Numerical Training Videos and Early Numerical Achievement: A Study on 3-Year-Old Preschoolers

Early numerical abilities predict later math achievement and could be improved in children by using various training methods. As the literature on the use of training videos to develop numerical abilities is still surprisingly scant, the aim of the present study was to test the efficacy of a numerical training video on the development of counting and number line knowledge in 3-year-old preschoolers. Far transfer effects to cardinality and working memory were also examined. The study involved 86 children randomly assigned to two intervention groups: a numerical training group exposed to videos on counting and number lines; and a control group exposed to videos on colors and animal names in a foreign language. After the video training, there was an improvement in the numerical training group’s counting skills, but not in their number line knowledge, and this improvement persisted six months later. The numerical training group also showed a far-transfer enhancement of cardinality six months after the intervention. Based on our results, numerical training videos could be effective in helping to enhance early numeracy skills in very young preschoolers.

The Pursuit of Effective Working Memory Training: a Pre-registered Randomised Controlled Trial with a Novel Varied Training Protocol

Working memory (WM) training, typically entailing repetitive practice with one or two tasks, has mostly yielded only limited task-specific transfer effects. We developed and tested a new WM training approach where the task paradigm, stimulus type, and predictability of the stimulus sequence were constantly altered during the 4-week training period. We expected that this varied training protocol would generate more extensive transfer by facilitating the use of more general strategies that could be applied to a range of WM tasks. Pre-post transfer effects following varied training (VT group, n = 60) were compared against traditional training (TT group, training a single adaptive WM task, n = 63), and active controls (AC, n = 65). As expected, TT evidenced strong task-specific near transfer as compared to AC. In turn, VT exhibited task-specific near transfer only on one of the measures, and only as compared to the TT group. Critically, no evidence for task-general near transfer or far transfer effects was observed. In sum, the present form of VT failed to demonstrate broader transfer. Nevertheless, as VT has met with success in other cognitive domains, future studies should probe if and how it would be possible to design WM training protocols that promote structural learning where common features of specific tasks would be identified and utilised when selecting strategies for novel memory tasks.

Learning to diagnose X-rays: a neuroscientific study of practice-related activation changes in the prefrontal cortex

Objectives Medical expertise manifests itself by the ability of a physician to rapidly diagnose patients. How this expertise develops from a neural-activation perspective is not well understood. The objective of the present study was to investigate practice-related activation changes in the prefrontal cortex (PFC) as medical students learn to diagnose chest X-rays. Methods The experimental paradigm consisted of a learning and a test phase. During the learning phase, 26 medical students were trained to diagnose four out of eight chest X-rays. These four cases were presented repeatedly and corrective feedback was provided. During the test phase, all eight cases were presented together with near- and far-transfer cases to examine whether participants’ diagnostic learning went beyond simple rote recognition of the trained X-rays. During both phases, participants’ PFC was scanned using functional near-infrared spectroscopy. Response time and diagnostic accuracy were recorded as behavioural indicators. One-way repeated measures ANOVA were conducted to analyse the data. Results Results revealed that participants’ diagnostic accuracy significantly increased during the learning phase (F=6.72, p<0.01), whereas their response time significantly decreased (F=16.69, p<0.001). Learning to diagnose chest X-rays was associated with a significant decrease in PFC activity (F=33.21, p<0.001) in the left dorsolateral prefrontal cortex, the orbitofrontal area, the frontopolar area and the frontal eye field. Further, the results of the test phase indicated that participants’ diagnostic accuracy was significantly higher for the four trained cases, second highest for the near-transfer, third highest for the far-transfer cases and lowest for the untrained cases (F=167.20, p<0.001) and response time was lowest for the trained cases, second lowest for the near-transfer, third lowest for the far-transfer cases and highest for the untrained cases (F=9.72, p<0.001). In addition, PFC activity was lowest for the trained and near-transfer cases, followed by the far-transfer cases and highest for the untrained cases (F=282.38, p<0.001). Conclusions The results suggest that learning to diagnose X-rays is associated with a significant decrease in PFC activity. In terms of dual-process theory, these findings support the notion that students initially rely more on slow analytical system-2 reasoning. As expertise develops, system-2 reasoning transitions into faster and automatic system-1 reasoning.

Predicting and Evaluating Treatment Response: Evidence Toward Protracted Response Patterns for Severely Impacted Students With Dyslexia

Great strides have been made in the development of effective methods of instruction for children with dyslexia. However, individual response to treatment varies, and weaknesses persist for some students with dyslexia despite otherwise effective instruction. Continued efforts are needed to support the prospective identification of poor response, particularly in routine intervention settings. The current study addressed whether indicators of dyslexia risk as outlined by hybrid diagnostic models predict response in children who received Tier 3 dyslexia intervention in their schools. The program’s efficacy has been previously documented in remediating reading abilities in children with dyslexia. Data were examined from 115 elementary-aged children who received routine Tier 3 dyslexia intervention in their schools. Logistic regression revealed powerful effects of preintervention fluency and gender in predicting response, with weaker effects of decoding and rapid naming. Attention-deficit/hyperactivity disorder status also played a role in predicting response. Phonological awareness and listening-reading comprehension discrepancy did not predict response. Profile analyses indicated near- and far-transfer of skill for the adequate response group, whereas growth in the poor response group was limited to near-transfer. Findings support a continuum of severity that may be associated with less robust growth and generalization over the course of the intervention.

Getting at Underlying Mechanisms of Far Transfer - the Mediating Role of Near Transfer

The extent that working memory training improves performance on untrained tasks is highly controversial. Here we address this controversy by testing the hypothesis that far transfer may depend upon near transfer using mediation models in three separate randomized controlled trials (RCTs). In all three RCTs, totaling 460 individuals, performance on untrained N-back tasks (near transfer) mediated transfer to Matrix Reasoning (a measure of fluid intelligence, representing far transfer). Untrained N-back performance also mediated transfer to a working memory composite (RCT 3). These findings support a model of N-back training in which transfer to untrained n-back tasks gates further transfer, at least in the case of working memory at the construct level, and matrix reasoning. This model can help adjudicate between the many studies and meta-analyses of working memory training that have provided mixed results but have not examined the relationship between near and far transfer on an individual differences level.

CHESS RESEARCH: RECENT TRENDS

Considerable research has been carried out on chess in the last seventy years. While classic research has centred on perception, memory, and decision making, contemporary research has focused on deliberate practice, individual differences, and education. Contrasting with classical research, which has mainly used experiments and computer modelling, more recent research has tended to use questionnaires, interviews, and analysis of computer databases as source of information. This article reviews these recent research trends, focusing on what has been learnt from chess research with respect to deliberate practice, intelligence, and transfer of skill. It also discusses ageing and risk taking between civilizations as examples of computer database analyses. Results clearly indicate that deliberate practice is a necessary, but not sufficient condition for achieving high levels of expertise. Other factors are important, some of which are innate. One of them is intelligence. Data show that chess players on average are more intelligent than individuals who do not play chess, and that chess skill positively correlates with intelligence. These results are unlikely to be explained by the hypothesis that chess leads to an increase of intelligence, as the results of experiments using chess instruction to bring about far-transfer effects are inconsistent. In addition, experiment designs used in chess instruction research are typically insufficient to allow strong conclusions about causality. Research using chess databases have led to interesting results, but its generalisability is likely to be limited. The article ends with recommendations for future research.

TRANSFER EFFECT OF N-BACK TRAINING: MATHEMATICAL IMPLICATIONS IN SCHOOL-AGE CHILDREN

Working memory (WM) is the system which is used for short-term storage and where information about cognitive tasks is manipulated. One of the most important characteristics of WM is its limited capacity, which restricts cognitive performance. Despite of this limit in WM capacity, the efficiency of WM can be improved with WM training and this training effect can be transferred to performance on complex tasks, such as mathematical operations. Such training tasks are complex and necessarily include core processes and these measures, therefore, contribute to difficulty to design tasks and interpret the outcomes for specific changes gained from the training. For example, n-back tasks which are used in a wide range of research are based on core training. Since core trainings address the executive functions of WM and enhance the domain-general aspects, increasing performance on domain-general factors may promote both near and far transfer effects of training. In the current study, WM training will be constructed on the basis of the interference framework that characterizes individual differences in WM performance. The aim of this study is to explore individual differences in training and the way transfer effects occur, evaluating gains from Mathematics proficiency. An adaptive version of n-back tasks will be implemented for the proposed study, within WM load and interference lures. The study will be carried out with 40 school-age children between the ages of 9 and 12, and Solomon four group design method will be used to group them. d’ (D-Prime) theory will be conducted in order to obtain detailed comparison between groups as well as interpretation of individual differences in processing of information.

Investigation of a Model-Based Working Memory Training With and Without Distractor Inhibition and Its Comparative Efficacy: A Randomized Controlled Trial on Healthy Old Adults

Background: Various working memory (WM) trainings have been tested, but differences in experimental designs, the lack of theoretical background, and the need of identifying task-related processes such as filtering efficiency limit conclusions about their comparative efficacy.Objectives: In this study, we compared the efficacy of a model-based WM training with (MB+) and without (MB) distractor inhibition on improving WM capacity to a dual n-back and active control condition.Methods: This randomized clinical trial included 123 healthy elderly adults (78 women, 45 men; aged 64.1 ± 8.3 years). All groups underwent 12 40-min training sessions over 3 weeks and four cognitive testing sessions. The first two sessions served as double baseline to account for practice effects. Primary outcome was WM capacity post-training measured by complex span tasks. Near and far transfer was assessed by simple span, n-back, visuospatial and verbal learning, processing speed, and reasoning tasks.Results: Due to preliminary termination (COVID-19), 93 subjects completed the post-training and 60 subjects the follow-up session. On a whole group level, practice effects occurred from prebaseline to baseline in WM capacity (b = 4.85, t(103) = 4.01, p &lt; 0.001, r = 0.37). Linear mixed-effects models revealed a difference in WM capacity post-training between MB+ and MB (b = −9.62, t(82) = −2.52, p = 0.014, r = 0.27) and a trend difference between MB+ and dual n-back (b = −7.59, t(82) = −1.87, p = 0.065, r = 0.20) and control training (b = −7.08, t(82) = −1.86, p = 0.067, r = 0.20). Univariate analyses showed an increase between pre- and post-training for WM capacity within MB+ (t(22) = −3.34, p &lt; 0.05) only. There was no difference between groups pre- and post-training regarding near and far transfer. Univariate analyses showed improved visuospatial learning within MB+ (t(21) = −3.8, p &lt; 0.05), improved processing speed (t(23) = 2.19, p&lt; 0.05) and n-back performance (t(23) = 2.12, p &lt; 0.05) in MB, and improved n-back performance (t(25) = 3.83, p &lt; 0.001) in the dual n-back training.Interpretation: A model-based WM training including filtering efficacy may be a promising approach to increase WM capacity and needs further investigation in randomized controlled studies.