Level Of Effort Research Articles (Page 1)

Science textbooks often include text and diagrams to aid learner understanding. Yet traditional written instructions in textbooks often separate them, which can increase cognitive load and hinder effective learning. This research proposes and tests a novel presentational format for written instruction that incorporates spatial contiguity, numbered reading sequences, and color matching, aiming to enhance science learning. The effectiveness of the novel format was assessed through two randomized experimental studies. The first study involved 349 high school students in a popular science context, and the second included 187 students in a complex physics course. The results revealed statistically significant improvements in students’ learning outcomes and self-perceived understanding when exposed to the novel instructional format. The improvements were particularly notable in the study focused on complex scientific laws in physics. Furthermore, students reported lower levels of mental effort with the novel format compared to traditional formats, particularly in contexts involving more challenging materials. These results align with cognitive load theory in multimedia learning. The novel presentational format can significantly enhance student learning outcomes and understanding level. It offers a practical and more efficient alternative for instructional material design.

Abstract It is generally thought that the better you are at performing a skill, the easier it is for you to perform it. Indeed, effortlessness is often seen as a defining characteristic of expertise. We question the idea that skill improvement invariably coincides with a reduction in the effort it takes to perform it. In place of the idea of effortless expertise, we argue for the view that one key characteristic of athletes, performing artists, and other highly skilled individuals who defy the power law of practice, which states that improvement in skill, while increasing rapidly at first, eventually plateaus, is the ability to maintain a high level of effort in both practice and performance. To support our view, we present a model of attention and conscious motor control in action that helps explain both why automaticity can lead to an improvement plateau and how exerting effort can sometimes enable one to defy the power law of practice.

Educational engagement is defined as the level of involvement, effort, and dedication that students show toward their academic activities, which is reflected in their willingness to become actively involved in the learning process. The purpose of this study was to determine the role of emotions in mediating between cognitive factors, such as motivation and personal values, and engagement. It also aimed to examine how emotions influence dropout intentions in higher education. The Mixed Multifactorial Scale of Educational Engagement (EMMEE) was administered to a sample of 692 students. The results were analyzed using Partial Least Squares Modeling (PLS-SEM) with Smart PLS 4 software. The findings show how motivation and personal values affect emotions, especially positive emotions, and how these emotions affect educational engagement, which reduces dropout intentions. The findings contribute to extending the theoretical framework of the academic engagement construct, contextualizing it within the university setting. They also highlight the central role of positive emotions as a particularly important dimension through which motivation and personal values influence engagement. The results underscore the need to implement methods, resources, and diverse approaches that foster motivation in higher education institutions. This study suggests strategies that should be considered in both dropout prevention plans and student retention policies.

ABSTRACT We study contests in which two groups compete to win (or not to win) a group‐specific public good/bad prize. Each player in the groups can exert two types of effort: one to help her own group win the prize and one to sabotage her own group's chances of winning it. The players in the groups choose their effort levels simultaneously and independently. We introduce a specific form of contest success function that determines each group's probability of winning the prize, taking into account players' sabotage activities. We show that two types of pure‐strategy Nash equilibrium occur, depending on parameter values: one without sabotage activities and one with sabotage activities. In the first type, only the highest valuation player in each group expends positive constructive effort, whereas in the second type, only the player with the lowest valuation (i.e., negative) in each group expends positive sabotage effort.

Abstract Rural environmental governance is the core link of rural revitalization. However, in practice, this model faces problems, such as a shortage of funds, unclear rights and responsibilities, and insufficient motivation. Therefore, by introducing a public–private partnership (PPP) model and based on principal-agent theory, this paper explores how to effectively design an incentive mechanism that will promote rural environmental governance. Firstly, a principal-agent incentive contract model is established, based on the PPP model, in which local governments are the principals and private enterprises are the agents. The analysis results show that, by reducing the risk aversion degree of private enterprises and improving their marginal output benefit coefficient, the investment intensity and effort level in environmental governance can be significantly enhanced. Secondly, in order to incorporate the participation of rural residents, the original model is expanded, and a PPP model principal-agent incentive contract model covering local governments, private enterprises, and rural residents is constructed. The analysis of this model shows that, compared with the non-cooperative model, the environmental governance model with the collaborative participation of local governments and rural residents is superior. Under the cooperative framework jointly constructed by local governments and rural residents, the enthusiasm of private enterprises to participate in environmental governance can be significantly improved by reducing the uncertainty of the external environment, alleviating the risk aversion degree of private enterprises, reducing the cost of environmental governance, and enhancing the overall efficiency of environmental governance. The research conclusions can provide scientific decision-making references for local governments when promoting rural environmental governance by applying the PPP model.

BackgroundIn hypoxemic patients, the respective effects of noninvasive respiratory support strategies on lung injury determinants remain unclear, primarily due to the difficulty of obtaining standardized measurements for all interventions within the same study. We conducted a systematic review and network meta-analysis to assess the effects of noninvasive strategies on transpulmonary driving pressure and inspiratory effort in patients with acute hypoxemic respiratory failure.MethodsWe conducted a systematic search (Ovid MEDLINE, Embase, Scopus, and PubMed) and performed a network meta-analysis of physiological studies involving hypoxemic adults published up to February 16th, 2025. We included studies that assessed inspiratory effort with esophageal manometry under at least two noninvasive respiratory support strategies [standard oxygen, high-flow nasal oxygen (HFNO), noninvasive ventilation (NIV), and continuous positive airway pressure (CPAP)]. Outcomes included transpulmonary driving pressure, inspiratory effort per breath and per minute, respiratory rate, and gas exchange. Treatment effects are displayed as mean differences [95% confidence intervals].ResultsAmong 5876 citations, thirteen studies (n = 312 patients) were included (mean PaO2/FiO2 = 131 (± 48) mmHg, mean respiratory rate = 28 (± 8) breaths*min−1). Compared to standard oxygen, HFNO and CPAP did not affect transpulmonary driving pressure or effort per breath. HFNO and NIV reduced effort per minute (-95 cmH2O*bpm [-140; -49] and -240 cmH2O*bpm [-284; -196], respectively), whereas CPAP did not. NIV lowered effort per breath (-5.9 cmH2O [-7.4; -4.4]) but increased driving pressure (3.4 cmH₂O [1.4; 5.4]). All strategies reduced respiratory rate, with HFNO producing the greatest decrease (HFNO: -5 breaths*min−1 [-6; -4]; CPAP: -2 breaths*min−1 [-4; -1]; NIV: -4 breaths*min−1 [-5; -2]); all interventions improved PaO2/FiO2, with CPAP and NIV showing greater effects than HFNO (CPAP: 67 mmHg [55; 80]; NIV: 82 mmHg [56; 108]; HFNO: 24 mmHg [5; 43]). None of the strategies affected PaCO2. ConclusionsNoninvasive strategies exert distinct physiological effects: HFNO and NIV reduce effort per minute, while only NIV decreases effort per breath but at the cost of increased driving pressure. CPAP has neutral effects on driving pressure and effort. CPAP and NIV provide greater improvements in oxygenation than HFNO. Individualized selection based on effort levels may help balance the benefits and risks of noninvasive support.PROSPERO registration:CRD42024564035.Supplementary InformationThe online version contains supplementary material available at 10.1186/s13054-025-05670-7.

To understand the changes in muscle force control ability and its association to gait biomechanics following anterior cruciate ligament reconstruction (ACLR). Twenty-five participants, 9 months following ACLR, performed isometric quadriceps (20%, 40% and 100% maximum voluntary isometric contraction [MVIC]) and hamstring (20% and 40% MVIC) contractions on an isokinetic dynamometer, tracing a target line. Torque variability using coefficient of variation, and complexity using sample entropy were calculated. Knee moments and knee flexion excursion were calculated from walking gait. Two-way mixed model analyses of variance were used for between-limb comparisons and Pearson's correlations to evaluate the associations between force variables and gait biomechanics. Quadriceps and hamstring torque variability changed depending on the limb and the effort level. Quadriceps variability was higher in the ACLR limb only at maximum effort (p = 0.039, Cohen's d = 0.437). Hamstring variability showed no differences at 40% but lower torque variability (p = 0.035, Cohen's d = -0.448) at 20%. Muscle force complexity was consistently higher in the ACLR limb compared to the noninjured limb, regardless of effort level. Additionally, as effort increased, muscle force became less complex in both limbs. Quadriceps variability was negatively associated with knee moments (r = -0.410, p = 0.042, better force control = higher knee extension moments). Hamstring complexity was positively associated with knee flexion excursion (r = 0.417, p = 0.038). Maximal strength was not associated with any gait biomechanics. Quadriceps and hamstring force control ability are altered and associated with gait biomechanics at 9 months post-ACLR. Rehabilitation should include exercises focused on force control to potentially help restore gait biomechanics. Level IV.

Purpose This study explores how Environmental, Social, and Governance (ESG) information disclosure affects carbon reduction efficiency in the construction industry. It identifies key ESG factors and analyzes the interaction mechanisms between governments and enterprises, aiming to develop a structured framework that promotes transparency, informs policy design, and enhances collaborative governance for sustainable construction. Design/methodology/approach A two-stage research design is employed. First, the DEMATEL-AISM approach is used to examine the causal relationships and hierarchical structure among 14 ESG-related factors, clarifying their influence pathways. Second, an evolutionary game model simulates strategic interactions between governments and construction firms under different parameter settings, including effort levels, environmental benefit coefficients, and reciprocity preferences. Sensitivity analysis is conducted to assess how these variables affect long-term strategic convergence. Findings The DEMATEL-AISM analysis identifies three core ESG drivers with the highest centrality and causal impact in the construction sector: S1 (subsidy and incentive mechanisms), S2 (information-sharing level), and G1 (technological innovation). Evolutionary game simulations reveal that cooperative strategies between governments and enterprises are more likely when the ESG quality standard (S0) exceeds 0.7 or when fixed incentives (SF) remain modest (SF = 0.2). Among all variables, the government's variable compensation coefficient (λ) plays the most decisive role in influencing enterprise disclosure behavior, highlighting the critical role of dynamic incentives in steering collaborative action. Originality/value Unlike prior studies that focus predominantly on empirical assessments or static models, this research integrates causal analysis with dynamic simulation to examine ESG disclosure mechanisms tailored to the construction industry. By modeling the interplay between information-sharing and strategic incentives, it offers a novel perspective on how targeted policy parameters can enhance ESG performance and carbon reduction. The findings provide actionable insights for designing effective incentive frameworks and improving stakeholder collaboration in sustainable construction governance.

As the core engine driving the intelligent transformation of global industries, artificial intelligence (AI) deep learning systems have shown a cross-organizational development trend that breaks through the boundaries of a single organization and profoundly reshaping the global industrial ecosystem. The research findings are as follows: (1) The joint cost-sharing model and the aggregated integration decision-making model demonstrate outstanding effectiveness at the technical incentive mechanism level of AI deep learning. (2) When the initial innovation level of the product is relatively high, the AI deep learning system is positively correlated with the effort level and innovation ability of the participants, in the joint cost-sharing and aggregated integration decision-making model, various entities and the entire AI deep learning system have been optimized. (3) Under the aggregated and integrated decision-making mode, the effort level of participants and subjects towards the AI deep learning system is the highest, and thus the level of the AI deep learning system also reaches the optimal level. Previous studies have overlooked cooperative selection models of AI. This article can effectively enhance the depth of collaboration among entities, improve the level of output, and provide a theoretical path for the timely upgrading and development of AI systems.

Here, we assess the potential of airborne eDNA (airDNA) metabarcoding to characterize arthropod and vertebrate assemblages in a tropical forest. We deployed 28 high-flow air samplers across a 1.5 km2 area on Barro Colorado Island, Panama, over two consecutive 24-hour periods and sequenced captured DNA using general eukaryotic and vertebrate-specific metabarcoding primers. AirDNA sampling detected 1293 arthropod operational taxonomic units (OTUs) with a COI primer set alongside 157 vertebrate OTUs representing birds, mammals, reptiles, amphibians, and fish with a 12S rRNA primer set. Arthropod richness was comparable to that quantified locally with light and Malaise trap surveys, while vertebrate richness exceeded that typically observed with conventional techniques. 76% of the arthropod OTU richness was assigned to Cecidomyiidae species. The level of field and lab effort employed in this study captured approximately 84% of the asymptotic richness for arthropods and 76% for vertebrates, implying that relatively little additional richness would have been quantified with additional effort within the same domain of sampling. Observed and asymptotic richness increased with the number of sites, the number of days a site was sampled, and the number of PCR replicates run per sample, highlighting the need to consider effort for future applications of airDNA to compare richness across systems. These results demonstrate that airDNA metabarcoding can efficiently and non-invasively profile high-diversity tropical terrestrial faunal assemblages.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-20767-3.

Lossless image compression relies heavily on prediction algorithms to reduce spatial redundancy before entropy coding. The JPEG XL standard employs a weighted average predictor that combines four sub-predictors with adaptive weighting; however, it uses fixed initial scaling factors regardless of the image content. This study introduces WOP8 (weighted optimization predictor for 8 sub-predictors), which extends the predictor diversity and optimizes initial weights using a genetic algorithm. Four additional predictors were incorporated—adaptive MED (JPEG-LS), enhanced adaptive median, Paeth (PNG), and GAP-based (CALIC)—forming an eight-predictor ensemble. A genetic algorithm with a population of 30 and 24 generations optimized the weight configurations by minimizing the compressed file size of the training data. Experiments were conducted on the Kodak and Tecnick datasets to evaluate performance and generalizability. The Kodak color dataset showed notable gains: with the weighted average predictor in isolation, WOP8 achieved a 0.24 BPP reduction (2.7% improvement) at high effort levels. Under standard JPEG XL operation mode, improvements were minor but consistent. These results confirm the value of targeted predictor optimization and demonstrate that genetic algorithms can effectively discover dataset-specific weighting patterns, offering a foundation for future component-level enhancements in JPEG XL.

In today's highly competitive business landscape, companies must swiftly adapt to changes and ensure that their employees remain motivated to achieve optimal productivity levels. One crucial factor in enhancing work motivation is the implementation of an effective reward system. This study aims to examine the effect of financial rewards on employee work motivation at SPD Speedometer, an automotive company. Employing a quasi-experimental design with a post-test-only control group, the research involved 60 employees divided into two groups: an experimental group receiving financial rewards and a control group receiving none. Work motivation was measured using a scale adapted from George and Jones (2012), covering three indicators: direction of behavior, level of effort, and level of persistence. The data were analyzed using the Mann-Whitney test, which revealed a significant difference in work motivation between the two groups, indicating that financial rewards substantially enhance employee motivation. These findings align with reinforcement theory and Herzberg's two-factor theory, both of which identify financial incentives as pivotal extrinsic motivators that drive positive work behavior. The practical implication suggests that a well-structured and equitable financial reward system can serve as an effective managerial strategy to boost employee motivation and productivity, particularly in the automotive industry.

Apathy, or loss of motivation, is a prominent syndrome accompanying both Alzheimer's and Parkinson's disease, in addition to other disorders. One approach to understanding motivational loss is to examine the processes underlying goal-directed behaviour. Weighing up rewarding outcomes against the effort costs required to obtain them - effort-based decision-making - is a core computation when deciding to act for outcomes. Whilst a growing body of evidence points to disruption of this computation in people with apathy, which underlying decision parameters drive this disruption, their neural associations, and whether these would generalise or differ across brain disorders has not been examined. People with amnestic mild cognitive impairment and probable Alzheimer's disease (aMCI/pAD) (n=37), Parkinson's disease (PD) undergoing workup for deep brain stimulation (n=51), and healthy controls (n=21) performed a physical effort-based decision-making task (Apple gathering task), and caregiver-rated apathy scores were recorded. Following a model-free analysis of choice data, we utilised a stepwise model-based approach to explore the relationship between latent cognitive processes underlying effort-based decision-making, motivation and brain metrics. First, choices made and reaction times were analysed using drift diffusion modeling to uncover latent cognitive processes. Next, associations between apathy, diagnosis and these latent cognitive processes were examined using linear regression models. Finally, associations between latent cognitive processes altered in apathy and brain structure and connectivity in a priori regions were examined using linear mixed models. Model free analysis of choice data showed that apathy in both groups was associated with reduced incentivisation by lower rewards, whereas apathy was associated with increased sensitivity to high effort costs in PD, but reduced sensitivity to effort in aMCI/pAD. Drift diffusion modeling revealed that increased drift rate to reject offers as a function of changing effort levels was significantly associated with lower motivation in PD, but not aMCI/pAD, which was associated with lower fractional anisotropy in the pathways linking the dorsal anterior cingulate cortex and the striatum in PD. Additionally, apathy across participants was associated with bias towards rejecting offers, captured by the decision bias parameter. Furthermore, this bias was associated with increased functional connectivity in the dorsal attention network. In sum, apathy in both aMCI/pAD and PD is associated with alterations in effort-based decision making, but there are differences in these changes with disease type. Disease-specific processes and pathology remain relevant in determining the underlying causes of disrupted motivation, whilst a cross-cutting approach to apathy is still informative from a framework perspective.

This research examines leader–team interactions in agile software development within a global context, with a focus on effort estimation. Drawing on principal–agent theory, we analyse the interaction on the assumption that the Scrum Master guides the development team under imperfect information. We model the interaction as a sequential game with incomplete information. In the first stage, the Scrum Master allocates resources to the development team; in the second stage, the team exerts effort. Both parties are characterised by types that capture their knowledge and skills. As these types are private information, we derive the Bayesian Nash equilibrium to determine the equilibrium effort levels.

Freehand pointing is a fundamental gesture commonly used for cursorless interactions. Prior work in HCI often elicits the same pointing behaviour – facing the target with an outstretched dominant arm and index finger. However, freehand pointing outside of HCI shows more variability across hand pose, usage, and coordination with gaze. To understand what variability exists and how it affects pointing performance, we collected data (N=23) using a hybrid motion capture system. To elicit a wide variety of pointing behaviours we included different levels of user effort and attention, as well as the widest range of target placements studied. We systematically characterised and described three distinct pointing behaviours, each with three different traits, ranging from accurate stereotypical pointing observed in prior works to more casual hip fire-style pointing. Our analysis demonstrates how different pointing behaviours affect pointing performance and highlights their importance when designing interactive systems for more naturalistic freehand pointing.

The present study aimed to investigate changes in muscle mechanical properties (velocity, force, and power) during the seated medicine ball throw (MBT) test under conditions of voluntary reduced effort across various loadings. Twelve males (21.0 ± 1.2 years) performed the MBT against four loadings (0.43 kg, 2 kg, 4 kg, 6 kg) and three effort levels (50%, 75%, and 100%). Results revealed a consistent decrease in absolute velocity was observed across all loading levels (p < 0.01), with the most pronounced alterations at the lowest load (0.43 kg; p < 0.001). In contrast, reductions in absolute force and power under reduced effort were more significant with higher loadings (2–6 kg; p < 0.01). The relative decreases in velocity and force were notably smaller than those in power (p < 0.001), with the relative decrease in power closely following effort instructions across all loadings. These findings highlighting muscle power as a key indicator of effort during loaded submaximal MBT. The study supports the use of loaded submaximal MBT in rehabilitation and exercise programs as an effective method to assess neuromuscular performance and manage exercise intensity for individuals unable to perform at maximum effort.

Arabic language learning opportunities offered by most higher education institutions can be compulsory or elective courses depending on the demands of the university. When studied as an elective course, students will follow it with varying levels of effort based on their own wishes. This study is based on the measurement of student engagement who take basic Arabic as a foreign language course option at Universiti Kebangsaan Malaysia. Specifically, this study was conducted to understand student attitudes in learning Arabic courses. The objective of the study is to identify the attitudes possessed by students when they learn Arabic. In addition, the researcher also intends to classify student attitudes with the aim of knowing the student’s response. Each item in this aspect of the study will also be described by the researcher to be linked to the performance of student engagement. This study uses a quantitative method by involving 49 UKM students who registered for the SKVA 5013 Arabic Language 1 course as a Citra course. An online questionnaire method via Google Forms was used. The study data is the result of a questionnaire instrument adapted into a percentage format. Each learning attitude is assessed as a percentage whether practiced or not. The results of the study found that SKVA 5013 students practiced almost all of the suggested attitudes in question. They showed a positive attitude in learning in addition to implementing an attitude of practicing basic Arabic language skills that coincided with the course structure. Therefore, teachers and coordinators who plan Arabic language teaching at the level of higher education institutions are expected to be able to organize a more conducive academic environment and syllabus so as to successfully achieve all the desired learning goals and produce excellence from the students.

We explore the competitive interaction between military and civilian firms on industrial transfer and Dual-Use Technology (DUT) development employing an evolutionary game theory. This work is intended to examine the effect of some strategic modes (Mix, Spin-In, and Spin-off) on the effort level, income generation and technological advancement. Optimum effort of military and civilian enterprises is analyzed by creating equilibrium conditions while performing the analysis. The study reveals that the Mix mode yields the highest combined effort and revenue for both firms and results in improved performance for both firms than in the other modes. The findings of the simulation study support these outcomes too; the Mix mode accelerates technical advancement more than the other modes; the Spin-In mode is in the middle; and the Spin-Off mode is the slowest. The revenue simulations support these findings where the Mix mode maximizes both personal and overall income for the military and civilian businesses. Therefore, the approach that this research reveals to hold the most effectiveness for the development of DUT, enhancement of industrial transfer and overall economic benefits for both sectors is the Mix mode. These implications are important for policy making involving the fostering of civil-military relations for innovation and technology transfer.

This study investigated how modulating subjective effort influences ball speed and spin rate in table tennis forehand topspin strokes, and examined discrepancies between perceived and actual output. Ten skilled male collegiate players performed strokes at five effort levels (60%, 70%, 80%, 90%, 100%). Objective measures included ball speed and spin rate, while subjective assessments involved introspective ratings of perceived control and strain. Both ball speed and spin rate generally increased with effort, indicating partial success in output modulation. However, under lower effort conditions—particularly for spin—participants exhibited excessive and unstable output, highlighting the difficulty of intentional suppression. Perceived strain increased linearly, while perceived control followed a nonlinear trend, with individual variation and a notable drop at 100%. Performance reproducibility, assessed via coefficient of variation, showed ball speed was less stable at lower efforts, while spin rate peaked in variability at 90%, indicating distinct challenges in regulating output types. These findings suggest that suppressing force demands more refined sensory calibration and self-monitoring than exerting it. Notably, “hitting softly” proved more difficult than maximizing effort, reframing motor control as the regulation rather than the amplification of force. From a practical perspective, training strategies such as visualizing subjective–objective mismatches, setting goals for reproducibility and suppression, and monitoring perceived control and strain may support more stable and self-regulated performance. Incorporating such approaches into coaching could enhance adaptability under variable or high-pressure conditions. This study provides a foundation for perceptual and introspective training strategies that prioritize modulation over maximization in racket sports.

Household food waste remains a persistent challenge despite widespread pro-environmental intentions. Drawing on Brehm’s Motivational Intensity Theory, this study examined how perceived difficulty and perceived ability interact with motivation to predict self-reported food waste. We surveyed 939 participants in Flanders and Spain, measuring motivation to avoid waste, self-rated perceived ability to manage food, meal planning perceived difficulty, and food waste. Moderated moderation analyses revealed that motivation and perceived ability each independently predicted lower waste. Crucially, a significant three-way interaction showed that motivation most effectively reduced waste when perceived difficulty was low and perceived ability was high; when perceived difficulty exceeded perceived ability, motivation had no mitigating effect. These findings underscore that effort mobilization influenced by both individual capacity and situational demands is key to closing the intention–behavior gap in food waste. Practically, interventions should go beyond raising awareness to simplify tasks and bolster consumers’ skills, aligning action demands with realistic effort levels.