Learner–Learner Interaction During Collaborative Pragmatic Tasks: The Role of Cognitive and Pragmatic Task Demands

This paper addresses a significant challenge in achieving collaborative tasks; how can a robot or multiple robots, endowed with a library of pre-learned primitive movements, generate multiple simultaneous coordinated robotic movements, adapting and optimizing those in the library, to complete one collaborative task? This work can thus be seen as a follow-up to the work with a motion presented as dynamic movement primitive (DMP) that now considers collaborative tasks and the existence of multiple robots/manipulators. Specifically, we start with a simple task using one DMP and extend it to accommodate the coordinated execution of multiple DMPs in robots with multiple manipulators or-alternatively-multiple robots with a single manipulator. We investigate mechanisms to jointly optimize multiple DMPs to perform one task in a coordinated fashion. The joint trajectory is built from initial DMPs learned for a single manipulator, and its optimization must comply with task-specific constraints. We illustrate the application of our approach both in a simulated environment and in a simulated and real Baxter robot.

Objective: A set of 4 driving related tasks were used to evaluate the potential for a modified Detection Response Task (DRT) to simultaneously measure visual and cognitive task demands. Background: The accurate assessment of cognitive and visual tasks demands in driving has become increasingly important. As of yet, no simple, cost effective approach has been found to measure visual demands in complex, multimodal tasks. Methods: Two experiments are presented which evaluate an extension of the standard DRT methodology. The discriminate sensitivity of the experiments is tested using an integrated testing configuration, which systematically increased visual demand across four conditions. Results: Results suggest that the standard DRT configurations are highly tuned to selectively evaluate cognitive demand but that a variant of the system may be able to simultaneously evaluate changes in both visual and cognitive task demands. Conclusions: These data suggest that the simple, rapid, and reliable assessment of both visual and cognitive task demands is possible, even in highly fluid systems with non-constant visual task requirements.

This study was an attempt to investigate the effects of three different task types, that is dictation task, individual reconstruction task, and collaborative reconstruction task on EFL learners' acquisition of two grammatical structures, gerunds and infinitives. These tasks were also accompanied by either explicit or implicit instructions to see whether explicit or implicit instruction was effective and useful in the final achievement of grammatical structures. 40 low-intermediate male High School learners of English in Lordegan, Iran, were selected as the participants of this study. A timed Grammaticality Judgment Test (GJT) was used for data collection. In order to compare the three groups under the study, both descriptive and inferential statistics were employed. To compare the means, one-way ANOVAs as well as t-test were used. The results of statistical analysis supported this hypothesis that significant differences existed in the performance of three groups of participants when they completed the treatments including dictation, individual reconstruction and collaborative reconstruction. The students who completed the collaborative reconstruction task outperformed the other two groups who completed the dictation task and individual reconstruction task. In addition, dictation group outperformed the individual reconstruction group. Moreover, the difference between explicit and implicit groups was significant. In addition, the explicit group outperformed the implicit group after receiving the special instructions. In other words, the explicit group performed better than the implicit group in acquisition of grammatical structures.

Unmanned underwater vehicles perform inspection and maintenance tasks in complex and changing environments. Some of these tasks require synchronous navigation of multiple vehicles, which is challenging. This paper proposes a synchronous navigation scheme for two BlueROV2 underwater vehicles for a coordinated multi-vehicle task. In the proposed scheme, the vehicles perform the collaborative task of grasping, transporting, and releasing an object. In this scheme, no vehicle-to-vehicle communication is required. A model-free second-order sliding mode controller with finite-time convergence is used to accomplish this task. The controller's convergence time is user-defined and does not depend on the physical or hydrodynamic parameters of the vehicle, unlike the other finite-time controllers found in the literature. Simulation experiments were conducted to verify the controller's performance, including high ocean currents as external disturbances. Comparisons were made with two state-of-the-art controllers with finite-time convergence. The results showed that the proposed controller achieved the best results, as the user-defined convergence time was achieved for both vehicles and the collaborative task was completed, no ripples, deviations, or oscillations were observed, and no chattering occurred. The results proved the robustness of the controller in the presence of high ocean currents without the need to readjust the parameters.

Cognitive control supports flexible behavior adapted to meet current goals and can be modeled through investigation of saccade tasks with varying cognitive demands. Basic prosaccades (rapid glances toward a newly appearing stimulus) are supported by neural circuitry, including occipital and posterior parietal cortex, frontal and supplementary eye fields, and basal ganglia. These trials can be contrasted with complex antisaccades (glances toward the mirror image location of a stimulus), which are characterized by greater functional magnetic resonance imaging (MRI) blood oxygenation level-dependent (BOLD) signal in the aforementioned regions and recruitment of additional regions such as dorsolateral prefrontal cortex. The current study manipulated the cognitive demands of these saccade tasks by presenting three rapid event-related runs of mixed saccades with a varying probability of antisaccade vs. prosaccade trials (25, 50, or 75%). Behavioral results showed an effect of trial-type probability on reaction time, with slower responses in runs with a high antisaccade probability. Imaging results exhibited an effect of probability in bilateral pre- and postcentral gyrus, bilateral superior temporal gyrus, and medial frontal gyrus. Additionally, the interaction between saccade trial type and probability revealed a strong probability effect for prosaccade trials, showing a linear increase in activation parallel to antisaccade probability in bilateral temporal/occipital, posterior parietal, medial frontal, and lateral prefrontal cortex. In contrast, antisaccade trials showed elevated activation across all runs. Overall, this study demonstrated that improbable performance of a typically simple prosaccade task led to augmented BOLD signal to support changing cognitive control demands, resulting in activation levels similar to the more complex antisaccade task.

Integration of computers into Foreign Language (fl) learning has become the allbut-inevitable direction for the future, given the (a) considerable benefits this affords for students of English as a Foreign Language (efl), (b) characteristics of today’s learners as Generation Z (González-Lloret & Ortega, 2014), and (c) widespread use of the internet in the twenty-first century. This situation has spurred a transformation of ComputerAssisted Language Learning (call) into Web-Facilitated Language Learning (wfll) as an alternative paradigm for efl teachers and learners. Furthermore, Task-Based Language Teaching (tblt) is likely to serve as a pedagogical framework in designing the web for the purpose of fl learning. The primary objectives of the present study were therefore to (a) develop a teacher-designed learning website, namely I Love Indonesia, and (b) gather information from high school learners of English in Indonesia with different attitudes towards call (positive/moderate/negative) in correlation with how they perceive wfll (agree/disagree) and perform web-based activities. Descriptive Statistics, if Function in Excel, Correlation Analysis, and Independent-samples T-test were employed in the study. Finally, the study findings demonstrate that (a) the majority of learners participating in the study have positive attitudes towards call, (b) all focused participants have positive perceptions of wfll and (c) learners with positive attitudes are likely to have more positive perceptions (to agree) than moderate and negative attitude learners (ones who disagree) on the use of the website for language learning. In addition, the website seems to benefit efl learners in some specific areas. Consideration should be given to working with 158 The jalt call Journal 2018: Regular Papers a greater number of learners over a longer period of time when conducting further studies on the effectiveness of the website for efl learners in order to be able to shed some light on the development of their language skills.

This study examined the complex relationships among task complexity, task-specific emotions, and learners' L2 writing performance. Sixty-one Chinese EFL learners were divided into two groups and completed two writing tasks in a counterbalanced order. They reported their perceptions about task complexity and their emotional experience during the task after completing each task. The results revealed that (1) task complexity exerted a significant negative effect on learners' writing performance in terms of content, but no significant effects on language use, organization and communicative achievement, or overall writing performance; (2) task complexity did not significantly affect learners' task enjoyment, task anxiety or task boredom; (3) task-specific emotions did not predict learners' overall writing performance in the simple task, while task anxiety exerted a significant negative effect on learners' performance in the complex task. These results are discussed with reference to the Cognition Hypothesis and the Control-Value Theory, particularly the intensified role of affect under increased cognitive demands and the negative impact of task anxiety on writing performance, offering pedagogical implications for L2 writing.

This study used a dual task design to investigate the effects of two different types of cognitive tasks on stability (as measured by center of pressure displacement) in young vs older adults with and without a history of falls. Two secondary cognitive tasks, a sentence completion and a visual perceptual matching task, were used to produce changes in attention during quiet stance under flat vs compliant surface conditions in 20 healthy young adults, 20 healthy older adults, and 20 older adults with a history of imbalance and falls. Postural stability was quantified using forceplate measures of center of pressure (COP). Speed and accuracy of verbal response on the cognitive tasks were also quantified. During the simultaneous performance of a cognitive and postural task, decrements in performance were found in the postural stability measures rather than the cognitive measures for all three groups. While no differences were found between the young adults and the older healthy adults on the firm surface, no task condition, when task complexity was increased (either through the introduction of a secondary cognitive task, or a more challenging postural condition such as standing on the compliant surface), significant differences in postural stability between the two groups became apparent. In contrast to the young and healthy older adults, postural stability in older adults with a history of falls was significantly affected by both cognitive tasks. Results suggest that when postural stability is impaired, even relatively simple cognitive tasks can further impact balance. Results further suggest that the allocation of attention during the performance of concurrent tasks is complex; depending on many factors including the nature of both the cognitive and postural task, the goal of the subject and the instructions.

Event Abstract Back to Event Demonstrating brain-level interactions between working memory load and driving demand level using fNIRS Jochem W. Rieger1*, Jakob Scheunemann1, Klas Ihme2, Frank Köster2, Meike Jipp2 and Anirudh Unni1 1 University of Oldenburg, Department of Psychology, Germany 2 Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institute of Transportation Systems, Germany Introduction and Goal The concept of mental workload is of particular importance in human factors and neuroergonomics because mental workload levels that saturate processing capacities will likely decrease performance and cognitive flexibility. Driving, like many other dynamic control tasks, concurrently imposes demands on multiple cognitive resources. In order to assess driver’s cognitive capacity utilization, we need to distinguish loads imposed on different cognitive resources and to characterize their interactions. It is currently not clearly understood how different cognitive task demands interact at the brain level and whether the neuronal markers that have been attributed to certain cognitive resources remain discriminative and predictive of cognitive states when humans operate in complex natural task environments such as driving. Hence, our goal is to investigate how changes in cognitive task demands related to increased lateral control in driving, a visuospatial control task, interacts with working memory load (WML) at the brain level and to predict the driving demand level from multichannel functional near infrared spectroscopy (fNIRS) deoxyhemoglobin (HbR) brain activation measurements. Methods We collected data from participants driving on a highway with moderate concurrent traffic and low or high levels of lateral control demands (driving outside and within construction sites with a narrower lane width) in the realistic Virtual-Reality lab at DLR, Braunschweig (Fischer et al., 2014). In order to manipulate WML levels, participants (n=15) performed an integrated speed regulation task in which they had to remember sequences of speed of varying length. The task resembles a number span task and required the adjustment of the speed when a new speed sign occurred but according to the sign shown n-signs back and to remember the new sign. We introduced five different WML levels (i.e. 0-back to 4-back) and new speed signs appeared every 20 seconds (for details see Unni et al. 2017). We recorded almost whole head fNIRS measurements at a rate close to 2Hz using two 16-channel NIRScout systems (NIRx Medizintechnik GmbH, Germany) during the 60 minutes of the experiment. We then used all fNIRS channels in a multivariate logistic ridge regression classifier with a 5-fold cross-validation for temporally resolved prediction of driving demand level (i.e. whether they drove within or outside the construction site). To gain insights into specific brain areas associated with driving demand level, we performed a univariate group-level analysis where we calculated the prediction model weights from a 5-fold cross-validated univariate logistic ridge regression of channel-wise fNIRS HbR separately for each WML level. Results On average over participants, we correctly predicted the driving demand (lateral control) level in 74.88% of the timepoints in an out-of-sample cross-validation of classifiers trained on the fNIRS data separately for each WML level. Mean accuracy scores significantly varied across WML levels (range 62% to 85% correct; F(4,70) = 7.32, p < .001) with better predictions for intermediate WML levels (1-back to 3-back). Training one classifier on fNIRS data across all WML levels severely degraded prediction performance (mean accuracy of 46%). These results indicate that cognitive resources recruited by lateral lane control, a visuospatial control task, interact with resources recruited by working memory at the brain level. In order to better understand the nature of these interactions, we analyzed how predictivity of brain regions for driving demands develops over WML levels. Figure 1B depicts group-level brain maps of classification separability from the univariate logistic ridge regression model. Activation changes in the parietal and lateral dorsal frontal areas allow for prediction of increased lateral control demand. The frontal areas (putative BA9/46/10) are known to be involved in tactical planning and execution of behavior and the parietal in visuomotor control. The maps show increasing predictivity of these areas with increasing WML levels up to WML-level 2. At WML level 3 and in particular level 4, the discriminative patterns diminish, indicating an interaction between WML and driving demands. We compared these brain maps to the results from Unni et al. 2017, who showed that it was possible to predict WML independent of lateral controls demands from the fNIRS data (average correlation between predicted and induced WML r = 0.61). Figure 1A shows brain areas that predict WML over different lateral control demand levels. In particular, the inferior frontal gyrus (IFG) and the temporo-occipital areas are predictive to the current WML level. The comparison of the anatomical locations of predictive maxima in Figures 1A (marked by white shapes) and 1B suggests only partial overlap between the brain resources predictive of the different task demands. Discussion We demonstrated fNIRS brain level indicators for interaction between WML and driving complexity. The prediction of driving demands from fNIRS data was possible for each WML level separately but dropped to guessing level when we tried to predict driving demands across WML levels. Conversely, we demonstrated the continuous time-resolved predictions of WML over different levels of driving demands in an earlier analysis performed on the same data (Unni et al. 2017). These results indicate an asymmetric pattern of interaction between tasks at the brain level. Moreover, despite the functional interaction, the predictive brain activation patterns show little overlap between the resources predictive for the different tasks. Interpreted in the framework of a multi-resource theory (Wickens, 2002), our brain recordings indicate that working memory and visuomotor coordination in vehicle control recruit different resources and more so with increasing task demand. Moreover, the two tasks appear to interact at a common, task unspecific cognitive resource at the brain level. The changing pattern of driving demand related brain areas across WML levels could indicate potential changes in the multitasking strategy with high levels of WML demand. Figure Caption Figure 1. (A) Weighted averaged group-level univariate correlation HbR brain maps showing brain areas sensitive to changes in WML independent of driving complexity. White shapes mark WML prediction maxima in all maps. (B) Weighted mean of channel-wise predictivity (Tjur R-squared coefficients) for driving demands at the different WML levels. Data for the two analyses were recorded in the same session with concurrent manipulation of WML and lateral control demands. Figure 1 Acknowledgements This work was funded by a grant of the Volkswagen Foundations to the Center for Critical Systems Engineering, a DFG-grant RI1511/2-1 to JWR, and KO 1990/5-1 to FK. References Fischer, M., Richter, A., Schindler, J., Plättner, J., Temme, G., Kelsch, J., & et al. (2014). Modular and Scalable Driving Simulator Hardware and Software for the Development of Future Driver Assistence and Automation Systems. In New Developments in Driving Simulation Design and Experiments: Driving Simulation Conference 2014. Paris, France. Retrieved from http://elib.dlr.de/90638/ Unni, A., Ihme, K., Jipp, M., & Rieger, J. W. (2017). Assessing the driver’s current level of working memory load with high density functional near-infrared spectroscopy: A realistic driving simulator study. Frontiers in Human Neuroscience, 11. https://doi.org/10.3389/fnhum.2017.00167 Wickens, C. D. (2002). Multiple resources and performance prediction, 3(2), 159–177. https://doi.org/10.1080/14639220210123806 Keywords: fNIRS, driving simulator, driving demands, lateral control demands, working memory, visuospatial attention, visuomotor control, Working memory load, Task interaction, task interaction at brain level, parietal cortex, inferior frontal cortex, occitpito temporal cortex Conference: 2nd International Neuroergonomics Conference, Philadelphia, PA, United States, 27 Jun - 29 Jun, 2018. Presentation Type: Oral Presentation Topic: Neuroergonomics Citation: Rieger JW, Scheunemann J, Ihme K, Köster F, Jipp M and Unni A (2019). Demonstrating brain-level interactions between working memory load and driving demand level using fNIRS. Conference Abstract: 2nd International Neuroergonomics Conference. doi: 10.3389/conf.fnhum.2018.227.00141 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 27 Mar 2018; Published Online: 27 Sep 2019. * Correspondence: Prof. Jochem W Rieger, University of Oldenburg, Department of Psychology, Oldenburg, Lower Saxony, 26111, Germany, jochem.rieger@uni-oldenburg.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Jochem W Rieger Jakob Scheunemann Klas Ihme Frank Köster Meike Jipp Anirudh Unni Google Jochem W Rieger Jakob Scheunemann Klas Ihme Frank Köster Meike Jipp Anirudh Unni Google Scholar Jochem W Rieger Jakob Scheunemann Klas Ihme Frank Köster Meike Jipp Anirudh Unni PubMed Jochem W Rieger Jakob Scheunemann Klas Ihme Frank Köster Meike Jipp Anirudh Unni Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Cilj ovog istraživanja bio je utvrditi kako stres utječe na obavljanje kognitivnih zadataka različitezahtjevnosti. U istraživanju su korištena tri kognitivna zadatka: zadatak pamćenja na raziniprepoznavanja, zadatak pamćenja na razini dosjećanja i problemski zadatak. Pretpostavljenoje da učinak stresa neće biti jednak na svim razinama zahtjevnosti zadatka, već da će doći dointerakcijskog djelovanja ovih dvaju faktora i to na način da će stres imati negativno djelovanjekod najzahtjevnijeg i ujedno kompleksnijeg zadataka (problemski zadatak), a pozitivno kodnajmanje zahtjevnog zadatka (pamćenje na razini prepoznavanja).U istraživanju je sudjelovalo ukupno 59 ispitanika, studenata Sveučilišta u Zadru čija je prosječnadob iznosila 20,75 godina. Sudionici su podijeljeni u tri grupe, pri čemu je svaka grupa obavljalajednu vrstu zadatka i to u dva navrata, jedan put u uvjetima sa, a drugi put u uvjetima bez stresa.Stres je izazivan prikazivanjem 20-minutnog isječka ratnog filma. Za svaki zadatak su postojaledvije paralelne forme (za svaku eksperimentalnu situaciju po jedna), a svaki sudionik je dolaziodva puta na ispitivanje, s razmakom od oko tjedan dana.Rezultati istraživanja pokazuju da kada je riječ o kognitivno najmanje zahtjevnom zadatku,pamćenju na razini prepoznavanja, izloženost stresu je dovela do poboljšanja učinka, nemaefekta stresa kada je riječ o srednje zahtjevnom zadatku (dosjećanje), dok kod problemskihzadataka, koji su s obzirom na kognitivne zahtjeve najkompleksniji i najzahtjevniji stres imanegativan utjecaj na učinak. Dakle, može se reći da na pitanje kakav je utjecaj stresa na učinaku kognitivnim zadacima nema jednoznačnog odgovora, već njegov utjecaj ovisi o zahtjevnostisamog zadatka.

This study takes 36 Chinese foreign language learners as the research subjects, and examines the influence of task complexity on their interactive discourse behavior (brief feedback, collaborative contribution, cooperative co-construction) and engagement (cognitive engagement, affective engagement, social engagement) in L2 peer collaborative writing. The findings indicate that: (i)Task complexity significantly affects brief feedback and collaborative contribution, but not cooperative co-construction. Specifically, the simple task obviously generates more brief feedback and collaborative contribution; (ii) Task complexity significantly affects learners’ cognitive and affective engagement, but not social engagement. Specifically, learners obviously demonstrated higher cognitive and affective engagement in the simple task. This study demonstrated the impact of task complexity on L2 peer interaction performance in the process of cooperative writing from both macro and micro levels, with the aim of providing insights for the practice and research of foreign language interactive teaching.

High school English learners often face intense Foreign Language Anxiety (FLA) due to examination pressures. This paper presents the design and implementation of ‘EngEERs’ (English Educational Escape Rooms), an innovative pedagogical framework that employs a ‘narrative-driven game loop’ to mitigate FLA. The intervention integrates immersion, collaborative puzzle-solving, and a failure-tolerant structure to reframe language use as a tool for narrative progression rather than academic performance. A quasi-experimental study involving 62 Chinese high school students was conducted to assess the framework's potential. Results from the Foreign Language Classroom Anxiety Scale indicated a statistically significant reduction in overall FLA within the experimental group, with notable decreases in Fear of Negative Evaluation and Test Anxiety. These preliminary findings provide concrete guidance and highlight the potential of EngEERs as a feasible and engaging approach for practitioners seeking to foster low-anxiety language learning environments.

L2 writing anxiety, working memory, and task complexity in L2 written performance

Introduction: Training in a certain skill not only culminates in better motor performance but also leads to neural adjustments and regulations in different brain regions. Aim: The present study aimed to psychologically assess event-related motor potential in motor-related cortical regions during simple and complicated tasks. Method: The current research was of a semi-experimental type with a single-phase post-test design without a control group. The participants of the present study consisted of all 20-32-year-old right-handed male table tennis players in Tehran, in 2019. A total of 8 samples were selected via convenience sampling. Data were collected at the National Brain Mapping Laboratory. Annett Hand Preference Questionnaire (1970), Ocular Dominance Testing Card (1910), the Newgy Robo Pong Model 2050 Digital Table Tennis Robot, and the Specific Test for Table Tennis Stroke (2016) were used to record speed from Radar gun, and cameras and judges’ scoring were also used to measure accuracy. Moreover, the two-way analysis of variance (ANOVA) statistical test was employed to assess the differences in two levels of task complexity in SPSS software version 24. Results: The results showed that the motor potential in the primary motor cortex region had a greater range in the simple task than in the complicated task (P=0.012); however, the premotor (P=0.008) and the posterior parietal cortical regions (P=0.026) of the complicated task had larger ranges than the simple task. Conclusion: According to the results of this study, the motor potential range is dependent on the task complexity level. Therefore, it is suggested that tasks with different complexity levels be taken into account in investigating event-dependent potentials.

Manufacturing industries are eager to replace traditional robot manipulators with collaborative robots due to their cost-effectiveness, safety, smaller footprint and intuitive user interfaces. With industrial advancement, cobots are required to be more independent and intelligent to do more complex tasks in collaboration with humans. Therefore, to effectively detect the presence of humans/obstacles in the surroundings, cobots must use different sensing modalities, both internal and external. This paper presents a detailed review of sensor technologies used for detecting a human operator in the robotic manipulator environment. An overview of different sensors installed locations, the manipulator details and the main algorithms used to detect the human in the cobot workspace are presented. We summarize existing literature in three categories related to the environment for evaluating sensor performance: entirely simulated, partially simulated and hardware implementation focusing on the ‘hardware implementation’ category where the data and experimental environment are physical rather than virtual. We present how the sensor systems have been used in various use cases and scenarios to aid human–robot collaboration and discuss challenges for future work.