Levels Of Task Complexity Research Articles

Human-Machine Function Allocation Method for Submersible Fault Detection Tasks

The operation and support (OS) officer is responsible for buoyancy regulation and fault detection of onboard equipment in the civil submersible. The OS officer carries out the above tasks through the human-machine interface (HMI) of a submersible buoyancy regulation and support (SBRS) system. However, the OS officer often faces uneven task frequency produced by fault tasks, which leads to an unbalanced mental workload and individual failures. To address this issue, we proposed a human-machine function allocation method based on level of automation (LOA) taxonomy and submersible task complexity (STC), aimed at improving human-machine cooperation in submersible fault detection tasks. Based on this method, we identified the LOA2 as the optimal human-computer function allocation scheme. In this study, three measurement techniques (subjective scale, work performance, and physiological status) were used to test 15 subjects to validate the effectiveness of the proposed optimal human-machine function allocation scheme. The GAMM test results also indicate that the proposed optimal human-machine function allocation scheme (LOA2) can improve the work performance of the operating system officials under low or high workloads and reduce the subjective workload.

A tale of the likable change: the role of change in leadership behavior in improving employees’ willingness to take risks

PurposeA crisis period can reduce employees’ willingness to take risks, which are important predictors of organizational performance. Built upon the broaden-and-build theory of positive emotions, this study aims to examine the role of leadership’s behavioral change in promoting the willingness to take risks, as mediated by liking, at two different levels of task complexity.Design/methodology/approachAn online survey has been answered by 281 employees of businesses with various scales, in different sectors in Indonesia. Indonesia was selected as it is among the countries with a high power distance culture. Hence, employees are expected to favor more directive leadership changes in the postpandemic context.FindingsDrawing upon the broaden-and-build theory of positive emotions, this study found that leaders’ behavioral change toward a more directive approach promotes a willingness to take risks, as the employees like this change regardless of the task’s complexity level.Research limitations/implicationsIn an organization where the employees’ willingness to take risks is critical, the leaders should not simply adopt empowering leadership, as suggested by previous studies. However, leaders need to ensure that any change in leadership behavior during the transition period, either toward a more directive or empowering style, is favorable for the employees, regardless of the level of complexity of the tasks.Originality/valueThis study contributes to the literature by demonstrating that Indonesian employees’ willingness to take risks increases only when the employees like the change in the style of leadership to a more directive one regardless of the level of task complexity. In addition, Indonesian employees have not perceived any substantial change in their leaders’ behavior after the pandemic, and they remain neutral about this type of leadership.

Impact of task type and task complexity on negotiation of meaning in young learners of Chinese as a second language

Abstract Negotiation of meaning (NoM) has played a facilitative role in second language acquisition. However, the existing studies have primarily focused on adult English language learners. This study investigated the impact of task type and task complexity on NoM strategies among young learners of Chinese as a second language, an underexplored group. The participants were 110 students in Hong Kong aged 10–12, mainly from Pakistan, India, Philippines, and Nepal. They were asked to perform four tasks with different task types and levels of task complexity in Cantonese (the primary Chinese dialect spoken in Hong Kong). In terms of task type, the study found that required information exchange tasks (i.e., information gap tasks) produced significantly more clarification requests, confirmation checks, self-repetitions, and other repetitions in terms of total numbers and numbers per 100 Chinese characters than the optional exchange tasks (i.e., decision-making tasks). Complex tasks, on the other hand, elicited significantly more confirmation checks than simple tasks. These findings provide useful insights for designing tasks that can promote greater use of NoM strategies in classroom practice.

Sitting versus standing work postures during simulated laparoscopic surgery: in terms of user preferences, comfort, performance and biomechanics

Prolonged standing in surgery has been linked to an increased risk of musculoskeletal disorders. The aim of this study was to determine whether sitting could serve as an alternative work posture in laparoscopic procedures. Twenty medical students in their third and fourth years were recruited. Sitting and standing were compared at two task complexity levels on a laparoscopic surgery simulator. Measured variables included user posture preferences, perceived discomfort, performance and biomechanics. Electromyography data from the upper trapezius and erector spinae muscles were analysed. Results showed that posture did not affect surgical performance and erector spinae muscle activation. Sitting showed higher muscle activation at the trapezius muscles; however, perceived discomfort was unaffected. Most participants preferred sitting for the difficult task and standing for the easy task. Findings showed that sitting, with appropriate seat design considerations, could serve as an alternative or even as a preferred work posture for simulated laparoscopic procedures.

Determining Cognitive Workload Using Physiological Measurements: Pupillometry and Heart-Rate Variability.

The adoption of Industry 4.0 technologies in manufacturing systems has accelerated in recent years, with a shift towards understanding operators' well-being and resilience within the context of creating a human-centric manufacturing environment. In addition to measuring physical workload, monitoring operators' cognitive workload is becoming a key element in maintaining a healthy and high-performing working environment in future digitalized manufacturing systems. The current approaches to the measurement of cognitive workload may be inadequate when human operators are faced with a series of new digitalized technologies, where their impact on operators' mental workload and performance needs to be better understood. Therefore, a new method for measuring and determining the cognitive workload is required. Here, we propose a new method for determining cognitive-workload indices in a human-centric environment. The approach provides a method to define and verify the relationships between the factors of task complexity, cognitive workload, operators' level of expertise, and indirectly, the operator performance level in a highly digitalized manufacturing environment. Our strategy is tested in a series of experiments where operators perform assembly tasks on a Wankel Engine block. The physiological signals from heart-rate variability and pupillometry bio-markers of 17 operators were captured and analysed using eye-tracking and electrocardiogram sensors. The experimental results demonstrate statistically significant differences in both cardiac and pupillometry-based cognitive load indices across the four task complexity levels (rest, low, medium, and high). Notably, these developed indices also provide better indications of cognitive load responding to changes in complexity compared to other measures. Additionally, while experts appear to exhibit lower cognitive loads across all complexity levels, further analysis is required to confirm statistically significant differences. In conclusion, the results from both measurement sensors are found to be compatible and in support of the proposed new approach. Our strategy should be useful for designing and optimizing workplace environments based on the cognitive load experienced by operators.

Task complexity and foreign language writing emotions as predictors of EFL writing performance

Emotions and task complexity have gained scant attention in EFL writing. This study, based on control-value theory and a positive psychology perspective, explores the relationship between task complexity, writing anxiety, writing boredom, writing enjoyment, and task complexity and writing emotions interaction on EFL writing performance among English major students in China’s educational context (N = 84). It has been found that difficult writing tasks can result in higher writing anxiety and lower writing boredom. By 6 × 2 between-subject ANOVA, there is a significant interaction of task complexity and different levels of writing anxiety, writing boredom, and writing enjoyment for the dimensions of language fluency, complexity, and accuracy among English major students in China’s educational context. This study is an initial step in extending the writing emotions and task complexity in the production of EFL writing, which promotes the mutual integration of emotion and cognition in EFL writing research and thus supplies suggestions for task-based EFL writing instruction.

Research on Nuclear Power Plant Operational Task Complexity Assessment Method Based on Group Decision Making and Deep Learning of EEG Signals

This study aims to explore the correlation between the operational task complexity of nuclear power plant (NPP) operators and electroencephalogram (EEG) features. Initially, we segmented EEG signals according to operational steps and extracted a total of 120 time domain, frequency domain, and time-frequency domain features. Subsequently, we applied an adaptive principal component analysis (PCA) dimensionality reduction method to process the features. On the other hand, three experts were invited to evaluate the complexity of the operational tasks, and their evaluation data were synthesized using a group decision-making approach. A correlation analysis was performed between these data and the PCA-reduced feature data, identifying the features with the highest correlation coefficient for each participant. Then we built a long short-term memory model with the data of the first group of participants to predict the task complexity value and tested it with the data of the second group of participants. Testing the model with data from the second group yielded favorable results, with a training set mean squared error (MSE) of 0.025 and a testing set MSE of 0.078. The results of this study indicate a significant correlation between specific EEG features and task complexity in the operational tasks of NPP operators. The model established through a combination of group decision making and machine learning methods effectively predicted the task complexity levels for operators in different operational tasks. This research provides a new perspective on NPP operators’ cognitive load and operational tasks, holding practical significance for operator training and workload management.

Psychological assessment of event-related motor potential in different brain regions in carrying out simple and complicated tasks

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.

Task complexity and task type

Abstract In Task-Based Language Teaching (TBLT), there is clearly a need for a balanced and flexible view of L1 use. Considering this, a matter of concern in TBLT is that learners might overuse their first language (L1) while performing complex tasks. To test this speculation, the present study investigated the effects of manipulating task complexity along resource-directing variables (+/− reasoning demands) of the Cognition Hypothesis on L1 use and its functions. Further it aimed to test the impacts of task type on L1 use and its functions. To do so, the interaction of 24 intermediate EFL learners while completing two different task types with two levels of task complexity was analyzed. The analysis of L1 words and turns indicated that both task complexity and task type affected L1 use significantly. The results further indicated that L1 was employed for a variety of purposes which were mainly affected by task complexity.

"Uncertainty and predictiveness modulate attention in human predictive learning": Correction to Chao, McGregor, and Sanderson (2020).

Reports an error in "Uncertainty and predictiveness modulate attention in human predictive learning" by Chang-Mao Chao, Anthony McGregor and David J. Sanderson (Journal of Experimental Psychology: General, Advanced Online Publication, Nov 30, 2020, np). In the article, formatting for UK Research Councils funding was omitted. The author note and copyright line now reflect the standard acknowledgment of and formatting for the funding received for this article. All versions of this article have been corrected. (The following abstract of the original article appeared in record 2020-88205-001.) Attention determines which cues receive processing and are learned about. Learning, however, leads to attentional biases. In the study of animal learning, in some circumstances, cues that have been previously predictive of their consequences are subsequently learned about more than are nonpredictive cues, suggesting that they receive more attention. In other circumstances, cues that have previously led to uncertain consequences are learned about more than are predictive cues. In human learning, there is a clear role for predictiveness, but a role for uncertainty has been less clear. Here, in a human learning task, we show that cues that led to uncertain outcomes were subsequently learned about more than were cues that were previously predictive of their outcomes. This effect occurred when there were few uncertain cues. When the number of uncertain cues was increased, attention switched to predictive cues. This pattern of results was found for cues (1) that were uncertain because they led to 2 different outcomes equally often in a nonpredictable manner and (2) that were used in a nonlinear discrimination and were not predictive individually but were predictive in combination with other cues. This suggests that both the opposing predictiveness and uncertainty effects were determined by the relationship between individual cues and outcomes rather than the predictive strength of combined cues. These results demonstrate that learning affects attention; however, the precise nature of the effect on attention depends on the level of task complexity, which reflects a potential switch between exploration and exploitation of cues. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

The Role of Instructions in Motor Learning of Oral Versus Nasalized Speech Targets.

The purpose of this study was to investigate how general, implicit instructions with auditory-perceptual emphasis; specific, explicit instructions with biomechanical focus; or both affect learning of oral-nasal balance control in speech. Thirty healthy, vocally untrained participants were assigned to one of three instructional groups (i.e., implicit, explicit, and integrated) and learned to produce oral versus nasalized vowel-, syllable-, and phrase-level targets during once-weekly sessions over 4 weeks. Learning gains and performance variability were analyzed using nasometry. We observed a significant main effect of instruction type on learning gains at phrase level (p = .016). Specifically, the integrated group (M = 59.8%) significantly outperformed the explicit group (M = 37.9%) and numerically outperformed the implicit group (M = 45.1%). For nasalized phrase targets, results revealed a significant main effect of instruction type on performance variability (p = .042), but pairwise comparisons between instruction groups were not significant. The integration of implicit processes via auditory-perceptual modeling and explicit processes via relevant biomechanical directives resulted in larger motor learning gains, especially at higher levels of task complexity (i.e., phrase) compared to providing implicit or explicit instruction alone. The higher performance variability (i.e., less stable productions) that was sometimes induced by explicit instruction did not negatively impact learning when integrated with implicit instruction. Clinical implications for speech/voice therapy models are discussed.

INTRINSIC, EXTRINSIC AND MNEMONIC FACTORS OF METACOGNITIVE MONITORING ACCURACY

The paper reports upon an investigation of metacognitive monitoring accuracy factors in learning tasks of university students. The experiment explores the contribution of some intrinsic, extrinsic and mnemonic factors such as type of learning material, task type, task complexity, and ease / difficulty of performing to metacognitive monitoring accuracy. The study was conducted among 233 university students. The empirical results show the predominance of metacognitive monitoring accuracy, while underconfidence is a downward trend. MMA (+ +) rates of metacognitive monitoring accuracy can be found in the easiest tasks on recollecting pairs of words and MMA (– –) rates – in general knowledge questions of medium difficulty. Overconfidence appears in the most difficult tasks on the deduction inferences and on the logical analogies. The results confirm the dependence of metacognitive monitoring accuracy on the level of ease / complexity of tasks and ease / difficulty of performing; the level of task complexity affects higher rates of metacognitive judgments’ inaccuracies, in particular, in the form of overconfidence. In open-answer questions there is a predominance of MMA (+ +) and MMA (– –) rates of metacognitive monitoring accuracy; underconfidence and overconfidence rates are also higher in openanswer questions. The more complex the task is, the greater is the confidence in the difficulty of performing. The results can be significant in the process of understanding the relationship between metacognitive monitoring accuracy and learning performance of university students.

Trust in Artificial Intelligent Agent while Completing a Procedural Construction Task

The use of AI-enabled recommender systems in construction activities has the potential to improve worker performance and reduce errors; however, the accuracy of such systems in providing effective suggestions is dependent on the quality of their training data. A within-subjects experimental study was conducted using a simulated recommender system for installation tasks to investigate the effect of system reliability and construction task complexity on worker trust, workload, and performance. Results indicate that overall trust in the AI agent was higher for the highly reliable condition but remained consistent across various levels of task complexity. The workload was found to be higher for low reliability and complex conditions, and the effect of reliability on performance was influenced by task complexity. These findings offer insights for designing recommender systems to support construction workers in completing procedural tasks.

SEX DIFFERENCES IN SELECTIVE AUDITORY ATTENTION DURING DICHOTIC LISTENING WITH DIFFERENT LEVELS OF COMPLEXITY: AN FMRI STUDY

A group of 20 healthy subjects (11 males and 9 females) performed a selective auditory attention task in a dichotic listening paradigm with different levels of perceptual load. Analysis of brain activation patterns measured with fMRI during selective listening to fusion speech with distractors of varying strengths revealed statistically significant sex differences in the topography of cortical activity. “Female male” effects dominated in the left superior temporal gyrus and the left pre and postcentral gyrus; while the most pronounced “male female” effects were found in the left islet, shell and frontal lobule. Statistically significant effects were also obtained by comparing activation patterns according to the level of task complexity: It was shown that masking with a female speaker’s voice caused greater activation of additional high-level information processing areas. The findings indicate the presence of sexual dimorphism in the organization of the selective auditory attention system.

Light phase does not affect operant sucrose self-administration in adult male C57BL/6JAbr mice

Circadian rhythm can have significant impacts on several physiological domains relevant to the expression of behaviour in mice, including body temperature, corticosterone levels, hormones and immune function. Mice are nocturnal; yet many behavioural studies are performed during the light phase, when mice are naturally inactive. Not surprisingly, the time of day when mice are behaviourally tested can significantly impact on domains such as locomotor activity, e.g. dark phase testing results in higher locomotion rates than light phase testing. However, effects on other behavioural domains, such as cognition, are not well-established, with inconsistent reports on improved cognition during dark phase testing compared to light phase testing in mice. Importantly, the impact of circadian rhythm on operant responding, a common task relevant to research into drug abuse and cognitive disorders, has rarely been investigated in mice. Here we evaluated if testing adult male C57BL/6JAbr mice in operant chambers during the light or dark phase affects acquisition of lever responding, lever discrimination under different fixed ratio (FR) schedules (FR1, FR2, FR4), and/or motivation under a progressive ratio schedule for 10% oral sucrose. We found no effect of circadian rhythm on levels of active and inactive lever pressing, or lever discrimination for oral sucrose at any stage of the experiment. These results may be due to high levels of motivation for sucrose under food restriction and low levels of task complexity limiting detection of any effect of light phase on operant behaviour.

Optimizing Human Performance to Enhance Safety: A Case Study in an Automotive Plant

Human factors play a relevant role in the dynamic work environments of the manufacturing sector in terms of production efficiency, safety, and sustainable performance. This is particularly relevant in assembly lines where humans are widely employed alongside automated and robotic agents. In this situation, operators’ ability to adapt to different levels of task complexity and variability in each workstation has a strong impact on the safety, reliability, and efficiency of the overall production process. This paper presents an application of a theoretical and empirical method used to assess the matching of different workers to various workstations based on a quantified comparison between the workload associated with the tasks and the human capability of the workers that can rotate among them. The approach allowed for the development of an algorithm designed to operationalise indicators for workload and task complexity requirements, considering the skills and capabilities of individual operators. This led to the creation of human performance (HP) indices. The HP indices were utilized to ensure a good match between requirements and capabilities, aiming to minimise the probability of human error and injuries. The developed and customised model demonstrated encouraging results in the specific case studies where it was applied but also offers a generalizable approach that can extend to other contexts and situations where job rotations can benefit from effectively matching operators to suitable task requirements.

Working memory, L2 proficiency, and task complexity: Independent and interactive effects on L2 written performance

AbstractThis study examined the independent effects of working memory (WM) and the interactive effects of WM/L2 proficiency and WM/task complexity on L2 written performance. The study followed a within–between-participant factorial design, with two levels of task complexity as the within-participant variable and L2 proficiency and WM as between-participants variables. The outcome measure was L2 writing performance as measured by CAF indices. Two groups of undergraduate students from a degree in English studies were invited to complete the simple and complex version of the “Fire-Chief” task. Task complexity was operationalized in terms of reasoning demands, and tasks were counterbalanced to avoid unwanted order effects. Participants also completed the Oxford Placement Test and a working memory test (n-back). Regarding independent effects, results show that WM did not have an effect on L2 writing performance. In contrast, L2 proficiency was the variable most connected to various dimensions of the text produced. As for interactive effects, no significant interaction between WM, proficiency, or task complexity was found. In contrast, L2 proficiency emerged as the sole significant predictor of L2 writing performance at both levels of task complexity.

Assessing self-regulated writing strategies, self-efficacy, task complexity, and performance in English academic writing

The present study focused on the assessment of how task complexity and learner variables (English proficiency level, self-regulated writing strategies, and writing self-efficacy belief) influence English academic writing for students in a foreign language context. The participants were 270 students from a medium-sized university in China. All participants completed measures on self-regulated writing strategies, self-efficacy, and an academic writing test. Guided research questions aimed to explore the extent to which task complexity and English proficiency level influenced writing performance along with how learners’ self-efficacy and self-regulated writing strategies mediated the role of task complexity in academic writing performance. Structural equation modelling results showed that task complexity and English proficiency level influenced learners’ writing performance. Self-efficacy beliefs and the use of self-regulated writing strategies mediated the role of task complexity on academic writing performance. Implications related to the assessment of task complexity, self-regulated writing strategies, self-efficacy, and academic writing were discussed.

Is ethical human resource management effective for ethical voice? Role of moral efficacy and moral task complexity

PurposeThe purpose of this study was to examine the underlying mechanism as well as the boundary effect between employees' perceived ethical human resource management (HRM) and ethical voice based on social cognitive theory. The authors expect that employees who perceive ethical HRM could develop their moral reasoning and conduct through one of the cognitive processes (i.e. vicarious experience).Design/methodology/approachBased on structural equation modelling and hierarchical regression analysis, the authors conducted a questionnaire survey on 265 employees and their immediate supervisors from a manufacturing company in China.FindingsEmployees' perceived ethical HRM was positively related to ethical voice, and moral efficacy mediated this relationship. Moral task complexity not only moderated the relationship between employees' perceived ethical HRM and moral efficacy but also moderated the indirect effect of employees' perceived ethical HRM on ethical voice such that the impact was stronger when the moral task complexity level is higher and weaker when low.Practical implicationsThis research model provides a framework through which organisations can diagnose potential ethical issues with the implementation of ethical HRM, as well as increase employee awareness of ethical values and then enhance their moral efficacy. Moreover, organisations can benefit from combining interventions and practices that influence the task design.Originality/valueThis study fills research gap by examining the mechanisms that shape employees' ethical voice from the perspective of HRM through moral efficacy and demonstrates that higher levels of moral task complexity contribute to higher levels of moral efficacy and ethical voice.

Cognitive tasks and combined statistical methods to evaluate, model, and predict mental workload.

Mental workload (MWL) is a concept that is used as a reference for assessing the mental cost of activities. In recent times, challenges related to user experience are determining the expected MWL value for a given activity and real-time adaptation of task complexity level to achieve or maintain desired MWL. As a consequence, it is important to have at least one task that can reliably predict the MWL level associated with a given complexity level. In this study, we used several cognitive tasks to meet this need, including the N-Back task, the commonly used reference test in the MWL literature, and the Corsi test. Tasks were adapted to generate different MWL classes measured via NASA-TLX and Workload Profile questionnaires. Our first objective was to identify which tasks had the most distinct MWL classes based on combined statistical methods. Our results indicated that the Corsi test satisfied our first objective, obtaining three distinct MWL classes associated with three complexity levels offering therefore a reliable model (about 80% accuracy) to predicted MWL classes. Our second objective was to achieve or maintain the desired MWL, which entailed the use of an algorithm to adapt the MWL class based on an accurate prediction model. This model needed to be based on an objective and real-time indicator of MWL. For this purpose, we identified different performance criteria for each task. The classification models obtained indicated that only the Corsi test would be a good candidate for this aim (more than 50% accuracy compared to a chance level of 33%) but performances were not sufficient to consider identifying and adapting the MWL class online with sufficient accuracy during a task. Thus, performance indicators require to be complemented by other types of measures like physiological ones. Our study also highlights the limitations of the N-back task in favor of the Corsi test which turned out to be the best candidate to model and predict the MWL among several cognitive tasks.