How working memory capacity and shifting matter for learning with worked examples—A replication study.

Although the existing literature has explored the link between cognitive functioning and speech recognition in noise, the specific role of fluid intelligence still needs to be studied. Given the established association between working memory capacity (WMC) and fluid intelligence and the predictive power of WMC for speech recognition in noise, we aimed to elucidate the mediating role of fluid intelligence. We used data from the n200 study, a longitudinal investigation into aging, hearing ability, and cognitive functioning. We analyzed two age-matched samples: participants with hearing aids and a group with normal hearing. WMC was assessed using the Reading Span task, and fluid intelligence was measured with Raven's Progressive Matrices. Speech recognition in noise was evaluated using Hagerman sentences presented to target 80% speech-reception thresholds in four-talker babble. Data were analyzed using mediation analysis to examine fluid intelligence as a mediator between WMC and speech recognition in noise. We found a partial mediating effect of fluid intelligence on the relationship between WMC and speech recognition in noise, and that hearing status did not moderate this effect. In other words, WMC and fluid intelligence were related, and fluid intelligence partially explained the influence of WMC on speech recognition in noise. This study shows the importance of fluid intelligence in speech recognition in noise, regardless of hearing status. Future research should use other advanced statistical techniques and explore various speech recognition tests and background maskers to deepen our understanding of the interplay between WMC and fluid intelligence in speech recognition.

It is well established that measures of reasoning ability and of working memory capacity (WMC) correlate positively. However, the question of what explains this relationship remains open. The purpose of this study was to investigate the capacity hypothesis, which ascribes causality to WMC. This hypothesis holds that people high in WMC are more successful in capacity-demanding cognitive tasks than people lower in WMC because they can temporarily maintain more information in the form of sub-goals, hypotheses, and partial solutions. Accordingly, this hypothesis predicts that the correlation between WMC and reasoning performance should increase as the capacity demands of the reasoning items increase. We tested this prediction using items from Raven's Progressive Matrices and two measures of WMC, complex span and the k estimate from the Visual Arrays task. Neither WMC measure showed the effect predicted by the capacity hypothesis. Furthermore, the results cannot be attributed to restriction of range in performance on the individual reasoning items. This finding adds to existing evidence calling into question the capacity hypothesis, and, more generally, the view that WMC has a causal influence on fluid intelligence.

Working memory capacity may be a critical factor that influences the effectiveness of collaborative learning; however, no studies have directly explored this effect. Using worked examples as learning tasks, Experiment 1 used a 2 (working memory capacity) × 2 (learning format) factorial design to examine the effects of collaborative learning versus individual learning of 4th-grade Chinese elementary school students with different working memory capacities. High-capacity learners displayed less working memory resource depletion and better transfer performance during collaborative learning than individual learning. In contrast, no differences were found among the low-capacity learners. Collaborative learning benefited high-capacity learners but not low-capacity learners, per our observations. To further optimize collaborative learning for low-capacity learners and expand the findings to heterogeneous collaborative learning, Experiment 2 adopted a 2 (member capacity) × 2 (group capacity) factorial design to explore the effects of member and group working memory capacity on collaborative learning in heterogeneous groups. High-capacity members displayed less working memory resource depletion and better far transfer performance in high-capacity groups compared to low-capacity groups. Simultaneously, all members had better near transfer performance in high-capacity groups compared to low-capacity groups. Both member and group working memory capacities influenced the effect of heterogeneous collaborative learning. However, low-capacity members only partially benefited from collaborative learning in high-capacity heterogeneous groups.

Wonderlic, working memory capacity, and fluid intelligence

Prospective associations between intelligence, working memory capacity, and intrusive memories of a traumatic film: Potential mediating effects of rumination and memory disorganization

Working memory capacity consistently correlates with fluid intelligence. It has been suggested that this relationship is partly attributable to strategy use: Participants with high working memory capacity would use more effective strategies, in turn leading to higher performance on fluid intelligence tasks. However, this idea has never been directly investigated. In 2 experiments, we tested this hypothesis by directly manipulating strategy use in a combined experimental-correlational approach (Experiment 1; N = 250) and by measuring strategy use with a self-report questionnaire (Experiment 2; N = 93). Inducing all participants to use an effective strategy in Raven's matrices decreased the correlation between working memory capacity and performance; the strategy use measure fully mediated the relationship between working memory capacity and performance on the matrices task. These findings indicate that individual differences in strategic behavior drive the predictive utility of working memory. We interpret the results within a theoretical framework integrating the multiple mediators of the relationship between working memory capacity and high-level cognition.

The relationship between baseline pupil size and intelligence

Collaboration scripts and heuristic worked examples have been described as powerful scaffolds to support skill acquisition in CSCL. While CSCL scripts particularly facilitate argumentative discourse within groups, heuristic worked examples provide heuristics and worked out pathways to solve domain-specific tasks. Yet, both scripts and heuristic worked examples are often designed in a one-size-fits-all fashion. Granting learners the opportunity to adapt these scaffolds to their self-perceived needs might be a way to further enhance their effects. We tested this assumption in two experiments. In experiment 1, we compared the effects of learning with adaptable and non-adaptable CSCL scripts. In experiment 2, we compared the effects of learning with adaptable and non-adaptable heuristic worked examples. University students (N = 167) learned repeatedly in pairs with either adaptable or non-adaptable scaffolding in the context of mathematical conjecture problems. Results show that adaptable CSCL scripts were partly helpful for students with higher levels of self-regulation skills. Non-adaptable maximal scaffolding supported learning of distinctive skill components. Social-discursive components were best facilitated by maximal heuristic worked examples through content knowledge scaffolds. In contrast, CSCL scripts best facilitated domain-specific skill components by scaffolding learners’ engagement in social discourse about domain knowledge. The study provides recommendations for designing adaptable scaffolding by taking into account the relation between the targeted skill component and the activities scaffolded in the learning process. We suggest conducting future studies on adaptable scaffolding with a focus on supporting learning regulation and group awareness to improve learners’ success in CSCL environments.

The worked example and expertise reversal effect in less structured tasks: Learning to reason about legal cases

Eighty‐three (83) high school chemistry students were administered tests of cognitive reasoning level, cognitive restructuring ability, disembedding ability, working memory capacity, and prior knowledge before a learning segment on balancing chemical equations by inspection. After a four‐day instructional segment utilizing direct teaching methodology, participants were given a posttest on balancing equations. Initial regression analysis indicated that a multicollinearity problem existed. Factor analysis and correlational data indicated that the reasoning, restructuring, and disembedding variables could be collapsed and redefined as a single restructuring variable. A hierarchial regression analysis was then performed, and the following conclusions were derived: (1) when prior knowledge alone is considered, students' understanding of chemical formulas significantly (p < 0.05) influences overall equation balancing performance; (2) when prior knowledge, restructuring, and working memory are considered, only restructuring ability significantly (p < 0.05) influences overall performance; (3) working memory capacity does not significantly (p < 0.05) influence overall performance but does on certain posttest items; (4) prior knowledge and restructuring ability also significantly (p < 0.05) influence performance on certain posttest items. Discussion includes the rationale for identifying the collapsed variable as restructuring and the absence of working memory capacity as a significant influence on overall performance.

The struggles faced by elder learners suffering from age-related cognitive decline are often overlooked by instructional designers. However, existing educational theories that already inform learning strategy development for other populations should also help establish instructional methods used to help elder learners. In this article, cognitive load theory frames an exploration of proposed means to slow or counteract the effects of age-related cognitive decline in elder learners. Attention is given to the ways in which multimedia learning methods adhering to certain principles of cognitive load theory can increase available working memory capacity. Evidence is provided to show that cognitive load theory-based practices can also facilitate one’s activation of prior knowledge and betters one’s attentional control. Additionally, elder learners benefit from tasks that include worked examples and goal-free problems, whereas conventional, goal-oriented problems impose greater extraneous load on an already taxed working memory. The outcomes of the present analysis can also be applied to stroke victims’ rehabilitation plans and may offer implications for individuals suffering from other brain injuries, attention deficit-hyperactivity disorder, or dementia-related illnesses.

Individuals scoring higher in tests of general cognitive abilities tend to perform better on novel and familiar mathematical tasks. It has been scarcely investigated how this superior mathematical performance relates to the amount of cognitive resources that is invested to solve a given task. In this study we propose that, on novel tasks, individuals with high cognitive abilities outperform less able individuals, because they allocate a higher amount of resources. On familiar tasks, however, individuals with higher abilities profit from more efficient processes compared to individuals of lower cognitive abilities. We tested this hypothesis by administering to 11th graders a geometric analogy task not practiced at school and an algebraic transformation task comprising operations that are routinely required during mathematical courses. General cognitive abilities were measured with Ravens Advanced Progressive matrices (fluid intelligence), the d2 (focused attention) and KAI-N (working memory capacity). Resource allocation was measured by assessing pupil diameter during the problem-solving process. Performance on both the analogy and the algebra task was correlated with general cognitive abilities, especially fluid intelligence. In line with our assumptions, a positive correlation between fluid intelligence and resource allocation was observed in the novel geometric analogy task, whereas the correlation was not significant in the more familiar algebra task.

Mental speed theories of intelligence suggest that people are smarter because they are faster. We argue that attention control plays an important and fundamental role in mediating the relationship between basic sensory processes and more complex cognitive processes such as fluid intelligence. One of the most successful paradigms for establishing a mental speed theory of intelligence is the inspection time task. In this article, we examine the mental speed and the attention control perspectives on the inspection time task and its relationship with fluid intelligence. Integrating experimental and correlational approaches, we find that attention control statistically explains the inspection time task's correlation with fluid intelligence and working memory capacity. Attention control and inspection time are correlated beyond their relationship with other measures of processing speed. Further, while we find no evidence that selective attention specifically is related to inspection time performance, both attention control and inspection time predicted declines in accuracy as participants sustained their attention over time; other measures of processing speed did not predict sustained attention performance. Collectively, these results indicate that inspection time is related to the ability to control attention, especially the ability to sustain attention over time. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

There has been minimal experimentation testing the effectiveness of icons (or interface features in general) on distributed team decision making. To overcome this deficiency, an experiment tested the effectiveness of a icon to remind team members to send information to their teammates, and a receive icon to tell them when they had received information, for a simulated, military task. As predicted, the icon was effective in maintaining information flow, particularly when time pressure was high and simulated teammates sent less information, because it reduced memory burden and supported proactive behavior. The receive icon was only effective in supporting decision accuracy when time pressure was low. As time pressure increased, participants' with the receive icon increasingly used a strategy of making decisions before reading the most important information, completely counter to expectations. These results illustrate the subtle, sometimes surprising way task characteristics (e.g., time pressure) can affect participants' strategies and, thereby, nullify the positive effect of displays on performance. The experiment also examined other task characteristics and working memory capacity, and showed how the lens model equation (LME) helped explain all effects on decision accuracy.

Starting from the assumption that working memory capacity is an important predictor of general fluid intelligence, we asked which aspects of working memory account for this relationship. Two theoretical stances are discussed. The first one posits that the important explanatory factor is storage capacity, roughly defined as the number of chunks possible to hold in the focus of attention. The second one claims that intelligence is explained by the efficiency of executive control, for instance, by prepotent response inhibition. We investigated 96 children at the age between 10 and 13. They completed a version of the n-back task that allows assessment of both storage capacity and inhibitory control. They also completed Raven’s Progressive Matrices as the fluid intelligence test and the Test for Creative Thinking - Drawing Production, for control purposes. We found that Raven’s scores correlated negatively with the number of unnecessary responses to irrelevant stimuli but they did not correlate with the number of signal detections. We conclude that children’s fluid intelligence depends on inhibitory control, with no relationship with storage capacity.