Task Difficulty Research Articles

LANGUAGE LEARNING THROUGH TASK-BASED SYNCHRONOUS COMPUTER-MEDIATED COMMUNICATION

A limited number of studies have been conducted on the influence of task features on language production in computer-mediated communication (CMC) environments despite the role of tasks on the language production of L2 students who are mostly non-native speakers (NNSs). Among the prominent hypotheses on the relationship between tasks and language production are the Cognition Hypothesis and the Trade-Off Hypothesis. The current study examined the effect of task structure on student language production in terms of syntactic complexity and fluency in CMC environments. A one-shot design study involved 46 NNS undergraduates in Malaysia and Japan. The respondents were divided into two groups: (1) respondents who performed the task with task structure (+TS) and (2) respondents who performed the task without task structure (-TS). The data were then analysed using a t-test. The present study supported the hypothesis positing that the utilisation of +TS contributes to an increase in syntactic complexity among NNSs, as well as the hypothesis proposing that the use of +TS results in improved fluency. The results also suggest examining additional variables related to task difficulty when designing tasks for CMC environments to assess their effects on fluency and syntactic complexity.

PCR92 Association of Rheumatoid Arthritis (RA) Patient Characteristics and Perceived Treatment Satisfaction, RA Impact on Life, and Task Difficulty with Promis Measures’ Physical Functioning and Upper Extremity Scores

PCR92 Association of Rheumatoid Arthritis (RA) Patient Characteristics and Perceived Treatment Satisfaction, RA Impact on Life, and Task Difficulty with Promis Measures’ Physical Functioning and Upper Extremity Scores

Comparing the efficacy of online vs. offline methods in modulating emotional responses through mental stress tasks

Emotion regulation and stress represent two complex, intertwined processes. Yet, there is a paucity of studies examining the effect of stress on emotional regulation among Vietnamese students, specifically the influence of online and offline experimental conditions. This study investigates these dynamics by subjective assessment of the emotional responses of the subjects participating in this study. The research was structured in three primary phases: preliminary, online (conducted via the Internet), and offline (conducted in person) experiments. The preliminary phase (N=16) aimed to validate the appropriateness of the International Affective Picture System (IAPS) picture library and emotional stimulation videos from previous studies. Participants in the online (N=30) and offline (N=45) experiments were divided into control and stress groups, distinguished by the difficulty and urgency of the mental arithmetic task (MAT). Participants were then asked to view photos and videos and to rate their subjective feelings using the Self-assessment Manikin (SAM). The online experimental session revealed that subjects under acute stress exhibited heightened sensitivity, as indicated by increased valence scores in the positive and neutral groups, and decreased scores for negative imagery (Positive: MD=0.292, p=0.0113; Neutral: MD=0.245, p=0.001; Negative: MD=-0.435, p<0.0001). An increase in arousal scores in the stress group was also observed for positive (p<0.0001) and neutral sets (p<0.0001). However, these findings were not replicated in the offline experiment session. In conclusion, the IAPS pictures have proven suitable for emotional studies among Vietnamese students.

Perceptions of task difficulty predict cognitive effort for older adults

ABSTRACT This study examined age differences in effort devoted to completing cognitively demanding tasks. Fifty-two younger adults ages 18–30 years (M age = 21.19) and 57 older adults ages 61–93 years (M age = 76.56) completed a series of memory tests. Following each test, participants rated the test’s difficulty and had their blood pressure measured. Effort was indexed by systolic blood pressure response (SBP-R) with greater increases in SBP-R reflecting more effort. Multilevel modeling was used to examine age differences in the intraindividual association between trial-level subjective task difficulty and trial-level effort. Results showed that increases in task difficulty were significantly related to decreases in SBP-R for the older but not younger adults, suggesting the older adults disengaged from the tests they perceived as highly difficult. Findings support Selective Engagement Theory (Hess, 2014), which suggests the perceived cognitive costs of completing difficult tasks may reduce older adults’ motivation to engage in the tasks.

A Comparison of Psychometric Properties of the American Board of Anesthesiology’s In-Person and Virtual Standardized Oral Examinations

Abstract Purpose The COVID-19 pandemic prompted training institutions and national credentialing organizations to administer examinations virtually. This study compared task difficulty, examiner grading, candidate performance, and other psychometric properties between in-person and virtual standardized oral examinations (SOEs) administered by the American Board of Anesthesiology. Method This retrospective study included SOEs administered in person from March 2018 through March 2020 and virtually from December 2020 through November 2021. The in-person and virtual SOEs share the same structure, including 4 tasks of preoperative evaluation, intraoperative management, postoperative care, and additional topics. The Many-Facet Rasch Model was used to estimate candidate performance, examiner grading severity, and task difficulty for the in-person and virtual SOEs separately; the virtual SOE was equated to the in-person SOE by common examiners and all tasks. The independent-samples and partially overlapping–samples t tests were used to compare candidate performance and examiner grading severity between these 2 formats, respectively. Results In-person (n = 3,462) and virtual (n = 2,959) first-time candidates were comparable in age, sex, race and ethnicity, and whether they were U.S. medical school graduates. The mean (standard deviation [SD]) candidate performance was 2.96 (1.76) logits for the virtual SOE, which was statistically significantly better than that for the in-person SOE (mean [SD], 2.86 [1.75]; Welch independent-samples t test, P = .02); however, the effect size was negligible (Cohen d = 0.06). The difference in the grading severity of examiners who rated the in-person (n = 398; mean [SD], 0.00 [0.73]) vs virtual (n = 341; mean [SD], 0.07 [0.77]) SOE was not statistically significant (Welch partially overlapping–samples t test, P = .07). Conclusions Candidate performance and examiner grading severity were comparable between the in-person and virtual SOEs, supporting the reliability and validity of the virtual oral exam in this large-volume, high-stakes setting.

Efficient Convex-Hull-Based Vehicle Pose Estimation Method for 3D LiDAR

Vehicle pose estimation with light detection and ranging (LiDAR) is essential in the perception technology of autonomous driving. However, because of incomplete observation measurements and sparsity of the LiDAR point cloud, it is challenging to achieve satisfactory pose extraction based on 3D LiDAR with the existing pose estimation methods. In addition, the demand for real-time performance further increases the difficulty of the pose estimation task. In this paper, we propose a novel vehicle pose estimation method based on the convex hull. The extracted 3D cluster is reduced to the convex hull, reducing the subsequent computation burden while preserving essential contour information. Subsequently, a novel criterion based on the minimum occlusion area is developed for the search-based algorithm, enabling accurate pose estimation. Additionally, this criterion renders the proposed algorithm particularly well-suited for obstacle avoidance. The proposed algorithm is validated on the KITTI dataset and a manually labeled dataset acquired at an industrial park. The results demonstrate that our proposed method can achieve better accuracy than the classical pose estimation method while maintaining real-time speed.

Age-related changes in the effects of induced positive affect on executive control in younger and older adults—evidence from a task-switching paradigm

ABSTRACT Positive affect has been shown to promote task-switching performance in healthy young adults. Given the well-documented age-related decline in executive functioning, we asked whether induced positive affect also helps to improve task-switching performance in older adults. Sixty-eight younger and older adults performed a switching task before and after they had watched cartoon clips (positive affect group) or documentaries (neutral affect group). Positive affect was associated with reduced error rates across all trial types in both age groups. In older adults, the increase in accuracy came at the expense of slower response times for task-switch trials, resulting in greater switch costs. This pattern of findings is inconsistent with the popular notion that positive affect supports greater cognitive flexibility. Instead, positive affect may trigger adjustments in response control settings – such as a shift in the speed-accuracy trade-off toward more cautious responding – depending on the experienced level of task difficulty.

Preference for Student Activity over Teacher Guidance: Effects of Task-Related Knowledge and Learner or Instructor Roles

During interactions within educational settings, individuals may find themselves in the position of a learner or an instructor. This study examined how individuals change their perceptions of task difficulty and their preferences for educational approaches oriented toward teacher guidance and student activity based on whether they possess task-related knowledge and whether they are in a learner or an instructor role. University students enrolled in teacher education programs were divided into four groups based on two variables: knowledge (with or without) and role (learner or instructor). Study 1 (N = 359) utilized a between-participants design, whereas Study 2 (N = 141) employed a mixed design, with role as a between-participants variable and knowledge as a within-participants variable. Participants with task-related knowledge perceived a mathematical problem to be less difficult and exhibited a stronger preference for student activity, and participants in the instructor role showed a stronger preference for student activity. These results suggest that individuals tend to distance themselves from teaching behaviors when they have task-related knowledge and are in an instructor position, thus highlighting the potential misalignment of preferences between learners who lack knowledge and more knowledgeable instructors.

Exposure to humans and task difficulty levels affect wild raccoons (Procyon lotor) learning.

Cognition helps wildlife exploit novel resources and environments. Raccoons (Procyon lotor) have successfully adapted to human presence, in part due to their cognitive abilities. However, interactions between humans and wildlife can create conflict. A better understanding of the raccoon's behavioral flexibility and learning ability could mitigate some conflicts. Our objective was to evaluate wild raccoons learning in contexts varying in terms of exposure to humans (recreational and preservation zoning within protected areas) and task difficulty. Learning can be evaluated over multiple exposures to a cognitive task. Across three years of experiment, we employed 2 food extraction tasks to gauge the change in problem-solving performance over trials. This assessment considered the success probability (the number of successful trials divided by the total number of trials) and the time taken to solve the puzzles. We also looked at the effects of 2 behavioral traits, exploratory diversity and persistence. We found strong evidence for learning over consecutive trials in terms of improved success probability. Improvement in terms of success probability and solving time was more pronounced with the initially easier task. We detected an increase in success probability over trials only in the recreation zones, and there was no evidence of an effect of behavioral traits. The improved performance attributed to learning was also maintained over consecutive years. We provide additional evidence that raccoons can learn how to solve a problem, resulting in a more effective solution in consecutive trials. Finally, we consider the management implications of dealing with raccoons accessing anthropogenic resources.

Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues

Since its introduction in November 2022, ChatGPT has rapidly gained popularity due to its remarkable ability in language understanding and human-like responses. ChatGPT, based on GPT-3.5 architecture, has shown great promise for revolutionizing various research fields, including code generation. However, the reliability and quality of code generated by ChatGPT remain unexplored, raising concerns about potential risks associated with the widespread use of ChatGPT-driven code generation. In this article, we systematically study the quality of 4,066 ChatGPT-generated programs of code implemented in two popular programming languages, i.e., Java and Python, for 2,033 programming tasks. The goal of this work is threefold. First, we analyze the correctness of ChatGPT on code generation tasks and uncover the factors that influence its effectiveness, including task difficulty, programming language, time that tasks are introduced, and program size. Second, we identify and characterize potential issues with the quality of ChatGPT-generated code. Last, we provide insights into how these issues can be mitigated. Experiments highlight that out of 4,066 programs generated by ChatGPT, 2,756 programs are deemed correct, 1,082 programs provide wrong outputs, and 177 programs contain compilation or runtime errors. Additionally, we further analyze other characteristics of the generated code through static analysis tools, such as code style and maintainability, and find that 1,930 ChatGPT-generated code snippets suffer from maintainability issues. Subsequently, we investigate ChatGPT’s self-repairing ability and its interaction with static analysis tools to fix the errors uncovered in the previous step. Experiments suggest that ChatGPT can partially address these challenges, improving code quality by more than 20%, but there are still limitations and opportunities for improvement. Overall, our study provides valuable insights into the current limitations of ChatGPT and offers a roadmap for future research and development efforts to enhance the code generation capabilities of artificial intelligence models such as ChatGPT.

Predicting changes in task difficulty perception based on visual behavior in mobile health information search

With the proliferation of online health resources, mobile health information search has become the new norm, in which the task difficulty perception in search affects the user's search experience. This study aimed to investigate the relationship between visual behavior that reflects users' cognitive processing and changes in perceived task difficulty, thereby predicting such changes.This study was conducted through a controlled experiment. 46 participants were recruited to complete four tasks. Visual behavior data were collected through eye-tracking technology, and changes in task difficulty perception were measured through pre-task and post-task questionnaires. The mobile health information search process is divided into three search activities: querying, browsing, and viewing activities. Predictors were inspected from the overall session and individual search activity levels using the Mann-Whitney U test, and then K-Nearest Neighbor, Extreme-Trees, Naive Bayesian, Support Vector Machine, Logistic Regression algorithms were used to predict and evaluate prediction effects.The results showed significant differences in participants' fixation and saccade behaviors between increases and decreases in task difficulty, both at the overall session and individual search activity level. The logistic regression algorithm demonstrated the highest predictive performance, Furthermore, visual behavioral indicators for the browsing activity proved to perform better relative to the other search activities.This study highlights the importance of visual behavioral indicators as reliable predictors of changes in users' perceived task difficulty in mobile health information search. It can help health information providers and administrators to provide timely and targeted assistance and implement effective guidance strategies.

Modeling Frustration Trajectories and Problem-Solving Behaviors in Adaptive Learning Environments for Introductory Computer Science

Frustration, an inherent part of the classroom, is routinely associated with negative stigmas, however, if appropriately managed it can be a highly effective tool for excelling students. Often referred to as eustress, it is the principle that follows the premise of introducing students to a topic they are not familiar with, causing frustration as they learn the currently unfamiliar topic. In the experiment, a correlating pattern involving behavior can properly monitor frustration in a way that remains productive to the student. This process can be emulated using artificial intelligence in schools (AIED) to create adaptive algorithms that provide students with unfamiliar topics until the point that said student becomes sufficiently frustrated, at which point the AI would slow down the curriculum. Through discernment patterns in learners’ frustration levels and problem-solving strategies, AI can dynamically adjust the difficulty of tasks to accommodate each student’s personal needs, as well as the pacing of instruction, and the provision of support. In doing so, AIED could mitigate the adverse effects of extreme frustration and reaping the benefits of frustration that pushes students to a farther level than our current educational system can provide. With AIED creating the ideal structure of adaptive scaffolded learning, students’ needs can be individually fostered in a way that most preferably suits them. This ability to push students into learning curriculum at such an intricate level will allow students to further develop their independence when solving future problems as the high difficulty will authenticate the student's ability to grasp the concept extensively. The intricate interplay between AIED and frustration models is crucial for advancing the frontiers of human knowledge and pushing students to achieve their full potential.

Employer representatives' experiences of supporting employees with cognitive impairments in a digital work environment.

Digital work poses cognitive demands on all employees, but the impact is greater for employees with cognitive impairments. Digitalization also has significant implications for employer representatives as they are responsible for the work environment. However, knowledge is scarce concerning employer representatives' perspectives on identifying needs and support for employees with cognitive impairments working in a digital work environment. To describe employer representatives' experiences of work environment management with focus on employees with cognitive impairments working in a digital environment. Focus group methodology was used. Six employer representatives with work environment responsibilities participated. One overall theme "Mastering the interconnected processes in a transformative digital work environment" as well as three themes "Facilitating good digital work conditions", "Identifying needs and difficulties in work tasks among employees' with cognitive impairments" and "Pursuing knowledge and collaborations to support employees with cognitive impairments" with subthemes were identified. The themes describe employer representatives' challenges and efforts to identify fluctuating needs in employees with cognitive impairments and, also, to organize and reduce cognitive demands in the work environment to support them. Managing the challenges of an evolving digital work environment and matching individual work ability of employees with cognitive impairments in relation to cognitive demands is an ongoing process. The participants valued cooperation with employees with cognitive impairments but lacked support from expertise. The need to develop and implement a functioning support system for vocational rehabilitation to ensure a sustainable work in digital work environments is indicated.

Current Status of Online Self-Learning Efficacy Level for High School Students

Self-efficacy in learning is an individual's belief in their ability to effectively achieve learning goals during autonomous learning. Its measurement is typically conducted through self-report questionnaires, aiming to comprehensively assess students' levels of self-efficacy in learning. Factors influencing self-efficacy in learning include personal successful experiences, personality traits, social support, learning environments, task difficulty, among others. Self-efficacy in learning is closely related to online learning, as it not only affects students' attitudes, motivation, and strategies in learning but also predicts their behaviors and outcomes in online learning. Therefore, enhancing students' self-efficacy in learning is crucial for promoting their autonomous learning and academic success in online learning environments.

Analysis of test results and test quality during certification of non-destructive testing specialists

This article analyzes the results of personal certification for eddy current testing of railway facilities. The influences of education level, the work experience, the candidate age on the qualifying examinations results are considered. The conformity between test task difficulties and certification candidate training is analyzed with Rasch method. The characteristic curves of test task difficulties and the characteristic curves of candidate training levels are constructed. The results general and special examinations of 2020 and 2021 are analyzed to identify extreme test questions. The research results enable to assess the candidate training and the test task difficulties through latent parameters measured as logit unit. The analysis identified test tasks with overstated and understated task difficulty logits compared with the logits of the candidate training, assessed the correspondence between test difficulties and training candidate level, and assessed a distribution uniformity of the tasks’ difficulty. The required training logit of candidates for the certification is calculated for successful passing general and special exam tests. The getting results give a basis for further analysis of the tasks complexity, identification the reasons for the insufficiency of the auditory material familiarization for the tasks with low rate of response, for making adjustments to the consulting sessions, as well as the content and form of the test.

Beyond numbers: the role of mathematics self-concept and spatial anxiety in shaping mental rotation performance and STEM preferences in primary education

IntroductionFactors such as low self-concept and anxiety have been shown to negatively impact mathematical achievement and spatial skills, as well as enjoyment of math-related subjects. Understanding these factors is crucial for promoting STEM interest and performance, particularly among primary school students.MethodsThis cross-sectional study examines the influence of gender, childhood development stage, maths self-concept, spatial anxiety, perceived difficulty, mental rotation performance, and STEM preferences in a sample of 144 primary school students (mean age M = 8.47), comprising 70 girls and 74 boys. Data were collected through four questionnaires and a computerized Mental Rotation Task (MRT).ResultsGirls and tweens (9-to-11-year-olds) exhibit lower maths self-concept, impacting their preference for maths as a STEM subject. Girls also demonstrate higher spatial anxiety and perceived difficulty of the MRT compared to boys. Maths self-concept is significantly associated with spatial anxiety and perceived difficulty, while gender is not. Maths self-concept shows marginal effects on students’ accuracy on the MRT, with evidence of a mediating effect of spatial anxiety.DiscussionThese findings underscore the importance of maths self-concept in shaping STEM preferences, particularly among girls and tweens. Additionally, maths self-concept serves as a mitigating factor for spatial anxiety and perceived difficulty in spatial tasks among primary school children. The study also suggests that spatial anxiety may contribute to gender disparities in mathematics and STEM-related domains. Further research is needed to explore interventions targeting maths self-concept and spatial anxiety to promote equitable STEM engagement amongst primary school students.

Mitigating Trunk Compensatory Movements in Post-Stroke Survivors through Visual Feedback during Robotic-Assisted Arm Reaching Exercises.

Trunk compensatory movements frequently manifest during robotic-assisted arm reaching exercises for upper limb rehabilitation following a stroke, potentially impeding functional recovery. These aberrant movements are prevalent among stroke survivors and can hinder their progress in rehabilitation, making it crucial to address this issue. This study evaluated the efficacy of visual feedback, facilitated by an RGB-D camera, in reducing trunk compensation. In total, 17 able-bodied individuals and 18 stroke survivors performed reaching tasks under unrestricted trunk conditions and visual feedback conditions. In the visual feedback modalities, the target position was synchronized with trunk movement at ratios where the target moved at the same speed, double, and triple the trunk's motion speed, providing real-time feedback to the participants. Notably, trunk compensatory movements were significantly diminished when the target moved at the same speed and double the trunk's motion speed. Furthermore, these conditions exhibited an increase in the task completion time and perceived exertion among stroke survivors. This outcome suggests that visual feedback effectively heightened the task difficulty, thereby discouraging unnecessary trunk motion. The findings underscore the pivotal role of customized visual feedback in correcting aberrant upper limb movements among stroke survivors, potentially contributing to the advancement of robotic-assisted rehabilitation strategies. These insights advocate for the integration of visual feedback into rehabilitation exercises, highlighting its potential to foster more effective recovery pathways for post-stroke individuals by minimizing undesired compensatory motions.

Duet playing in dementia care: a new therapeutic music technology

Purpose Supporting the relational worlds of people living with dementia, especially the spousal dyad, is a growing focus in dementia care as is advancing the therapeutic use of music in dementia care. This paper describes a mixed-methods, multi-phase, iterative research study designed to develop the Music Memory Makers (MMM) Duet System, a novel therapeutic music technology, that allows non-musicians to play a personalized repertoire of songs arranged as duets. Methods Following a pilot phase to iteratively assess and refine the MMM Duet System for recreational and therapeutic purposes, multiple sources of data were used to investigate five older spousal dyads’ experiences with the system, two couples living with dementia and three who were not. We assessed perceptions of task difficulty, joint agency, and enjoyment as well as therapeutic benefits associated with enhancing the spousal relationship and sense of couplehood. Results Findings suggest playing meaningful songs together is an enjoyable interactive activity that prompts musical reminiscence, involves joint agency, and supports relationship continuity within a relational, positive approach to dementia care. All couples mastered the task, none evaluated it as “very challenging,” and positive couple interactions were evoked, commonly before and after playing the duets. Conclusions The MMM Duet System is recommended for further research and development as an innovative way to support couples living with dementia with commercial implications, and as a new music technology suitable for use as a research tool.

An exploratory characterization of speech- and fine-motor coordination in verbal children with Autism spectrum disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder often associated with difficulties in speech production and fine-motor tasks. Thus, there is a need to develop objective measures to assess and understand speech production and other fine-motor challenges in individuals with ASD. In addition, recent research suggests that difficulties with speech production and fine-motor tasks may contribute to language difficulties in ASD. In this paper, we explore the utility of an off-body recording platform, from which we administer a speech- and fine-motor protocol to verbal children with ASD and neurotypical controls. We utilize a correlation-based analysis technique to develop proxy measures of motor coordination from signals derived from recordings of speech- and fine-motor behaviors. Eigenvalues of the resulting correlation matrix are inputs to Gaussian Mixture Models to discriminate between highly-verbal children with ASD and neurotypical controls. These eigenvalues also characterize the complexity (underlying dimensionality) of representative signals of speech- and fine-motor movement dynamics, and form the feature basis to estimate scores on an expressive vocabulary measure. Based on a pilot dataset (15 ASD and 15 controls), features derived from an oral story reading task are used in discriminating between the two groups with AUCs > 0.80, and highlight lower complexity of coordination in children with ASD. Features derived from handwriting and maze tracing tasks led to AUCs of 0.86 and 0.91, however features derived from ocular tasks did not aid in discrimination between the ASD and neurotypical groups. In addition, features derived from free speech and sustained vowel tasks are strongly correlated with expressive vocabulary scores. These results indicate the promise of a correlation-based analysis in elucidating motor differences between individuals with ASD and neurotypical controls.

AiroTouch: enhancing telerobotic assembly through naturalistic haptic feedback of tool vibrations.

Teleoperation allows workers to safely control powerful construction machines; however, its primary reliance on visual feedback limits the operator's efficiency in situations with stiff contact or poor visibility, hindering its use for assembly of pre-fabricated building components. Reliable, economical, and easy-to-implement haptic feedback could fill this perception gap and facilitate the broader use of robots in construction and other application areas. Thus, we adapted widely available commercial audio equipment to create AiroTouch, a naturalistic haptic feedback system that measures the vibration experienced by each robot tool and enables the operator to feel a scaled version of this vibration in real time. Accurate haptic transmission was achieved by optimizing the positions of the system's off-the-shelf accelerometers and voice-coil actuators. A study was conducted to evaluate how adding this naturalistic type of vibrotactile feedback affects the operator during telerobotic assembly. Thirty participants used a bimanual dexterous teleoperation system (Intuitive da Vinci Si) to build a small rigid structure under three randomly ordered haptic feedback conditions: no vibrations, one-axis vibrations, and summed three-axis vibrations. The results show that users took advantage of both tested versions of the naturalistic haptic feedback after gaining some experience with the task, causing significantly lower vibrations and forces in the second trial. Subjective responses indicate that haptic feedback increased the realism of the interaction and reduced the perceived task duration, task difficulty, and fatigue. As hypothesized, higher haptic feedback gains were chosen by users with larger hands and for the smaller sensed vibrations in the one-axis condition. These results elucidate important details for effective implementation of naturalistic vibrotactile feedback and demonstrate that our accessible audio-based approach could enhance user performance and experience during telerobotic assembly in construction and other application domains.