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Deciding What to Do: Developments in Children’s Spontaneous Monitoring of Cognitive Demands
Abstract
How do children decide which tasks to take on? Understanding whether and when children begin to monitor cognitive demands to guide task selection is important as children gain increasing independence from adults in deciding which tasks to attempt themselves. In this article, we review evidence suggesting a developmental transition in children’s consideration of cognitive demands when making choices about tasks: Although younger children are capable of monitoring cognitive demands to guide task selection, spontaneous monitoring of cognitive demands begins to emerge around 5–7 years. We describe frameworks for understanding when and why children begin to monitor cognitive demands, and propose additional factors that likely influence children’s decisions to pursue or avoid cognitively demanding tasks.
... In addition, the trade-off we found requires the evaluation of the effort of different strategies, and studies have shown that spontaneous metacognition is only starting to emerge between 5-7 years of age (Niebaum & Munakata, 2020). ...
... Our paradigm had a few design features that may have helped support this trade-off in younger children. First, visual cues can facilitate children's spontaneous metacognitive monitoring (Niebaum & Munakata, 2020). In fact, while 5-year-olds were not able to choose an easier task when given no visual cues or prompts (O'Leary & Sloutsky, 2017), they were able to when the visual cues were provided (Wang & Bonawitz, 2022). ...
Most work on working memory development has children remember a set of items as well as they can. However, this
approach sidesteps the extended mind, the integration of external information with memory. Indeed, adults prefer to
use external resources (e.g., lists, models) but will remember more as the cost to access them increases. Here, in our
shopping game, we investigated this trade-off in 5- to 8-year-olds. Using a touchscreen, children shopped in a virtual
store. Their shopping list and the store were not visible simultaneously but could be toggled. We manipulated access
cost by varying a delay (0–4 s) before the list’s reappearance. Across three preregistered experiments at two sites
(the United States and China, N = 141), a pattern emerged: When it was costlier to do so, children revisited the list
less often, studied it longer, and selected more correct items. Also, children recognized the costs, identifying the no-
delay condition as easier. Young children showed a cost-dependent trade-off of external-resource use versus working
memory.
... One of the primary reasons to exploit external resources is to reduce cognitive effort (Hayhoe & Ballard, 2005;Risko & Gilbert, 2016), but this requires recognizing the demands of one's goals, and one's strategies for reaching them. The ability to monitor and control one's cognitive effort (Niebaum et al., 2019;Niebaum & Munakata, 2020;O'Leary & Sloutsky, 2017), and the ability to perceive cognitive effort as costly (Chevalier, 2018;Ganesan & Steinbeis, 2022) gradually emerge during early childhood. 5-8 years of age seems to be the most important period in this regard. ...
... 5-8 years of age seems to be the most important period in this regard. Shifts in the use of external resources require monitoring the effort needed to use working memory (Kelly & Risko, 2022), and children's ability to identify, or opt for, an 'easier' task (Niebaum et al., 2019(Niebaum et al., , 2021Niebaum & Munakata, 2020;O'Leary & Sloutsky, 2017) or use external resources selectively based on the difficulty of a task (Armitage et al., 2020;Bulley et al., 2020) is beginning to emerge around 5 years of age. For instance, 6-year-olds, but not 4-5-yearolds, will, similarly to the Risko et al. study (2014) with adults, physically rotate a paper map as opposed to engaging in mental rotation (Armitage & Redshaw, 2022). ...
Most work in the last 50 years on visual working memory and attention has used a classic psychophysical setup: participants are instructed to attend to, or remember, a set of items. This setup sidesteps the role of cognitive control; effort is maximal, tasks are simple, and strategies are limited. While this approach has yielded important insights, it provides no clear path toward an integrative theory (Kristjánsson & Draschkow, 2021) and, like studying a town’s walkability by having its college students run the 50-yard dash, it runs the danger of focusing on edge cases. Here, in this theoretical opinion article, we argue for an approach with a Gibsonian flavor where dynamic relationships between the agent and the environment are understood functionally, in light of an agent’s goals. This means a shift in emphasis from the performance of the mechanisms underlying a narrow task (“remember these items!”) to their control in pursuit of a naturalistic goal (“make a sandwich!”, Land & Hayhoe, 2001). Here, we highlight the sampling-remembering trade-off between exploiting goal-relevant information in the environment versus maintaining it in working memory. We present a dynamic feedback model of this trade-off – where the individual weighs the subjective costs of accessing external information versus those of maintaining it in memory – using insights from existing cognitive control models based on economic principles (Kool & Botvinick, 2018). This trade-off is particularly interesting in children, as the optimal use of internal resources is even more crucial when limited. Our model makes some specific predictions for future research: 1) an individual child strikes a preferred balance between the effort to attend to goal-relevant information in the environment versus the effort to maintain it in working memory, and 2) in order to maintain this balance as underlying memory and cognitive control mechanisms improve, the child will have to increasingly shift toward remembering.
... At the same time, strategically dividing cognitive labor may be more difficult than dividing physical labor for young children because of potential differences at each of the three theorized steps outlined above. First, children could have more difficulty reasoning about another's chances of success at tasks requiring cognitive skill than physical skill (Niebaum & Munakata, 2020). Cognitive skills like knowledge or mental capacity have few, if any, concrete correlates available prior to observing their success or failure. ...
... positive feedback from answering correctly) after being compared to a peer (Magid & Schulz, 2015). Another possibility is that children were driven to reduce their cognitive effort, choosing questions that could be answered very quickly and without much thought (see Halberda & Feigenson, 2008;Niebaum & Munakata, 2020). Yet another possibility is that children were driven to repair their reputation following an unfavorable comparison (see Shaw et al., 2014 for an example within the literature on fairness). ...
Strategic collaboration according to the law of comparative advantage involves dividing tasks based on the relative capabilities of group members. Three experiments (N = 405, primarily White and Asian, 45% female, collected 2016–2019 in Canada) examined how this strategy develops in children when dividing cognitive labor. Children divided questions about numbers between two partners. By 7 years, children allocated difficult questions to the skilled partner (Experiment 1, d = 1.42; Experiment 2, d = 0.87). However, younger children demonstrated a self‐serving bias, choosing the easiest questions for themselves. Only when engaging in a third‐party collaborative task did 5‐year‐olds assign harder questions to the more skilled individual (Experiment 3, d = 0.55). These findings demonstrate early understanding of strategic collaboration subject to a self‐serving bias.
... Metacognitive monitoring refers to evaluating the current circumstances, including cognitive demands, and making judgments about one's performance based on past experience, proficiency, and feedback, whereas metacognitive control refers to coordinating one's behaviors toward the optimal outcome (J. Niebaum & Munakata, 2020;O'Leary & Sloutsky, 2019). Although metacognitive control seems to lag behind metacognitive monitoring, both show sustained progress throughout childhood (Bryce et al., 2015;Destan et al., 2014;Krebs & Roebers, 2010). ...
Objective: Unlike adults, children often fail to coordinate their behavior away from unnecessary cognitive demands to conserve effort. The present study investigated whether greater conflict monitoring may contribute to metacognitive monitoring of cognitive demands, which in turn may support greater cognitive demand avoidance with age. Method: Electroencephalogram data were recorded while 54 adults and fifty-four 5- to 10-year-old children completed a demand selection task, where they chose between versions of a task with either higher or lower demands on cognitive control. Results: Both adults and children avoided the high-demand task, showing that, in some circumstances, children as young as 5 years can avoid unnecessary cognitive demands. Critically, midfrontal theta power predicted awareness of cognitive demand variations, which in turn predicted demand avoidance. The relationship between midfrontal theta power and demand awareness was negative and did not change between age groups. Conclusion: Together, these findings suggest that metacognitive monitoring and control are based in part on conflict monitoring in both children and adults.
... Theories of Change of Integrated EF Interventions Increasingly, education scientists and policy makers have proposed a much more specific need to embed EF into the context of the target transfer domain, in this context mathematics (EF + Math, n.d.; Mulcahy et al., 2021;Niebaum & Munakata, 2020). In parallel, cognitive neuroscientists have also strongly argued that differential recruitment of circuits involved in mathematics-specific EFs (e.g. ...
A vast body of work highlights executive functions (EFs) as robust correlates of mathematics achievement over the primary and preschool years. Yet, despite such correlational evidence, there is limited evidence that EF interventions yield improvements in early years mathematics. As intervention studies are a powerful tool to move beyond correlation to causality, failures of transfer from executive functions interventions are, we argue, highly problematic for both applied and theoretical reasons. We review the existing correlational and intervention literature at complementary neuroscientific, cognitive, developmental and educational levels. We appraise distinct theories of change underpinning the correlations between EF and early mathematics, as well as explicit or implicit theories of change for different types of EF interventions. We find that isolated EF interventions are less likely to transfer to improvements in mathematics than integrated interventions. Via this conceptual piece, we highlight that the field of EF development is in need of (1) a clearer framework for the mechanisms underpinning the relationships between early EF and other developing domains, such as mathematical cognition; (2) clearer putative theories of change for how interventions of different kinds operate in the context of EF and such domains; (3) and greater clarity on the developmental and educational contexts that influence these causal associations. Our synthesis of the evidence emphasises the need to consider the dynamic development of EFs with co-developing cognitive functions, such as early math skills, when designing education environments. [234 words].
... To choose a suitable level of task-difficulty, one needs to know one's actual performance level in a given task. Metacognition improves with age throughout childhood and adolescence (e.g., Destan & Roebers, 2015;Forsberg et al., 2021), and children become increasingly able to select suitable task-difficulty levels (Niebaum & Munakata, 2020) or adjust their study times in cognitive tasks (Dufresne & Kobasigawa, 1989). Depending on the context, older adults have shown overconfidence (Crawford & Stankov, 1996;Shing et al., 2009), but also underconfidence (Hertzog & Touron, 2011) in cognitive tasks. ...
In everyday life, individuals often need to make choices about the difficulty level of tasks they wish to perform. Here, we investigate age- and gender-related differences in the monitoring of discrepancies between the difficulty of a given task and one’s own performance level, and in the likelihood to select task difficulties that match one’s performance level. Male and female children, teenagers, younger adults, and older adults (total N = 160) were asked to play a modified version of the BINGO game. Task difficulty was operationalized as the number of cards played simultaneously. We expected that (a) discrepancies between individuals’ self-selected difficulty levels and their objectively assessed maximum manageable task difficulty (MMTD) would be lowest in early adulthood; (b) children and teenagers, on average, would select relatively difficult task difficulties; and (c) males would overestimate their performance levels, on average, to a greater extent than females. As predicted, younger adults selected task difficulties closest to their MMTD. All other age groups, including older adults, chose task difficulties above their MMTD. The expected gender differences were restricted to children, with boys showing more pronounced performance overestimations than girls. Children and teenagers fluctuated more in their difficulty choices than adults, and many of them, especially boys, occasionally chose difficulty levels far beyond their performance capabilities. We conclude that task-difficulty choices are an interesting topic for lifespan studies. Future research should systematically vary the physical risk involved in a task, and also include the presence of peers.
... unts, participants should treat multi-task sets that recruit more shared representations as more costly than sets that recruit more separated representations (Musslick & Cohen, 2021). Developmental studies using this task may also help understand the interplay between learning, information-seeking, and effort (Chevalier, 2018;Munakata et al., 2012;J. Niebaum & Munakata, 2020;J. C. Niebaum et al., 2019;Snyder & Munakata, 2010). ...
Effort-based decisions, in which people weigh potential future rewards against effort costs required to achieve those rewards, have largely been studied separately for cognitive or physical effort, yet most real world actions incur both cognitive and physical effort costs. What is the relationship between cognitive and physical effort costs? Here we attempt to formalize the mechanisms underlying effort-based decisions and address methodological challenges to isolate and measure the factors contributing to such decisions (including sensitivity to reward and effort costs).
Patch foraging is an ecologically valid reward rate maximization problem with well developed theoretical tools to understand choices. We developed the Effort Foraging Task to isolate and quantify the cost of both cognitive and physical effort using a computational model. We embedded cognitive or physical effort costs into a patch foraging sequential decision task. Participants chose between harvesting a depleting patch, or traveling to a new patch that was costly in time and effort. Participants' exit thresholds (reflecting the reward they expected to receive by harvesting when they chose to travel to a new patch) were sensitive to cognitive and physical effort demands, allowing us to quantify the perceived effort cost in monetary terms. Individual differences in cognitive and physical effort costs were positively correlated, suggesting that these are perceived and processed in common terms across different domains. We found patterns of correlation of both cognitive and physical effort costs with self-reported cognitive function, anhedonia, depression, anxiety, and fatigue. This suggests that our task captures decision mechanisms closely associated with real-world motivation, and can be used to study individual variation in effort-based decisions across different domains of cost.
... Later in development, 4to 5-year-olds demonstrate metacognitive awareness by reporting more confidence for items that they answer correctly versus incorrectly (Hembacher & Ghetti, 2014) and by proactively selecting evidence that will be easier for them to discriminate (Siegel et al., 2021). However, some aspects of metacognition may be later developing (Metcalfe & Finn, 2013;Niebaum & Munakata, 2020). For example, after doing poorly on a memory test, 4-to 5-year-old children do not allocate more study time when presented with the same task again (Flavell et al., 1970). ...
Learning requires effort, but children cannot try hard at everything. Here, we evaluated whether children use their improvement over time to decide whether to stick with a challenge. To eliminate the effect of individual differences in ability or prior knowledge, we created a novel paradigm that allowed us to surreptitiously control children's performance. Across three preregistered experiments (N = 319, ages 4 to 6 in the United States), we found that children who were given evidence that their performance was improving were more likely to persist on a challenging task than children who were given evidence that their performance was constant, even when final performance was matched. This effect was robust to differing reward contingencies, across in-person and online testing contexts, and was driven by the demotivating effect of constant performance. Our results suggest that young children will be more persistent if they are guided away from too-difficult tasks and toward opportunities that enable steady growth. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
... PES seems to increase until around 7 to 9 years of age and then starts to decline until adolescence (de Mooij et al., 2022;Gupta et al., 2009;Jones et al., 2003;Schachar et al., 2004). Children appear to initially employ reactive control and start to employ the more efficient proactive control (i.e., find a good speed of responding by balancing speed and accuracy from the beginning) only from 8 years of age onward (Chevalier et al., 2015;Niebaum & Munakata, 2020). As another indication of more efficient posterror adjustment, the variability in response times decreases from 5 to 15 years of age (Brewer & Smith, 1989). ...
Slowing down responses after errors (i.e., post-error slowing [PES]) is an established finding in adults. Yet PES in young children is still not well understood. In this study, we investigated (a) whether young children show PES in tasks with different types of cognitive conflict and differing demands on executive functions, (b) whether PES is adaptive and efficient in the sense that it is associated with better task performance, and (c) whether PES correlates between tasks. We tested 4- to 6-year-old children on the Funny Fruits task (FF; n = 143), a Stroop-like task that incorporates semantic conflict and taxes children’s inhibition skills, and the Hearts and Flowers task (HF; n = 170), which incorporates spatial conflict and taxes children’s inhibition skills in its incongruent block and taxes both inhibition and cognitive flexibility (rule-switching) skills in its mixed block. A subgroup of children were tested on both FF and HF (n = 74). Results revealed that, first, children showed PES in FF and both blocks of HF, indicating that PES occurs in both types of conflict and under varying executive demands. Second, PES was associated with task accuracy, but only for FF and the mixed HF. Third, a between-task association in PES emerged only between FF and the mixed HF. Together, these findings indicate that PES is still a developing strategy in young children; it is present but only adaptive for, and correlates between, semantic inhibition and spatial flexibility.
Young children typically engage in cognitive control reactively in response to specific situations, rather than proactively preparing for them. The developmental change from reactive to proactive control seems to happen gradually across early development and ultimately results in a qualitatively different behavior pattern. However, existing evidence is mainly based on cross-sectional designs. Thus, this study adopted a longitudinal design to examine the transition from reactive control to proactive control in preschoolers. Sixty preschoolers aged 4 (n = 31) and 5 (n = 29) were recruited and required to complete two cognitive control tasks (i.e., an AX-Continuous Performance Test and a Cued Task-Switching task) twice within a five-month interval. The results showed that the children improved their cognitive control skills across both tasks, demonstrating a predominantly reactive control pattern during the time interval. This improvement reflects an age-related gradual change, which is a preparation for evolving into a qualitatively different behavioral pattern over time. These findings provide longitudinal evidence for the developmental change from reactive to proactive control in early childhood strategies.
Despite the importance of persistence in early learning, we know little about how children reason about outcomes that result from their efforts. Here we examined the role of effort type (i.e., physical vs. cognitive) and intensity (i.e., high vs. low effort) in shaping children's decision making about effort‐based rewards. Five‐ to 7‐year‐olds ( N = 133) were assigned to one of four conditions (High Physical Effort, Low Physical Effort, High Cognitive Effort, Low Cognitive Effort) and completed a series of tasks to construct a toy. Tasks varied in the type (physical/cognitive) and intensity (high/low) of effort required to complete them. After constructing their toy, children completed a series of tasks to probe how much they valued that toy. Across conditions, children preferred their toy and gave it a higher monetary value, relative to a stranger's. However, when choosing their toy came at a cost, children no longer preferred it. Only children who built their toy through either cognitive or low effort were willing to incur a cost for their toy. Older children, across conditions, were also more likely to incur a cost for their toy. These findings demonstrate that by age five, children are sensitive to variations in effort type and intensity, and these factors shape how they evaluate effort‐based rewards.
Greater sensitivity to the cost of effortful engagement has long been implicated in the development of Attention Deficit Hyperactivity Disorder (ADHD). The current study evaluated preferential choice to engage in demanding tasks, and did so in combination with computational methods to interrogate the process of choice. Children aged 8-12 with (n = 49) and without (n = 36) ADHD were administered the cognitive effort discounting paradigm (COG-ED, adapted from Westbrook et al., 2013). Diffusion modelling was subsequently applied to the choice data to allow for a better description of the process of affective decision making. All children showed evidence of effort discounting, but, contrary to theoretical expectations, there was no evidence that children with ADHD judged effortful tasks to be lower in subjective value, or that they maintained a bias towards less effortful tasks. However, children with ADHD developed a much less differentiated mental representation of demand than their non-ADHD counterparts even though familiarity with and exposure to the experience of effort was similar between groups. Thus, despite theoretical arguments to the contrary, and colloquial use of motivational constructs to explain ADHD-related behavior, our findings strongly argue against the presence of greater sensitivity to costs of effort or reduced sensitivity to rewards as an explanatory mechanism. Instead, there appears to be a more global weakness in the metacognitive monitoring of demand, which is a critical precursor for cost-benefit analyses that underlie decisions to engage cognitive control.
Sometimes we should persist to succeed. But other times it might be wiser to give up on the task at hand and focus our energy on something new. Knowing whether a task is worth the effort potentially requires multiple capacities, including sensitivity to one’s own likelihood to succeed on the current problem, the associated costs with continuing to pursue it, and evaluation of opportunities for reward from the success. But these capacities may be particularly challenging for young children. Here we ask how young children are sensitive to cognitive cost (one’s capacity and the opportunity cost of persisting) and reward probability (how likely they are to receive a reward when succeeding) when making decisions. Using a simple counting task, we showed that 4- to 5-year-old children in the US (N = 40, pre-registered) chose to give up more when the task was more difficult (and therefore cognitively more costly), especially when the probability of reward was low. These results extend previous findings and suggest the ability to consider and evaluate cognitive cost and reward probability may be in place by 4 years of age.
This Element describes the main theories that guide contemporary research in cognitive development along with research discoveries in several important cognitive abilities: attention, language, social cognition, memory, metacognition and executive function, and problem solving and reasoning. Biological and social contributions are considered side-by-side, and cultural contributions are highlighted. As children participate in social interactions and learn to use cultural symbols and tools to organize and support their thinking, the behaviors and understandings of the social community and the culture more broadly become an integral part of children's thoughts and actions. Culture, the natural ecological setting or habitat of human beings, plays a significant role by providing support and direction for cognitive development. Without the capacity to learn socially, human cognition would be markedly different from what it is today.
Success in life is linked to executive functions, a collection of cognitive processes that support goal-directed behaviors. Executive functions is an umbrella term related to cognitive control, self-control, and more. Variations in executive functioning predict concurrent success in schooling, relationships, and behavior, as well as important life outcomes years later. Such findings may suggest that certain individuals are destined for good executive functioning and success. However, environmental influences on executive function and development have long been recognized. Recent research in this tradition demonstrates the power of social contextual influences on children's engagement of executive functions. Such findings suggest new interpretations of why individuals differ in executive functioning and associated life outcomes, including across cultures and socioeconomic statuses. These findings raise fundamental questions about how best to conceptualize, measure, and support executive functioning across diverse contexts. Future research addressing real-world dynamics and computational mechanisms will elucidate how executive functioning emerges in the world.
Expected final online publication date for the Annual Review of Developmental Psychology, Volume 3 is December 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
This essay brings together two lines of work—that of children’s cognition and that of complexity science. These two lines of work have been linked repeatedly in the past, including in the field of science education. Nevertheless, questions remain about how complexity constructs can be used to support children’s learning. This uncertainty is particularly troublesome given the ongoing controversy about how to promote children’s understanding of scientifically valid insights. We therefore seek to specify the knowledge–complexity link systematically. Our approach started with a preliminary step—namely, to consider issues of knowledge formation separately from issues of complexity. To this end, we defined central characteristics of knowledge formation (without considerations of complexity), and we defined central characteristics of complex systems (without considerations of cognition). This preliminary step allowed us to systematically explore the degree of alignment between these two lists of characteristics. The outcome of this analysis revealed a close correspondence between knowledge truisms and complexity constructs, though to various degrees. Equipped with this insight, we derive complexity answers to open questions relevant to science learning.
Age-related progress in cognitive control reflects more frequent engagement of proactive control during childhood. As proactive preparation for an upcoming task is adaptive only when the task can be reliably predicted, progress in proactive control engagement may rely on more efficient use of contextual cue reliability. Developmental progress may also reflect increasing efficiency in how proactive control is engaged, making this control mode more advantageous with age. To address these possibilities, 6-year-olds, 9-year-olds, and adults completed three versions of a cued task-switching paradigm in which contextual cue reliability was manipulated. When contextual cues were reliable (but not unreliable or uninformative), all age groups showed greater pupil dilation and a more pronounced (pre)cue-locked posterior positivity associated with faster response times, suggesting adaptive engagement of proactive task selection. However, adults additionally showed a larger contingent negative variation (CNV) predicting a further reduction in response times with reliable cues, suggesting motor preparation in adults but not children. Thus, early developing use of contextual cue reliability promotes adaptiveness in proactive control engagement from early childhood; yet, less efficient motor preparation in children makes this control mode overall less advantageous in childhood than adulthood.
Direct instruction facilitates learning without the costs of exploration, yet teachers must be selective because not everything can nor needs to be taught. How do we decide what to teach and what to leave for learners to discover? Here we investigate the cognitive underpinnings of the human ability to prioritize what to teach. We present a computational model that decides what to teach by maximizing the learner’s expected utility of learning from instruction and from exploration, and we show that children (aged 5–7 years) make decisions that are consistent with the model’s predictions (that is, minimizing the learner’s costs and maximizing the rewards). Children flexibly considered either the learner’s utility or their own, depending on the context, and even considered costs they had not personally experienced, to decide what to teach. These results suggest that utility-based reasoning may play an important role in curating cultural knowledge by supporting selective transmission of high-utility information.
The present study aims to investigate what factors determine students’ engagement in mathematics. We examined the predictive relationships between interest, effort cost (i.e., the cost of making the effort), and three forms of academic engagement: persistence, cognitive engagement, and effort avoidance. In addition, we examined gender differences in these relationships. We recruited 546 8th and 9th graders for this study. Consistent with previous research, interest worked as a strong positive predictor of persistence and cognitive engagement, and it predicted effort avoidance negatively. Moreover, interest negatively predicted the perception of effort cost, which in turn positively predicted effort avoidance. Gender differences were found in the mean values of effort avoidance and in the prediction by interest of the perception of effort cost. Male students reported higher effort avoidance than female students, and the prediction by interest of the perception of effort cost was stronger among female students than among male students. These findings provide new insights into students’ engagement in mathematics and the role of interest and effort cost in it.
It is often argued that metacognition includes 2 components: monitoring and control. However, it is unclear whether these components can operate independently, or whether they always operate as part of a hierarchy. The current study attempts to address this issue. In Experiment 1 (N = 90), age-related differences were assessed to examine the developmental trajectories of monitoring and control in 5- and 7-year-old children and adults. In Experiment 2 (N = 90) and Experiment 3 (N = 90), a scaffolding approach was taken with the same age groups to investigate correspondences in intervention-related changes in monitoring and control. Several dissociations between monitoring and control were found: In Experiment 2, strategy instruction affected metacognitive control, but not metacognitive monitoring, whereas in Experiment 3, performance feedback affected metacognitive monitoring, but not metacognitive control. These findings suggest that the monitoring and control components of metacognition can operate independently, challenging simple feed-forward models of metacognition.
Preschoolers are sensitive to differences in individuals’ access to external resources (e.g., tools) in division of labor tasks. However, little is known about whether children consider differences in individuals’ internal resources (e.g., abilities) and whether children can flexibly allocate roles across different goal contexts. Critically, factors that are relevant to role allocation in collaborative contexts may be irrelevant in competitive and prosocial ones. In three preregistered experiments, we found that 4- and 5-year-olds (mean: 54 months; range: 42–66 months; N = 132) used age differences to infer relative ability and appropriately allocate the harder and easier of two tasks in a dyadic cooperative interaction (Experiment 1), and appropriately ignored relative ability in competitive (Experiment 2) and prosocial (Experiment 3) contexts, instead assigning others the harder and easier roles, respectively. Thus, 3-and-a-half- to 5-year-olds evaluate their own abilities relative to others and effectively allocate roles to achieve diverse goals.
What do people feel like doing after they have exerted cognitive effort or are bored? Here, we empirically test whether people are drawn to rewards (at the neural level) following cognitive effort and boredom. This elucidates the experiences and consequences of engaging in cognitive effort, and compares it to the consequences of experiencing boredom, an affective state with predicted similar motivational consequences. Event-related potentials were recorded after participants (N=243) were randomized into one of three conditions - boredom (passively observing strings of numbers), cognitive effort (adding 3 to each digit of a four-digit number), or control. In the subsequent task, we focused on the feedback negativity (FN) to assess the brain's immediate response to the presence or absence of reward. Phenomenologically, participants in the boredom condition reported more fatigue than those in the cognitive effort condition, despite reporting exerting less effort. Results suggest participants in the boredom condition exhibited larger FN amplitude than participants in the control condition, while the cognitive effort condition was neither different from boredom nor control. The neural and methodological implications for ego depletion research, including issues of replicability, are discussed.
Human cognition is characterized by subjective experiences that go along with our actions, but the nature and stability of these experiences remain largely unclear. In the current report, the subjective experience of difficulty is studied and it is proposed that this experience is constructed by integrating information from multiple cues. Such an account can explain the tight relationship between primary task performance and subjective difficulty, while allowing for dissociations between both to occur. Confirming this hypothesis, response conflict, reaction time and response repetition were identified as variables that contribute to the experience of difficulty. Trials that were congruent, fast or required the same response as the previous trial were more frequently rated as easy than trials that were incongruent, slow or required a different response as the previous trial. Furthermore, in line with theoretical accounts that relate metacognition to learning, a three day training procedure showed that the influence of these variables on subjective difficulty judgments can be changed. Results of the current study are discussed in relation to work on meta-memory and to recent theoretical advancements in the understanding of subjective confidence.
Previous research attempted to explain how humans strategically adapt behavior in order to achieve successful task performance. Recently, it has been suggested that one potential strategy is to avoid tasks that are too demanding. Here, we report three experiments that investigate the empirically neglected role of metacognitive awareness in this process. In these experiments, participants could freely choose between performing a task in either a high-demand or a low-demand context. Using subliminal priming, we ensured that participants were not aware of the visual stimuli creating these different demand contexts. Our results showed that participants who noticed a difference in task difficulty (i.e., metacognitive aware participants) developed a clear preference for the low-demand context. In contrast, participants who experienced no difference in task difficulty (i.e., metacognitive unaware participants) based their choices on variables unrelated to cognitive demand (e.g., the color or location associated with a context), and did not develop a preference for the low-demand context. Crucially, this pattern was found despite identical task performance in both metacognitive awareness groups. A multiple regression approach confirmed that metacognitive awareness was the main factor driving the preference for low-demand contexts. These results argue for an important role of metacognitive awareness in the strategic avoidance of demanding tasks.
In spite of its familiar phenomenology, the mechanistic basis for mental effort remains poorly understood. Although most researchers agree that mental effort is aversive and stems from limitations in our capacity to exercise cognitive control, it is unclear what gives rise to those limitations and why they result in an experience of control as costly. The presence of these control costs also raises further questions regarding how best to allocate mental effort to minimize those costs and maximize the attendant benefits. This review explores recent advances in computational modeling and empirical research aimed at addressing these questions at the level of psychological process and neural mechanism, examining both the limitations to mental effort exertion and how we manage those limited cognitive resources. We conclude by identifying remaining challenges for theoretical accounts of mental effort as well as possible applications of the available findings to understanding the causes of and potential solutions for apparent failures to exert the mental effort required of us.
Two experiments investigated the development of metacognitive monitoring and control, and conditions under which children engage these processes. In Experiment 1, 5-year-olds (N = 30) and 7-year-olds (N = 30), unlike adults (N = 30), showed little evidence of either monitoring or control. In Experiment 2, 5-year-olds (N = 90) were given performance feedback (aimed at improving monitoring), instruction to follow a particular strategy (aimed at improving control), or both. Across conditions, feedback improved children's monitoring, and instruction improved both monitoring and control. Thus, children's poor metacognitive performance likely reflects a difficulty engaging the component processes spontaneously rather than a lack of metacognitive ability. These findings also suggest that the component processes are distinct, with both undergoing protracted development.
In the current set of experiments our goal was to test the hypothesis that individuals avoid courses of action based on a kind of metacognitive evaluation of demand in a Demand Selection Task (DST).Individuals in Experiment 1 completed a DST utilizing visual stimuli known to yield a dissociation between performance and perceived demand. Patterns of demand avoidance followed that of perceived demand. Experiment 2 provided a replication of the aforementioned results, in addition to demonstrating a second dissociation between a peripheral physiological measure of demand (i.e., blink rates) and demand avoidance. Experiment 3 directly tested the assumption that individuals make use of a general metacognitive evaluation of task demand during selections. A DST was utilized in a forced-choice paradigm that required individuals to either select the most effortful, time demanding, or least accurate of 2 choices. Patterns of selections were similar across all rating dimensions, lending credit to this notion.Findings are discussed within a metacognitive framework of demand avoidance and contrasted to current theories
Metacognitive Evaluation in the Avoidance of Demand. Available from: https://www.researchgate.net/publication/299461174_Metacognitive_Evaluation_in_the_Avoidance_of_Demand [accessed Mar 29, 2016].
Young children engage cognitive control reactively in response to events, rather than proactively preparing for events. Such limitations in executive control have been explained in terms of fundamental constraints on children's cognitive capacities. Alternatively, young children might be capable of proactive control but differ from older children in their metacognitive decisions regarding when to engage proactive control. We examined these possibilities in three conditions of a task-switching paradigm, varying in whether task cues were available before or after target onset. RTs, ERPs, and pupil dilation showed that 5-year-olds did engage in advance preparation, a critical aspect of proactive control, but only when reactive control was made more difficult, whereas 10-year-olds engaged in proactive control whenever possible. These findings highlight metacognitive processes in children's cognitive control, an understudied aspect of executive control development.
The purpose of this review is to present a new perspective on children's development of transfer of learning. The focus is on transfer of the effectiveness of a skill (i.e., improved performance), rather than just the transfer of the skill (e.g., a strategy) itself. Specifically, we examined the role of strategy utilization deficiencies, along with cognitive capacity, in the transfer of a memory strategy and, especially, strategy effectiveness (increased recall). Executive functions, metacognition, and mindset were considered as mechanisms that can both facilitate and hinder transfer of strategy effectiveness. Implications for theorizing about both transfer and utilization deficiencies were discussed.
Why does performing certain tasks cause the aversive experience of mental effort and concomitant deterioration in task performance? One explanation posits a physical resource that is depleted over time. We propose an alternative explanation that centers on mental representations of the costs and benefits associated with task performance. Specifically, certain computational mechanisms, especially those associated with executive function, can be deployed for only a limited number of simultaneous tasks at any given moment. Consequently, the deployment of these computational mechanisms carries an opportunity cost - that is, the next-best use to which these systems might be put. We argue that the phenomenology of effort can be understood as the felt output of these cost/benefit computations. In turn, the subjective experience of effort motivates reduced deployment of these computational mechanisms in the service of the present task. These opportunity cost representations, then, together with other cost/benefit calculations, determine effort expended and, everything else equal, result in performance reductions. In making our case for this position, we review alternative explanations for both the phenomenology of effort associated with these tasks and for performance reductions over time. Likewise, we review the broad range of relevant empirical results from across sub-disciplines, especially psychology and neuroscience. We hope that our proposal will help to build links among the diverse fields that have been addressing similar questions from different perspectives, and we emphasize ways in which alternative models might be empirically distinguished.
The ability to flexibly break out of routine behaviors develops gradually and is essential for success in life. We discuss three key developmental transitions toward more flexible behavior. First, children develop an increasing ability to overcome habits by engaging cognitive control in response to environmental signals. Second, children shift from recruiting cognitive control reactively, as needed in the moment, to recruiting cognitive control proactively, in preparation for needing it. Third, children shift from relying on environmental signals for engaging cognitive control to becoming more self-directed. All three transitions can be understood in terms of the development of increasingly active and abstract goal representations in prefrontal cortex.
The present study aimed at identifying the effects of mood treatment, personality factors, and metacognitive knowledge of
effort–i.e., conceptualization of effort and perceptions of effort regulation–on metacognitive experiences of students, particularly
on their reported feeling of difficulty and estimate of effort. The sample comprised 474 students of 5th and 7th grade of
both genders. The participants were tested in two phases. In the first phase, they were asked to respond to questionnaires
measuring (a) metacognitive knowledge of effort, (b) maths self-concept, (c) goal orientations, and (d) a test of maths ability.
In the second phase, participants were subjected to mood treatment–neutral, positive, and negative– and were asked to solve
a mathematical problem. They also rated their prospective metacognitive experiences before solving the problem and the retrospective
ones after solving it. Mood treatment interacted with gender in the case of performance but it had no effect on metacognitive
experiences. A series of regression analyses showed that positive mood, personality factors, and feeling of difficulty predicted
the prospective estimate of effort. Only feeling of difficulty and performance predicted the retrospective estimate of effort.
No effect of metacognitive knowledge of effort on estimate of effort was found.
Behavioral and economic theories have long maintained that actions are chosen so as to minimize demands for exertion or work, a principle sometimes referred to as the law of less work. The data supporting this idea pertain almost entirely to demands for physical effort. However, the same minimization principle has often been assumed also to apply to cognitive demand. The authors set out to evaluate the validity of this assumption. In 6 behavioral experiments, participants chose freely between courses of action associated with different levels of demand for controlled information processing. Together, the results of these experiments revealed a bias in favor of the less demanding course of action. The bias was obtained across a range of choice settings and demand manipulations and was not wholly attributable to strategic avoidance of errors, minimization of time on task, or maximization of the rate of goal achievement. It is remarkable that the effect also did not depend on awareness of the demand manipulation. Consistent with a motivational account, avoidance of demand displayed sensitivity to task incentives and covaried with individual differences in the efficacy of executive control. The findings reported, together with convergent neuroscientific evidence, lend support to the idea that anticipated cognitive demand plays a significant role in behavioral decision making.
How children learn from positive and negative performance feedback lies at the foundation of successful learning and is therefore of great importance for educational practice. In this study, we used functional magnetic resonance imaging (fMRI) to examine the neural developmental changes related to feedback-based learning when performing a rule search and application task. Behavioral results from three age groups (8-9, 11-13, and 18-25 years of age) demonstrated that, compared with adults, 8- to 9-year-old children performed disproportionally more inaccurately after receiving negative feedback relative to positive feedback. Additionally, imaging data pointed toward a qualitative difference in how children and adults use performance feedback. That is, dorsolateral prefrontal cortex and superior parietal cortex were more active after negative feedback for adults, but after positive feedback for children (8-9 years of age). For 11- to 13-year-olds, these regions did not show differential feedback sensitivity, suggesting that the transition occurs around this age. Pre-supplementary motor area/anterior cingulate cortex, in contrast, was more active after negative feedback in both 11- to 13-year-olds and adults, but not 8- to 9-year-olds. Together, the current data show that cognitive control areas are differentially engaged during feedback-based learning across development. Adults engage these regions after signals of response adjustment (i.e., negative feedback). Young children engage these regions after signals of response continuation (i.e., positive feedback). The neural activation patterns found in 11- to 13-year-olds indicate a transition around this age toward an increased influence of negative feedback on performance adjustment. This is the first developmental fMRI study to compare qualitative changes in brain activation during feedback learning across distinct stages of development.
Developmental changes in executive function are often explained in terms of core cognitive processes and associated neural substrates. For example, younger children tend to engage control reactively in the moment as needed, whereas older children increasingly engage control proactively, in anticipation of needing it. Such developments may reflect increasing capacities for active maintenance dependent upon dorsolateral prefrontal cortex. However, younger children will engage proactive control when reactive control is made more difficult, suggesting that developmental changes may also reflect decisions about whether to engage control, and how. We tested awareness of temporal control demands and associated task choices in 5-year-olds and 10-year-olds and adults using a demand selection task. Participants chose between one task that enabled proactive control and another task that enabled reactive control. Adults reported awareness of these different control demands and preferentially played the proactive task option. Ten-year-olds reported awareness of control demands but selected task options at chance. Five-year-olds showed neither awareness nor task preference, but a subsample who exhibited awareness of control demands preferentially played the reactive task option, mirroring their typical control mode. Thus, developmental improvements in executive function may in part reflect better awareness of cognitive demands and adaptive behavior, which may in turn reflect changes in dorsal anterior cingulate in signaling task demands to lateral prefrontal cortex.
Research on executive function in early childhood has flourished in recent years. Much of this work is premised on a view of development of executive function as the emergence of a set of domain-general component processes (e.g., working memory updating, inhibitory control, shifting). This view has shaped how we think about relations between executive function and other aspects of development, the role of the environment in executive-function development, and how best to improve executive function in children who struggle with it. However, there are conceptual and empirical reasons to doubt that executive function should be defined in this way. I argue that the development of executive function is better understood as the emergence of skills in using control in the service of specific goals. Such goals activate and are influenced by mental content such as knowledge, beliefs, norms, values, and preferences that are acquired with development and are important to consider in understanding children’s performance on measures of executive function. This account better explains empirical findings than the component-process view; leads to specific, testable hypotheses; and has implications for theory, measurement, and interventions.
Developmental changes in executive function are often explained in terms of core cognitive processes and associated neural substrates. For example, younger children tend to engage control reactively in the moment as needed, whereas older children increasingly engage control proactively, in anticipation of needing it. Such developments may reflect increasing capacities for active maintenance dependent upon dorsolateral prefrontal cortex. However, younger children will engage proactive control when reactive control is made more difficult, suggesting that developmental changes may also reflect decisions about whether to engage control, and how. We tested awareness of temporal control demands and associated task choices in 5- and 10-year-olds and adults using a demand selection task. Participants chose between one task that enabled proactive control and another task that enabled reactive control. Adults reported awareness of these different control demands and preferentially played the proactive task option. Ten-year-olds reported awareness of control demands but selected task options at chance. Five-year-olds showed neither awareness nor task preference, but a subsample who exhibited awareness of control demands preferentially played the reactive task option, mirroring their typical control mode. Thus, developmental improvements in executive function may in part reflect better awareness of cognitive demands and adaptive behavior, which may in turn reflect changes in dorsal anterior cingulate in signaling task demands to lateral prefrontal cortex.
Is boredom bad? It is certainly common: Most everybody gets bored. There is a sense that boredom sometimes causes bad things to happen (e.g., substance use, self-harm) and sometimes causes good things to happen (e.g., daydreaming, creativity), but it is hard to understand what boredom does without first understanding what it is. According to the meaning-and-attentional-components (MAC) model of boredom and cognitive engagement, the emotion of boredom signals deficits in attention and meaning. Much like pain, it may not be pleasant, but boredom critically alerts us that we are unable or unwilling to successfully engage attention in meaningful activities. Whether that is good or bad rests ultimately on how we respond.
The Cambridge Handbook of Motivation and Learning - by K. Ann Renninger February 2019
*Draft version 10/26/18 submitted for peer review. Please do not circulate or cite without author's permission* Recent research has proposed that the ‘law of less work’ holds for cognitive work (Kool, McGuire, Rosen, & Botvinick, 2010), with people preferring easier over more difficult cognitive tasks. Using two different adaptations of a demand selection task, we show that interest, but not self-efficacy, can influence this effect, such that participants make more choices that involve cognitive work. Interest was also associated with lower feelings of fatigue. In two studies, participants (N=63 and N=158) repeatedly made a choice between completing a difficult or easy math problem. Results show that liking math (but not perceived math skill) predicts choosing more difficult (vs. easy) math problems. Two more studies use the Academic Diligence Task (Galla et al., 2014) where high school students (N=447 and N=884) could toggle between a math task and playing a video game/watching videos. In these studies, we again find that math interest relates to greater proportion of time spent on the math problems. Three of these four studies also examined perceived fatigue, finding that interest relates to lower fatigue. An internal meta-analysis of the four studies finds a small but robust effect of interest on both the willingness to exert greater effort, and the experience of less fatigue (despite engaging in more effort). The meta-analytical effect of self-efficacy on effort exertion and fatigue is non-significant.
Human prosocial behaviors are supported by early‐emerging psychological processes that detect and fulfill the needs of others. However, little is known about the mechanisms that enable children to deliver benefits to others at costs to the self, which requires weighing other‐regarding and self‐serving preferences. We used an intertemporal choice paradigm to systematically study and compare these behaviors in 5‐year‐old children. Our results show that other‐benefiting and self‐benefiting behavior share a common decision‐making process that integrates delay and reward. Specifically, we found that children sought to minimize delay and maximize reward, and traded off delays against rewards, regardless of whether these rewards were for the children themselves or another child. However, we found that children were more willing to invest their time to benefit themselves than someone else. Together, these findings show that from childhood, other‐ and self‐serving decisions are supported by a general mechanism that flexibly integrates information about the magnitude of rewards, and the opportunity costs of pursuing them. A video abstract of this article can be viewed at: https://youtu.be/r8S0DGe7f8Q
In the context of learning, cost has mostly been discussed under the expectancy-value framework and defined as the perceived negative consequences of task engagement. The issue of cost has recently attracted growing interest among scholars, because it may provide insights regarding how to predict students’ avoidance motivation and behavior. In the present study, we investigated the potential benefits of an expectancy-value-cost approach for predicting outcomes related to adolescent students’ academic motivation and achievement in math. Using two data sets (N = 637 and N = 211) of middle and high school students, we found that cost could successfully explain additional variance in multiple different variables related to academic motivation and achievement, beyond what could be predicted by expectancy and value. In particular, cost emerged as an important factor in predicting adolescent students’ adoption of avoidance goals, negative classroom affect, maladaptive academic outcomes, and exam scores. Findings of the present study extend the scope of expectancy-value theory by highlighting the importance of using expectancy, task value, and cost together to predict students’ academic motivation and educational outcomes.
Young adults adaptively coordinate their behavior to avoid demands placed on cognitive control. We investigated how this adaptive coordination develops by having 6-7- and 11-12-year-olds and young adults complete a demand selection task, in which participants could select between two tasks that varied in cognitive control demands via differences in rule switch frequency. Adults and older children exhibited significant preference for selecting the less demanding task, as well as a metacognitive signal guiding adaptive demand avoidance behavior across a variety of behavioral and self-report assessments. In contrast, despite evidence of differential demands on cognitive control, younger children did not coordinate their task selections to avoid higher demand. Together, these findings suggest that sensitivity and adaptive responses to control demands emerge with development and are consistent with gradual development of lateral prefrontal cortex, dorsal anterior cingulate cortex, and their functional connectivity, which support effort avoidance in adults.
According to prominent models in cognitive psychology, neuroscience, and economics, effort (be it physical or mental) is costly: when given a choice, humans and non-human animals alike tend to avoid effort. Here, we suggest that the opposite is also true and review extensive evidence that effort can also add value. Not only can the same outcomes be more rewarding if we apply more (not less) effort, sometimes we select options precisely because they require effort. Given the increasing recognition of effort's role in motivation, cognitive control, and value-based decision-making, considering this neglected side of effort will not only improve formal computational models, but also provide clues about how to promote sustained mental effort across time.
Many behavioral paradigms used to study individuals' decision-making tendencies do not capture the decision components that contribute to behavioral outcomes, such as differentiating decisions driven toward a reward from decisions driven away from a cost. This study tested a novel decision-making task in a sample of 403 children (age 9 years) enrolled in an ongoing longitudinal study. The task consisted of three blocks representing distinct cost domains (delay, probability, and effort), wherein children were presented with a deck of cards, each of which consisted of a reward and a cost. Children elected whether to accept or skip the card at each trial. Reward–cost pairs were selected by using an adaptive algorithm to strategically sample the decision space in the fewest number of trials. Using person-specific regression models, decision preferences were quantified for each cost domain with respect to general tolerance (intercept), as well as parameters estimating the effect of incremental increases in reward or cost on the probability of accepting a card. Results support the relative independence of decision-making tendencies across cost domains, with moderate correlations observed between tolerance for delay and effort. Specific decision parameters showed unique associations with cognitive and behavioral measures including executive function, academic motivation, anxiety, and hyperactivity. Evidence indicates that sensitivity to reward is an important factor in incentivizing decisions to work harder or wait longer. Dissociating the relative contributions of reward and cost sensitivity in multiple domains may facilitate the identification of heterogeneity in suboptimal decision making. Copyright
Cognitive effort is costly and this cost likely influences the activities that children engage in. Yet, little is known about how school-age children perceive cognitive effort. The subjective value of cognitive effort, that is, how valuable or costly effort is perceived, was investigated in 73 7- to 12-year-olds using an effort-discounting paradigm. In two studies, it varied with task difficulty but not age, was predicted by actual effort engagement but not actual success, and related to trait interest in effortful activities and proactive control engagement. Children are sensitive to cognitive effort and use it to guide behaviors, suggesting that poor performance may often reflect reluctance to engage cognitive effort rather than low ability.
Emerging cognitive control supports increasingly adaptive behaviors and predicts life success, while low cognitive control is a major risk factor during childhood, making it essential to understand how it develops. The present study provides evidence for an age-related shift in the type of information that children prioritize in their environment, from objects that can be directly acted upon to cues signaling how to act. Specifically, gaze patterns recorded while 3- to 12-year-olds and adults engaged in a cognitive control task showed that whereas younger children fixated on targets that they needed to respond to before gazing at task cues signaling how to respond, older children and adults showed the opposite pattern (which yielded better performance). This shift in information prioritization has important conceptual implications, suggesting that a major force behind cognitive control development may be non-executive in nature, as well as opening new directions for interventions.
Emerging executive function, which allows children to control their thoughts and actions, predicts success in life. A key challenge for children is to engage control in a way that matches ever-changing demands of tasks. In addition to engagement of more control resources and more mature control strategies, developing executive function also requires that children coordinate available control strategies more flexibly as they age. More optimal coordination of control (or meta-control) ensures dynamic adjustment of control engagement to match more effectively moment-to-moment variations in the demands of tasks and results in more economic cognitive functioning.
In the current studies, we addressed the development of effort-based object valuation. Four- and 6-year-olds invested either great or little effort in order to obtain attractive or unattractive rewards. Children were allowed to allocate these rewards to an unfamiliar recipient (dictator game). Investing great effort to obtain attractive rewards (a consonant situation) led 6-year-olds, but not 4-year-olds, to enhance the value of the rewards and thus distribute fewer of them to others. After investing effort to attain unattractive rewards (a dissonant situation), 6-year-olds cognitively reduced the dissonance between effort and reward quality by reappraising the value of the rewards and thus distributing fewer of them. In contrast, 4-year-olds reduced the dissonance behaviorally by discarding the rewards. These findings provide evidence for the emergence of an effort-value link and underline possible mechanisms underlying the primacy of cognitive versus behavioral solutions to dissonance reduction.
© The Author(s) 2015.
Cognitive control is accompanied by observable negative affect. But how is this negative affect experienced subjectively, and are these feelings related to variation in cognitive control? To address these questions, 42 participants performed a punished inhibitory control task while periodically reporting their subjective experience. We found that within-subject variation in subjective experience predicted control implementation, but not neural monitoring (i.e., the error-related negativity, ERN). Specifically, anxiety and frustration predicted increased and decreased response caution, respectively, while hopelessness accompanied reduced inhibitory control, and subjective effort coincided with the increased ability to inhibit prepotent responses. Clarifying the nature of these phenomenological results, the effects of frustration, effort, and hopelessness-but not anxiety-were statistically independent from the punishment manipulation. Conversely, while the ERN was increased by punishment, the lack of association between this component and phenomenology suggests that early monitoring signals might precede the development of control-related subjective experience. Our results indicate that the types of feelings experienced during cognitively demanding tasks are related to different aspects of controlled performance, critically suggesting that the relationship between emotion and cognitive control extends beyond the dimension of valence.
© 2015 Society for Psychophysiological Research.
Cognitive effort has been implicated in numerous theories regarding normal and aberrant behavior and the physiological response to engagement with demanding tasks. Yet, despite broad interest, no unifying, operational definition of cognitive effort itself has been proposed. Here, we argue that the most intuitive and epistemologically valuable treatment is in terms of effort-based decision-making, and advocate a neuroeconomics-focused research strategy. We first outline psychological and neuroscientific theories of cognitive effort. Then we describe the benefits of a neuroeconomic research strategy, highlighting how it affords greater inferential traction than do traditional markers of cognitive effort, including self-reports and physiologic markers of autonomic arousal. Finally, we sketch a future series of studies that can leverage the full potential of the neuroeconomic approach toward understanding the cognitive and neural mechanisms that give rise to phenomenal, subjective cognitive effort.
The ability to experience uncertainty (i.e., uncertainty monitoring) is an important skill that enables us to optimize our performance by acting cautiously or seeking additional information when we feel uncertain, and by expressing our knowledge when we feel certain (i.e., uncertainty control). Research reveals that even young preschoolers can introspect on uncertainty and act appropriately based on these introspections. We conclude that uncertainty monitoring and control can be driving forces of cognitive development during the preschool years. In this article, we review the emerging literature on this topic, highlight open questions, and draw connections with other research domains.
Selected cognitive developments presumed to mediate the development of achievement motivation are described. 4 levels of reasoning or causal schemes involving the concepts of effort and ability were isolated and age trends from 5 to 13 years presented. The developments of capacity to infer ability required by tasks of different difficulty levels and the belief that more difficult tasks have greater incentive value of success were described. These achievements occurred at about the same time as the development of the second level of reasoning about effort and ability. It is suggested that these findings help account for certain developmental changes in achievement behavior. Perception of own academic attainment was less closely related to attainment in young children than older children. The age changes in perception of own attainment and causal schemes are held to be likely to contribute to age increases in the stability of individual differences in achievement behavior and academic attainment. The educational implications of the study are noted.
2 experiments were conducted to examine the relationships between cognitive level, intrinsic motivation, and responses to extrinsic rewards and praise. In experiment 1, 90 4-10-year-old children were divided into 3 cognitive ability groups on the basis of their performance on a battery of classification tasks. When allowed to choose among learning centers which differed in the level of understanding of classification required, all 3 cognitive ability groups spent the most time in the centers which were just beyond their initial ability levels, and they rated these centers as most interesting and moderately difficult. In experiment 2, the children received either rewards, praise, or no rewards for working in a learning center which was either at, above, or below their predicted levels of classification interest. Rewards had little effect on intrinsic motivation among children whose motivation was initially low and decreased it among children whose motivation was initially high. Praise also had mixed effects-highly motivated children with an internal locus of control increased in intrinsic motivation following praise, while highly motivated children with an external locus of control decreased in intrinsic motivation following praise. The implications of these results for the understanding of intrinsic motivation and for educational practice were discussed.
A core component of cognitive control - the ability to regulate thoughts and actions in accordance with internally represented behavioral goals - might be its intrinsic variability. In this article, I describe the dual mechanisms of control (DMC) framework, which postulates that this variability might arise from qualitative distinctions in temporal dynamics between proactive and reactive modes of control. Proactive control reflects the sustained and anticipatory maintenance of goal-relevant information within lateral prefrontal cortex (PFC) to enable optimal cognitive performance, whereas reactive control reflects transient stimulus-driven goal reactivation that recruits lateral PFC (plus a wider brain network) based on interference demands or episodic associations. I summarize recent research that demonstrates how the DMC framework provides a coherent explanation of three sources of cognitive control variation - intra-individual, inter-individual and between-groups - in terms of proactive versus reactive control biases.
Everyday life requires frequent shifts between cognitive tasks. Research reviewed in this article probes the control processes that reconfigure mental resources for a change of task by requiring subjects to switch frequently among a small set of simple tasks. Subjects' responses are substantially slower and, usually, more error-prone immediately after a task switch. This 'switch cost' is reduced, but not eliminated, by an opportunity for preparation. It seems to result from both transient and long-term carry-over of 'task-set' activation and inhibition as well as time consumed by task-set reconfiguration processes. Neuroimaging studies of task switching have revealed extra activation in numerous brain regions when subjects prepare to change tasks and when they perform a changed task, but we cannot yet separate 'controlling' from 'controlled' regions.
The psychology of learning and motivation: Advances in research and theory
- T. O. Nelson
- L. Narens
The differentiation of the concepts of difficulty and ability
- J G Nicholls
- A T Miller
Nicholls, J. G., & Miller, A. T. (1983). The differentiation of the concepts of difficulty and ability. Child Development, 54, 951-959.
https://doi.org/10.2307/1129899