Introduction
The 21st century has brought innovations in education that provide more inclusive and accessible classroom environments, deploy technologies that advance digital and media literacies, and reshape pedagogy away from rote memory and toward investigative, collaborative learning (; .). Successfully participating in these dynamic learning environments as a student requires fewer knowledge prerequisites and more diverse and adaptive skills, including self-reflective, innovative, collaborative, rational, technological, and problem-solving competences (; ). However, despite sustained efforts and ever-increasing investments from governments and corporate interests (.), educational outcomes (in aggregate) have not improved as part of both short and long-term global trends (). This current stagnation in global educational performance (as measured by PISA scores) results from a wide array of factors that may range from classroom pedagogy and assessment methods () to structural components ().
When considering educational systems such as schools or school boards, a broad set of sociological, budgetary, and technological factors impact learning outcomes beyond individual student capabilities: learning is a complex, dynamic, and self-organizing process (). As acknowledged by , learning science is a fledgling field without the type of applied theory and knowledge that allows policy-makers and educators to shape their practices to optimize student learning. In reviewing relevant literature (e.g., ; ), the authors of this paper have identified sustained attention as a significant factor with an evident gap between attentional demands of 21st century learning and the attentional resources of 21st century students. However, advancements in neuroscience and technology may have opened sustained attention to direct intervention.
The importance of attention is not a new discovery: teachers have been rapping their meter sticks against blackboards for centuries. However, sustained attention is not required exclusively for tasks such as remaining oriented to lecture content and completing independent worksheets. In the 21st century classroom, attention also plays a central role in inquiry-based learning (), long-term skill acquisition and development (), and self-directed learning (). Evidence indicates that sustained attention is an increasingly scarce cognitive resource: a global decline in both the quantity and quality of reading (), recent increases in the rate of Attention Deficit Hyperactivity Disorder (ADHD) diagnoses (), and the advent of culturally-induced attention deficits () are all indicators of declining attentional capacities.
Sustained attention involves a prolonged act of directing cognitive resources toward exogenous or endogenous stimuli to pursue a goal (). Attention emerges from a dynamic process between multiple opposed neurological systems (top-down attentional networks and a bottom-up attentional network; ). Loosely construed, the top-down networks are implicated in purposeful goal-oriented activities (), while the bottom-up network is active in response to threats and opportunities (). Both sets of networks are active during sustained attentional activities. In states of “prolonged focus,” a dynamic balance in activity is established between the networks (). Whereas in states of “distraction,” the bottom-up network is dominant and excessively active (), in states of fixated “hyperfocus,” the top-down networks are overactive ().
Learning Behaviors and Executive Functions in the 21st Century Classroom
Building adaptive competences is the primary learning objective and a key differentiating factor of the 21st century educational paradigm (). For students to be more successful in learning and academic achievement, it follows that executive functioning, self-regulation, and learning skills must be shaped in a manner commensurate with classroom activity and learning objectives. Executive function and self-regulation are coupled by the and identified as “mental processes that enable us to plan, focus attention, remember instructions, and juggle multiple tasks successfully.” These skills and competences are interrelated and developed through practice, feedback, and scaffolded support, although the specific channels for development are not yet well understood (). The composite nature of executive functions has led the authors to separate executive functions into the processes described above and learning skills into the more granular activities that they are composed of in supporting problem solving, creative expression, and critical thinking. These behaviors include initiative taking, planning, organizing, self-monitoring, and sustaining working memory.
Network Activity During Sustained Attention
Correlative research combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) data has shown that theta (4.0–7.5 Hz; ) and beta (13.0–35.0 Hz; ) activity in the prefrontal cortex (PFC) are related to sustained attentional performance (). Specifically, participants in conditions with high power levels in the beta band relative to the theta band (beta/theta ratio) showed greater attentional control and inhibition of impulses (). Further, individuals diagnosed with ADHD have shown dysfunction of the anterior cingulate cortex (), resulting in lowered beta/theta ratios, particularly in the PFC region ().
Building Attention Using Neurofeedback Training
Centered on the principle of neuroplasticity, Neurofeedback is a method of providing explicit real-time feedback on specific neurological activity to build regulation of the same. It creates transparency and awareness of autonomous processes so that participants, through the repetitive introduction of appetitive stimuli as reinforcement, may exercise greater control over these processes beyond the training regime (). This reinforcement process has been described as multifactorial, with operant conditioning acting on a primary level and a more complex set of psychological factors linked to prospective alternative treatment modalities acting on a secondary level ().
Empirical research has shown that participants in Neurofeedback Training (NT) trials experienced increased beta/theta ratios (; ), which were associated with decreases in distracted behaviors (). Cognitive training has also been used as an intervention for students with impingements to their learning, and EEG data have shown normalization of alpha, beta, theta, delta, and gamma activity as a result at particular site locations associated with participants’ academic skill development (). Similarly, recent work by has shown increases in alpha activity post-training for students diagnosed with ADHD in NT and cognitive training activities, indicative of a shift in brain function. These changes in neurological activity were associated with improvements in school learning and life skills.
Clinical findings for treating ADHD, including those described above, motivate the current argument that NT may have productive application as a tool for generalized training of sustained attention. Given the growing discrepancy between attentional requirements and available resources, and the current educational focus on metacognitive skills to shape and improve attention (), the classroom stands out as a viable candidate for training and testing with neurofeedback.
As part of a battery of tests, EEG has shown predictive value in diagnosing ADHD (). As a prospective treatment for ADHD, NT has emerged as a clinical tool in reducing distracted and impulsive behaviors to below diagnostic thresholds as identified by scores on the DSM-IV rating scale, Conners, Barkley, and other validated rating scales (). Various training protocols have been tested, including variability in training length and frequency, electrode placement, and target EEG frequency (). In aggregate, NT has shown significant clinical value in treating ADHD across training protocols and when studied using various research methods, including prospective control, prospective pre/post, and retrospective pre/post (). In particular, several training protocols have become more prominent, with 73% of studies included in the meta-analysis by featuring Beta-Theta training with a mode of 30 training sessions per study.
Along with variability in training protocols, various electrode placements have been used in experimental NT trials. Many lab and clinical studies have featured Cz electrode placement, as illustrated in and FP1/2, and FCz positions (). Study designs have been shifting based on the growing market of commercially available EEG headsets. These headset designs have shifted toward the frontal placement of electrodes because of the opportunity for direct skin contact (with dry electrodes) and proximity to the frontal lobe, which has been implicated in attentional network activity (). Research by has shown that “Standard neurofeedback protocols in the treatment of ADHD can be concluded to be a well-established treatment with medium to large effect sizes and 32% to 47% remission rates and sustained effects as assessed after 6 to 12 months.”
Existing literature has provided minimal focus on applying NT in building sustained attention outside of tightly controlled and confined clinical and laboratory settings, with participants diagnosed with ADHD as their primary concern. Motivated by a growing need for attentional resources in the general population of students, the authors of this paper have identified an opportunity to construct and test hypotheses focused on building sustained attention in the classroom. From an educational perspective, the authors are interested in the translational impact of sustained attention on executive functions and learning behaviors. In particular, this paper tests four research hypotheses:
NT is efficacious as an in situ training tool to build sustained attention in students.
Students translate growth in attention into improvements in executive functions and learning behaviors in the classroom.
Active participation drives training outcomes such that students who grow more engaged with training will experience increasing gains in sustained attention and executive functions.
Initial attentional level impacts both scale and variability of training outcomes.
Seminal work by has shown specificity in treating ADHD using NT in applied classroom settings and has provided encouraging results post-training with a 6-month follow-up. The findings from have inspired the current exploratory research, which has shifted the application of NT from treating ADHD to building sustained attentional capacity. Learning in the 21st century is predicated on a series of skills and learning behaviors including task initiation, planning, organization of materials, and self-monitoring, which may be enhanced through greater sustained attention.
Methods
Training Protocol
In situ training entailed two recurrently scheduled 30-min neurofeedback sessions per week for a 27-week training period throughout the school year, administered in a dedicated classroom. All participants were pooled and assigned to one of four training groups (of maximum size five) using block randomization. This randomized assignment yielded heterogeneous groups with respect to ADHD diagnosis. Two training groups of size five and two groups of size four were generated as a result. Each training session was supervised and observed by an experienced educational research assistant. All training sessions were preceded by a preparation phase that required the research assistant to clean and sterilize the MindWave (NeuroSky) EEG headsets. Once the headsets were readied, participants (with the aid of the research assistant) wirelessly connected them (via Bluetooth SPP profile) to their associated computers (running Windows 8). Headset connectivity was confirmed before training and intermittently as needed using Brainwave Visualizer 2.0 (NeuroSky). After successfully pairing their EEG headset and computer, participants played pre-selected NT gaming software for the duration of their 30-min training session. Initial training sessions (approximately 10–15) involved playing Focus Pocus (Neurocog) until game completion. During subsequent sessions, participants were given the choice of training games to play from an assortment preinstalled from the NeuroSky Store (Invaders Reloaded, Man.Up, Blink, Card Memory, Focus Pocus, Hunting, and The Adventures of NeuroBoy).
The MindWave EEG is a single dry electrode headset (FP1 position) with a grounding and reference ear clip (A1 position). The headset sampled unprocessed EEG signals (3–100 Hz) at 512 Hz and transformed the data into proprietary power spectra bins identified as Attention, Meditation, and Zen composed of combinations of Alpha, Beta, and Theta EEG activity (). The spectral signals were communicated to the training software and provided real-time feedback to participants during gameplay. For instance, “Invaders Reloaded is a vertically scrolling 3D shoot-em-up with a twist; Your ship’s weapons and powerups (sic) are controlled by your concentration. The harder you concentrate, the faster and more powerful your shots will become” (). In this particular game, the movement of the player’s ship is controlled by the keyboard, and the firing rate and power of the weapons are governed by the EEG signal output of the Attention bin, such that participants who exhibit greater attentional state control experience better real-time success in gameplay. The other games all involved similar training of the Attention bin—intended to develop the sustained attention of players—and Focus Pocus also included explicit training of impulse inhibition, working memory, and different state control activities based on training the proprietary power spectra bins identified as Meditation and Zen.
Participants and Sampling
The selection procedure involved sampling exclusively from a single independent school (grades 4–12) located in Toronto, ON, Canada. All full-time students were invited to participate, and 18 volunteered after informed consent was obtained from the participants’ families. Participant information is summarized as follows:
Ages 10 to 13
Three female and 15 male
Seven parent/guardian-reported diagnoses of ADHD
Because this applied research was conducted without institutional affiliation, an ethics committee was not available for approval or oversight. The authors followed the APA’s Ethics Code () and consulted with a Toronto-based psychologist and psychometrist to inform the consent process, research design, and choice of measurement instruments. Participant recruitment occurred through a multi-layered approach, commencing with an invitation to join, sharing the research proposal, outlining the training protocols, and providing a health exclusion list for NT, which included five contraindicative disorders: epilepsy, seizure disorder, diabetes, hypoglycemia, and bipolar disorder. Following the invitation, an information night was held for interested students and parents, where the research proposal was presented verbally and visually, followed by opportunities for individual inquiries. After agreeing to participate in the explicitly identified non-compensatory study, all families provided informed consent before joining.
Research Design
This study’s experimental training protocols were designed to be implemented in situ on students in a school setting. The study was planned as a one-group pretest-posttest quasi-experimental design, with outcome measures scored by the participants’ homeroom teachers (). Teacher ratings were chosen over parent ratings because the two are seen interchangeably in terms of validity as outcome measures in rating clinical efficacy (), and teachers have direct and exclusive observations of many of the learning behaviors of interest in this study. Pre-and-post-training data were collected using teacher-scored Conners 3rd Edition™ (Pearson Canada Assessment, Inc.) and Behavior Rating Inventory of Executive Function (BRIEF, PAR Inc.) psychometric scales. Additionally, the research assistant collected intermittent training-based observation data using the Behavioral Observation of Students in Schools (BOSS, Pearson).
Measured Variables
Before conducting the study, the authors reviewed available outcome measures for sustained attention, executive functions, and learning behaviors. While acknowledging that performance-based measures fit consistently with the applied nature of this research, the authors prioritized repeatability and the internal validity checks available in psychometric scales (; ). The Conners 3rd Edition™ and BRIEF scales are used widely in NT research, and clinical settings (e.g., ; ) and strongly connect to the intended learning outcomes for students. In particular, the authors reviewed the granular behavioral observations included in the Inattention scale of the Conners 3rd Edition™ and successfully mapped them to the operationalized description of sustained attention for this study. Similarly, the authors reviewed the individual behavioral observations included in the Task Initiation, Working Memory, Planning and Organization, Organization of Materials, and Self-Monitoring indices of the BRIEF and successfully mapped them to a core set of activities expected of a student engaged in 21st-century learning and frequently in deficit among students with lower attentional capacities ().
Outcome measures were calculated as within-participant differences in t scores for attention, executive functions, and learning behaviors. Given that t scores for each of these sub scales represent the population-based ranking of the frequency of ineffectual behaviors within the domain, a change in t score quantifies a change in the relative rate of the included ineffectual behaviors. In particular, changes to participant capacity for sustained attention were measured by calculating differences in the Inattention scale of Conners 3rd Edition™. The development of executive function skills was measured as differences in the Behavior Regulation Index, Metacognition Index, and Global Executive Composite from the BRIEF. Changes in learning behaviors were measured as differences in the Task Initiation, Working Memory, Planning and Organization, Organization of Materials, and Self-Monitoring scales that compose the Metacognition Index of the BRIEF.
Two independent measures were also collected for this study: participation level in training and ADHD diagnosis. Within-session off-task behavior was measured from a random selection of three participants per training session using the BOSS. Output from the BOSS was aggregated across off-task behavior types into a single binary measure indicating whether a participant was on-task or off-task during a particular observation interval. The percentage of intervals with no observable off-task behavior during a session was used as the primary metric for training participation. To quantify participants’ baseline attentional levels, parents and guardians were prompted to identify previous ADHD diagnoses during study registration, and the outcomes were confirmed with data from the participants’ psychoeducational assessments, with diagnoses made by psychometrists using the Diagnostic and Statistical Manual of Mental Disorders edition of the time of the assessments.
Data Analysis
The exploratory nature of this research suggests several implications for the treatment and type of data used in this study. The sample was drawn from a homogeneous population, and inferences are limited in scope to apply to students at the school being studied. Due to the small sample size, all data are treated as nonparametric. All test statistics were calculated using R, and the corresponding probability of an acceptable type I error (α) was set at .05.
To test whether participants experienced changes in their capacity for sustained attention, the authors implemented two statistical tests. The first test assessed the relative number of participants who benefited from the NT by implementing a one-sample goodness-of-fit chi-squared test, comparing experimental observations to an expected (chance) outcome of 50%. The second test evaluated the relative magnitude of the changes in sustained attention using a one-tailed dependent samples sign-test.
A one-tailed Spearman’s correlation coefficient was calculated to investigate the relationship between changes in participants’ capacity for sustained attention and the development of executive functioning skills and learning behaviors between these outcome measures. Specifically, ρ was calculated for changes in sustained attentional capacity and changes in each of the executive function skills and the individual learning behavior scales of the BRIEF’s Metacognition Index.
The relationship between participation in training and outcome was assessed using two statistical tests. Median on-task training level was correlated (one-tailed Spearman’s rank) against changes in sustained attentional capacity and changes in executive functioning skills. Further, the dependence of participants’ changes in sustained attention and executive functioning skills on their individual training trajectory was evaluated using a series of chi-squared tests.
In assessing the impact of baseline attentional levels on outcomes, participant data were grouped based on their parent or guardian-reported ADHD diagnosis for analysis. A two-sample chi-squared goodness-of-fit test was calculated to compare the relative number of participants who experienced attentional benefits between ADHD diagnosed and undiagnosed blocks. Further, changes to the magnitude and variability of sustained attentional capacity and executive functioning skills were compared between ADHD diagnosed and undiagnosed participants using the common language effect size and the nonparametric Levene test for each measure.
Exclusion Criteria
Participant data were excluded from analyzes in cases where the contained psychometric validity scales were flagged for possible inconsistencies or biases in scoring. Specifically, participant 3 was excluded from all analyzes, including measures taken from the Conners 3rd Edition™, and participants 1 and 18 were excluded from all analyzes, including measures taken from the BRIEF.
Results
Efficacy of in Situ Training
Testing indicates that students benefited from the school-based NT with decreases in the relative frequency of inattentive behaviors following their training (as indicated by negative differences in t scores). As illustrated in Figure 1, 71% (12 of 17) of participants showed improvements in their capacity for sustained attention (p = 0.073) based on pre and post-training differences in Inattention scores. Further, the dependent-samples sign-test, assessing the central tendency of the within-participant changes in Inattention, revealed an aggregate median value of −6 (p = 0.038).
Figure 1
Within-participant differences in the relative frequency of inattentive behaviors.
Note. ap < 0.05.
Translating Changes in Attention to Changes in Executive Functioning
Analysis reveals that decreases in the relative frequency of inattentive behaviors are associated with decreases in the relative frequency of ineffectual executive functioning (as indicated by negative differences in t scores for both Inattention and executive functioning indices). Correlation coefficients were calculated for pre and post-training differences in Inattention scores and the corresponding changes in the three executive function indices. This analysis yielded Spearman’s p values of 0.40, 0.68, and 0.66 for Behavior Regulation, Metacognition, and the Global Executive Composite, respectively (see Figure 2 for an illustrated scatterplot of the within-participant changes in Inattention and executive functioning). The probabilities corresponding to the correlation coefficients (n = 15) for the Behavioral Regulation, Metacognition, and Global Executive Composite measures were .054, .0028, and .0028, respectively.
Figure 2
Association between post-pre NT changes in executive functioning and sustained attention.
Note. cp <0.05.
Reviewing the components of the executive function indices of the BRIEF revealed that the Metacognitive index relates most directly to the learning behaviors students participate in at school. Correlation coefficients (Spearman’s p) were calculated for within-participant differences in each of the key behavior scales and the corresponding changes in Inattention. As Table 1 illustrates, variability in pre and post-training differences in attention explains a high proportion of variability in the changes to planning and organization skills and a moderate proportion of variability in changes to working memory capacity.
Participation Level and Changes in Attention and Executive Functioning
Analysis shows that improvements in attention and executive functioning occur independently of the trajectory of participants’ engagement level in training (i.e., improving or declining/remaining constant over time). Moreover, chi-squared results support that increasing on-task activity throughout training is not predictive of attentional gains or increases in executive functioning. Refer to Table 2 for the frequency counts and corresponding Χ2 test statistics illustrating the association between training participation and changes to sustained attention and executive functioning. Further investigation reveals small correlations between median on-task participation level during training and within-participant differences in Inattention, Behavioral Regulation, Metacognition, and the Global Executive Composite (Spearman’s p values of −0.16, 0.19, −0.28, and −0.22, respectively).
Impact of ADHD on Attentional and Executive Functioning Behavioral Changes
Analyzing the within-participant changes in inattention and executive functioning when considering participants based on their ADHD status (seven with diagnoses and nine without) illustrates notable highlights (see Tables 3 and 4 for a summary of observations). The first of these findings was a moderate effect size of ADHD status on improving the capacity for sustained attention following NT (with non-ADHD diagnosed participants experiencing greater gains in attention). The second highlight was a moderate effect of ADHD status on improving executive functioning (with ADHD diagnosed participants experiencing greater gains in Behavioral Regulation, Metacognition, and the Global Executive Composite indices). The third key finding was that ADHD status did not materially impact the variability in attentional or executive functioning responses to training. Further analysis demonstrated homogeneity of response throughout the trial, 71% (5 of 7) of ADHD diagnosed participants and 67% (6 of 9) of non-ADHD diagnosed participants showed growth in their capacity for sustained attention (p = 1.0).
Discussion
Together, the results of this research support that NT holds promise as a training tool for building individual student capacity for sustained attention and that growth of this cognitive capacity can translate into more effective learning behaviors in the classroom. It is important that the empirical outcomes be reviewed within the context of the limitations of the sampling process and outcome. Moreover, the results should be considered exploratory pilot research to establish the plausibility of in situ NT.
Empirical research supports NT as a Level 5 treatment modality for ADHD based on its documented efficacy and specificity (; ). The research conducted in this study used methods, outcome measures, and technologies consistent with such clinical settings and brought them into a school environment. The results of this research corroborate existing clinical studies (), with NT showing specificity in building sustained attentional capacity, observed by decreases in the relative frequency of inattentive behaviors of the participants. Further, the efficacy of this intervention (71% of participants showing growth in sustained attention) mirrors the clinical efficacy estimated for stimulant medications in treating ADHD (70%–90%; ). The encouraging results of this exploratory study warrant further applied research.
The primary focus of this study is on translating sustained attention improvements into actionable and observable learning behaviors in the classroom. The results show that changes in sustained attention explain 46% of the variability in changes to Metacognition. Further, participants translated gains in sustained attention into improvements in specific learning behaviors. Planning and Organization was most directly associated with attention such that students who experienced the largest increases in sustained attention most aptly improved their organizational abilities. Notable among these planning skills are anticipating next steps, breaking tasks into manageable activities, and communicating key ideas. Additionally, participants with the largest gains in sustained attention experienced improvements in their capacity to hold information in mind while processing multiple problem-solving steps. Together, these findings support the second hypothesis and highlight tangible and observable components of learning that may be influenced through gains in sustained attention acquired during NT. Given the results from the first hypothesis test, these findings endorse the premise that NT shows efficacy as a training tool to help participants become more effective at learning in the classroom.
Observable participation level in NT did not appear to be related to training outcomes. Moreover, sustained attention and learning behaviors improved independently of participation level and training trajectory. These results indicate that observation of on-task/off-task behavior during training may not indicate engagement with the training activity and performance within the training environment. One implication of this finding underlies the importance of investigating individual versus group training effects and the need for within-training session performance task measurements. Participants in this study remained within consistent training groups (containing 4–5 students) throughout their training. Social dynamics and training-group size effects were extraneous to this study and may have impacted training efficacy. Furthermore, training software did not provide performance metrics to allow time series analysis. Together, these implications suggest potential future methodological directions of applied NT research. With training software in place to provide metrics of individual within-session participation, research can build an understanding of group dynamics, group size effects, and optimal training conditions.
In clinical and school settings, NT has been studied in the context of treating ADHD (; ). The central premise of this body of work is that participants have started from a position of deficit and have benefited from the training. What has not been established in the literature is the training effect on participants who do not start from the same deficit position. Although many factors may influence how efficacious NT is for an individual and how well they can translate gains in attention into observable learning behaviors, initial attentional capacity is a key starting point for these future investigations. The results of this study indicate that participants starting with higher levels of sustained attention experienced greater training effects on their attention. Moreover, baseline attentional level is not predictive of whether a participant experiences improvements in sustained attention from NT, but higher starting levels facilitate greater gains in attention.
ADHD diagnosed participants overperformed their non-ADHD peers in building executive functioning skills and capacities. Groups of participants experienced gains in both sustained attention and executive functioning, with the highest performances contingent on the attentional starting point. Together, these findings indicate that finer granularity and performance ties in outcome measures are required in future research to better understand the mechanisms of translating gains in attention into observable learning behaviors.
Consistent with other treatment modalities for ADHD (e.g., pharmacological; ), NT has been effective for large proportions of participants (). However, empirical evidence has not yet identified a priori factors that distinguish prospective participants as more or less likely to benefit from the training. The results of this study support a similar inference that a majority of students may benefit from generalized NT, though significant work is required to understand factors predictive of sustained attentional growth from NT. This premise can be viewed in the frame of empirical work by , who identified ADHD as a heterogeneous disorder. The implications of these participant-to-participant differences are that no single solution will be a panacea for treating ADHD or serve as a tool for building all students’ sustained attention. Policy-makers, schools, and educators will need to be innovative and explore various strategies and understand which students NT would be an appropriate tool for and which ones it will not be.
The results of the current research should be interpreted in the context of existing investigations on the sustainability of improvements in attention from NT. Work by illustrated that gains in attention were maintained 6 months post-training. With a goal of long-term capacity building in an academic setting, it will be essential to understand the trajectory of student skill and capacity development over years as students’ brains develop. In particular, research should focus on whether sustained attentional capacity, executive functions, and learning behaviors require periodic “top up” training to sustain performance or whether active use of these capacities and skills will perpetuate the performance. Future research should also consider within-session performance metrics of sufficient fidelity to identify the threshold of effective training length for each individual to prevent potential overtraining.
Conclusions
Empirical study has focused on using EEG technology as prognostic and treatment tools for ADHD (), and the results of this study support that it may have wider educational application as a tool for enabling more effective learning. Although the sampling in this study limits the generalizability of these conclusions, the authors feel encouraged that further study is warranted based on the outcomes. Several methodological implications can be inferred from this research, including the need to capture direct performance metrics and social dynamics in situ to better understand the nature of training results and the translation of training into learning behaviors. Aiming to support student learning in an ever-evolving 21st-century classroom requires reframing our thinking about how students learn. Therefore, sustained attention as a potentially trainable capacity that may enable students to learn more effectively or efficiently warrants further research.
The authors of this paper would like to acknowledge Vanessa Rowlin and Pam Foreht for their contributions to this research.
Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding The author(s) received no financial support for the research, authorship, and/or publication of this article.
Jason Krell
https://orcid.org/0000-0001-8551-1579
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