Task Difficulty Research Articles

The Key Role of Gestures in Spatial Tasks for Students With Intellectual Disability.

The gestures produced by children with intellectual disability (ID) in spatial tasks are rarely considered, although they have a supporting role in the formation of thought. In this research study, we analyzed the number of gestures, the type of gestures, and their role in the expression of knowledge of students with ID. Twenty students (12-17 years old) with ID and 40 students with typical development (TD) matched on visual-spatial level (n = 20) and on language level (n = 20) participated in the research. Students with ID made significantly more gestures in relation to the number of words spoken compared to their peers with TD. Thirty percent of the expressive communication of students with ID came from gestures alone, and 60% of the responses contained at least one gesture. Finally, the higher the level of task difficulty, the more gestures the students made.

Assessing the Role of Homework in Enhance Students Performance in Private Primary School in Arusha City

The purpose of this study was to investigate the role of homework in enhancing students’ academic performance in Arusha city. The specific objectives were to investigate the extent of homework given to students and its contribution to their academic performance in private primary schools. The study adopted a cross-sectional design and a quantitative approach, collecting data from 48 respondents, including 30 students and 18 teachers, using questionnaires. The tools were validated by experts and pilot tested to ensure reliability. Data were analyzed using descriptive statistics with SPSS, and results were presented in tables and figures. Ethical considerations were observed, and all sources were cited in the Harvard style. The findings indicate that most teachers assign homework daily and students agreed that homework improves their time management and understanding of topics. However, opinions vary on the difficulty of homework tasks. The study concluded that homework is a crucial tool for reinforcing learning and developing essential skills. It was recommended that the government ensure homework aligns with curriculum goals, teachers regularly assess homework tasks and parents provide a supportive environment for homework completion.

Gesture centric interaction: evaluating hand and head gestures in touchless cursor control

Touchless interfaces have gained considerable importance in the modern era, particularly due to their user-friendly and hygienic nature of interaction. This article presents the designing of two touchless cursor control systems based on hand gestures and head movements utilising the MediaPipe framework to extract the key landmarks of the hand and face utilising a laptop camera. The index finger’s landmark points are tracked and converted to corresponding screen coordinates for cursor control. Similarly, yaw and pitch angles of head movements are computed in the head movement-based cursor design. A comprehensive performance evaluation of the two proposed systems based on a two-dimensional (2D) Fitts’ law experiment revealed superior performance for the hand gesture-controlled cursor compared to the head movement-controlled cursor with throughputs of 0.59 bps and 0.53 bps respectively. Participants also favoured hand gesture-based cursor control over head movement-based cursor control in terms of overall experience and task difficulty.

YOLO-GE: An Attention Fusion Enhanced Underwater Object Detection Algorithm

Underwater object detection is a challenging task with profound implications for fields such as aquaculture, marine ecological protection, and maritime rescue operations. The presence of numerous small aquatic organisms in the underwater environment often leads to issues of missed detections and false positives. Additionally, factors such as the water quality result in weak target features, which adversely affect the extraction of target feature information. Furthermore, the lack of illumination underwater causes image blur and low contrast, thereby increasing the difficulty of the detection task. To address these issues, we propose a novel underwater object detection algorithm called YOLO-GE (GCNet-EMA). First, we introduce an image enhancement module to mitigate the impact of underwater image quality issues on the detection task. Second, a high-resolution feature layer is added into the network to improve the problems of missed detections and false positives for small targets. Third, we propose GEBlock, an attention-based fusion module that captures long-range contextual information and suppresses noise from lower-level feature layers. Finally, we combine an adaptive spatial fusion module with the detection head to filter out conflicting feature information from different feature layers. Experiments on the UTDAC2020, DUO and RUOD datasets show that the proposed method achieves an optimal detection accuracy.

GCLmf: A Novel Molecular Graph Contrastive Learning Framework Based on Hard Negatives and Application in Toxicity Prediction.

In silico methods for prediction of chemical toxicity can decrease the cost and increase the efficiency in the early stage of drug discovery. However, due to low accessibility of sufficient and reliable toxicity data, constructing robust and accurate prediction models is challenging. Contrastive learning, a type of self-supervised learning, leverages large unlabeled data to obtain more expressive molecular representations, which can boost the prediction performance on downstream tasks. While molecular graph contrastive learning has gathered growing attentions, current models neglect the quality of negative data set. Here, we proposed a self-supervised pretraining deep learning framework named GCLmf. We first utilized molecular fragments that meet specific conditions as hard negative samples to boost the quality of the negative set and thus increase the difficulty of the proxy tasks during pre-training to learn informative representations. GCLmf has shown excellent predictive power on various molecular property benchmarks and demonstrates high performance in 33 toxicity tasks in comparison with multiple baselines. In addition, we further investigated the necessity of introducing hard negatives in model building and the impact of the proportion of hard negatives on the model.

Increased listening effort and cochlear neural degeneration underlie behavioral deficits in speech perception in noise in normal hearing middle-aged adults.

Middle-age is a critical period of rapid changes in brain function that presents an opportunity for early diagnostics and intervention for neurodegenerative conditions later in life. Hearing loss is one such early indicator linked to many comorbidities later in life. However, current clinical tests fail to capture hearing difficulties for ∼10% of middle-aged adults seeking help at hearing clinics. Cochlear neural degeneration (CND) could play a role in these hearing deficits, but our current understanding is limited by the lack of objective diagnostics and uncertainty regarding its perceptual consequences. Here, using a cross-species approach, we measured envelope following responses (EFRs) - neural ensemble responses to sound originating from the peripheral auditory pathway - in young and middle-aged adults with normal audiometric thresholds, and compared these responses to young and middle-aged Mongolian gerbils, where CND was histologically confirmed. We observed near identical changes in EFRs across species that were associated with CND. Perceptual effects measured as behavioral readouts showed deficits in the most challenging listening conditions and were associated with CND. Additionally, pupil-indexed listening effort increased even at moderate task difficulties where behavioral outcomes were matched. Our results reveal perceptual deficits in middle-aged adults driven by CND and increases in listening effort, which may result in increased listening fatigue and conversational disengagement.

Don't Throw Away Your Notebook: Effects of Task Difficulty and Presentation Medium on Memory Performance.

People are increasingly reliant on various electrical devices for learning and memory, yet the implications and consequences of this dependence remain poorly understood. The present study aimed to investigate how learning through electrical media impacts recall under varying task difficulties. During this study, participants encoded information related to daily life situations (low difficulty), academic conceptual knowledge (middle difficulty), or associative word pairs (high difficulty), presented on smartphones, computers, or paper. At test, they recalled the omitted content based on the provided cue information. A significant screen-inferiority effect was observed for both computers and smartphones. However, the impairment related to computers disappeared in the retrieval of daily life situations and academic conceptual knowledge, whereas the impairment associated with smartphones was consistently present across all tasks. These results suggest that memory performance is modulated by the interaction between the presentation medium and the specific demands of the task, highlighting a more pronounced screen-inferiority memory effect when the media restrict the depth of processing or when the memory tasks pose greater external challenges. A deeper understanding of these factors can guide the optimization of electrical devices to enhance human memory abilities and functions.

Driver Behavior Mechanisms and Conflict Risk Patterns in Tunnel-Interchange Connecting Sections: A Comprehensive Investigation Based on the Behavioral Adaptation Theory

Tunnel-interchange sections are characterized by complex driving tasks and frequent traffic conflicts, posing substantial challenges to overall safety and efficiency. Enhancing safety in these areas is crucial for the sustainability of traffic systems. This study applies behavior adaptation theory as an integrated framework to examine the impact of environmental stimuli on driving behavior and conflict risk in small-spaced sections. Through driving simulation, 19 observation indicators are collected, covering eye-tracking, heart rate, subjective workload, driving performance, and conflict risk. The analysis, using single-factor ranking (Shapley Additive Explanation), interaction effects (dependence plots), and multi-factor analysis (Structural Equation Modeling), demonstrates that driving workload and performance dominate the fully mediating effects between external factors and conflict risk. High-load environmental stimuli, such as narrow spacing (≤500 m) and overloaded signage information (>6 units), significantly elevate drivers’ stress responses and impair visual acuity, thereby increasing task difficulty and conflict risk. Critical factors like saccade size, heart rate variability, lane deviation, and headway distance emerge as vital indicators for monitoring and supporting driving decisions. These findings provide valuable insights for the operational management of small-spacing sections and enhance the understanding of driving safety in these areas from a human factor perspective.

Validation and Comparison of Non-stationary Cognitive Models: A Diffusion Model Application

AbstractCognitive processes undergo various fluctuations and transient states across different temporal scales. Superstatistics are emerging as a flexible framework for incorporating such non-stationary dynamics into existing cognitive model classes. In this work, we provide the first experimental validation of superstatistics and formal comparison of four non-stationary diffusion decision models in a specifically designed perceptual decision-making task. Task difficulty and speed-accuracy trade-off were systematically manipulated to induce expected changes in model parameters. To validate our models, we assess whether the inferred parameter trajectories align with the patterns and sequences of the experimental manipulations. To address computational challenges, we present novel deep learning techniques for amortized Bayesian estimation and comparison of models with time-varying parameters. Our findings indicate that transition models incorporating both gradual and abrupt parameter shifts provide the best fit to the empirical data. Moreover, we find that the inferred parameter trajectories closely mirror the sequence of experimental manipulations. Posterior re-simulations further underscore the ability of the models to faithfully reproduce critical data patterns. Accordingly, our results suggest that the inferred non-stationary dynamics may reflect actual changes in the targeted psychological constructs. We argue that our initial experimental validation paves the way for the widespread application of superstatistics in cognitive modeling and beyond.

Burning fields, fading memories: exploring the effects of sugarcane burning on air quality and cognitive functioning – A case study in Northeast Thailand

This study assessed the relationship between PM2.5 concentration and the working memory of sugarcane farmers (n = 444) in Khon Kaen Province, one of the largest sugarcane producers in the Northeast region of Thailand. The relationship between the ambient PM2.5 concentrations and the working memory of sugarcane farmers was evaluated using two working memory outcomes. These outcomes included a working memory difficulty score derived from self-report of difficulty in daily tasks that require working memory and an objective memory test score consisting of a set of number recall exercises. The PM2.5 concentration data in this study were obtained from air quality monitoring stations located in the vicinity of the study locations, ensuring both precision and relevance to local air conditions. The regression results showed that farmers in the low-burn farming zone had less difficulty with working memory and better performance on number recall exercises, compared to farmers in the high-burn farming zones, even after controlling for health and socio-economic factors. Our findings highlight the potential impacts of PM2.5 exposure on the cognitive functions of farmers who burn sugarcane residues in Thailand. Our study supports the need for the government of Thailand or health agencies to establish an effective policy to reduce sugarcane residue burning in Thailand.

The benefit of choice on task performance: Reduced difficulty effects in free-choice versus forced-choice tasks.

We investigated how self-determined (free) versus imposed (forced) choices influence task performance. To this end, we examined how changes in perceptual and central decision-processing difficulties affect task performance in an environment where free-choice and forced-choice tasks were intermixed. In Experiments 1 (N = 43) and 2 (N = 42), perceptual processing difficulty was varied by altering colored dot proportions (easy vs. hard color discrimination task). In Experiment 3 (N = 58), decision-processing difficulty was adjusted by changing the rotation degree of letters (easy vs. hard letter rotation task). Across all experiments, both free-choice and forced-choice performance were more impaired with harder stimuli, but this effect was generally less pronounced in freely chosen tasks. Specifically, this was evident from significant interactions between processing mode (free vs. forced) and difficulty (easy vs. hard) in the mean reaction times (RTs) for the tasks with the difficulty manipulation. Thus, processing in free-choice tasks is generally less affected by environmental changes (i.e., variation in information difficulties). We discuss how the benefit of self-determined choices over imposed choices can be explained by motivational and performance-optimization accounts, while also considering the finding that participants adjusted their task choices toward tasks with easier stimuli (i.e., significant main effect of task difficulty on choosing the task with the difficulty manipulation). Specifically, we discuss how having control over task choices might lead to more stable information processing and allow people to choose more difficult tasks when this increased difficulty has a relatively small impact on their performance.

Determining the optimal challenge point for learning motor skills in children with attention deficit/hyperactivity disorder

The purpose of this study was to investigate the optimal challenge point for learning motor skills in children with and without attention deficit/hyperactivity disorder (ADHD). Ninety-six 9- to 10-year-old children, including 48 children with ADHD and 48 neurotypical children, were randomly assigned to one of four practice groups with varying levels of nominal and functional task difficulty. They performed 63 trials of a dart throwing task in the acquisition phase and 18 trials in the retention and transfer tests a day later. The results showed that neurotypical children outperformed children with ADHD in all phases of the study. Both groups improved in the acquisition phase and performed better in the retention and transfer tests. Interestingly, low nominal task difficulty was associated with better learning for both groups, despite lower average performance for children with ADHD. Thus, despite their performance differences, we did not find a difference in the effective challenge point between children with ADHD and their neurotypical peers.

Assessing indoor and outdoor noise quality and associated health impacts at selected schools in Surat, India

An optimal ambient environment is crucial for healthy development, yet the excess of vehicles and inadequately planned educational infrastructures compromise cognitive growth in children. This study evaluates the impact of ambient noise on student cognition in five schools situated along city arterial and sub-arterial roads. A total of 717 students from grades 7, 8, 9, and 11 participated. Noise levels were measured in prevailing noisy conditions (PC) and controlled silence conditions (SC) within classrooms using the Kimo dB300 sound level meter. The observed differences in noise levels between PC and SC varied across grades, showing reductions of 4.7 ± 3.5 dB, 6.1 ± 0.7 dB, 6.7 ± 1.3 dB, and 4.4 ± 3.46 dB for grades 7, 8, 9, and 11, respectively. Statistical analyses revealed significant differences in the average noise levels under both conditions. Furthermore, cognitive task performance in PC and SC was significantly different, as evidenced by paired t-tests in tasks such as multiplication, word formation, reasoning, and sentence construction. Dimension reduction techniques identified room acoustics, task difficulty, speech intelligibility, mental deficiency, and annoyance as critical factors affecting learning abilities. Teachers reported that major impacts of noise include annoyance, sleeplessness, headache, and hearing impairment.

Assessing Static Balance, Balance Confidence, and Fall Rate in Patients with Heart Failure and Preserved Ejection Fraction: A Comprehensive Analysis.

Chronic heart failure (CHF) is a complex clinical syndrome, associated with frailty, higher fall rates, and frequent hospitalizations. Heart Failure (HF) and preserved ejection fraction (HFpEF) is defined as a condition where a patient with HF have a diagnosis of left ventricular ejection fraction (LVEF) of ≥ 50%. The risk of HFpEF increases with age and is related to higher non-cardiovascular mortality. The aim of this study was to evaluate static balance and examine the effect of task difficulty on the discriminating power of balance control between patients with HFpEF (Patients with HFpEF) and their healthy controls. Moreover, the associations between static balance parameters, balance confidence, falls, lean muscle mass, and strength were assessed. Seventy two patients with HFpEF (mean age: 66.0 ± 11.6 years) and seventy two age- and gender-matched healthy individuals (mean age: 65.3 ± 9.5 years) participated in this study. Participants underwent a 30 s bilateral stance (BS) test and a 20 s Tandem-Romberg stance (TRS) on a force platform, evaluating the Range and Standard Deviation of Center of Pressure (COP) displacement parameters in both axes. Balance confidence was evaluated by the Activities-Specific Balance Confidence (ABC) Scale, and the number of falls during the last year was recorded. Lower limb strength was measured using an isokinetic dynamometer, isometric leg strength, and a Sit-to-Stand test. Bioelectrical impedance analysis was conducted to assess lean fat mass, lean fat mass index, and lean%. Patients with HFpEF presented with lower static balance in BS and TRS compared to healthy controls (p < 0.05), lower balance confidence by 21.5% (p < 0.05), and a higher incidence of falls by 72.9% (p < 0.05). BS was a better descriptor of the between-group difference. Furthermore, static balance, assessed in controlled lab conditions, was found to have little if no relationship to falls, strength, lean muscle mass, and balance confidence. Although no correlation was noted between the static balance parameters and falls, the fall rate was related to balance confidence, age, muscle strength, and lean fat.

Interference of mid-level sound statistics underlie human speech recognition sensitivity in natural noise.

Recognizing speech in noise, such as in a busy restaurant, is an essential cognitive skill where the task difficulty varies across environments and noise levels. Although there is growing evidence that the auditory system relies on statistical representations for perceiving 1-5 and coding4,6-9 natural sounds, it's less clear how statistical cues and neural representations contribute to segregating speech in natural auditory scenes. We demonstrate that human listeners rely on mid-level statistics to segregate and recognize speech in environmental noise. Using natural backgrounds and variants with perturbed spectro-temporal statistics, we show that speech recognition accuracy at a fixed noise level varies extensively across natural backgrounds (0% to 100%). Furthermore, for each background the unique interference created by summary statistics can mask or unmask speech, thus hindering or improving speech recognition. To identify the neural coding strategy and statistical cues that influence accuracy, we developed generalized perceptual regression, a framework that links summary statistics from a neural model to word recognition accuracy. Whereas a peripheral cochlear model accounts for only 60% of perceptual variance, summary statistics from a mid-level auditory midbrain model accurately predicts single trial sensory judgments, accounting for more than 90% of the perceptual variance. Furthermore, perceptual weights from the regression framework identify which statistics and tuned neural filters are influential and how they impact recognition. Thus, perception of speech in natural backgrounds relies on a mid-level auditory representation involving interference of multiple summary statistics that impact recognition beneficially or detrimentally across natural background sounds.

An embedded computational framework of memory: Accounting for the influence of semantic information in verbal short-term memory

We introduce the Embedded Computational Framework of Memory (eCFM), a model that integrates structured semantic word representations with an instance-based memory model to account for the influence of semantic information in verbal short-term memory. The eCFM combines principles from the episodic MINERVA 2 model and the semantic Latent Semantic Analysis model. After reviewing how semantic information impacts verbal short-term memory performance, we demonstrate eCFM’s ability to reconcile various phenomena within a common computational framework. Our model captures key findings, such as the influence of semantic information in serial recall, its reduction in serial reconstruction, and the impact of task difficulty on semantic information. In five experiments, we tested predictions derived from the eCFM. Experiments 1 and 2 manipulated list organization, with Experiment 1 using alternating lists of related or unrelated words and Experiment 2 using blocked lists. Experiment 3 varied presentation rates, Experiment 4 revisited the detrimental effect of semantic information on order information, and Experiment 5 explored false recall. We found that semantic information interacts with list composition, presentation rate affects the magnitude of its influence, and semantic information impacts order information contrary to the dominant view. Additionally, increasing the number of related study words to a non-studied semantic lure boosts false recall. The eCFM captured these findings as well as memory at the item level. Our demonstration provides insight into the cognitive mechanisms underlying verbal short-term memory and the interplay of semantic and episodic memory processes in recall.

H3T: Hierarchical transferable transformer with TokenMix for unsupervised domain adaptation

Recent research has been focused on exploring the capabilities of Vision Transformers (ViTs) in Unsupervised Domain Adaptation (UDA). This approach typically involves providing more significant attention to fine-grained common information through patch-level transferable discrimination. However, prematurely assigning narrow-range transferability information at the encoding stage can sparse image information, thereby increasing the difficulty of downstream tasks. Therefore, we propose a Hierarchical Transferable Transformer with TokenMix (H3T), which maintains the allocation of fine-grained transferability at the encoding stage while enhancing the learning strength of image information through feature mixup. To address the challenge of missing sample labels in the target domain within the domain adaptation task, we have specifically designed the TokenMix Module (TMM) for ViTs. This module learns the style information from both domains while alleviating the impact of image sparsity on downstream tasks. Furthermore, to enhance the semantic connections among narrow-range image transfer messages, we propose the Hierarchical Discriminative Module (HDM), which also serves a critical role in encoding discriminative information. Our approach underwent comprehensive experimentation across five datasets of varying sizes, demonstrating its effectiveness. Our code is available at https://github.com/reyihua/H3T.

Measuring Impairment-Specific Gains in Individual Cognitive Rehabilitation Through a Systematic Therapy Protocol.

This study investigated treatment-induced performance gains in memory function following therapy through the Intensive Cognitive Communication Rehabilitation (ICCR) program for young adults with acquired brain injury (ABI). We aimed to determine the utility of a novel approach to measuring memory performance improvement across semesters of therapy using (a) systematic treatment tasks called Individualized Quantitative Protocols (IQPs) as compared to (b) standardized measures of memory function. Retrospective IQP data spanning five consecutive ICCR semesters were collected from patients (N = 13) with ABI. Raw task-accuracy data were scaled to account for task difficulty gradation. Linear mixed-effects models (LMMs) were used to evaluate the degree of memory improvement-measured by scaled IQP scores-as a function of therapy duration, age, time postinjury, and aphasia; pre- to posttreatment effect sizes were also calculated. For comparison, similar LMMs were run using standardized metrics of memory abilities as the outcome measure. Results showed significant treatment-induced improvements, with gains at the session level (β = 2.76; t = 2.23; p = .047), when improvement was measured using IQP scaled scores. Standardized metrics did not show significant improvement as a function of therapy. Effect size analysis mirrored LMM results, with a large (d = 0.92, 95% confidence interval [0.35, 1.49]) pre- to posttreatment effect when change was measured using IQP scaled scores and a small effect for standardized measures. This preliminary study demonstrates the utility of a granular, individualized metric to index significant impairment-based performance gains following ICCR treatment. These results introduce promise for future analysis of complex treatment data. Additionally, they provide another lens with which to assess treatment progress and its significance. https://doi.org/10.23641/asha.27045937.

Improving Physical Fitness through a Circuit Games Model

This study aims to determine how effectively these circuit games can enhance physical fitness among young students and whether this approach can lead to measurable improvements in their overall physical health and capabilities. This study employs the action research method to assess the impact of circuit games on improving student fitness. By observing changes in student behavior and physical capabilities, the researcher aims to determine the effectiveness of the circuit game model in enhancing overall fitness. The TKSI (Test Kebugaran Siswa Indonesia) is used as a key tool to measure and evaluate the students’ fitness levels throughout the study. Through this approach, the study seeks to provide insights into how circuit training games can be effectively utilized to boost physical fitness among students. The results stated that physical fitness is a crucial asset for students, as it significantly enhances their ability to perform daily activities and tasks efficiently. Students with good physical fitness are generally better equipped to handle the demands of both academic and extracurricular activities, while those with lower fitness levels often struggle with fatigue and difficulty in daily tasks. Circuit training games offer a dynamic approach to fitness, combining aerobic exercises with strength training and flexibility. These games involve various stations, each designed to target different aspects of physical fitness, and require students to complete each station within a set time before moving on to the next.

대학 내 이공계 학생의 액션러닝 참여 경험에 관한 현상학적 연구

The purpose of this study is to gather the experiences of engineering and science students participating in action learning within universities and to explore the factors that indicate the support they require from these experiences. To achieve this objective, the phenomenological research method proposed by Colaizzi(1978) was employed to identify the common experiences of the participants. A purposive sampling method was utilized to select six engineering and science students who engaged in action learning as research participants. Data were collected through unstructured in-depth interviews, participant observation, and a thorough literature review. The results revealed three categories, ten theme clusters, and twenty-five themes. Based on the characteristics of engineering and science students identified through their action learning experiences, their support needs encompass 'a deficiency in communication skills', 'challenges associated with selecting manufacturing companies', 'an increased necessity for persuasion and study due to the specialization of their majors', and 'a discrepancy in perceived task difficulty between instructors and students'. The role of facilitators in addressing these needs was also examined.