cited by
216
References
81
Citations by year
2026: 15 · 2025: 22 · 2024: 23 · 2023: 15 · 2022: 34 · 2021: 21 · 2020: 27 · 2019: 34 · 2018: 17 · 2017: 8
FWCI
3.73
Type
journal article
Language
en
Open access
Locations
  • Developmental Psychology (publishedVersion)
  • PubMed (publishedVersion)
  • London School of Economics and Political Science Research Online (London School of Economics and Political Science) (acceptedVersion)
  • London School of Economics and Political Science Theses Online (London School of Economics and Political Science) (submittedVersion)
Topics
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
  • Physical Sciences › Mathematics › Statistics and Probability › Cognitive and developmental aspects of mathematical skills
  • Social Sciences › Psychology › Neuropsychology and Physiological Psychology › Developmental and Educational Neuropsychology
Keywords
working memory training, far transfer, typically developing children, fluid intelligence, visuospatial working memory, short-term memory, mathematics achievement, literacy, academic skills, training effectiveness
MeSH terms
Literacy, Adolescent, Attention, Child, Psychology, Child, Child, Preschool, Cognition, Humans, Inhibition, Psychological, Intelligence, Learning, Memory, Short-Term, Mathematical Concepts

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.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-08.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-08.

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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