# TRAINING AND ENHANCING EXECUTIVE FUNCTION

EDITED BY : Gian Marco Marzocchi, Maria Carmen Usai and Steven J. Howard PUBLISHED IN : Frontiers in Psychology

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ISSN 1664-8714 ISBN 978-2-88966-103-9 DOI 10.3389/978-2-88966-103-9

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# TRAINING AND ENHANCING EXECUTIVE FUNCTION

Topic Editors:

Gian Marco Marzocchi, University of Milano-Bicocca, Italy Maria Carmen Usai, University of Genoa, Italy Steven J. Howard, University of Wollongong, Australia

Citation: Marzocchi, G. M., Usai, M. C., Howard, S. J., eds. (2020). Training and Enhancing Executive Function. Lausanne: Frontiers Media SA. doi: 10.3389/978-2-88966-103-9

# Table of Contents

Per Normann Andersen, Marita Eggen Klausen and Erik Winther Skogli

*34 Program for the Neuropsychological Stimulation of Cognition in Students: Impact, Effectiveness, and Transfer Effects on Student Cognitive Performance*

Caroline de Oliveira Cardoso, Alessandra Gotuzo Seabra, Cristiano Mauro Assis Gomes and Rochele Paz Fonseca

*50 Sustained Effect of Music Training on the Enhancement of Executive Function in Preschool Children*

Yue Shen, Yishan Lin, Songhan Liu, Lele Fang and Ge Liu

*64 Executive Functions Can Be Improved in Preschoolers Through Systematic Playing in Educational Settings: Evidence From a Longitudinal Study*

Ricardo Rosas, Victoria Espinoza, Felipe Porflitt and Francisco Ceric

Carolien A. van Houdt, Cornelieke S. H. Aarnoudse-Moens, Aleid G. van Wassenaer-Leemhuis, A. R. Céleste Laarman, Corine Koopman-Esseboom, Anton H. van Kaam and Jaap Oosterlaan

*143 Enhancing Executive Functions Through Social Interactions: Causal Evidence Using a Cross-Species Model* Rosemarie E. Perry, Stephen H. Braren, Millie Rincón-Cortés, Annie N. Brandes-Aitken, Divija Chopra, Maya Opendak, Cristina M. Alberini, Regina M. Sullivan and Clancy Blair *154 Coding in Primary Grades Boosts Children's Executive Functions* Barbara Arfé, Tullio Vardanega, Chiara Montuori and Marta Lavanga *173 Improving Executive Functions at School in Children With Special Needs by Educational Robotics* Maria Chiara Di Lieto, Emanuela Castro, Chiara Pecini, Emanuela Inguaggiato, Francesca Cecchi, Paolo Dario, Giovanni Cioni and Giuseppina Sgandurra *190 Is Cognitive Training Effective for Improving Executive Functions in Preschoolers? A Systematic Review and Meta-Analysis* Nicoletta Scionti, Marina Cavallero, Cristina Zogmaister and Gian Marco Marzocchi *213 Everyday Practices and Activities to Improve Pre-school Self-Regulation: Cluster RCT Evaluation of the PRSIST Program* Steven J. Howard, Elena Vasseleu, Marijka Batterham and Cathrine Neilsen-Hewett *228 Empowering Executive Functions in 5- and 6-Year-Old Typically Developing Children Through Educational Robotics: An RCT Study* Maria Chiara Di Lieto, Chiara Pecini, Emanuela Castro, Emanuela Inguaggiato, Francesca Cecchi, Paolo Dario, Giovanni Cioni and Giuseppina Sgandurra *238 Enhancing Executive Control: Attention to Balance, Breath, and the Speed*  Versus *Accuracy Tradeoff* Varsha Singh and Vaishali Mutreja

# Editorial: Training and Enhancing Executive Function

#### Gian Marco Marzocchi 1 \*, Maria Carmen Usai 2 and Steven J. Howard3

*1 Department of Psychology, University of Milan-Bicocca, Milan, Italy, 2 Department of Education, University of Genoa, Genoa, Italy, 3 Early Start and School of Education, University of Wollongong, Wollongong, NSW, Australia*

Keywords: executive functions, training, rehabilitation, cognitive control, technological interventions

**Editorial on the Research Topic**

#### **Training and Enhancing Executive Function**

Executive Function (EF) refers to a complex set of cognitive control processes necessary for adaptive functioning in daily life. EFs are predictive of intellectual achievement, health, wealth, and quality of life across the entire life span (Moffitt et al., 2011), often more so than IQ or socioeconomic status (Bertollo and Yerys, 2019). Evidence suggests that EFs can be distinguished into three core capacities (working memory, inhibition, and shifting), which combine to support the higher-order cognitive processing (e.g., planning, problem solving) required to remain goal-directed, resist contrary impulses and distraction, and pursue more-positive (rather than most-immediate) outcomes. Given this foundational importance, there has been increasing interest in improving EFs. The goals of this line of research have been 2-fold: to improve EFs; and, as a consequence, stimulate generalized improvements to other cognitive and life domains.

Yet approaches to stimulate EF change are highly discrepant, have yielded inconsistent effects and limited transfer to untrained abilities and outcomes, and there is little agreement about the underlying mechanisms of change that are needed to stimulate development in EFs (and EF-related trajectories and outcomes). This special issue thus aimed to provide a snapshot of current evidence, approaches and perspectives on EF intervention, to highlight emerging insights, to stimulate a reconciliation, and to identify a unified way forward. Typifying contemporary investigations in this field, we characterize submissions to this special issue as falling into one of five approaches for fostering EFs: play-based and curricular approaches; technology-leveraged approaches; physical approaches; strategy-based approaches; and investigations of plausible causal mechanisms. In our conclusion, we offer some of our take-aways and suggestions for a possible way forward in this area.

#### Approved by:

*Katharina J. Rohlfing, University of Paderborn, Germany*

\*Correspondence: *Gian Marco Marzocchi<EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to Developmental Psychology, a section of the journal Frontiers in Psychology*

Received: *30 June 2020* Accepted: *22 July 2020* Published: *28 August 2020*

#### Citation:

*Marzocchi GM, Usai MC and Howard SJ (2020) Editorial: Training and Enhancing Executive Function. Front. Psychol. 11:2031. doi: 10.3389/fpsyg.2020.02031*

### PLAY-BASED AND CURRICULAR APPROACHES

The largest category of submissions to this special issue pertained to play-based and/or curricular approaches to fostering EFs with pre-school and primary school children. In this approach, everyday playful situations and activities were used to inject EF challenge into real-world situations, with the aim of promoting EFs and related abilities (e.g., school readiness, learning). For instance, the PRSIST Program (Howard et al.), Red Light Purple Light Circle Time Games (McClelland et al.), and Chicco and Nana (in the Italian version; Traverso et al.) supported pre-school educators to engage young children in EF-injected activities and games. Each program generated small improvement in EFs, with the latter two also generating gains in academic learning when curricular content was added. Similar EF gains were found amongst primary school students 8 months after completion of a school-based program of EF games and activities (Rosas et al.).

Other studies within this category integrated EF challenge into school curricula and activities. For instance, the PENcE program (de Oliveira Cardoso et al.) yielded EF benefits after teacher-led

**5**

instruction of EF strategies, which were practiced during inschool activities and then extended to real-world situations. Teacher-rated EFs also improved after an arts- and culturefocused program that injected EF challenge into music, drama, dance, literature, art, and/or photography lessons (Andersen et al.), and objectively measured EFs similarly improved after a pre-school music program (Shen et al.).

While we consider these as play-based and curricular approaches, of course alternative classifications are possible and there is substantial overlap between these and subsequent studies. In fact, many of these programs also included technology, motor activities, and/or strategy-based instruction that are central to approaches otherwise classified. This highlights the likelihood of a set of general principles of effective EF intervention, which may need to be adjusted to align with the "what, where, who, why, and how" of EF intervention.

### TECHNOLOGY-LEVERAGED APPROACHES

Several studies used a technology-leveraged approach to improve EFs across different populations, including typically developing, special needs, and preterm children from preschool- to school-age. Although we characterized five studies as technology-leveraged intervention, we can distinguish two distinct approaches to technology use amongst them. In one case, the technological tools were used to deliver the intervention. This is the case of the intervention presented in van Houdt et al.'s study, where the BrainGame Brian Training sought to improve EF abilities in a randomized controlled trial involving school-aged children born very preterm. Another example is Rossignoli-Palomeque et al.'s study, in which the Nexxo-training app was supplemented by metacognitive strategies given by an instructor to improve inhibition and vigilance abilities. Technology was also employed as a vehicle for the delivery of Exergames, where body movements were necessary to play a computer game through connected devices (Mossmann et al.). Consistent amongst these approaches was their engagement and challenge of EFs through effortful tasks (Diamond and Ling, 2016), although EF improvements were inconsistent and there were limited generalized improvements in untrained and realworld outcomes.

The other approach, which in the current set of studies seemed to be more promising in terms of EF gains, was when a technology-based intervention exploited use of computational processes to perform activities in the real world, such as with the educational robotics approach (Di Lieto, Castro et al.; Di Lieto, Pecini et al.). That is, educational robotics uses programming principles that are used to manipulate concrete objects (i.e., robots) to speculate and test effects of this manipulation. In doing so, these approaches seek to promote not only academic skills, but also domain-general skills such as planning, problemsolving and metacognitive abilities. In our compilation, this approach yielded effects in both school- and pre-school-aged children, and with special needs groups. A similar approach, based on computational thinking and code processing activities (Arfé et al.), yielded significantly improved planning and inhibition skills.

Taken together, these results suggest that technology can provide a virtual environment to stimulate EF challenge, but that this can be more or less effective in promoting EF and in generalizing benefit to real-world behavior. More positive results seemed to drive from interventions in which technology compelled children to engage EFs in activities played outside of a virtual environment.

### PHYSICAL APPROACHES

Another approach sought to leverage the physical body to promote EF. Several possible mechanisms for such an effect have been suggested. Singh and Mutreja's study explored the mechanisms through which specific body activities might influence EF, specifically investigating the association of postural and breath control with EF, through Yoga training. The authors suggest that attention to postural and breath control during yoga asanas and pranayama, respectively, may play a key role in enhancing EF. Inhibition was shown to benefit from yoga training, in particular, compared to working memory or shifting.

### STRATEGY-BASED APPROACHES

In contrast to previous studies that target expansion of EF capacities, Chan et al. adopted a strategy-promotion approach to improve effective and efficient use of EFs. This approach provides participants with explicit instruction and practice to improve strategies useful in situations where it is necessary to exercise EF control. In this study, children became able to generalize and apply different strategies to novel problem-solving tasks, on which they did not receive any explicit instruction.

### CAUSAL MECHANISMS INVESTIGATION

Another promising approach to investigate the causal mechanisms for promoting EFs is represented by Perry et al.'s contribution, in which a rat model was employed to investigate the extent to which social experiences and the acquisition of social skills contribute to the development of EFs. Although it is unclear to what extent these findings can be extended to human situations, it represents an experimental confirmation with rats of negative impacts of early adverse conditions and the role of social relations as a moderator of EF development.

## CONCLUSIONS

An average effect of EF training with preschoolers was provided by Scionti et al.; they found small EF improvement, probably due to young age of the participants and weak specialization of their EFs. Moreover, they found that these programs were significantly more effective for developmentally at-risk children (e.g., ADHD, low SES) than for typically developing children.

In conclusion, we propose that future studies on EF training should integrate, comparatively evaluate, and reconcile across different approaches (play and curriculum based, leveraging new technologies) to discern principles for effective EF intervention. These approaches should stimulate both cognitive and emotional-motivational aspects of EF to increase likelihood of far transfer to real-world outcomes of interest (e.g., academic

### REFERENCES

and life success). Finally, EF studies should pay particular attention to what works for whom, and under what conditions.

### AUTHOR CONTRIBUTIONS

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

wealth, and public safety. Proc. Natl. Acad. Sci. U.S.A. 108, 2693–2698. doi: 10.1073/pnas.1010076108

**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2020 Marzocchi, Usai and Howard. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Far-Transfer Effects of Strategy-Based Working Memory Training

#### Sharon Chan1 \*, Ulrich Mueller2 and Michael E. J. Masson2

1 University of Toronto, Applied Psychology and Human Development, Toronto, ON, Canada, 2 Department of Psychology, University of Victoria, Victoria, BC, Canada

We assessed the transfer effects of training working memory strategies to a novel problem-solving task. Previous WM training studies have produced little evidence for transfer across contexts. In the current study, 64 6- to 9-year-olds were randomly assigned to one of four training conditions: semantic and rehearsal training, semantic training only, rehearsal training only, and treated control group. All training groups performed significantly better on the transfer task than the control group, but training groups did not differ significantly from each other. Implications of the findings for cognitive interventions and future WM training studies are discussed.

#### Edited by:

Steven J. Howard, University of Wollongong, Australia

#### Reviewed by:

Barbara Carretti, University of Padova, Italy Kate Cockcroft, University of the Witwatersrand, South Africa Helen St Clair-Thompson, Newcastle University, United Kingdom

> \*Correspondence: Sharon Chan<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Developmental Psychology, a section of the journal Frontiers in Psychology

Received: 13 February 2019 Accepted: 16 May 2019 Published: 04 June 2019

#### Citation:

Chan S, Mueller U and Masson MEJ (2019) Far-Transfer Effects of Strategy-Based Working Memory Training. Front. Psychol. 10:1285. doi: 10.3389/fpsyg.2019.01285 Keywords: working memory, strategy training, problem solving, executive function, far transfer

# INTRODUCTION

Working memory (WM) is a limited-capacity system responsible for temporary storage and simultaneous processing and manipulation of information (Baddeley, 2003; Müller and Kerns, 2015). WM has been linked to general intelligence and reasoning skills (Süß et al., 2002; Kane et al., 2004; Au et al., 2015), and shown to be predictive of academic outcomes such as school readiness and achievement (Bull and Lee, 2014; Müller and Kerns, 2015). Deficits in WM have also been implicated in neurodevelopmental disorders (Melby-Lervåg et al., 2012). Given the important role of WM capacity in cognitive processes and scholastic skills, considerable attention has been given to WM training with the goal of improving WM capacity (Karr et al., 2014; Melby-Lervåg et al., 2016; Weicker et al., 2016). A central issue in assessing the effectiveness of WM training concerns the transfer of training effects. If WM training produces improvements only in a narrow set of tasks that are highly similar to the trained task (near transfer), then it is hardly worthwhile investing resources in this type of training. Rather, to be considered effective, training effects should generalize to untrained tasks that are dissimilar from the trained task (far transfer; Barnett and Ceci, 2002). Furthermore, to be considered effective, training effects should also transfer temporally, that is, be maintained over time.

Independent reviews of training studies have arrived at different conclusions with regard to the effectiveness of WM training (see Klingberg, 2010; Shipstead et al., 2010; Morrison and Chein, 2011; Melby-Lervåg and Hulme, 2013; Karbach and Verhaeghen, 2014; Karr et al., 2014; Au et al., 2015; Melby-Lervåg et al., 2016; Weicker et al., 2016). Current research provides evidence for reliable short-term gains that generalize to somewhat similar WM tasks (intermediate transfer), yet there is no evidence that "working memory training convincingly produces effects that generalize to important real-world cognitive skills . . . even when assessments take place immediately after training" (Melby-Lervåg et al., 2016, p. 523; see also Shipstead et al., 2010; Melby-Lervåg and Hulme, 2013).

**8**

One reason for the inconsistent findings is the failure to pay attention to the distinction between untreated and treated (or active) control groups (Melby-Lervåg et al., 2016). In treated control groups, participants engage in activities that aim to provide equivalent exposure to non-experimental variables that may otherwise act as confounds, such as time spent interacting with the experimenter, or equivalent time looking at comparable stimuli. However, such filler activities lack the essential features characteristic of the training. In non-treated control groups, variables other than the intended training may be causing differences between groups. To illustrate the importance of treated control groups, consider a handful of studies measuring far-transfer training effects of non-verbal ability (e.g., Nutley et al., 2009; Jaeggi et al., 2011). In these studies, significant training effects were not detected when treated as opposed to untreated control groups were used. Furthermore, far transfer rarely has been documented in studies using treated control groups in combination with randomized designs (Wass et al., 2012; Melby-Lervåg et al., 2016). Thus, training studies should strive to include treated control groups to increase internal validity of the research design (Melby-Lervåg et al., 2016).

A further reason for inconsistent findings is that training methods may vary in their intended scope and specificity of training. WM training methods can generally be categorized as either core-based if they target domain-general abilities, or strategy-based if they target specific cognitive strategies that change how information is organized and encoded (Morrison and Chein, 2011). Core training methods are attractive because they are designed to target domain-general WM mechanisms. Such training would not be associated with a particular type of information or sensory modality, but would aid in the overall encoding, maintenance, and retrieval of information. Core-based training paradigms are necessarily complex because the training task must satisfy a long roster of criteria (see Morrison and Chein, 2011, for discussion), but such complexity often presents a challenge for task design and the interpretation of results when trying to identify specific mechanisms of change.

Another more problematic assumption made by advocates of core-based training is that because the training task is complex and involves core processes, observed improvements on the trained task equates to improvements in overall domaingeneral abilities. However, such effects can be interpreted as context-bound practice effects, and there is insufficient evidence that learning would transfer to new tasks that differ in presentation format.

In order to differentiate true training effects in core-processing ability from practice effects, one must be able to demonstrate transfer to a novel post-training task. The use of a novel posttraining task, in turn, creates the problem that training and post-training tasks may not be tapping into the same underlying constructs. To circumvent this problem, researchers in cognitive training may adopt an alternative bottom-up approach by directly training specific strategies that are reflective of more efficient domain-general abilities, and which then can be applied to a variety of contexts. Strategies are effortful, goal-directed processes that enhance performance by facilitating information encoding, maintenance, and retrieval (St Clair et al., 2010; Morrison and Chein, 2011). In strategy-based training studies, participants are explicitly taught to use the strategy of interest and then encouraged to use and refine their mastery of specific skills in practice. In some situations, the specificity of strategy training is a grave limitation in itself, but in differentiating between strategies that promote a way of doing (e.g., remembering numbers in groups of threes to facilitate memorization), and those strategies that promote a way of thinking (e.g., chunking information at large makes memorization easier), strategies may serve as effective tools in new situations. Working memory strategies, in particular, can be used in different situations with analogous WM demands. For example, although rehearsal can be applied to remember discrete items in a list, it can also be used in combination with a mnemonic or acronym to remember more complex information such as a sequence of instructions or steps to a problem. Because of the omnipresence of WM demands in everyday situations, the training of WM strategies may benefit performance in multiple situations.

There are several additional advantages of strategy-based training over core-based training. First, core-based training programs tend to include a compilation of several tasks with the expectation that one training task, or some combination of training tasks, will produce an effect (e.g., Holmes et al., 2009). This results in a time-consuming and intensive endeavor that is not cost effective in time or resources (e.g., in the above study, training required 35 min per day for 20 days spread out between 5 and 7 weeks). Moreover, researchers are left to speculation at worst and theorizing at best, in pinpointing the specific components of the training program that are responsible for the training effects. By training specific strategies, it is easier to isolate and test the mechanisms or processes that account for improved performance.

Second, research shows that children with higher WM capacity differ from their peers in their patterns of strategy use. Although children with higher WM capacity may be benefiting from a combination of factors, individual differences have been shown to exist in children's selection and implementation of strategies, and these individual differences in strategy use account for significant variance in performance on WM tasks (Engle et al., 1992; McNamara and Scott, 2001; Turley-Ames and Whitfield, 2003; Friedman and Miyake, 2004; Dunlosky and Kane, 2007; Kaakinen and Hyönä, 2007). The efficacy of strategy-based training may therefore lie in closing the gap between individuals with higher and lower WM capacity by bringing the strategy use of individuals with lower WM capacity on par with those with higher WM capacity.

Related to this idea are the two opposing hypotheses about the cause-and-effect relation of strategy use and WM capacity (Bailey et al., 2008). The strategy-as-effect hypothesis suggests that having higher WM capacity allows one to be more strategic in how information is processed and encoded, which in turn contributes to better performance on WM tasks. Alternatively, the strategy-as-cause hypothesis claims that strategy use is the direct cause of individuals demonstrating higher WM capacity. For example, a rehearsal strategy allows a person to retain more information, resulting in a higher span score. In support of the strategy-as-cause hypothesis, Dunning and Holmes (2014) found

that WM training gains were mediated by spontaneous memory strategy use. Further support for this hypothesis comes from a study by St Clair et al. (2010) who found that comprehensive WM strategy training led to significant improvements in WM tasks assessing the phonological loop and central executive. Regardless of whether the strategy-as-effect or strategy-as-cause hypothesis is correct, remediation of strategy use could result in increases in WM capacity.

One pathway by which strategy use may facilitate performance on WM tasks involves decreasing the cognitive load placed on processing and encoding of information, thereby freeing up resources for storage. We argue that three developmental changes in strategy use, in particular, may impact efficiency in processing and encoding information.

First, several lines of research show that as children age, they increasingly organize information during both encoding and retrieval (Tulving, 1962; Shiffrin and Atkinson, 1969; Schleepen and Jonkman, 2012). Grouping and organization of information is particularly useful in facilitating delayed retrieval (Lange et al., 1990) and consolidation in long-term memory (Tulving, 1962; Schleepen and Jonkman, 2012). Interestingly, a recent study suggests that not all grouping strategies are equal: categorization based on semantic features (e.g., types of dogs) has been shown to improve memory performance more than categorization based on perceptual features or personal associations (e.g., animals that the child liked, disliked or feared) (Schelble et al., 2012). One possibility is that categorization provides more salient cues that link many concepts for quick retrieval. Children and adults with higher WM capacity were also found to use the classification strategy more often independently and spontaneously than peers with lower capacity (Rosen and Engle, 1997; McNamara and Scott, 2001; Schleepen and Jonkman, 2012). Some evidence points to more efficient patterns of strategy leading to better performance on tests of WM capacity, rather than higher WM capacity per se. For instance, Schelble et al. (2012) showed that children's use of a semantic strategy made a stronger contribution in predicting retrieval performance than did their individual WM capacity scores. Moreover, although children with higher WM capacity have been found to be more strategic than children with lower WM capacity in free recall tasks, presenting participants with retrieval cues which prompted better strategy selection eliminated this difference (Unsworth et al., 2013). This finding suggests that effective organizational strategies such as semantic categorization could compensate for lower WM capacity in a demanding retrieval task.

A second developmental change in strategy use concerns the shift from non-verbal to verbal encoding by means of verbal or phonological rehearsal. Rehearsal is particularly useful when there is a delay between the presentation of information and recall, as rehearsal helps maintain and refresh information in verbal short-term memory (Morrison and Chein, 2011). There are two processes involved with rehearsal, the initial recoding of visual stimuli into a verbal format, followed by the rehearsal of recoded items in the phonological store; children may struggle with rehearsal by failing on the first or both of these steps (Flavell et al., 1966). Rehearsal develops gradually starting from about 5–6 years of age but more consistent use of this strategy is not apparent until about 6–8 years of age as noted by phonological similarity effects (lower recall of lists consisting of phonologically similar items) and articulatory suppression effects (reduced recall when required to repeatedly produce a taskunrelated verbalization while encoding target items) occurring only in older but not younger children (Henry et al., 2000; Lehmann and Hasselhorn, 2007; Henry et al., 2012).

Although the acquisition of rehearsal follows a developmental progression, rehearsal training has been shown to improve WM task performance in both developmentally delayed (Conners et al., 2008) and typically developing children and adults (Ford et al., 1984; Ornstein and Naus, 1985). Furthermore, the use of rehearsal as a memory strategy appears to be particularly beneficial for children with lower WM spans (Turley-Ames and Whitfield, 2003).

A third developmental shift in strategy use involves the transition from passive maintenance to active refreshing of information in WM. This shift occurs around 7 years of age (Camos and Barrouillet, 2011). According to the taskswitching model (Towse and Hitch, 1995; Hitch et al., 2001), younger children fail to implement maintenance activities while performing a concurrent task, resulting in time-based decay of the memory trace. Instead, they passively hold items in memory without any attempt at active maintenance. Thus, their ability to hold items in memory is greatly affected by the duration of the delay period between presentation and recall. Older children have an increased capacity to control attention and monitor cognitive processes, allowing them to allocate attention during processing to reactivate, or refresh memory traces in real time (Camos and Barrouillet, 2011).

In the present study, we compare the independent and cumulative effects of two strategies (rehearsal and semantic organization) on WM capacity. The two strategies differ in terms of their mechanisms and advantages. The rehearsal strategy is useful for refreshing and maintaining unrelated information, but may be susceptible to distraction, and it is constrained by children's short-term storage for auditory information. A semantic strategy in contrast, is less constrained by an individual's short-term storage, and instead relies on the cued activation of associated networks stored in long-term memory. This strategy may be more effective in retrieving larger amounts of information that can be visualized, but requires more planning (e.g., the foresight and ability to categorize on multiple levels) and may also be susceptible to commission or intrusion errors.

### Current Study

The primary goal of this study was to examine whether strategybased training would transfer to a novel problem solving task. The design of this study takes into account several important considerations including the use of treated controls, a strategybased training paradigm, and the careful selection of strategies that map onto the identified developmental changes that children undergo as they move from being less efficient to more efficient strategy users. There were three training conditions and one control group. One group received rehearsal training (R), another group received semantic training (S), and a third group received training in both strategies (S+R). Children were trained in

semantic organization and/or rehearsal with the expectation that both strategies would improve efficiency of processing, thus freeing up mental resources in WM for storage, with the result that WM capacity could be increased. By extension, increased WM capacity would produce improvements in problem-solving performance that incorporates a WM component.

As mentioned above, rehearsal and semantic categorization strategies have been independently used in previous training studies to increase WM capacity. However, these studies have typically involved older children, and did not assess their use in younger children who may not be spontaneously using these strategies very efficiently, if at all. Furthermore, no prior study has looked at the combined effect of rehearsal and semantic categorization training, nor have previous studies examined training of these strategies in the context of a fartransfer post-test.

We expected that children who received WM training would outperform children in the control group, as developmental research has shown that children between 6 and 8 years use these strategies with varying degrees of success. We further predicted that the combined training condition (S+R) would be more effective than the individual training conditions, given that children in the S+R condition would be provided with more tools to increase their WM capacity. Among the singlestrategy conditions, we expected that semantic-strategy training would be more effective than verbal-rehearsal training because previous research has demonstrated that children and adults with higher WM capacity tend to use deeper encoding strategies that create meaningful networks between the items to be remembered (Friedman and Miyake, 2004; Dunlosky and Kane, 2007).

Far-transfer effects were assessed using a novel problemsolving task that was qualitatively different from the task on which children were trained. Performance on this problemsolving task was expected to improve with the use of trained strategies, as WM demands were embedded within the task, but children had to (a) realize on their own that strategies would be helpful to the task and (b) choose to use them under conditions of increased cognitive demand and interference. Careful attention was given to the use of appropriate control tasks to address previous concerns about the use of untreated control groups. Control tasks were selected to correspond to semantic and rehearsal training phases. These control tasks were comparable in time, type of stimuli involved, and level of mental stimulation to the training tasks. All groups therefore spent approximately the same amount of time interacting with the experimenter.

Additionally, we examined a near-transfer effect for the semantic categorization strategy (e.g., Black and Rollins, 1982). Specifically, we tested whether children who were trained in semantic categorization would use this strategy post-training in a free recall task that involved a new set of stimuli.

### MATERIALS AND METHODS

### Participants

Sixty-five typically developing children aged 6–9 years were recruited from private and public schools within Victoria, BC, Canada. Flyers were distributed to children in school and interested children and parents contacted the researcher for participation. To ensure that participants could follow instructions, only children who had English language fluency and the absence of any developmental delay and/or learning disabilities as reported by their parents were included in the study. Written and informed consent was obtained from parents for children's participation, and child assent was obtained verbally. Data from one child was excluded due to an inability to understand and follow the instructions. The 64 remaining children completed all the pretests, training phases, and post-test measures over a single 1.5-h session.

Sixteen participants were randomly assigned to each of four conditions, with the only requirement that the age distribution was kept relatively similar between groups. There were no significant differences between the mean ages across groups. The S+R group (M age = 7.5; males = 9) received training in both S and R strategies. Controls (M age = 7.4; males = 7) received only the filler tasks in place of both semantic and rehearsal training. The S group (M age = 7.2; males = 7) received semantic training and rehearsal control tasks. The R group (M age = 7.4; males = 9) received rehearsal training and semantic control tasks. Thus, each group of children received two sets of tasks that were comparable in administration time and complexity. While the S+R group received two training sets, the S and R group received one each of a training set and a filler set. Treated controls received two filler sets. Filler sets are described in detail below.

### Measures

#### Pretests

To assess whether any between-group differences existed on relevant WM and short term memory abilities which could potentially lead to differences in performance on the novel problem solving task, several pretest measures were administered including a visual memory task (memory for matrices), a verbal memory task (forward and backward digit span), as well as a free-recall task to examine use of clustering or organizational strategies prior to training. A full breakdown of the item-level questions and scoring criteria are provided in **Appendix B**.

### **Forward and backward digit-span tasks**

In the forward digit-span task, children were asked to recall lists of digits. Numbers were read to children at a pace of one number per second, and were prompted to repeat the list in the same serial order with, "Ready? Go." Children received a score of 1 for a correct response, and a score of 0 for an incorrect response. Points were summed for a total score. The task was discontinued after two consecutive scores of 0. In the backward-span task, children were asked to recall the list in the reverse order in which it had been presented, using the same prompt and scoring criteria.

#### **Visual short-term memory (VSTM) task (Logie and Pearson, 1997; recall version)**

The child was presented with a matrix pattern drawn on white cards in which half the squares, chosen randomly, were colored red. The pattern was displayed for 2 s and then removed, followed by a further 2-s delay during which the child was shown a blank

white card. The child was then given an empty version of the same matrix and asked to point to the squares that previously were colored red. Matrices increased in size, with the proportion of red squares always fixed at 0.5. Children's responses on each of the three trials of Matrices were recorded live by the experimenter on a blank grid. Correct squares were then tallied for each trial, and an average score was computed.

### **Free-recall pretest**

The task was adapted from Black and Rollins (1982). Free-recall tasks are traditionally administered to adults in a written list format but given that some children in this age group would not be actively using verbal strategies and had limited reading skills, pictures were used instead. Colored photos were used instead of black and white line drawings to provide a more realistic and ecologically valid representation of objects (Moreno-Martínez and Montoro, 2012). Five cards each from four categories (insects, fruits, vehicles, and furniture) were chosen for use in the free recall task, for a total of twenty items. Different items were used in the post-test and the free recall post-test. Highfrequency items previously used with children from each category were preferentially selected (Snodgrass and Vanderwart, 1980; Rabinowitz, 1984). Following the example of Black and Rollins (1982), duration of study time was determined by the child. At the end of the study period, the examiner collected the cards and asked the child to name as many items as possible. During recall, if the child appeared to run out of answers, they were prompted once with, "Can you remember any more?" before recall was terminated. The decision to allow the child to determine study time was also made with two considerations: firstly, that a timed study period would be stressful and anxiety-provoking for children and could impair their ability to remember, and secondly, that the vast majority of children in initial testing were able to self-report in a reasonable time frame as to when they were ready to have the cards taken away. The total number of correct responses was recorded live.

### Training Tasks

The goal of this short-term intensive training was to increase children's familiarity with and hone their correct use of strategies. Therefore, accuracy was not recorded or analyzed for the training tasks. Children were also encouraged to try as many times as possible until they arrived at the correct answer. Only one item was correct in any given array of objects. The duration of each section of training was kept as closely as possible to around 10–12 min, with control tasks timed for a similar duration.

#### **Semantic-categorization training tasks**

These tasks encouraged children to organize information based on their common abstract properties (e.g., things that hold liquid, things that fly, etc.). Children were first trained to think in terms of categories, and then to apply them strategically. Training involved two phases. In phase A, children had to make decisions about which object in a group did not belong with the others. For example, on one slide, children were shown a butterfly, beetle, spider, and banana. They were asked, "Which does not belong?" followed by, "What do the other ones have in common?" Nine training sequences were administered for Phase A of the training (see **Appendix C** for all training items). The number of items presented in each array ranged from 4 to 6 objects. Two levels of difficulty were administered. In the first five training sequences, objects in the same category shared the same identity (e.g., they are all insects, vehicles, furniture...). Children were then prompted that items in the final four sequences would be similar in ways that were harder to see (e.g., container/noncontainer, animate/inanimate, things that travel on land/water). Children were given the opportunity to discuss their ideas for each training sequence with the experimenter and were debriefed on all correct answers.

In phase B of semantic training, a scaffolded free-recall task was administered. Children were first prompted to sort the cards by their categories (fruit, insects, furniture, vehicles). Next, they were instructed to use the strategy of thinking about the similarity among items ("If you study the cards that are similar together, such as all the fruit together, it will be easier to remember them"). Black and Rollins (1982) had found this method of explanation to be most effective in encouraging children to adopt the category clustering strategy. The experimenter checked whether children could identify a few of the items that were similar and moved these cards closer together to better illustrate the grouping. Once it was clear that children had a grouping strategy in mind, they were given 3 min for recall. As accuracy was not measured during the training, children were given positive reinforcement for their attempts at using the strategy. Children were also debriefed on their performance and given feedback for correct application of the categorization strategy.

#### **Semantic control tasks**

In the first control task, children were given a regular deck of playing cards and asked to find all the cards that fit an arbitrary criterion of color and shape (e.g., all the red hearts, black clubs, etc.). In the second control task, the experimenter randomly selected a few cards from the free-recall deck (e.g., apple, ant, spider) and children were asked to tell a story about the items.

### **Phonological-rehearsal training**

The goals of the rehearsal tasks were to train children in (1) recoding visual information into verbal information, and then (2) maintaining that verbal information in temporary storage through rehearsal. In the first phase of training children were asked to label a list of pictures out loud. They were then asked to rehearse the list until they felt ready to report the items without referring to the pictures. This recording of pictures into words followed by rehearsal was practiced over four trials of increasing list length, starting with three items and ranging up to seven items, with item length increasing by one item in each added trial (see **Appendix C** for full list). For example, on the first training sequence, children would see images of an ant, eye, and car. They were asked to label these objects and verbally rehearse them out loud, followed by several more repetitions either out loud or through inner speech. They were told to let the experimenter know when they were ready to have the pictures removed, and then repeated the items they had rehearsed. Effort was praised, as was successful memorization of increasingly longer sequences. In the second phase of rehearsal training, word lists were presented orally without the use of pictures, and children were tasked with recalling lists after a short delay. Children were then tasked with practicing this rehearsal strategy over five trials, starting with a sequence of three items and ranging up to a sequence of seven items. The sequence length increased by one item in each added trial. As the goal of training was mastery of the technique, children were allowed to repeat trials as necessary.

### **Rehearsal control tasks**

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Children were asked to read from a picture book with the help from the experimenter, or engage in a discussion about what they did on the weekend or about upcoming activities at home or school for the duration of approximately 10 min.

### Post-tests

### **Problem-solving task**

A problem-solving game was developed for this study. The most important function of the problem-solving post-test was to assess the cross-contextual far-transfer of any potential training effect. As such, novelty was a critical aspect of the task. Omitting to include a problem-solving pretest came with certain advantages and disadvantages, and the decision was ultimately made for several reasons: (a) Even though exposing children to a problemsolving pretest is often expected in a pre-post-test design, pretest administration has the disadvantage of introducing a practice effect, which reduces novelty of the task; (b) The average running time for this study was approximately 1.5 h. With the problemsolving task taking a large proportion of this time, adding a pretest would have necessitated a second testing session, which was not feasible at the time of data collection. Several safeguards were implemented to ensure as much as possible that groups had no significant differences at pretest: (1) A memory battery was administered at pretest (visual matrices, digit spans, free recall) to ensure that no between-group differences existed on a variety of potentially relevant memory abilities. These measures were then examined in relation to the problem-solving post-test in a subsequent regression analysis; (2) Near-transfer (recall post-test) and far-transfer (problem-solving task) are clearly distinguished in the results; (3) The use of random assignment usually safeguards against pre-existing group differences, and (4) The use of a treated control group with appropriate filler tasks ensured that pre–post differences would be related to intervention effects and not to unspecific factors (e.g., engagement with children). Overall, we believed that these measures compensated for the lack of the problem-solving pretest, while retaining the novelty effect for assessing far-transfer.

The problem-solving task was structured like a shopping game where the child had to retrieve items from a teddy bear's list. It involved three adjacent rooms: two troll houses where children collected cards with pictures of items, and the bear's house in between. The goal of the task was to retrieve all the cards on bear's list while making as few errors as possible (see **Appendix A** for task instructions). Each child completed three different lists of items (three trials). Each trial consisted of 24 target items, with each item repeating only once across the three trials. There were a total of 48 possible cards, with 12 items of each category (Animate: aquatic animals, terrestrial animals; Inanimate: school supplies, wearable items). One troll housed animate categories and the other housed inanimate categories, but children were not told of this arrangement. Children were first introduced to the bear, and then to each of the trolls. Each troll had a coin bank for the child's payment in order to open the box of cards. The experimenter enforced correct token use. To elicit strategy use, several constraints were put in place for the problem-solving task: (1) Children received only six tokens to pay the trolls. Each time a troll's box was opened, a coin was forfeited. Once all the coins had been used, the trial was terminated, regardless of whether or not all cards had been collected. Thus, there were no explicit rules about when or how often the child could return to consult the bear's list, nor any explicit penalty for selecting incorrect cards, but the limited number of tokens forced children to maximize the cards they would get with a visit to a troll. (2) Maximally seven cards were allowed to be kept in the basket at any given time. The number 7 was placed on the side of the basket, to serve as a visible reminder of this rule. This constraint ensured that children did not walk away with the entire deck of cards at once. During the collection process, children could collect cards in any order they liked. This allowed children to make plans about the best way to collect cards. (3) Upon returning to the bear's house, the cards were placed on bear's "shelf " (two empty marked-out rows) in the same order as bear's list. This rule was designed to help children keep track of remaining cards. (4) Children were told that in order to win the game, all correct cards had to be retrieved while making as few mistakes as possible and using as few of the coins as possible. Children did not have access to the bear's list while in the Trolls' rooms and had to remember which items to retrieve. **Figure 1** shows the setup of the list in bear's house. Children were permitted to consult the list again when they returned to the bear's house to place their collected cards. None of the children were given any explicit instruction that they should use a particular strategy or that the items could be sorted into categories.

We expected performance on this task to be improved by our specific training for several reasons. The 24-items presented in target lists would far exceed any individual's maximum capacity, and children who received training in either or both strategies

would be equipped with tools to improve WM at all stages including encoding, maintenance, and retrieval, an advantage that the control group would not have in such a demanding task. In addition, the task constraints, as well as children's own WM capacity limits would be best overcome by the use of both strategies. For instance, a child could first plan to visit the room with the animate items, grouping animate items from the bear's list using a rehearsal strategy, and then visit the room with the inanimate items on a separate trip, again using rehearsal for these items. Use of a rehearsal strategy alone meant that items from different categories rehearsed by the child would not be completed on the same trip, as each room housed only animate or only inanimate items. Similarly, children who used a semantic strategy only would not benefit from the use of rehearsal to maintain and refresh items in memory while shifting through the deck of cards and be prone to making more intrusion or commission errors.

For each of the three trials, the following outcomes were recorded: number of correct cards retrieved, number of errors, number of tokens used, and the number of cards retrieved for each token. Performance scores were computed as follows: total number of correct cards retrieved over three trials (maximum = 72), total number of errors over three trials, and total tokens used (maximum of 18 over three trials). A performance index was calculated by subtracting total errors (E) from total correct cards (C), divided by number of used tokens (T): (C-E)/T.

### **Post-training free recall**

A post-training free-recall task was administered to all groups after the game as a near-transfer measure. The post-test used a different set of stimuli and categories (e.g., body parts, nature, instruments, kitchen utensils) than were used in the pre-test.

### RESULTS

First, we compared the results of baseline WM and clustering pre-measures across groups. Second, far-transfer effects were compared across groups by looking at performance on the problem-solving task. Third, to evaluate near-transfer effects, groups that received semantic-categorization training were compared to those that did not in their performance on the posttraining recall task. Finally, we evaluated the construct validity of the problem-solving task.

### Pretests

Prior to analyzing training effects, group performance on a variety of pretests was examined to ensure that there were no significant group differences in memory abilities which could have led to between group differences in our post-test. Group means for pretest measures can be found on **Table 1**.

Given that digit span scores are not expected to be normally distributed (Babikian et al., 2006), Kruskal–Wallis tests were used to test group differences on the digit forward and backward span total and longest span. The test revealed that the total scores for both forward, χ 2 (3) = 2.96, p = 0.40, and backward χ 2 (3) = 3.05 p = 0.38 digit span were not significantly different across groups.

Shapiro–Wilk normality tests suggested that matrices W(64) = 0.97, p = 0.119, number of cards W(64) = 0.97, p = 0.14 and ARC W(64) = 0.57, p = 0.57 at pretest of the free recall were normally distributed. Box's M suggested that equal covariance matrices of the dependent variables can be assumed across groups F(9,41255.3) = 0.84, p = 0.58, and Levene's test showed that variance of matrices F(3,60) = 1.32, p = 0.28 and number of correctly recalled cards F(3,60) = 0.25, p = 0.86 were assumed equal across groups. A MANOVA was conducted to test the between-group differences for matrices and the pretest free recall. Results using Pillai's trace showed no significant between-group differences for these measures F(1.38,120) = 1.38, p = 0.23.

These findings suggest that there were no significant baseline differences between groups on the pretests of visual and verbal short-term memory and WM, as well as in the tendency to use a clustering/organizational strategy. Based on these findings it is reasonable to conclude that no group had any short-term or WM advantage compared to other groups prior to training.

### Near-Transfer Training Effects

We expected to see far-transfer effects only if near-transfer effects were first established, as more proximal transfer would predict more distal transfer. To reduce testing time, we prioritized the measurement of near-transfer to one task, specifically the freerecall task, because it was quick to administer and was a wellestablished measure for at least one of our trained strategies. Participants were grouped together depending on whether they received semantic strategy training (S+R and S) or not (R and control). The mean number of correctly recalled items in groups that had not received semantic training was 11.00 (SD = 2.91) at pretest and 10.47 (SD = 3.35) at post-test. The means of the groups that had received semantic training were 12.03 (SD = 2.8) at pretest and 13.16 (SD = 4.78) at posttest. A 2x2 repeated measures ANOVA revealed a significant main effect for the factor of semantic training, F(1,62) = 5.55, p < 0.05, η 2 p = 0.08; participants who received semantic training did better on the free-recall task than those who did not receive semantic training. There was also a significant interaction between the within-subjects variable of time (pre- vs. post- test) and training condition F(1,62) = 4.19, p < 00.05, η 2 p = 0.06, indicating a larger positive change in performance for the semantic training condition.

### Relationship Between Problem-Solving Task and Working Memory

The novel problem-solving post-test was designed such that it made demands on WM processes. Specifically, children were required to remember items, correctly select these remembered items from a series of stimuli including both targets and distractors, inhibit retroactive interference from previous sets of remembered items, and simultaneously hold the rules of the game in mind. To check whether the problem-solving task indeed made WM demands, we examined the correlations between the verbal and visual pretest WM measures and the problem-solving task. Forward digit span, r(62) = 0.28, p < 0.05, backward digit span, r(62) = 0.34, p < 0.01, and matrices, r(62) = 0.31, p < 0.05, all

Chan et al. Evidence for Working Memory Training

were significantly correlated with the problem-solving task. Next, we entered digit span forward, digit span backward, and Matrices as predictors of problem-solving performance into a regression model. This analysis showed that matrices and backward digit span tasks explained 15.9% of the variance in problem-solving performance (R 2 adjusted = 0.159), F(3,60) = 4.96, p < 0.01, and significantly predicted problem-solving performance (β = 0.27, p < 0.05, and β = 0.28, p < 0.05, respectively). The forward digit span was not a significant predictor of problem-solving performance (β = 0.09, p = 0.50).

### Far-Transfer Training Effects on the Problem-Solving Task

For the problem-solving task, the performance index (C-E)/T was computed using the total scores ([total correct – total errors]/total tokens used) across three trials of the task. A univariate ANOVA with training condition as the independent variable was conducted to examine whether problem-solving performance differed as a result of which training group children were assigned. Results revealed a significant main effect for condition, F(3,60) = 3.04, p < 0.05, η 2 p = 0.13. Post hoc analyses using least significant difference (LSD) revealed statistically significant differences in the problem-solving performance index (C-E)/T between the control group and each of the three training groups. As can be seen in **Table 3**, on average, the control participants collected fewer cards than any of the training groups. Importantly, medium to large effect sizes were found for all three comparisons made between treatment groups and the control group (see **Table 2**). The largest effect size was found for the difference between the control group and the group that received both interventions (S+R). The three training groups (S+R, S, R) did not differ significantly from each other.

Due to the correlations between the pretest memory measures and the problem-solving post-test, a one-way ANCOVA was also conducted to examine whether post-test group differences remained when including the digit span tests, matrices, and freerecall pretest measures as covariates. Results showed a significant main effect for condition F(3,60) = 2.80, p < 0.05, η 2 p = 0.13. Post hoc analyses again revealed that there were statistically significant differences in the problem-solving performance between the control group and the semantic training group (p < 0.05); the rehearsal training group (p < 0.05), and the S+R group (p = 0.05). No significant differences were found between the three training groups.

TABLE 2 | Mean differences between groups on problem-solving outcomes over all trials.

∗Significant at p < 0.05; large effect size d > 0.8.

A breakdown of correct cards retrieved per trial is shown in **Table 2**, as well as means for total errors across three trials, and number of tokens used. No significant differences in token usage were found.

Perfect performance on this task would have involved collection of 72 cards in total, however no child collected all three lists in their entirety and without error, which demonstrated that the task was sufficiently challenging yet nuanced enough to show variability in performance across children.

### DISCUSSION

The main finding of this study is that strategy-based training produced a far-transfer effect in a novel problem-solving task. The control group performed significantly worse on the problemsolving task than all three training groups. Most importantly, children were not coached into using specific methods to complete the problem-solving task, but had to recall and execute the strategies by themselves in a context that differed considerably from training (Barnett and Ceci, 2002). Surprisingly, there was no statistically significant difference in receiving combined training of both strategies compared to only one strategy.

A possible explanation for why there was no significant difference in problem-solving performance between the combined and separate training conditions is that the problemsolving task may not have been sensitive enough to capture the effects of the combined training. It is possible that these effects would have emerged if a more demanding outcome measure or a longer interval between training and test had been used. It is also possible that the training phase itself was too short.

ARC is a measure that reflects children's use of the clustering strategy in the Free Recall task (see Senkova and Otani, 2012).

Total performance = (C-E)T.

Cognitive training studies are generally time intensive, spanning multiple sessions over weeks. Training effects might have been amplified if there had been multiple training sessions to help consolidate learning.

Alternatively, children may not have benefited more from the combined training than from the single-strategy training because they may have used only one strategy although they had received training on both. Controlling the use of two strategies, in this case, first categorizing stimuli, and then rehearsing words recoded from pictures, would require the metacognitive ability to select and implement separate strategies in a logical sequence. This, in turn, requires the comparison and evaluation of different strategies, a mental task that may be difficult to do while attempting to implement a strategy (Whitebread, 1999; Touron et al., 2010). In a task that is cognitively demanding with multiple subordinate goals, children with limited cognitive resources will likely make less adaptive strategy choices (Imbo et al., 2007). Moreover, children with lower WM are more likely to experience a version of "utilization deficiency" (Bjorklund et al., 1994; Gaultney et al., 2005), such that, despite being instructed to use a particular strategy or seemingly comprehending the steps in its application, they fail at implementing the strategy due to limited cognitive resources. According to Lovett and Anderson (1996), available processing capacity in WM is a constraint that limits the amount of attention that can be distributed over concurrent tasks. Younger children who have lower WM capacity may not always be able to effectively implement strategies in spite of training. In conclusion, the effortful task of alternating and deciding between two strategies may actually impede the ability to use both, and if one strategy is easier to implement, a child may default to using only one. In addition to this possibility, the relatively small sample size in each condition would make it more difficult to detect differences between the training groups, especially if only a small effect size differentiates the groups.

An underpowered sample size was a notable limitation of this study. Due to the time intensive nature of pre- and post-test intervention studies, large sample sizes for these types of studies are achieved with some difficulty. The current study was also completed under a narrow time constraint, which made further data collection unfeasible. A one-way ANOVA would require a large sample size (n = 280) to detect a medium effect size (0.25) for four groups, using a 95% confidence interval. In the current study with a sample size of 65 the observed power for detecting a medium effect size was 0.338. Replication of this study with a sufficiently powered sample would ensure that a Type II error was not being made with respect to the lack of significant differences between the different training conditions.

The current findings also did not support our second hypothesis that children who were taught to use only a categorization strategy would outperform those who were taught only rehearsal. As previously mentioned, rehearsal may be less effortful than semantic categorization, and in cognitively demanding tasks, children tend to use less effortful strategies (Beilock and DeCaro, 2007). Our problem-solving task involved many rules in addition to memorizing items, and with these aspects demanding the child's attention, the ability to use a more complex strategy efficiently may have been impaired. The near-transfer effect found in this study lends credence to this explanation. When comparing the group that received semantic training to the group that did not receive semantic training on the much less demanding free-recall post-test, those who received semantic training outperformed those who received rehearsal training.

Finally, the semantic training group may not have performed better than the rehearsal group because of intrinsic limitations to the categorization strategy. Semantic categorization is a good strategy for recalling a large number of items because of primed associations. However, it may actually impede performance in a task that places emphasis on accuracy for the very same reason. During free-recall tasks, participants occasionally make intrusion and repetition errors. In the current problemsolving task, retroactive inference between trials heavily impeded accuracy because targets remembered from a previous list may not have been targets on a current list. Accuracy was also an important component of the problem-solving task; if clustering both increased recall but also elevated the propensity for intrusion and repetition errors, the overall performance would be compromised. Future studies should seek to determine whether semantic strategies are more helpful when retroactive interference is reduced between trials. Retroactive interference could be removed by using each target for only one trial. A follow up study would also be improved by replication with more clearly distinguished categories, as the groups of aquatic and terrestrial animals may have been too similar for some children to fully benefit from using a categorization strategy. Nevertheless, despite the possible interference that children may have experienced

while using a semantic strategy, the data showed that the semantically trained group still significantly outperformed the control group, suggesting that this strategy was overall successful in improving performance in a far-transfer task.

Lastly, it is important to distinguish between cross-temporal and cross-contextual transfer. Cross-contextual transfer is highly relevant to our understanding of how training effects can be transferred to real world environments. Although both crosstemporal and cross-contextual considerations are important, the focus of this study was on cross-contextual transfer, largely in part because of the narrow time constraints of data collection. Producing a sustained change is ideal, but longevity of a training effect may sometimes be secondary to the nature of change itself. Training which produces improvements in only a narrowly constrained set of outcomes may not be viewed as successful as training which produces improvement across multiple outcomes, particularly if those outcomes involve higher order cognitive process or more complex domains.

A challenge for the training literature has been to find a compromise in the similarities and differences between the trained and untrained tasks. On one hand, similarities between the tasks are part of the point of training studies: common elements must be identified and isolated in training, and improvement in these common elements are what we measure in transfer effects. If these common elements are unknown or inconsistent, predicting and implying transfer is impossible (Noack et al., 2009). On the other hand, if there is too much overlap between the trained task and post-test limits, then gains will likely be limited to near-transfer. In this study, we can clearly identify the common elements between training and post-test, as well as the overlapping elements between pretest and posttest. These common elements are in sum: a measurably capacity for short term storage of verbal and visual stimuli, a process whereby visual information is recoded into verbal information, the ongoing maintenance and refreshing of this information, and ways of organizing information effectively for more effective encoding and retrieval. Our training tasks focus on improving these elements, and the post-test recruits exactly these abilities.

At the same time, we acknowledge that it is debatable whether far-transfer has occurred in our study. The determination of whether far-transfer has taken place requires the administration of a series of post-test measures dissimilar enough from the trained tasks to suggest change at the level of broad abilities (Noack et al., 2009). We are less confident that our short training has made changes in any one broad domain. Nevertheless, the study demonstrated that the trained strategies could be used in a context where there was substantially higher cognitive load, as evidenced by the many other rules, constraints, and distractors, and where application of the strategies was less transparent and arguably more difficult to implement. Arguably, because of these features, the post-tests were at least somewhat dissimilar from the trained tasks, while retaining the common elements which underlie transfer.

### Near-Transfer Training Effects

A secondary goal of this study was to replicate near-transfer effects of semantic strategy training. We expected near-transfer effects for WM training more generally, because previous research has shown considerable evidence for near-transfer effects in training of executive functions (e.g., Klingberg et al., 2002; Turley-Ames and Whitfield, 2003; Li et al., 2008; Karbach and Kray, 2009). Results showed a significant interaction between type of training and pre- versus post-test free recall. Children who received semantic training showed a small but consistent improvement from pretest to post-test on the free recall task, whereas the performance of children who did not receive semantic training did not show this gain.

### Summary

The results of this study show that strategy-based WM training produced a far-transfer effect on a problem-solving task. Groups in all three training conditions outperformed control participants in problem solving. This research is important because it shows that children are able to generalize specific strategies to a completely novel problem-solving task with which they have no prior experience, and where no explicit instruction is given on how to complete the task. Moreover, not only were the test stimuli different from the ones used in training, the task demands that children were tested on (i.e., use of semantic categorization or rehearsal) were embedded in a game where other complex rules and hierarchical goals had to be kept in mind while remembering and implementing strategies. The positive findings of our relatively short training study stand in stark contrast to other research showing no evidence of far-transfer even in testing that immediately follows training. In our view, several factors contributed to the success of this training. First, we selected strategies that are developmentally appropriate in that these strategies were emerging but not yet mastered or used consistently by the target age group. Secondly, prior research has demonstrated these strategies to be used very effectively by individuals with higher WM capacity. In other words, children who do well in WM-related tasks employ exactly the strategies that were trained in the current study. Thirdly, in training these strategies we used very concrete, explicit instruction, and the ease of their use allowed them to be applied readily. Our finding shows that application is not limited to near transfer, but also generalizes to a new context.

Undoubtedly, more work is necessary to better understand the causal relation between components of WM and different types of higher-order abilities. Nevertheless, in examining our between-group differences, we found a large effect size for the difference between the combined training (Semantic+Rehearsal) condition and the control group, a marginally large effect size for the difference between Rehearsal training condition and the control group, and a medium effect size for the difference between the Semantic training condition and the control group. These medium to large effect sizes are exciting as they suggest that training simple strategies that focus on improving cognitive efficiency can potentially moderate children's performance on higher-order tasks, particularly when task demands reflect components of training. The fact that combined training produced the largest effect size suggests that such training has the potential to have an additive effect.

Our training focused on practicing and fine-tuning strategies that emerge in children who are between 6 and 9 years old, suggesting that one direction of future research on WM training should focus on enhancing and scaffolding the effective use of cognitive strategies that are developmentally appropriate and contextually relevant. This study also replicated near-transfer effects, showing that those who received semantic training did better on a free-recall task after training whereas those who did not receive such training did not show improvement. This second finding is also important because it suggests that rehearsal and semantic categorization are two conceptually different mechanisms by which children can more effectively encode and maintain information in WM. Follow-up studies should further tease apart the unique contributions of these different strategies using more intensive training paradigms and larger samples. Future studies should be conducted to determine whether longterm gains can be produced by this type of WM training. In addition, there is a need to explore longer-term, distributed training paradigms, that take place over time and adjust for children's changing competencies, as well taking into account individual differences in other factors related to task performance such as attention and motivation.

Finally, it is important to discuss several limitations of the present study. Despite the promising training effects, given the time constraint of data collection it was not feasible to conduct extended training over multiple sessions. Working memory training studies have typically involved several training sessions (about half an hour long each) over the span of a few weeks. Although the relationship between the quantity and effectiveness of training may be variable, it is likely that a more intensive training program would achieve longer-term training effects than a single session lasting half an hour as in the present study. In particular, children who were trained in two strategies may have benefited from more training sessions because of the complexity of mastering and applying two strategies.

Lastly, children's baseline WM could be more precisely established in future studies to more clearly look at how children with low WM respond to training in comparison to children with high WM. It is also important that individual differences are not underestimated in any learning situation. Aside from baseline WM, other relevant factors such attention, emotional regulation, anxiety, or curiosity may have influenced children's responsiveness to training and their ability to transfer training to a novel problem solving context. We also acknowledge that claiming far-transfer may be ambitious as it remains unclear to

### REFERENCES

what extent our training could lead to permanent changes in a broad cognitive domain. Nevertheless, the study did demonstrate that trained strategies were used in the pursuit of a complex goal in a cognitively demanding context, in which children were not instructed to use these strategies, and in which, consequently, it arguably was more difficult to implement them.

### DATA AVAILABILITY

The datasets generated for this study are available on request to the corresponding author.

### ETHICS STATEMENT

This study was approved by the University of Victoria Human Research Ethics Board (Protocol No. 13-156) on May 13, 2013, and deemed minimal-risk.

### AUTHOR CONTRIBUTIONS

SC contributed to all aspects of this study (conceptualization, design and methodology, data collection, interpretation, and write up). This study was designed and conducted as a part of the author's M.Sc. requirements. UM contributed to all aspects of this study (conceptualization, methodology, interpretation, and write up) as the first author's academic supervisor during the study's completion. MM contributed to the methodology, interpretation, and write up as an integral member of the first author's thesis committee.

### ACKNOWLEDGMENTS

This work was supported in part by a Natural Sciences and Engineering Research Council of Canada discovery grant to MM.

### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg. 2019.01285/full#supplementary-material

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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Chan, Mueller and Masson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Art of Learning – An Art-Based Intervention Aimed at Improving Children's Executive Functions

Per Normann Andersen1 \*, Marita Eggen Klausen2 and Erik Winther Skogli3

1 Faculty of Social and Health Sciences, Inland Norway University of Applied Sciences, Lillehammer, Norway, 2 Faculty of Education, Inland Norway University of Applied Sciences, Lillehammer, Norway, 3 Division of Mental Health Care, Child and Adolescent Psychiatric Clinic, Innlandet Hospital Trust, Lillehammer, Norway

Executive functions (EFs) can be conceptualized as a mean of behavioral self-regulation, and difficulties with EFs may adversely affect school success, social function, and cognitive and psychological development. Research about EFs and how they are affected by various educational and psychosocial factors is sparse. EFs are of great importance to understand how children can handle the challenges that they meet at various stages of development. There has been an increased focus on programs aimed at improving EFs, either as a primary outcome, or as a supplemental result of a specific activity. In this randomized controlled study, 66 children (31 girls, mean age 7:1 years) were given an arts and culture rich intervention (Art of Learning) aimed at improving EFs. EFs were assessed with the Behavior Rating Inventory of Executive Functioning-teacher version (BRIEF-teacher form) before, immediately after, and 6 months after intervention. Outcome in the intervention group was compared to children from two schools serving as controls (n = 37, 18 girls, mean age 7:3 years). In addition, teachers from intervention schools were also interviewed both individually and in focus groups. The results reveal that both groups improved their EFs, as measured with BRIEF, over time on the global executive composite (GEC) score, the metacognition index, and on behavioral regulation index (BRI). However, the intervention group displayed a significantly greater improvement than the control group on GEC and BRI. The teacher interviews reveal positive effects for the children when it comes to several aspects: collaboration, conflict management, inclusion, vocabulary, and confidence. These factors are regarded as important for EFs development and academic outcome. The results support the notion of best training transfer effects for tasks addressing global executive functioning and specifically behavioral regulation skills (BRI).

Keywords: Art of Learning, behavioral self-regulation, BRIEF, executive function, executive function training, metacognition

### INTRODUCTION

Executive functions (EFs) can be conceptualized as a mean of behavioral self-regulation, crucial for children's social function, and cognitive and psychological development (Alloway, 2009). EFs seem to be situated in neural networks including prefrontal cortex, striatum, and the basal ganglia (Middleton and Strick, 2001), showing considerable development throughout childhood,

#### Edited by:

Maria Carmen Usai, University of Genoa, Italy

#### Reviewed by:

Barbara Arfé, University of Padova, Italy Xiao Pan Ding, National University of Singapore, Singapore

\*Correspondence: Per Normann Andersen<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Developmental Psychology, a section of the journal Frontiers in Psychology

Received: 21 April 2019 Accepted: 15 July 2019 Published: 31 July 2019

#### Citation:

Andersen PN, Klausen ME and Skogli EW (2019) Art of Learning – An Art-Based Intervention Aimed at Improving Children's Executive Functions. Front. Psychol. 10:1769. doi: 10.3389/fpsyg.2019.01769

**21**

reaching adult-like levels in middle adolescence (Best and Miller, 2010). Thus, difficulties with EFs have shown to adversely affect school success, social function, and cognitive and psychological development (Diamond, 2013; Zelazo et al., 2016; Pellicano et al., 2017; Morgan et al., 2018). There are no generally agreed definition of EFs. One reason for this might be different research approaches to the construct, either through studies of functional outcome of frontal lobes lesions/damage, or examining different cognitive functions thought to regulate goaldirected behaviors and studies investigating development of cognitive control strategies and self-regulation (Cirino et al., 2018). However, a definition commonly used is provided by Miyake and Friedman (2012) and refer to EFs as "a set of general-purpose control processes that regulate one's thoughts and behaviors". Another common conceptualization refer to EFs as "the attention-regulation skills that make it possible to sustain attention, keep goals and information in mind, refrain from responding immediately, resist distraction, tolerate frustration, consider the consequences of different behaviors, reflect on past experiences, and plan for the future" (Zelazo et al., 2016).

There is some ambiguity as to whether EFs can be judged as a unitary construct or as a set of independent components. Miyake et al. (2000) has gained a lot of support in their effort to bridge the different constructs into a unity/diversity hypothesis of EFs. In this view, EFs are both related and separate cognitive functions. The unity/diversity hypothesis of EFs finds evidence for both distinct and common loadings of inhibition, working memory (WM), and cognitive flexibility in EFs (Miyake et al., 2000; Best and Miller, 2010; Diamond, 2013). These functions are regarded as foundations for other higher-order cognitive skills, such as reasoning, problem solving, and planning (Diamond, 2013).

Inhibition comprises cognitive functions such as self-control, selective/focused attention, and cognitive inhibition. Inhibitory control improves rapidly in early childhood, followed by a less dramatic change through adolescence (Best and Miller, 2010). Poor inhibitory control is associated with reduced quality of life, and relatively small improvements may have huge gains (Moffitt et al., 2011).

The most commonly used definition of WM defines the construct as the active maintenance and manipulation of information within a limited time span (Baddeley, 2003). WM have been shown to be crucial for children's learning capacity, and academic achievement in school (Alloway et al., 2005; Alloway, 2009). As the development of WM is closely related to the maturation of inhibitory control, the developmental trajectory of WM is often difficult to disentangle from inhibition (Best and Miller, 2010). That said, converging evidence indicate a more protracted period of development for WM, showing improvement at least through adolescence (Best and Miller, 2010).

Cognitive flexibility refers to the ability to adapt to changing situations requiring different thoughts and behaviors (Hill, 2004). The failure in generating novel solutions and to use appropriate levels of representations in mental processing may hinder creative responses in situations with open-end outcomes (Ridley, 1994). Cognitive flexibility is important for the behavior required in daily social activities (Memari et al., 2013). Cognitive flexibility presupposes inhibitory control and WM showing a protracted period of development through adolescence (Best and Miller, 2010).

The notion of EFs as interrelated, but at same time distinct components are also supported in a recent study by Cirino et al. (2018). When assessing EFs in 846 children from 8 to 12 years they found a common factor and five separate factors. Two components were WM related; span/manipulation with planning and updating. The other three were generative fluency, self-regulated learning (SRL), and metacognition (MCOG). The EFs trident of WM, inhibition, and cognitive flexibility from the unity/diversity model of EFs by Miyake et al. (2000) was not supported, which is also the case in other studies evaluating model fit in children (Huizinga et al., 2006; Espy et al., 2011; Lee et al., 2013; but see Miyake and Friedman, 2012). The two WM components found by Cirino et al. (2018) fit well into the constructs of WM given above. SRL can be described within the concept of EFs given by Zelazo et al. (2016) comprising planning, reasoning, and problem-solving abilities. MCOG refers to the ability to monitor, manipulate, and regulate other cognitive processes (Cirino et al., 2018). The ability to monitor and regulate cognitive processes has been a central feature of the EFs models given by Barkley (1997). EFs can also be conceptualized as a mean of behavioral self-regulation where inhibition in particular has been associated with childhood aggression (Barkley, 1997; Poland et al., 2016). A metacognition index (MI) is incorporated as a main scale in the Behavior Rating Inventory of Executive Functioning (BRIEF), contrasting the behavioral regulating abilities in the Behavioral Regulation Index (BRI) (Gioia et al., 2000a). Behavior regulation have in previous studies been associated with social function (Kenworthy et al., 2009), while metacognitive skills may be of greater importance for school performance (Carretti et al., 2014). Although describing the concept of EFs with different operationalization's, the abovementioned descriptions seem to entail some of the same cognitive mechanisms. The overarching notion of EFs as a cognitive process regulating thoughts, behavior, and emotions important for everyday functioning seems to be unanimous. And as early EFs functioning predicts later EFs functioning (Moffitt et al., 2011), interventions aimed at improving EFs are important.

The link between EFs and creativity is somewhat debated. Radel et al. (2015) found that less inhibitory control was associated with more fluent generation of ideas, one central aspect of creativity. On the other hand, being able to cognitively inhibit unrelated ideas is found to improve ideational fluency and flexibility (Benedek et al., 2012). The modulation of defocused attention together with controlled processing/selective focused attention can be regarded as processes needed for cognitive flexibility which is associated with creativity (Zabelina and Robinson, 2010).

Several approaches, both direct and indirect interventions aim to increase EFs in children. These approaches span from games, digital games, art programs, social pretend play, mindfulness, physical exercise, martial arts to parent training, and specific educational practices (Diamond, 2012; Hsu et al., 2014; Zelazo et al., 2016). Evidence for effects are mixed and are usually measured with neuropsychological measures with relatively low

correlation to everyday EFs as it unfolds in the classroom (Toplak et al., 2013). Several pedagogical practices have shown evidence for improving EFs in children; however, the evidence for these are also mixed (for review see Jacob and Parkinson, 2015; Zelazo et al., 2016). Further, the unity/diversity hypothesis by Miyake et al. (2000) also raises the question whether different intervention programs will show best effect on behavioral self-regulation, metacognitive skills, or result in more global EFs improvements.

The best evaluated of these programs, "Tools of the Mind," "Head Start REDI," and the "Chicago School Readiness Program (CRSP)" are designed for kindergarten. Malleability of EFs is thought to be best in pre-school years (Diamond, 2014). The "Promoting Alternative Thinking Skills" program (PATHS; Greenberg et al., 1995) is to our knowing the only program designed for elementary school. PATHS is designed to promote emotional and social functioning, and to reduce behavior problems. This focus is thought to improve EFs as well (Riggs et al., 2006). Bierman et al. (2008a) reported improved emotionregulation and social problem solving in a randomized controlled trial (RCT) of 356 pre-kindergarten children enrolled in PATHS curricula (Bierman et al., 2008a). Small to moderate effects of this RCT was further reported for improved examiner ratings of the children's attention, and performance on a neuropsychological test assessing EFs (i.e., the dimensional Card Sort Task) (Bierman et al., 2008b). In older age groups, however, effects of PATHS school curricula are reported to be smaller (d = 0.1–0.2) than for pre-kindergarten studies (Morris et al., 2014).

Art of Learning (AoL) is a program that combines teacher professional development with a children's learning program over a period of 12 weeks (Creativity Culture and Education, 2018). The AoL program hypothesizes that an arts rich, creative learning program, delivered intensively in schools over several weeks can have a positive impact on the development of EFs and attainment in children (Creativity Culture and Education, 2018). AoL aims to improve teachers understanding of creative skills and EFs. Furthermore, to help teachers gain more confidence in using arts-based approaches and learning to improve attainment across the curriculum. AoL seeks to improve children's understanding of their own creativity and help them develop their EFs. The activities in the program focus on each of the following art forms: music, theatre/drama, dance, literature/poetry, visual arts, and photography/digital art. AoL is largely based upon the review of the existent literature by Diamond (2014), giving evidence that EFs interventions using arts and physical activities are most promising. AoL has not yet been evaluated.

Executive functions are usually assessed through laboratorybased neuropsychological testing, measuring optimal performance at a given time and with very limited distracting stimuli. Hence, laboratory-based testing may not adequately represent how children are able to utilize their EFs in the complexity of more naturalistic settings, and questions have been raised about the ecological validity and generalizability of neuropsychological test results (McCue and Pramuka, 1998). Furthermore, assessing EFs using neuropsychological test batteries is also time-consuming and costly. The BRIEF, which is used in this study tries to accommodate this critique aiming to measure EFs abilities needed for everyday adaptive behavior and functioning through teacher completion of the BRIEF rating scale (Gioia et al., 2000a). This together with interviews with participating teachers trying to capture both near and far transfer effects of the intervention.

The first aim of the current study was to examine whether an arts rich intervention constructed to improve children's EFs would yield any effect on a measure on everyday EFs as reported by children's teachers, and as reported in interviews. Based on current knowledge we hypothesized that the intervention group would have a greater improvement overall in everyday EFs than the children in the control group. Our second aim was to delineate whether this intervention program, delivered intensively in schools, will have a differential impact on behavioral self-regulation and MCOG. According to findings reported by Carretti et al. (2014) we hypothesized that the group receiving intervention will show a greater improvement in MCOG than the control group. We did not expect to find greater improvement in behavioral self-regulation in the group receiving intervention compared to the control group.

### MATERIALS AND METHODS

### Participants

A total of 103 children (49 girls) between 6.1 and 9.3 years (**Table 1**) were recruited from five different public schools in the rural area of Gudbrandsdalen in Norway. Children from three schools (grades 1–2) received the 12-week long AoL intervention and children from the last two schools (grades 1–3, see **Table 2**) served as a control group. Children in the control group worked with their curricula in a traditional manner and received no specific intervention during the trial period. All schools had volunteered to participate in the study. The schools were randomly selected to either intervention or control conditions. At baseline (T1), EFs for all children were assessed by their teachers with the BRIEF-teacher form (Gioia et al., 2000a). The same teachers assessing children's EFs at T1 also reassessed them post-intervention (T2) and after 6 months (T3). Demographic characteristics are presented in **Tables 1**, **2**.

Focus group interviews with teachers were conducted at the intervention schools, as well as individual interviews with one

BRIEF – GEC T1, Behavior Rating Inventory of Executive Function – Global Executive Composite Time 1; NS, not significant.

TABLE 2 | Number of participants in different grades and numbers of interviews conducted in parenthesis.

teacher at each of these schools. Three focus group interviews and three individual interviews in total. Strategic committees were made by discussing with the principals of two of the schools, which teacher had been active in the project all the way, and who had qualifications to be able to provide good information in the interview. At the third school, only one of the teachers had time to join the interview. Therefore, an accessibility selection was made there. That is to say – the sample was strategically based on the fact that the participant represented properties that were relevant to the problem, and the method for selecting this teacher was based on the teacher being available. All the teachers met up at the agreed time to a 1.5 h per group interview and 1 h per individual interview.

### Art of Learning

Art of Learning is an arts rich, creative learning program delivered intensively in schools and aims to have an impact on the development of creative skills, EFs, and attainment in children (Creativity Culture and Education, 2018). AoL is a practice-based program where artists work in partnership with teachers to support planning and implementation of lessons. The program has a duration of 12 weeks and comprises predesigned creative learning practices from six different artforms (music, theatre/drama, dance, literature/poetry, visual arts, photography/digital) delivered 1 h (60 min) a day 3 days a week (see **Supplementary Data Sheets 1–6** for examples). Each activity is specially designed to address either one or more of the EFs; inhibition, WM, or mental flexibility. The sessions consisted of a selection of 36 predetermined art activities and were translated and adapted to the Norwegian context. They involved a large upheaval of everyday life for the intervention group, while for the control group it meant having teaching as normal. The artists came to the intervention schools and conducted the predetermined arts activities with the children in collaboration with the teachers. The artist and the teacher themselves, designs and deliver a 1-h activity (60 min) each week based on the experiences they gain from the program. The artists' work in one class over a period of 6 weeks and then another artist follows the class for the remaining 6 weeks. The children received a total of 240 min, or 4 h of arts activities each week, through the 12 weeks. The sessions were structured based on the children engaging with activities from the different art forms. Each art form (music, theatre/drama, dance, literature/poetry, visual arts, photography/digital) was devoted to 6 sessions, or 2 weeks.

The sessions were built up according to a fixed structure: warm-up, main activity, and reflection. Each session schedule provided instructions on time usage, materials needed, room setup, guidance on how to conduct the activity, and which EFs the session aimed to train (**Table 3**). It was up to the artists and the teachers to adapt the sessions to the group of children. The artists recorded all changes from the original plans after each session and have since been filed in the project database.

Principals and teachers from the intervention schools, as well as the artists, were trained ahead of the intervention to ensure that they understood and could conduct the practical aspects and the content by being part of the AoL, introducing them to the aims and explaining the different elements of the program (see **Supplementary Appendix 1**). They were also given a comprehensive lecture of EFs and its relation to learning and creativity. Teachers from control schools were not given this information or training, this to ensure they did not alter their pedagogical practices accordingly.

Artists who were to carry out the activities were recruited based on experience from previous, similar activities in schools. They were placed at the various intervention schools on the basis of a desire for continuity. It was stressed that the artists should become acquainted with the children and the teachers and vice versa, based on which arts the artists worked with. Planning time for the artist and teachers at least once a week was provided. How the days were organized, and when time was allocated for planning varied from school to school. The schools were given all the material they needed before the intervention period, except for material they had easy access to at each school. Otherwise, the artists were responsible for ensuring that all material was ready before each session, and for preparing it. During the intervention, the Project Leader visited all the schools to ensure program fidelity.

### Measures

The BRIEF rating scale (5–18 years) assesses everyday executive functioning and provides information about cognitive, emotional, and behavioral regulatory processes (Gioia et al., 2000b). BRIEF-teacher form is completed by the child's teacher and contains 86 items measuring different empirically derived aspects of EFs behaviors. These are Inhibit, Shift, Emotional Control, WM, Initiate, Plan/Organize, Organization of Materials, and Monitor. These eight clinical scales form two broad classifications of executive functioning; Behavioral Regulation (BRI) and Metacognition (MI), as well as an overall Global Executive Composite (GEC) score (Gioia et al., 2000a). The current study used the Norwegian version of the teacher form. The teacher form has shown high internal consistency with a Cronbach's α ranging from 0.80 to 0.98, and with test–retest reliability correlations for BRI = 0.92, for MI = 0.91, and for GEC = 0.91. Further, correlational analysis provide evidence for convergent and divergent validity through comparisons with other established scales for behavior (Gioia et al., 2000a). Studies have reported discrepancies comparing European children with the American norm sample in favor of European children scoring better than American norms (Fallmyr and Egeland, 2011; Huizinga and Smidts, 2011; Hovik et al., 2014). Of interest in the current study are the broad measures BRI, MI, and the overall GEC. Raw scores are used in the analyses. Lower raw scores

Art of Learning

fpsyg-10-01769 July 30, 2019 Time: 18:29 # 5

IC, inhibitorycontrol; WM, working memory; CF, cognitive flexibility.

on the BRIEF indicate better EFs. The teachers completing the BRIEF were the same teachers who led the intervention in the classroom together with the artists.

Information from BRIEF-teacher form was supplemented with a partially structured interview, in which the questions and topics are pre-arranged, but with the opportunity and openness for the informants' experiences as well as room for follow-up questions along the way.

### Analysis

SPSS version 24 was used for statistical analysis. Significant results are reported at the p ≤ 0.05 level. Demographic characteristics are investigated using chi-square test for independence (gender) and independent samples t-test (age). Mixed between-within subjects' ANOVA (mixed ANOVA) were used to investigate possible interaction effects in EFs development across groups (intervention vs. controls, girls vs. boys). Significant interaction effects were followed up with repeated-measures ANOVA for each group. Indications of violations of the assumption of sphericity will be reported together with Greenhouse–Geisser corrected tests of within-subjects' effects. Significant interaction effects from mixed ANOVAs were also followed up with paired samples t-tests to investigate differences within groups between T1−T2 and T2−T3.

The semi-structured interview had eight different topics: aims, the sessions, executive functioning, academic functioning, social functioning, role of the teacher, methods, and improvements. Six teacher interviews with three 1st and three 2nd grade teachers from three schools with a duration of approximately 60–90 min were conducted. All the interviews were recorded using a telephone recorder before being transferred to a computer with anonymous titles. After all the interviews were completed, they were structured for analysis by transcription. All participants became anonymous in the enrolment. The computer program QDA Miner Lite was used for coding and categorization. In this process, several meaningful categories were extracted, and a selection of these was included in this report. The categories are related to statements made by the informants about the phenomena they had experienced along the way and after the intervention. The material was read and reviewed several times.

This study was carried out in accordance with the recommendations of the Norwegian Centre for Research Data with written informed consent from parents of all subjects. All parents gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the Norwegian Centre for Research Data.

### RESULTS

### Behavior Rating Inventory of Executive Function (BRIEF)

The results from the BRIEF for the intervention group and control group are presented in **Table 4**. The mixed ANOVA for GEC revealed a significant interaction effect of group × time [F(2,202) = 4.4, p = 0.014, η 2 p = 0.042] indicating greater improvement on results in favor of the intervention group (**Figure 1**). A repeated measure ANOVA for each group revealed that both had improved scores on GEC over time, intervention group: F(2,130) = 19.2, p < 0.001, η 2 p = 0.228. For the control group Mauchly's test indicated a violation of the assumption of sphericity, χ 2 (2) = 16.3, p < 0.001, results from Greenhouse– Geisser (ε = 0.73)-corrected tests: F(1.49,52.5) = 4.05, p = 0.035, η 2 p = 0.101. A paired-samples t-test for the intervention group revealed a significant improvement from T1 to T2 [t(65) = 3.58, p = 0.001, d = 0.30] and from T2 to T3 [t(65) = 2.56, p = 0.013, d = 0.26]. A paired-samples t-test for the control group revealed a significant improvement from T1 to T2 [t(36) = 2.81, p = 0.008, d = 0.20] but not from T2 to T3 [t(36) = −0.7542, p = 0.456, d = −0.04]. There was no significant interaction effect of group × time on the mixed ANOVA for MI (**Figures 2, 4**). A significant effect of time was found for MI [F(2,202) = 11.9, p < 0.001, η 2 p = 0.105]. The mixed ANOVA for BRI showed a significant interaction effect of group × time, F(2,202) = 5.3, p = 0.006, η 2 p = 0.050 (**Figures 3, 5**). A repeated measures ANOVA shows a significant effect of time for BRI in the intervention group F(2,130) = 20.3, p < 0.001, η 2 p = 0.237, but not for the control group F(2,72) = 1.85, p = 0.164, η 2 p = 0.049. A paired-samples t-test for the intervention group revealed a significant improvement from T1 to T2 [t(65) = 3.42, p = 0.001, d = 0.27] and from T2 to T3 [t(65) = 2.96, p = 0.004, d = 0.30]. A paired-samples t-test for the control group revealed no significant improvement from T1 to T2 [t(36) = 1.81, p = 0.077, d = 0.14] nor from T2 to T3 [t(36) = −0.862, p = 0.378, d = −0.04].

We found no significant interaction effects between time, group, and gender on GEC, MI, or BRI [GEC, F(2,198) = 0.28, p = 0.755, η 2 p = 0.003; MI, F(2,198) = 0.01, p = 0.988, η 2 p = 0.000; BRI, F(2,198) = 1.54, p = 0.216, η 2 p = 0.015]. Neither did we find any interaction effects between time and gender.

### Semi-Structural Interviews With Teachers

The coding and categorization process extracted the following categories relevant for the aims of this article.

#### Collaboration

The teachers from all three schools described that the project gave the children new tools to succeed in cooperation with others. The students had to discuss solutions, give and take, individualists had to open to others' views and ideas. The teachers believed that intervening with classroom dynamics provided a better school environment.

### Conflict Management

The teachers all report that the children's abilities to resolve conflicts improved because of the intervention. At one school, the teachers report that both children and teachers have a new approach in conflicts, as the children have learned new concepts and tools to resolve conflicts, and the teachers have become better at challenging the children to reflect upon difficult situations. In another school, the teachers report improved generosity in the

TABLE 4 | Results on BRIEF-teacher form (raw scores) at T1, T2, and T3: means and standard deviations within the intervention and control groups, and results from mixed model ANOVA.

BRIEF, Behavior Rating Inventory of Executive Function; GEC, global executive composite; MI, metacognition index; BRI, behavioral rating index; NS, not significant.

group, the children accept each other in a new way, and no one is laughing at each other.

#### Inclusion

In the interviews, the teachers emphasize the effect the project has had for inclusion. Some describes how the children, through collaborating with several, not just the best friends, create a better school environment. They see that children who were previously left out are included – that everyone is included in a different way than before. The established groups were dissolved, and the children expanded their circle of friends.

#### Vocabulary

The teachers all report that the children have expanded their vocabulary. They describe, respectively, how the children have acquired a richer language, learned new concepts, and have become more reflective. One teacher describes how the children gained a larger conceptual apparatus and thus were able to verbalize how they experienced the sessions. That children who initially just didn't want to be involved at the end were able to verbalize their own internal conflicts and how they could solve it. Furthermore, teachers describe how children's ability to take conversational turns also had improved.

#### Confidence

All schools describe that the children have become more confident in expressing their own opinions, and in taking responsibility for group achievements. Teachers from all schools believe the intervention has given the children mastery and a sense of increased self-confidence.

### DISCUSSION

The results reveal that both groups improve their EFs, as measured with BRIEF, over time on the GEC score, the MI and on BRI. However, the group receiving the intervention had a significantly greater improvement than the control group on GEC and BRI. The teacher interviews reveal several effects of the project. They report positive effects for the children when it comes to; collaboration, conflict management, inclusion, vocabulary, and confidence. The results revealed no gender differences regarding development of EFs throughout the study period.

### Global Executive Composite

The first aim of the current study was to examine whether an arts rich intervention constructed to improve children's EFs would

yield any effect on a measure on everyday EFs, as reported by children's teachers. Based on current knowledge we hypothesized that the intervention group would have a greater improvement overall in everyday EFs than the children in the control group. As expected, the intervention group displayed greater improvement overall with more than twice as large effect sizes, on a measure on everyday executive function (GEC) as reported by children's teachers, compared to the control group.

These results indicating a global effect of AoL are consistent with previous research showing a significant transfer effect of school curricula aiming to enhance EFs (Diamond and Lee, 2011). These findings are also corroborated by the reports from the teachers involved in the intervention and their reflections upon the effects it had on the participants when it comes to social competence, verbal abilities, and self-assurance. One potential explanation for this wide transfer effect of school curricula programs such as AoL may be the emphasis on dynamic EFs training in all activities, across different situations that may stay in contrast to more specialized EFs programs showing less generalized effect (Lillard and Else-Quest, 2006; Riggs et al., 2006; Diamond, 2007). As can be seen from **Figure 1**, GEC improvement in the intervention group and the control group divert from each other from the timepoint that the intervention was discontinued and until follow-up after 6 months. However,

it must be noted that this global effect on improved EFs in the intervention group compared to the control group may primarily be driven by improved BRI in the intervention group. As a main difference between groups across time was found for the BRI, improved BRI scores in the intervention group attributes to most of the overall GEC score based on both MI and BRI. There is a possibility that the teachers involved in the intervention gradually altered their pedagogical practices to be more in accordance with AoL, so the prolonged effect may be directly related to the intervention. Such learning gains for teachers have also been reported from previous evaluations of other creative, arts and culture rich school curricula (Thomson et al., 2015).

### Behavioral Self-Regulation

Our second aim was to delineate whether this intervention program, delivered intensively in schools, will have a differential impact on behavioral self-regulation and MCOG. According to findings reported by Carretti et al. (2014) we hypothesized that the group receiving intervention will show a significantly greater improvement in MCOG than the control group. We did not expect to find significantly greater improvement in behavioral self-regulation in the group receiving intervention compared to the control group. Contrary to our expectations, we did not find support for greater improvement in MCOG for the intervention group, compared to the control group. Surprisingly, the intervention group displayed a greater improvement in behavioral regulation with four times as large effect sizes compared to the control group. Thus, findings from the current study did not support our hypothesis that an arts rich intervention, constructed to improve children's EFs would yield a particular effect on EFs sub-functions shown to be crucial for school performance (Carretti et al., 2014). Where the MI reflect the child's ability to get engaged in planful and organized problem-solving, as well as, updating and shifting of information needed, the BRI to a higher extent comprises subscales reflecting the child's ability to initiate, inhibit, and modulate behavior, emotions, and activities (Gioia et al., 2000b).

Interestingly, results from our study showing improved behavioral regulation are consistent with findings by Bierman et al. (2008a) reporting better emotion-regulation and social problem-solving skills in pre-kindergarten children after being enrolled in PATHS curricula. Along the same lines, the reduction in problem behavior (d = 0.53−0.89) was the main finding in one "CRSP" – RCT of 609 preschool children, showing more moderate improvements in academic skills (d = 0.20−0.63) (Raver et al., 2009, 2011).

A similar main effect on improved behavioral outcome is evident in our study. When inspecting paired-samples t-tests for the intervention group, the global effect of AoL from T1 to T2 (GEC: d = 0.30) and from T2 to T3 (GEC: d = 0.26) is mainly driven by improved BRI (T1−T2: d = 0.27; T2−T3: d = 0.30). The effect sizes of t-tests from T1 to T2 and T2 to T3 are also small, below, or in line with comparable studies mentioned above. However, the effect sizes from the mixed measures ANOVA's are larger (η 2 p = 0.237) and indicate that these children continue to improve their EFs more than controls from T1 to T3, although improvements are small to moderate. Albeit the findings from the RCTs by Bierman et al. (2008a), and Raver et al. (2009, 2011) are based on preschool children from low-income families, our findings corroborate previous results elucidating the centrality of improved emotional–behavioral regulation when aiming to improve EFs through different intervention programs.

Furthermore, as previous research has reported behavior regulation to be closely linked to social function (Kenworthy et al., 2009), and metacognitive competences of more importance for school performance (Carretti et al., 2014), our findings from both BRIEF and teacher interviews may indicate that the main advantage of such intervention programs will be related to children's social function, rather than on academic outcome. However, improved social function may boost academic outcome, in the long run, as improved social competencies enhance cooperation needed for solving many of the tasks given in school settings. Egeland and Fallmyr (2010) have speculated that the BRIEF's emotional regulation scale (a subscale of BRI) reflects the emotional and motivational aspects in EFs (i.e., hot EFs), in contrast to the less emotional items constituting the remaining scales in the BRIEF. In line with the interpretation by Egeland and Fallmyr (2010), improved BRI may reflect the necessities identified by Diamond (2014), that effective EFs training programs also help children to reduce stress, increase joy, make children feel they belong and improve physical fitness, i.e., in sum programs that not only will improve EFs and physical health, but also the children's mental health (Diamond, 2014). This assumption coincides with the conclusions from a critical review of a similar creative arts/culture-based curricula interventions, highlighting the benefits for well-being, citizenship, work-related skills, and habits (Thomson et al., 2015). Thus, improved BRI in the intervention group may not only reflect less problems with behavioral regulation, but also, according to Egeland and Fallmyr (2010) improved emotional regulation skills, and better mental health.

### Metacognition

One potential interpretation of our results showing no greater improvement on MI in the intervention group, compared to the control group may be that potential improvements related to academic problem-solving activities (MI) may be more easily overlooked by teachers than the more overt behavior regulation competencies incorporated in the BRI. Previous research with clinical samples has shown that parents and teachers often report more behavioral symptoms, while children often report more symptoms about themselves than parents and teachers do regarding anxiety and depression (Faraone et al., 1995; Grills and Ollendick, 2002; Sciutto et al., 2004; Rothen et al., 2009; Skogli et al., 2013). Consequently, teacher ratings may be informative regarding behavioral regulation, but less sensitive regarding metacognitive competencies in children at school.

### Strengths and Limitations of the Study

Strengths of the current study is a global intervention specifically aimed at improving executive functioning and the use of an everyday EFs measure pre, post, and 6 months after intervention.

Living in a society with low socio-economic differences and very high attendance to public schools, the study comprises a relatively representative group of pupils. The randomized controlled trial design and the implementation of both qualitative and quantitative data are also regarded as a strength. As the interventions were governed by teachers and artists in classrooms there is a possibility that interventions diverted slightly from how it was originally planned. The project manager visited each school to observe the sessions in order to check fidelity; however, no checklists or other means of checking fidelity were applied. A major limitation is using only teacher reports as outcome measure. This may cause some difficulties regarding a potential teacher–child disagreement. Due to this potential informant variance, it may be stated that what we actually measure is the teacher's apprehension of the child and not the child's capabilities. Therefore, improved EFs may more precisely reflect the teachers altered apprehension of the child. Teachers investment of time and energy to make the intervention work may also reflect how they rate their children after the intervention. However, as the effect was more visible after 6 months this is less likely.

### CONCLUSION

In conclusion, the AoL program shows promising effects on behavioral self-regulation (BRI) improvement in children aged 6– 9 years as reported both from teacher rating scales and interviews. The executive subfunctions underpinning social competencies rather than academic outcome seem to be most affected by the intervention. It remains to be seen if this in turn will improve academic functioning as well.

### DATA AVAILABILITY

The datasets generated for this study are available on request to the corresponding author.

### REFERENCES

### ETHICS STATEMENT

This study was carried out in accordance with the recommendations of the Norwegian Centre for Research Data with written informed consent from parents of all subjects. All parents gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the Norwegian Centre for Research Data.

### AUTHOR CONTRIBUTIONS

PA collected the quantitative data material, did the statistical analyses, and made the first draft of the manuscript. MK did the interviews and the qualitative analyses. ES wrote parts of the manuscript. All authors contributed to the interpretation of both statistical and qualitative analyses, proofread and revised the manuscript, and gave approval to the publication.

### FUNDING

The intervention was funded by Kulturtanken – Arts for Young Audiences in Norway and Oppland County Municipality.

### ACKNOWLEDGMENTS

The authors wish to thank Marie Othilie Hundevadt and Linda Sandholdt for their contributions making this project possible.

### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg. 2019.01769/full#supplementary-material

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Andersen, Klausen and Skogli. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Program for the Neuropsychological Stimulation of Cognition in Students: Impact, Effectiveness, and Transfer Effects on Student Cognitive Performance

Caroline de Oliveira Cardoso1 \*, Alessandra Gotuzo Seabra2 , Cristiano Mauro Assis Gomes3 \* and Rochele Paz Fonseca4