Task Goals Research Articles

Extremely virtual and incredibly physical

Abstract Digital mediation strategies are key soft skills to develop amongst students as they prepare to interact in increasingly collaborative settings, socially and professionally. Defined as a set of communication strategies deployed to reach mutual agreement over a dispute, mediation enables students’ cooperation in task-based language teaching settings. However, there is an absence of research investigating learning practices in digital social spaces that allow students to develop mediation strategies while using foreign languages to achieve group task goals. In this article, we will outline and compare the results of two case studies exploring the interaction potential of digital educational activities: Digital Storytelling and Digital Social Reading. The analysis of students’ multimodal conversations during the activities shows that while there are intrinsic interactional affordances related to the technologies (StoryMaps, izi.Travel, ThingLink, Immerse and Glose for Education) used in educational contexts, fostering students’ mediation strategies has only been feasible through a sound instructional methodology. Starting from the data analysis, pedagogical implications are drawn to help language teachers implement virtual technologies to boost students’ digital mediation strategies to act successfully in their professional and social lives. Considerations include pre-activity tech and strategy training and the integration of asynchronous and synchronous moments of reflection. Further discussion pertains to creating a community of practice collaborating to understand tool usability for attaining activity goals.

Role of the dorsolateral prefrontal cortex in processing temporal anomalies retained in working memory

IntroductionTime is a crucial abstract construct, allowing us to perceive the duration of events. Working memory (WM) plays an important role in manipulating and storing the different features of environmental stimuli, including temporal features. Different brain structures, including the dorsolateral prefrontal cortex, are involved in time processing.MethodsHere we investigated the functional aspects of time processing by using functional near-infrared spectroscopy (fNIRS) to assess changes in DLPFC activity. A modified version of the “Times Squares Sequences” (TSS) task was used, in which participants are required to match sequences of squares that have fixed or variable durations.ResultsFindings showed that the DLPFC activates when information necessary for later comparison needs to be maintained online, as is common in visuo-spatial WM tasks. Importantly, the DLPFC deactivates when a temporal anomaly is detected.DiscussionThis deactivation occurs because the temporal anomaly does not require ongoing maintenance for later comparison, thus demanding fewer cognitive resources from the DLPFC. This seemingly counterintuitive effect can be attributed to the temporal aspects being irrelevant to the primary task goals. This finding highlights the crucial role of implicit temporal interference and establishes a strong connection between timing and executive cognitive processes.

Task goals shape the relationship between decision and movement speed.

The speed at which we move is linked to the speed at which we decide to make these movements. Yet, the principles guiding such relationship remain unclear: while some studies point towards a shared invigoration process boosting decision and movement speed jointly, others rather indicate a tradeoff between both levels of control, with slower movements accompanying faster decisions. Here, we aimed (1) at further investigating the existence of a shared invigoration process linking decision and movement and (2) at testing the hypothesis that such a link is masked when detrimental to the reward rate. To this aim, we tested 62 subjects who performed the tokens task in two experiments (separate sessions): Experiment 1 evaluated how changing decision speed affects movement speed while Experiment 2 assessed how changing movement speed affects decision speed. In the latter experiment, subjects were either encouraged to favor decision speed (fast decision group) or decision accuracy (slow decision group). Various mixed model analyses revealed a coregulation of decision (urgency) and movement speed in Experiment 1 and in the fast decision group of Experiment 2, but not in the slow decision group despite the fact that these same subjects displayed a coregulation effect in Experiment 1. Altogether, our findings support the idea that coregulation occurs as a default mode but that this form of control is diminished or supplanted by a tradeoff relationship, contingent on reward rate maximization. Drawing from these behavioral observations, we propose that multiple processes contribute to shaping the speed of decisions and movements.

A Review of Pluralistic Image Completion

Abstract. Image inpainting has always been a major problem in the field of scientific research. How to fill in the damaged area of the image to make the image look realistic is the main goal of the image inpainting task. In recent years, with the rapid development of machine learning, the researchers started using machine learning to assist in image inpainting. The most representative one is image inpainting based on generative models. The classic idea of restoration is to generate a restoration result with the highest quality and the most realistic appearance. However, as long as the result is reasonable, image inpainting allows for multiple restoration results. For this reason, the field of pluralistic image completion was born. This paper introduces pluralistic image completion and reviews past research in this field. This paper divides pluralistic image completion methods into three categories: VAE-based, GAN-based, and Transformer-based, and gives examples of various representative methods and the latest research in this field. This paper also introduces the available datasets and evaluation metrics. A discussion is given based on the performance of these three categories of methods and the prospects for the development of the field of pluralistic image completion. This review can serve as a reference for researchers in the field of image inpainting. It provides a table of datasets that can be used to evaluate and compare the listed methods and looks forward to possible developments and applications in this field in the future.

Balancing Academics and Athletics: Examining Academic and Athletic Identity Profiles in a Large Sample of NCAA Division I College Athletes

College athletes balance academic and athletic roles and, as a result, can hold different combinations of academic and athletic identities. The purpose of this study was to identify common identity profiles in a large sample of Division I (elite) college athletes in the U.S. and to examine these profiles on a number of measures in academics and athletics: performance, motivation (e.g., achievement goals, autonomous motivation, competence, interest, effort, value, persistence, passion), satisfaction, and ethical conduct (e.g., cheating, plagiarism, sportspersonship, gamesmanship, aggression). Profiles were derived in Study 1 (N = 1124) and cross-validated with an independent sample in Study 2 (N = 184). Results showed four common identity profiles: (1) fully engaged college athletes with the highest academic and athletic identities, (2) committed athletes with a low academic identity and a high athletic identity, (3) academics-focused college athletes with an average academic identity and a low athletic identity, and (4) academically unengaged athletes with an extremely low academic identity and a low athletic identity. The identity profiles differed significantly across the measures of academic and athletic performance, achievement motivation (mastery, performance, task, and ego goals), satisfaction, and ethical conduct (academic misconduct, homework cheating, plagiarism, test cheating, sportspersonship, gamesmanship, instrumental aggression) in Study 1, as well as autonomous motivation (competence, relatedness, value/usefulness, effort/importance), academic persistence, and athletic passion (harmonious, obsessive) in Study 2. Taken together, findings provided evidence of both the multidimensional nature of college athletes’ identities and the heterogeneity of the college athlete population. Overall, these findings point to the importance of concurrent examination of academic and athletic identities as separate yet interrelated dimensions in research studies. This approach allows for a comprehensive understanding of college athletes' experiences and provides a more nuanced perspective on their identity development.

EXPRESS: Advancing an account of hierarchical dual-task control: A focused review on abstract higher-level task representations in dual-task situations.

Dual tasks are a common phenomenon in everyday life. In dual-task contexts, we perform two component tasks in temporal overlap, which usually results in impaired performance in one or both of these component tasks relative to single-task contexts. Numerous studies have examined dual-task interference at the level of response selection, but only few studies addressed the cognitive representation of a dual task and the cognitive mechanisms controlling these representations. The present review outlines recent empirical findings and theoretical developments concerning these two issues. In detail, the review focuses on different components of a cognitive dual-task representation, including the representation of component-task specific information (i.e., information about the goal and stimulus-response mapping of a component task), the representation of component-task order information (i.e., information about the order in which the component tasks have to executed), and the representation of dual-task identity information (i.e., information about which two component tasks have to be performed). A particular emphasis is placed on the cognitive representation of dual-task identity information, which is examined in a recent research line employing the task-pair switching logic as an empirical approach. By conceptualizing a dual-task representation as a hierarchical multi-component representation, the review integrates the research line on the cognitive representation of dual-task identity information with those on the representation of component-task specific information and of component-task order information. Based on this conceptualization, the review provides a new theoretical contribution to dual-task research and highlights an integrative perspective on the different components of cognitive dual-task representations.

Interactive Segmentation for Medical Images Using Spatial Modeling Mamba

Interactive segmentation methods utilize user-provided positive and negative clicks to guide the model in accurately segmenting target objects. Compared to fully automatic medical image segmentation, these methods can achieve higher segmentation accuracy with limited image data, demonstrating significant potential in clinical applications. Typically, for each new click provided by the user, conventional interactive segmentation methods reprocess the entire network by re-inputting the click into the segmentation model, which greatly increases the user’s interaction burden and deviates from the intended goal of interactive segmentation tasks. To address this issue, we propose an efficient segmentation network, ESM-Net, for interactive medical image segmentation. It obtains high-quality segmentation masks based on the user’s initial clicks, reducing the complexity of subsequent refinement steps. Recent studies have demonstrated the strong performance of the Mamba model in various vision tasks; however, its application in interactive segmentation remains unexplored. In our study, we incorporate the Mamba module into our framework for the first time and enhance its spatial representation capabilities by developing a Spatial Augmented Convolution (SAC) module. These components are combined as the fundamental building blocks of our network. Furthermore, we designed a novel and efficient segmentation head to fuse multi-scale features extracted from the encoder, optimizing the generation of the predicted segmentation masks. Through comprehensive experiments, our method achieved state-of-the-art performance on three medical image datasets. Specifically, we achieved 1.43 NoC@90 on the Kvasir-SEG dataset, 1.57 NoC@90 on the CVC-ClinicDB polyp segmentation dataset, and 1.03 NoC@90 on the ADAM retinal disk segmentation dataset. The assessments on these three medical image datasets highlight the effectiveness of our approach in interactive medical image segmentation.

Non-invasive brain-machine interface control with artificial intelligence copilots.

Motor brain-machine interfaces (BMIs) decode neural signals to help people with paralysis move and communicate. Even with important advances in the last two decades, BMIs face key obstacles to clinical viability. Invasive BMIs achieve proficient cursor and robotic arm control but require neurosurgery, posing significant risk to patients. Non-invasive BMIs do not have neurosurgical risk, but achieve lower performance, sometimes being prohibitively frustrating to use and preventing widespread adoption. We take a step toward breaking this performance-risk tradeoff by building performant non-invasive BMIs. The critical limitation that bounds decoder performance in non-invasive BMIs is their poor neural signal-to-noise ratio. To overcome this, we contribute (1) a novel EEG decoding approach and (2) artificial intelligence (AI) copilots that infer task goals and aid action completion. We demonstrate that with this "AI-BMI," in tandem with a new adaptive decoding approach using a convolutional neural network (CNN) and ReFIT-like Kalman filter (KF), healthy users and a paralyzed participant can autonomously and proficiently control computer cursors and robotic arms. Using an AI copilot improves goal acquisition speed by up to 4.3 × in the standard center-out 8 cursor control task and enables users to control a robotic arm to perform the sequential pick-and-place task, moving 4 randomly placed blocks to 4 randomly chosen locations. As AI copilots improve, this approach may result in clinically viable non-invasive AI-BMIs.

Effects of Constraining Postural Sway During Upper-Limb Precision Aiming Task Practice in Individuals with Stroke

Individuals post-stroke commonly demonstrate alterations in motor behavior with regard to both task performance and the motor strategies used in pursuit of task goals. We evaluated whether constraining postural sway (motor strategy) during practice would affect upper-limb precision aiming performance (task performance) and postural control adaptations. Adults with stroke stood on a force plate while immersed in a virtual scene displaying an anterior target. Participants aimed to position a virtual laser pointer (via handheld device) in the target. Participants then completed practice trials involving aiming at a lateral target. For this practice session, participants were randomized to either (a) a “constraint” group wherein they received physical constraint to limit postural sway, or (b) a “no-constraint” group. Task performance and postural control were assessed before and after practice, and transfer to another upper-limb task was evaluated. After practice, both groups improved paretic upper-limb performance. For the target task, the no-constraint group showed task-sensitive changes in postural control. The constraint group showed no changes in postural control. At transfer, the constraint group increased postural sway. Constraining postural sway after stroke should be carefully considered with the recognition that postural sway arises from exploratory movements involved in the discovery of adaptable motor solutions.

Differences in motivational dynamics between experienced cyclists and untrained participants during an incremental endurance exercise task

PurposeThe conflict between the desire to reduce effort during exercise and the performance goal of the exercise task contributes to explaining endurance exercise performance. However, whether the trajectories of these two motivational responses systematically differ across individuals with different characteristics is poorly understood. The present study examined whether changes in desire to reduce effort and performance goal value across moderate, heavy, and severe exercise intensity domains differed between cyclists and untrained, but active participants. MethodsFifty participants (14 cyclists and 36 untrained) completed an incremental step test on a cycle ergometer, in which work rate was increased by 25 W every 4 min until voluntary exhaustion. Desire to reduce effort, performance goal value, and blood lactate concentration (for determination of exercise intensity domains) were measured every 4 min and the data were analysed using multilevel modelling. ResultsDesire to reduce effort increased quicker for untrained participants in the moderate exercise intensity domain (b = 1.66, p < .001) and across the whole trial (b = 1.64, p < .001), compared to cyclists (b = .69, and b = 1.14, respectively, both p < .001). Untrained participants reported similar performance goal value at the beginning of the trial (b = 16.02, p < .001), compared to cyclists (b = 17.25, p < .001). Beyond moderate intensities, the performance goal value decreased significantly for the untrained participants (b = −.70, p < .001) but significantly increased for cyclists (b = .45, p = .01). This pattern was also observed when focusing solely on the severe intensity domain (cyclists: b = .90, p < .001; untrained: b = −.84, p < .001). ConclusionThere are distinct differences in the desire to reduce effort and performance goal value between cyclists and untrained athletes. Identifying these systematic differences enhances the credibility of the desire-goal conflict framework in explaining endurance performance and provides insight into the type and timing of interventions that might be successful in improving performance.

Anticipating multisensory environments: Evidence for a supra-modal predictive system

Our perceptual experience is generally framed in multisensory environments abundant in predictive information. Previous research on statistical learning has shown that humans can learn regularities in different sensory modalities in parallel, but it has not yet determined whether multisensory predictions are generated through a modality-specific predictive mechanism or instead, rely on a supra-modal predictive system. Here, across two experiments, we tested these hypotheses by presenting participants with concurrent pairs of predictable auditory and visual low-level stimuli (i.e., tones and gratings). In different experimental blocks, participants had to attend the stimuli in one modality while ignoring stimuli from the other sensory modality (distractors), and perform a perceptual discrimination task on the second stimulus of the attended modality (targets). Orthogonal to the task goal, both the attended and unattended pairs followed transitional probabilities, so targets and distractors could be expected or unexpected. We found that participants performed better for expected compared to unexpected targets. This effect generalized to the distractors but only when relevant targets were expected. Such interactive effects suggest that predictions may be gated by a supra-modal system with shared resources across sensory modalities that are distributed according to their respective behavioural relevance.

The influence of categorical stimuli on relational memory binding.

Binding of arbitrary information into distinct memory representations that can be used to guide behavior is a hallmark of relational memory. What is and is not bound into a memory representation and how those things influence the organization of that representation remain topics of interest. While some information is intentionally and effortfully bound-often the information that is consistent with task goals or expectations about what information may be required later-other information appears to be bound automatically. The present set of experiments sought to investigate whether spatial memory would be systematically influenced by the presence and absence of distinct categories of stimuli on a spatial reconstruction task. In this task, participants must learn multiple item-location bindings and place each item back in its studied location after a short delay. Across three experiments, participants made significantly more within-category errors (i.e., misassigning one item to the location of a different item from the same category) than between-category errors (i.e., misassigning one item to the location of an item from a different category) when categories were perceptually or semantically distinct. These data reveal that category information contributed to the organization of the memory representation and influenced spatial reconstruction performance. Together, these results suggest that categorical information can influence memory organization, and not always to the benefit of overall task performance.

RAF-Unet: A Remote Sensing Identification Method for Forest Land Information with Modified Unet

Abstract Carrying out remote sensing refinement identification of forest land in complex environment is of great significance for timely mapping of forest distribution. Aiming at the problem that remote sensing images have bias in the extraction of forest land information data, based on the semantic segmentation algorithm Unet, combining the ResNet50 deep learning network, the attention mechanism module and the feature pyramid structure, we construct RAF-Unet (ResNet+Attention+FPN+Unet) to improve the extraction of forest land information data. The ResNet50 classification network is used as the encoder of the Unet network to extract the feature maps at five different scales; then, the attention mechanism module is introduced in the decoder stage of the Unet network to extract the key task goal information by learning the weight values of the features; finally, the feature pyramid structure is used in the output stage of the encoder to fuse the information from the shallow network and the deep network to extract the remote sensing forest land information in the image. The results show that the RAF-Unet algorithm outperforms the Unet algorithm in all the indexes, with a precision of 95.24%, a recall of 91.80%, an F1-score value of 93.49%, an intersection over union of 87.63%, and an accuracy of 93.68%; the validity of the modules is verified by the ablation experiments, and the ResNet network, the attention mechanism, and the feature pyramid structure are all effective in improve the classification effect. It helps the forestry department to better manage and dynamically monitor forestry information, which is of great significance to the scientific development, utilization and protection of forest land resources.

Mapping cognitive activity from electrocorticography field potentials in humans performing NBack task

Objective. Advancements in data science and assistive technologies have made invasive brain-computer interfaces (iBCIs) increasingly viable for enhancing the quality of life in physically disabled individuals. Intracortical microelectrode implants are a common choice for such a communication system due to their fine temporal and spatial resolution. The small size of these implants makes the implantation plan critical for the successful exfiltration of information, particularly when targeting representations of task goals that lack robust anatomical correlates. Approach. Working memory processes including encoding, retrieval, and maintenance are observed in many areas of the brain. Using human electrocorticography (ECoG) recordings during a working memory experiment, we provide proof that it is possible to localize cognitive activity associated with the task and to identify key locations involved with executive memory functions. Results. From the analysis, we could propose an optimal iBCI implant location with the desired features. The general approach is not limited to working memory but could also be used to map other goal-encoding factors such as movement intentions, decision-making, and visual-spatial attention. Significance. Deciphering the intended action of a BCI user is a complex challenge that involves the extraction and integration of cognitive factors such as movement planning, working memory, visual-spatial attention, and the decision state. Examining field potentials from ECoG electrodes while participants engaged in tailored cognitive tasks can pinpoint location with valuable information related to anticipated actions. This manuscript demonstrates the feasibility of identifying electrodes involved in cognitive activity related to working memory during user engagement in the NBack task. Devoting time in meticulous preparation to identify the optimal brain regions for BCI implant locations will increase the likelihood of rich signal outcomes, thereby improving the overall BCI user experience.

Prior coordination solutions shape motor learning and transfer in redundant tasks

Motor learning does not occur on a ‘blank slate’, but in the context of prior coordination solutions. The role of prior coordination solutions is likely critical in redundant tasks where there are multiple solutions to achieve the task goal – yet their influence on subsequent learning is currently not well understood. Here we addressed this issue by having human participants learn a redundant virtual shuffleboard task, where they held a bimanual manipulandum and made a discrete throwing motion to slide a virtual puck towards a target. The task was redundant because the distance traveled by the puck was determined by the sum of the left- and right-hand speeds at the time of release. On the first day, 37 participants in different groups practiced symmetric or asymmetric solutions. On the second day, all participants transferred to a common criterion task, which required an asymmetric solution. Results showed that: (i) the symmetry of the practiced solution affected motor variability during practice, with more asymmetric solutions showing higher exploration of the null space, (ii) when transferring to the common criterion task, participants in the symmetric group showed much higher null space exploration, and (iii) when no constraints were placed on the solution, participants tended to return to the symmetric solution regardless of the solution originally practiced. Overall, these results suggest that the stability of prior coordination solutions plays an important role in shaping learning in redundant motor tasks.

Dogs with prior experience of a task still overimitate their caregiver

Domestic dogs have been shown to copy their caregiver’s actions, including ones which are causally-irrelevant to a physical goal—a behaviour called “overimitation”. In a new overimitation task with a non-food reward, this study investigated “causal misunderstanding”—falsely assuming causally-irrelevant actions to have functional relevancy—as an explanation for dog overimitation (N = 81). By providing dogs with prior experience of the task to learn about the consequences of its irrelevant box-stepping and relevant bucket-opening action to obtain a toy-ball, we tested whether and when dogs would copy their caregiver’s irrelevant-action demonstrations. Dogs with and without prior experience were compared to a third (control) group of dogs, who had neither prior experience nor caregiver demonstrations of the task. Results revealed that the timing of overimitation, rather than its frequency, was closely related to dogs' prior experience: dogs with prior experience attended to their reward first, then interacted with the irrelevant box later (“post-goal overimitation”), while dogs without prior experience first interacted with the irrelevant box (“pre-goal overimitation”). Our results suggest that, when action consequences are understood, dogs are overimitating for a secondary social goal that is clearly distinct from the task goal of obtaining a physical reward.

A Review of Prospective Managers Towards Career Management with Self-Efficacy and Proactive Behavior

This paper review to discuss self-effort efficacy and proactive behavior regarding the materialisation of career management among prospective managers. Career management implies that there is a definite direction to the career goals and purposes based on the analysis of strengths, preferences, and interests. Academic self-efficacy, or students’ perception of their abilities, can be considered a key factor in respect to task approach, goal striving and accomplishment in academic domains. Self efficacy on the other hand involves high levels of initiate behaviors, being obligated to the goals that have been set, and remaining determined with challenges that may come along the way. Employing the self-efficacy and proactive behaviour constructs of the future managers, this research aims at establishing their career management behaviour patterns. Such implications highlight the importance of self-efficacy as an element helping to boost creativity and resulting in the advancement of career management. they were able to develop a confident sense of their creative potential, it will help them in their professional careers. The study also takes into account the environmental influences affecting career management such as learning needs and the event risks for example training.

The effect of performance contingent reward prospects flexibly adapts to more versus less specific task goals.

In some situations, for example, when we expect to gain a reward in case of good performance, goal-driven top-down attention is particularly strong. Little is known about the task specificity of such increases of top-down attention due to environmental factors. To understand to what extent performance-contingent reward prospects can result in specific and unspecific changes in cognitive processing, we here investigate reward effects under different levels of task specification. Thirty-two participants performed a visual or an auditory discrimination task cued by two consecutive visual stimuli: First, a reward cue indicated if good performance was rewarded. Second, a task cue announced either which of the two tasks would follow (precise cue) or that both tasks would follow equally likely (imprecise cue). Reward and task cue preciseness both significantly improved performance. Moreover, the response time difference between precisely and imprecisely cued trials was significantly stronger in rewarded than in unrewarded trials. These effects were reflected in event-related potential (ERP) slow wave amplitudes: Reward and preciseness both significantly enhanced the contingent negative variation (CNV) prior to the task stimulus. In an early CNV time interval, both factors also showed an interaction. A negative slow wave prior to the task cue was also significantly enhanced for rewarded trials. This effect correlated with the reward difference in response times. These results indicate that reward prospects trigger task-specific changes in preparatory top-down attention which can flexibly adapt over time and across different task requirements. This highlights that a reward-induced increase of cognitive control can occur on different specificity levels.

Attention to event segmentation improves memory in young adults: A lifespan study.

People spontaneously segment an observed everyday activity into discrete, meaningful events, but segmentation can be modified by task goals. Asking young adults to attend to event segmentation while watching movies of everyday actions improved their memory up to 1 month later (Flores et al., 2017). Does attending to event segmentation improve memory across the lifespan? Participants between the ages of 20 and 79 watched movies of actors performing everyday activities while intentionally encoding them for a recall and a recognition memory test 1 week (Experiment 1) or 1 month (Experiment 2) later. In addition to intentionally encoding the movies, half of the participants segmented the movies into fine-grained events. Young adults who segmented recalled more words in their recall responses than those who intentionally encoded 1 week and 1 month later. Middle-aged adults benefited from the intervention after a 1-week delay but not after a 1-month delay. Older adults over the age of 70 did not benefit from attending to segmentation. Of those who segmented, young and older adults showed similar agreement about the locations of event boundaries. Together, the results suggest that older adults are less able, compared to young adults, to maintain or retrieve well-encoded event memories after a delay. In addition, individual differences in segmentation agreement predicted memory up to 1 month later, regardless of age. These results suggest a practical and easy-to-implement intervention for improving recall of everyday events in young and middle-aged adults that is ineffective in older adults. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Pacing Behavior Development: The Role of Task Experience and the Presence of Competitors.

Self-regulation of effort during exercise (i.e. pacing) is a determinant of exercise performance, which develops during childhood and adolescence. Yet, the various aspects of pacing under development, such as the capability to use task experience and retain the task goal in the presence of other competitors, have remained relatively unexplored. 9 adolescents (14.9 ± 2.1 years old) and 14 adults (24.2 ± 3.2 years old) completed four 4-km cycling trials in a well-controlled laboratory setting. After one familiarization visit, trials were performed in random order: alone, with the goal to finish the trial as fast as possible (AloneTime), with a competitor and the same goal (CompTime), or with a competitor and the goal to finish first (CompFirst). Within each age group, repeated measurement ANOVAs (p < 0.05) examined the differences in the estimated task duration, pacing behavior (distribution of mean power output per 500 m) and performance (finish time) between visits (4) or conditions (3). In contrast to adults (p < 0.05, η2p > 0.20), adolescents did not exhibit a change in estimation of task duration, pacing behavior or performance over repeated visits (p > 0.05, η2p < 0.10). Adolescents altered their pacing behavior in the presence of a competitor independent of the task goal (CompTime & CompFirst), whereas adults only demonstrated this alteration when instructed to finish first (CompFirst). Adolescents are still developing the capability to 1) use experience from previous tasks to adjust their pacing behavior, and 2) inhibit the intuitive action of engaging with the competitor to retain the more abstract task goal of finishing the trial as fast as possible. These findings establish novel experimental evidence for the underpinnings of pacing behavior development.