Task Level Research Articles

Cardiomyocyte engineering: The meeting point of transcription factors, signaling networks, metabolism and function.

Direct cardiac reprogramming or transdifferentiation is a relatively new and promising area in regenerative therapy, cardiovascular disease modeling, and drug discovery. Effective reprogramming of fibroblasts is limited by their plasticity, that is, their ability to reprogram, and depends on solving several levels of tasks: inducing cardiomyocyte-like cells and obtaining functionally and metabolically mature cardiomyocytes. Currently, in addition to the use of more classical approaches such as overexpression of exogenous transcription factors, activation of endogenous cardiac transcription factors via controlled nucleases, such as CRISPR, represents another interesting way to obtain cardiomyocytes. Therefore, special attention is given to the potential of synthetic biology, in particular the CRISPR system, for the targeted conversion of only certain subpopulations of fibroblasts into cardiomyocytes. However, obtaining functionally and metabolically mature cardiomyocytes remains a challenge despite the range of recently developed approaches. In this review, we summarized current knowledge on the function and diversity of human cardiac fibroblasts and alternative cell sources for invitro human cardiomyocyte models. We examined in detail the transcription factors that initiate cardiomyogenic reprogramming and their interactions. Additionally, we critically analyzed the strategies used for the metabolic and physiological maturation of induced cardiomyocytes.

Enhancing individual task performance and productivity: an ethnographic observational study of supported employment among social services clients in Finland

BackgroundThe purpose of the study was to investigate the various aspects of employees’ work environment, including their job characteristics; the level of support provided by supervisors, job coaches and coworkers; and their perceptions of job performance and productivity from the perspectives of both employees and supervisors in the context of sustainable employability in supported employment interventions. This study was part of the Finnish Work Ability Programme Evaluation Study (2020–2024).MethodsThis study is theoretically informed by the concepts of specific work ability and sustainable employability, as well as how health affects productivity at the task level—approach. The research is based on qualitative data obtained through ethnographic fieldwork, nonparticipating observing with interaction at work, which includes observing employed individuals in their workplaces. Additionally, we recorded discussions, took photos at work, and conducted interviews with supervisors and job coaches.ResultsThe main findings were that persons with disability or decreased work ability were employed in precarious low-productivity work, with limited opportunities for more sustainable employment. Several means from public employment services to decrease the employer’s personnel costs were used. The supervisors appeared to have a strong grasp of each employee’s task-specific productivity level. Supervisors had to adapt their usual tasks to provide extra support for employees, often focusing more on work performance. The role of coworkers and the work community as whole was also important. The personal support of job coaches during the employment phase was crucial, but their role in the workplace was unclear, especially to employers.ConclusionsTo strengthen sustainable careers, the matching of jobs and individuals should be promoted through closer and productivity-oriented cooperation with employers and work communities in vocational rehabilitation and re-employment. The chosen qualitative research strategy, ethnographic fieldwork at work and multi-perspective data collection provided new interpretations of the possibilities for sustainable employability using the Supported Employment method. From the perspectives of both enabling prolonged working careers for employees and providing a clear understanding of task-performance-based productivity to employers, there is a need for more microlevel data on what happens in work and workplaces, particularly the social mechanisms through which results are achieved.

Fine Tuning of an Advanced Planner for Cognitive Training of Older Adults.

Developing effective cognitive training tools for older adults, specifically addressing executive functions such as planning, is a challenging task. It is of paramount importance to ensure the implementation of engaging activities that must be tailored to the specific needs and expectations of older adults. Furthermore, it is essential to provide the appropriate level of complexity for the planning task. A human-centred approach was used to address the issues identified in the design of the tool. Two pilot studies were conducted with older adults to fine-tune the training task and optimize its suitability for them. This also led to an enhancement of the underlying planning engine, transitioning from a simple fast-forward planner (PDDL4J) to an advanced heuristic search planner (ENHSP). The results show that user studies enabled the development of a cognitive training system that gradually increased the proposed difficulty levels of the planning task while maintaining usability and satisfaction among older adults. This highlights the importance of conducting user studies when implementing cognitive training tools for older adults.

Visualizing the Knowledge Domain of Research on Cognates: A Bibliometric Analysis

Cognates constitute an essential aspect of lexical processing, and numerous scholars have made significant contributions to studying their processing patterns, influential variables, and theoretical models. However, there has been a lack of systematic reviews that comprehensively examine the body of research on cognates, including their primary research topics, theories, findings, and future directions. The present study conducted a bibliometric analysis of the 726 recordings from 2001 to 2021 retrieved from the Web of Science database. The results revealed that: (1) studies on cognates were mainly conducted in countries using alphabetic languages; (2) cognate processing remains as the focus in the research domain; (3) cognate effect are modulated by factors at word, task, and participant level; (4) BIA+ model is widely used to account for cognate processing. The limitations and potential implications for future cognate research are discussed.

Screening for Depression and Anxiety Using a Nonverbal Working Memory Task in a Sample of Older Brazilians: Observational Study of Preliminary Artificial Intelligence Model Transferability.

Anxiety and depression represent prevalent yet frequently undetected mental health concerns within the older population. The challenge of identifying these conditions presents an opportunity for artificial intelligence (AI)-driven, remotely available, tools capable of screening and monitoring mental health. A critical criterion for such tools is their cultural adaptability to ensure effectiveness across diverse populations. This study aims to illustrate the preliminary transferability of two established AI models designed to detect high depression and anxiety symptom scores. The models were initially trained on data from a nonverbal working memory game (1- and 2-back tasks) in a dataset by thymia, a company that develops AI solutions for mental health and well-being assessments, encompassing over 6000 participants from the United Kingdom, United States, Mexico, Spain, and Indonesia. We seek to validate the models' performance by applying it to a new dataset comprising older Brazilian adults, thereby exploring its transferability and generalizability across different demographics and cultures. A total of 69 Brazilian participants aged 51-92 years old were recruited with the help of Laços Saúde, a company specializing in nurse-led, holistic home care. Participants received a link to the thymia dashboard every Monday and Thursday for 6 months. The dashboard had a set of activities assigned to them that would take 10-15 minutes to complete, which included a 5-minute game with two levels of the n-back tasks. Two Random Forest models trained on thymia data to classify depression and anxiety based on thresholds defined by scores of the Patient Health Questionnaire (8 items) (PHQ-8) ≥10 and those of the Generalized Anxiety Disorder Assessment (7 items) (GAD-7) ≥10, respectively, were subsequently tested on the Laços Saúde patient cohort. The depression classification model exhibited robust performance, achieving an area under the receiver operating characteristic curve (AUC) of 0.78, a specificity of 0.69, and a sensitivity of 0.72. The anxiety classification model showed an initial AUC of 0.63, with a specificity of 0.58 and a sensitivity of 0.64. This performance surpassed a benchmark model using only age and gender, which had AUCs of 0.47 for PHQ-8 and 0.53 for GAD-7. After recomputing the AUC scores on a cross-sectional subset of the data (the first n-back game session), we found AUCs of 0.79 for PHQ-8 and 0.76 for GAD-7. This study successfully demonstrates the preliminary transferability of two AI models trained on a nonverbal working memory task, one for depression and the other for anxiety classification, to a novel sample of older Brazilian adults. Future research could seek to replicate these findings in larger samples and other cultural contexts.

Acute cannabidiol administration reduces alcohol craving and cue-induced nucleus accumbens activation in individuals with alcohol use disorder: the double-blind randomized controlled ICONIC trial.

Although alcohol use disorder (AUD) is highly prevalent, only a few medications are approved for its treatment leaving much room for improvement. Cannabidiol (CBD) might be a particularly promising candidate, with preclinical data suggesting that CBD is effective in targeting AUD symptoms and disease processes that drive alcohol use and relapse, due to its anti-craving, stress-reducing, and anti-compulsive effects. Here we report data from the double-blind randomized controlled ICONIC trial that compared the effects of a single dose of 800 mg cannabidiol against placebo (PLC) in N = 28 individuals with AUD. Cue-induced nucleus accumbens (NAc) activation, alcohol craving during a combined stress- and alcohol cue exposure session, as well as craving during an fMRI alcohol cue-reactivity task and CBD plasma levels served as outcomes. Individuals receiving CBD showed lower bilateral cue-induced NAc activation (tleft_NAc(23) = 4.906, p < 0.001, d = 1.15; tright_NAc (23) = 4.873, p < 0.001, d = 1.13) and reported significantly lower alcohol craving after a combined stress- and alcohol cue exposure session (Fgroup(1,26) = 4.516, p = 0.043, eta2 = 0.15) and during the fMRI cue-reactivity task (Fgroup(1,24) = 6.665, p = 0.015, eta2 = 0.23). CBD levels were significantly higher in the CBD group (t(25) = 3.808, p < 0.001, d = 1.47) and showed a significant negative association with alcohol craving during the cue exposure experiment (r = -0.394, pFDR = 0.030) and during fMRI (r = -0.389, pFDR = 0.030), and with left and right NAc activation (rleft_NAc = -0.459, pFDR = 0.030; rright_NAc = -0.405, pFDR = 0.030). CBD's capacity to reduce stress- and cue-induced alcohol craving and to normalize NAc activation - a region critical to the pathophysiology of AUD - contribute to understanding the neurobiological basis of its clinical effects and support its potential as a treatment option for AUD. Clinical Trials Registry: DRKS00029993.

Mild behavioral impairment in people with mild cognitive impairment: Are the two conditions related?

Mild cognitive impairment (MCI) and mild behavioral impairment (MBI) are both considered potential prodromal stages of dementia, especially Alzheimer's disease. Previous literature has lacked specific information about MBI in individuals with MCI and associations of several aspects of both, MBI and MCI. Our aim was to investigate whether associations exist between aspects of MBI and aspects of cognitive performance in certain dimensions of the Montreal Cognitive Assessment (MoCA). We used baseline data from the double-blind randomized controlled intervention MCI-CCT-study. Current cognitive performance of individuals with MCI was measured with the MoCA. MBI was assessed with the MBI Shortscale (MBI short), which was administered through a self-report interview. Associations were assessed with Pearson correlations. Sensitivity analyses were conducted for gender and cognition. Group differences were examined with independent samples t-tests or Welch test. Significant correlations were considered in binary logistic regressions under control of covariates. There was no significant correlation between the current MoCA and MBI short scores in the total sample or in the gender-related analysis. Using dichotomized cognitive performance, significant correlations between MCI and MBI were revealed for individuals with lower MoCA scores. On the task level, several significant associations were identified between MoCA dimensions and MBI dimensions in the total sample and in the sensitivity analyses, also under control of covariates. Our findings support the hypothesis that with increasing cognitive decline, the association between MCI and MBI becomes stronger. Furthermore, a certain cut-off on the MoCA must be reached to identify a correlation.

Association of serum‐based mitophagy biomarkers and spatial navigation performance in Alzheimer´s disease

AbstractBackgroundMitophagy is a process of intracellular protein homeostasis through which cells eliminate senescent and dysfunctional mitochondria. Altered mitophagy contributes to Alzheimer´s disease (AD) pathology and is associated with worse cognitive functions. We evaluated association of levels of mitophagy proteins (ULK1, BNIP3L, PINK1, and TFEB in serum and ULK1 and PINK 1 in cerebrospinal fluid [CSF]) with spatial egocentric (body‐centered) and allocentric (world‐centered) navigation performance, which is typically impaired in early stages of AD.MethodParticipants with AD aMCI (n=39), mild AD dementia (n=19), and cognitively normal (CN) older adults (n=20) underwent cognitive assessment and brain MRI. Diagnosis of AD was supported by positivity of AD biomarkers in CSF or amyloid PET imaging. Spatial navigation assessment was performed using real‐space and computerized versions of a human analog of the Morris Water Mate Test (hMWM). The hMWM had four tasks: first, with start position and landmarks (combined allocentric‐egocentric), second, only with start position (egocentric), third, only with landmarks (allocentric), and fourth, with landmarks after 30 minutes (allocentric delayed).ResultLevels of mitophagy proteins in the CN group were not associated with performance in any of the spatial navigation tasks (ps &gt; .091). In the AD aMCI group, higher levels of CSF PINK1 were associated with more accurate spatial navigation performance in the computerized egocentric‐allocentric task (r = ‐0.39; p = .030) and the association of higher levels of CSF ULK1 with worse spatial navigation performance in computerized allocentric delayed task approached statistical significance (r = 0.36; p = .054). Levels of mitophagy proteins in the AD dementia group were not associated with performance in any of the spatial navigation tasks (ps &gt; .068).ConclusionHigher level of CSF PINK1 was associated with more accurate egocentric‐allocentric spatial navigation performance in computerized task and higher levels of CSF ULK were associated with worse allocentric navigation performance. These findings support the hypothesis that normal cognition requires efficient mitophagy and more research is needed to evaluate the role of various mitophagy markers in AD.

A multi-core makespan model for parallel scientific workflow execution in cloud computational framework

Researchers have shown a lot of potential in optimizing cloud-based workload-scheduling over the past few years. However, executing scientific workloads inside the cloud is time-consuming and costly, making it inefficient from both a financial and productivity standpoint. As a result, there are many investigations conducted, with the general trend being to speed up the rate of processing and establish a cost-effective system, whereby customers are billed according to their actual use. In addition, energy-consumption is capable of being reduced, especially if the available resources are heterogeneous; however, few investigations have optimized multi-core with analyzing makespan parameters collectively to fulfill the quality of service (QoS) and service level agreement (SLA) of the workload task. In this research, we introduce an optimal scheduling for a heterogeneous distributed cloud computing environment called task aware makespan optimized scheduler (TAMOS) that guarantees requirements across the task levels of scientific workflows. The energy and time required to carry out specific workflows are significantly reduced by using this TAMOS strategy. The TAMOS framework was studied using the scientific workflows namely, inspiral and sipht. When compared to the conventional method of scheduling work, our methodology used less energy and makespan.

Large language models impact on agricultural workforce dynamics: opportunity or risk?

Motivated by the rapid advancement of large language models (LLMs), this study explores the potential impact of them on agricultural labor market. Starting from the task level of each of the 15 selected occupations, their exposure to LLMs was assessed by rating the extent to which the required abilities are aligned with those of LLMs, taking also into account the importance of the abilities in each occupation. Findings indicate that while LLMs can significantly enhance cognitive functions, they cannot fully replace the physical, psychomotor, and sensory abilities. As a consequence, while certain tasks are either partially or highly susceptible to LLM implementation, a considerable proportion, involving manual responsibilities, remains largely unaffected. It was seen that occupations heavily reliant on data are at greater risk of substitution. Conversely, some occupations will probably experience an augmenting effect, as LLMs will automate certain cognitive routine tasks, freeing up human workers to focus on more creative non-routine aspects. Furthermore, a negative correlation between exposure to LLMs and exposure to robotization was found highlighting the interconnected dynamics between these two variables within the analyzed context. In conclusion, although LLMs can offer substantial benefits, their integration necessitates careful consideration of their inherent limitations to maximize efficacy and mitigate risks in the agricultural sector.

Performance monitoring of improvisation and score-playing in a turn-taking piano duet: An EEG study using altered auditory feedback.

In music ensemble performance, perception-action coupling enables the processing of auditory feedback from oneself and other players. However, improvised actions may affect this coupling differently from predetermined actions. This study used two-person EEG to examine how pianists responded to altered pitch feedback to their own or their partner's actions while they alternated scores or improvised melodies. Feedback-related negativity (FRN) response for self-action was greater in scored than improvised conditions, indicating the enhanced action encoding by playing the score. However, subsequent P3a and P3b responses for self-action were not different across score and improvisation. Further, the P3b response was greater when the two pianists exchanged similar types of melodies (i.e., both improvised or both scores) compared with different types of melodies, suggesting that later cognitive processes may be associated with the task relevance or level of jointness. The presence of the FRN and P3 complex in self-generated improvised action points to the dynamic nature of performance monitoring even without preconceived action plans. In contrast, the FRN and P3 complex in partner-generated improvised actions were subdued compared to the baseline, likely due to the unpredictable nature of the improvised actions of others. Finally, we found a tendency that higher trait empathy was associated with smaller self-action FRN, possibly implying musicians' prioritization of joint goals. Overall, our results suggest that improvisation in a musical turn-taking task may be distinct from score-playing for the earlier processes of performance monitoring, whereas later processes might involve updating a joint representation of the musical context.

Mapping the Creative Process in Arts Education: From Task to Theory

Abstract Creativity stands as a cornerstone of contemporary education, fostering innovation, problem-solving, and dynamic thinking in today’s learners. However, how creativity is defined can vary significantly across different creative fields, contributing to complexity about its nature and role in education. This article explores the definition and application of creativity across various creative arts domains—music, visual art, dance, and drama. This article looks at creativity in these domains at the level of the curriculum, and in examples of classroom tasks. Curriculum analysis showcases alignment among domains with the creative process through its sequential strands—Explore, Develop, Perform, and Explain, specifically in the content relating to Explore—reflecting educational standards that promote structured creativity. Task level analysis reveals how students engage with specific activities mirroring creative stages, fostering meta-awareness of the creative process during learning tasks in drama and music, and evaluating existing artworks’ ability to communicate meaning as in visual art. Theoretical perspectives reveal broad similarities in the creative process across the levels, with nuances such as collaborative processes being more pronounced in dance and drama. Despite limitations such as focussing on a small number of curriculum and task examples, this article provides insight into the commonalities of the creative process across artistic domains and educational levels.

Determining skill mix and optimal multidisciplinary team composition: A scoping review.

Holistic care models aligned to population care needs are needed to help leaders shed pre-existing mindsets when determining skill mix and Multidisciplinary Team (MDT) composition. Using a PRISMA flowchart, a narrow eligibility criterion, and a research question, this scoping review resulted in 9 frameworks/models published between January 2000 and September 2023. Analysis showed common methodological elements such as a population needs-based approach, a systematic process, engagement, three or more professions reporting task or competency level analysis, change advocacy, and reliance on population and workforce supply data. Key system enablers were sponsorship, access to population needs-based and workforce supply data, a learning management system for MDT development, and health human resource policies and governance to drive health system redesign to distribute an equitable workforce. This scoping review offers health leaders and policy-makers options and next-step considerations to inspire fresh thinking for making evidence-informed decisions about skill mix and MDT composition.

Offshore wind project installations: an advanced approach for weather risk assessments

Abstract This paper presents the development of a sequence-based simulation tool for the weather risk assessment of offshore work processes. The approach developed at the Fraunhofer Institute for Wind Energy Systems is the Advanced Weather Time Series Scheduling (Ad-WATSS) method. For statistical significance, this method combines hindcast weather time series of many years with the weather restrictions associated with offshore activities. The method is incorporated into the software tool COAST, where a project plan schedule is simulated by placing activities according to their operational limits, constraints and relationships, and minimum-required time for each operation. A scenario of an offshore wind installation project in the North Sea is used as reference test case for a weather risk assessment using the developed tool and ERA5 weather data. The assessment is then compared with the weather window statistics approach, based on the same weather data sets. The results from both approaches are analysed and compared on a project and task level detail. The results from the sequence-based simulations show that the method is able to capture the long-term variability and extreme events in weather conditions, making it a reliable tool for the simplification of the weather data-based planning, validation, and assessment of offshore projects.

Identifying non-cooperative participation in web-based elicitation of acceptability judgments

In this paper, we discuss different sources of noise or other detrimental effects in the elicitation of experimental data. These effects may emerge due to the loss of control in unsupervised web-based elicitation, be task-related, or emerge due to questionnaire designs that lack sufficient means to identify inapt participants. We describe a stepwise process to reach elicited data at the highest attainable level in web-based Acceptability Judgment Tasks (AJTs). In the first step, the questionnaire design, we focus especially on a careful construction of appropriate filler and control items and introduce an alternative to instructional manipulation checks appropriate for AJTs, namely attention items. The second step is to choose the right platform to elicit experimental data from. Lastly, we will show how to employ latency- and response-based methods – analyses of response times as well as of responses to the specialized items – to reliably detect inapt participants.

Mortality and causes of death in Serbia: redistribution of garbage codes to ischemic heart disease

Abstract Background Cardiovascular diseases are ranked as the number one cause of death in Serbia, and one-fifth of them present ischemic heart disease (IHD). However, the physicians certifying the cause of death have either not been adequately involved in how to complete a death certificate according to the current International Statistical Classification of Diseases (ICD-10) or due to a high level of administrative tasks sometimes fail to complete the process of death certification. That is why we aimed to investigate the garbage codes (GCs) and the effects of their redistribution on underlying cause of death (CoD) estimates for IHD for 2015 and 2020. Methods Data from Belgrade mortality statistics in 2015 and 2020 were used to describe the occurrence and redistribution of garbage codes (GCs), defined as unspecified or impossible causes of death. In order to redistribute GCs we observed the underlying, antecedent, immediate causes and other conditions that contributed to deaths. Redistribution was done by consulting GBD methodology for GC proportional redistribution. The ICD-10 code range for IHD is I20-I25. Results In Belgrade, 17% (4022/23663) and 20.9% (5818/27775) of the deaths were coded with a garbage code in 2015 and 2020, respectively. In 2015, 2102 deaths (10.7% of all well-defined CoD) were attributed to IHD, while in 2020, 1806 (8,2% of all well-defined CoD) deaths were attributed to IHD. Finally, we redistributed a total of 452 deaths (GC type 1 203.9, GC type 2 122.1 and GC type 3 126.2 deaths) and 572 deaths (GC type 1 250.1, GC type 2 110.9, GC type 3 210.7 and GC type 4 22) due to IHD in 2015 and 2020, respectively. These calculations indicate a total number of 2554 and 2378 deaths due to IHD in 2015 and 2020, respectively. Conclusions A more detailed analysis of local practices, as well as continuing medical education in the field of death certification, could be a step forward in the future process of decreasing the number of GCs. Key messages • Since the huge number of deaths was added to ischemic heart disease in 2015 and 2020, it is crucial to focus on a more reliable disease surveillance system including better coding practices. • A deep understanding of the garbage codes and their redistribution could significantly shape future decisions on factors contributing to ischemic heart diseases.

Investigating Lane Departure Warning Utility with Survival Analysis Considering Driver Characteristics

Previous studies have focused on the impact of individual factors on lane departure warning (LDW) utility during driving. However, comprehensive analysis has not been considered based on multiple variables, such as driver characteristics. This paper aims to propose a methodology in exploring the utility of LDW under varied warning timing situations, focusing on changes in driving style and distraction level to obtain the optimal warning timing matching relationship. A driving simulator experiment with a mixed 4 × 3 factor design was conducted. The design matrix includes four level of secondary task (ST) conditions and three warning timings situations for drivers with various driving styles. To estimate the utility of the LDW system, lane departure duration (LDD) was selected as a time-based measure of utility. Both the Kaplan-Meier method and COX model were applied and compared. Combined with questionnaire results, the results indicate that both driving style and distraction state are significant influence factors. Generally, the results suggest that the more aggressive drivers lead to the more severe lane departure behavior and they preferred late warning. In terms of distraction state, the LDD increases with the level of ST remarkably. This implies that the earlier warning timing should be given for the higher-level distraction state condition. It was also observed that adaptive warning timing is needed based on the analysis of the interactive effect among multiple variables. The results provide empirical data for the optimization of LDW system design.

Autonomous Robot Task Execution in Flexible Manufacturing: Integrating PDDL and Behavior Trees in ARIAC 2023.

The Agile Robotics for Industrial Automation Competition (ARIAC) was established to advance flexible manufacturing, aiming to increase the agility of robotic assembly systems in unstructured and dynamic industrial environments. ARIAC 2023 introduced eight agility challenges involving faulty parts, flipped parts, faulty grippers, robot malfunctions, sensor blackouts, high-priority orders, insufficient parts, and human safety. Given the unpredictability of these scenarios, it is impractical to develop a specific strategy for each possible situation. To address these issues, this paper presents a hierarchical framework for autonomous robotic task generation and execution in dynamic scenarios. The framework is divided into a task level and an execution level. Initially, an immediate task management strategy is adopted at the task level, which reasonably decomposes dynamic tasks and allocates short-term tasks to the floor robot and ceiling robot. Later, at the execution level, each robot is designed with an agent architecture that combines PDDL planning with the quick response of behavior trees. Finally, the effectiveness and practicality of the proposed framework were thoroughly validated in ARIAC 2023.

Assessing Difficulty Levels of Mathematical Tasks through Subjective and Behavioral Criteria

Assessing Difficulty Levels of Mathematical Tasks through Subjective and Behavioral Criteria

Impact of goal orientation on moral competence development in youth

The study had two aims. The first was to investigate correlation between specific types of goal orientation as a predictor of prosocial and antisocial functioning and level of moral competences. The second, was to verify whether goal orientation has an impact on the development of moral competences of students participating in a pedagogical intervention based on non-linear pedagogy. Task and Ego Orientation in Sport Questionnaire and Moral Competence Test were used to assess 468 secondary school students aged 15 in goal orientation and moral competences level. There was no correlation between the level of task and ego orientation and the level of moral competence. Under the influence of pedagogical experiment students with high level of task orientation achieved a statistically significantly higher change in the level of moral competences (η2 = 0.04). Study suggests that high level of task orientation is more susceptible to the development of moral competencies. Also, employing a non-linear pedagogy model in physical education, provides a conducive environment for the development of moral competences and should be implemented in the training of future physical education teachers.