In tennis, service requires a variety of complicated movements. Given the importance of taking the initiative to obtain points in a tennis match, it is crucial to make full use of speed and spin rate of service. Generally, a service that requires a higher spin rate would slow down, and a service that has increased speed would have a decreased spin rate. For players who are disadvantaged in height, although controlling spin rate is essential, slowing down service speed should be (...) avoided. For these players, the challenge of service is to improve the speed without decreasing the spin rate. Players must also be trained to build physical strength required for this skill. It is not uncommon to work on physical training without a racket; however, few studies have reported on the effects of cultivated physical strength on on-court tennis performance. Therefore, this study aimed to propose physical measurements that could be used as indices to improve service performance in 58 elite Japanese junior male players. To test service performance, we used TrackMan tennis radar device to assess speed, spin rate, impact height, and impact depth. To test physical strength, we measured 5- and 20-m sprint, broad jump, medicine ball throw. We used a significant multiple regression equation to predict the first service speed obtained from the broad jump and the Medicine ball throw. Additionally, a strong correlation was obtained between the predicted and measured values. In addition to physical strength, we suggest that the depth of the impact point is important for improving the first service speed. However, we were not able to identify the physical strength test items that improve service spin rate. Other item should be examined in the future to determine the physical strength associated with spin rate. This result could help connect physical training and service performance. (shrink)

This article presents a cognitive map proposed to be associated with understanding of the “system concept,” one component of the physics principle of Newton's second low. A definition of the concept is followed by the results of a problem‐solving experiment designed to investigate whether or not good problem solvers possess cognitive structures similar to the one proposed. Think‐aloud protocols were collected as subjects solved a series of physics problems involving Newton's second law. Coding schemes were used to analyze these protocols (...) and to develop a quantitative index intended to reflect the extent to which subjects possessed certain components of the proposed structure. This index proved a highly significant predictor of performance on Newton's second law transfer problems contained in a written exam. In contrast, performance on a set of familiar problems in the same written exam was not a good predictor of performance on transfer problems. These results indicate that cognitive structures that connect the equation ΣF = ma and the concept of choosing appropriate systems are at least part of what constitutes understanding of the principle of Newton's second law. Implications for physics education and problem‐solving research are presented. (shrink)

Recent initiatives to enhance retention and widen participation ensure it is crucial to understand the factors that predict students' performance during their undergraduate degree. The present research used Structural Equation Modeling to test three separate models that examined the extent to which British Psychology students' A‐level entry qualifications predicted: their performance in years 1–3 of their Psychology degree, and their overall degree performance. Students' overall A‐level entry qualifications positively predicted performance during their first year and (...) overall degree performance, but negatively predicted their performance during their third year. Additionally, and more specifically, students' A‐level entry qualifications in Psychology positively predicted performance in the first year only. Such findings have implications for admissions tutors, as well as for students who have not studied Psychology before but who are considering applying to do so at university. (shrink)

Academic performance occupies an important role in adolescent development. It reflects adolescents’ cognitive ability and also shapes their academic and career paths. Students who are satisfied with their school performance tend to show higher self-esteem, confidence, and motivation. Previous research has suggested that students’ problem behaviors, such as Internet Addiction, and academic values, including intrinsic and utility values, could predict satisfaction with academic performance. However, the influence of IA and academic values has not been thoroughly explored in (...) Chinese contexts where the pressure for academic success is heavy. This study examined the relationships between IA, academic values, and satisfaction with academic performance using two waves of data collected from secondary school students in four cities in mainland China. The matched sample included a total of 2,648 Grade 7 or 8 students. Participants completed the same questionnaire containing validated measures at both waves with a 1-year interval. In line with the hypotheses, multiple regression analyses showed that Wave 1 IA was a significant negative predictor of Wave 2 intrinsic value, utility value, and satisfaction with academic performance and their changes. Results of mediation analyses revealed that only intrinsic value, but not utility value, positively predicted satisfaction with academic performance. Structural equation modeling analyses also showed similar findings. Two observations are concluded from the present findings: IA impaired students’ intrinsic value, utility value, and perceived satisfaction with academic performance; two aspects of academic values demonstrated different influences on satisfaction with academic performance. These findings provide implications for the promotion of academic satisfaction experienced by students and the prevention of negative effects of IA. (shrink)

College students have gradually become the main force of entrepreneurship in mass entrepreneurship and innovation. However, their entrepreneurial performance was not as good as expected. We have carried out research to analyze the predictive factors of entrepreneurial performance of college students and put forward targeted suggestions, hoping to be helpful to improve their entrepreneurial performance of them. Based on questionnaire data obtained from 2,097 college student entrepreneurs, this study uses the structural equation model to analyze (...) the predictive factors of the entrepreneurial performance of college students. The survey results of the questionnaire show that both personal and behavioral factors influence the entrepreneurial performance of college students. In this study, personal factors in this study mainly include entrepreneurial willingness, personality, and ability of entrepreneurs. Behavioral factors mainly refer to the positive behaviors of entrepreneurs that can affect entrepreneurial performance. (shrink)

The spacing effect is among the most widely replicated empirical phenomena in the learning sciences, and its relevance to education and training is readily apparent. Yet successful applications of spacing effect research to education and training is rare. Computational modeling can provide the crucial link between a century of accumulated experimental data on the spacing effect and the emerging interest in using that research to enable adaptive instruction. In this paper, we review relevant literature and identify 10 criteria for rigorously (...) evaluating computational models of the spacing effect. Five relate to evaluating the theoretic adequacy of a model, and five relate to evaluating its application potential. We use these criteria to evaluate a novel computational model of the spacing effect called the Predictive Performance Equation. Predictive Performance Equation combines elements of earlier models of learning and memory including the General Performance Equation, Adaptive Control of Thought—Rational, and the New Theory of Disuse, giving rise to a novel computational account of the spacing effect that performs favorably across the complete sets of theoretic and applied criteria. We implemented two other previously published computational models of the spacing effect and compare them to PPE using the theoretic and applied criteria as guides. (shrink)

Student performance and its evaluation remain a serious challenge for education systems. Frequently, the recording and processing of students’ scores in a specific curriculum have several flaws for various reasons. In this context, the absence of data from some of the student scores undermines the efficiency of any future analysis carried out in order to reach conclusions. When this is the case, missing data imputation algorithms are needed. These algorithms are capable of substituting, with a high level of accuracy, (...) the missing data for predicted values. This research presents the hybridization of an algorithm previously proposed by the authors called adaptive assignation algorithm, with a well-known technique called multivariate imputation by chained equations. The results show how the suggested methodology outperforms both algorithms. (shrink)

The fields of machine learning (ML) and cognitive science have developed complementary approaches to computationally modeling human behavior. ML's primary concern is maximizing prediction accuracy; cognitive science's primary concern is explaining the underlying mechanisms. Cross-talk between these disciplines is limited, likely because the tasks and goals usually differ. The domain of e-learning and knowledge acquisition constitutes a fruitful intersection for the two fields’ methodologies to be integrated because accurately tracking learning and forgetting over time and predicting future performance based (...) on learning histories are central to developing effective, personalized learning tools. Here, we show how a state-of-the-art ML model can be enhanced by incorporating insights from a cognitive model of human memory. This was done by exploiting the predictive performance equation's (PPE) narrow but highly specialized domain knowledge with regard to the temporal dynamics of learning and forgetting. Specifically, the PPE was used to engineer timing-related input features for a gradient-boosted decision trees (GBDT) model. The resulting PPE-enhanced GBDT outperformed the default GBDT, especially under conditions in which limited data were available for training. Results suggest that integrating cognitive and ML models could be particularly productive if the available data are too high-dimensional to be explained by a cognitive model but not sufficiently large to effectively train a modern ML algorithm. Here, the cognitive model's insights pertaining to only one aspect of the data were enough to jump-start the ML model's ability to make predictions—a finding that holds promise for future explorations. (shrink)

The competition in higher education has increased, while lecturers are involved in multiple assignments that include teaching, research and publication, consultancy, and community services. The demanding nature of academia leads to excessive work load and stress among academicians in higher education. Notably, offering the right motivational mix could lead to job satisfaction and performance. The current study aims to demonstrate the effects of extrinsic and intrinsic motivational factors influencing job satisfaction and job performance among academicians working in Malaysian (...) private higher educational institutions. Cross-sectional data were collected from the Malaysian PHEIs and the randomly selected 343 samples. The data analysis was performed with the dual analysis of partial least square structural equation modeling and artificial neural network analysis. As a result, it was found that financial rewards, promotion, performance appraisal, classroom environment, and code of conduct significantly predicted job satisfaction. The code of conduct, autonomy, and self-efficacy strongly influenced job performance. The relationship between job satisfaction and job performance was highly moderated by self-efficacy. It was suggested from the ANN analysis that the three prominent factors influencing job satisfaction are financial rewards, performance appraisal, and code of conduct. The analysis supported three significant factors influencing job performance: self-efficacy, performance appraisal, and code of conduct. The management of PHEIs should build the correct policies to transform job satisfaction into job performance. Self-efficacy plays an essential role in activating job performance. Other significant motivating factors that promote job satisfaction and performance, such as emotional intelligence, mindfulness, and other personal traits, should be included in future studies. In addition, future research could use a mixed-method or multi-respondent approach to investigate the important variables and their impact on lecturers’ job satisfaction and performance. (shrink)

The 2019 Pandemic has forced students to take online classes, increasing their stress levels and negatively impacting their academic performance. This issue urges the development of a mechanism to make online learning more effective in this nerve-racking time. Therefore, the present study has integrated the task technology fit model and the DeLone and McLean Model of Information Systems Success to address the stated issue. The data were collected from 330 and 326 students of top-ranked public and private universities of (...) Punjab, respectively. The theoretical framework was analyzed with the help of structural equation modeling using Analysis of Moment Structures. The findings indicate that overall quality positively predicts performance through the mediating role of user satisfaction and TTF. The overall quality also positively elevates performance through the mediating role of user satisfaction and actual usage of the system. Moreover, perceived usefulness proved to be a moderator between overall quality and user satisfaction. Finally, the expected practical and theoretical implications have also been discussed. (shrink)

Does the human mind resemble the machines that can behave like it? Biologically inspired machine-learning systems approach “human-level” accuracy in an astounding variety of domains, and even predict human brain activity—raising the exciting possibility that such systems represent the world like we do. However, even seemingly intelligent machines fail in strange and “unhumanlike” ways, threatening their status as models of our minds. How can we know when human–machine behavioral differences reflect deep disparities in their underlying capacities, vs. when such failures (...) are only superficial or peripheral? This article draws on a foundational insight from cognitive science—the distinction between performance and competence—to encourage “species-fair” comparisons between humans and machines. The performance/competence distinction urges us to consider whether the failure of a system to behave as ideally hypothesized, or the failure of one creature to behave like another, arises not because the system lacks the relevant knowledge or internal capacities (“competence”), but instead because of superficial constraints on demonstrating that knowledge (“performance”). I argue that this distinction has been neglected by research comparing human and machine behavior, and that it should be essential to any such comparison. Focusing on the domain of image classification, I identify three factors contributing to the species-fairness of human–machine comparisons, extracted from recent work that equates such constraints. Species-fair comparisons level the playing field between natural and artificial intelligence, so that we can separate more superficial differences from those that may be deep and enduring. (shrink)

Structural equation model trees are data-driven tools for finding variables that predict group differences in SEM parameters. SEM trees build upon the decision tree paradigm by growing tree structures that divide a data set recursively into homogeneous subsets. In past research, SEM trees have been estimated predominantly with the R package semtree. The original algorithm in the semtree package selects split variables among covariates by calculating a likelihood ratio for each possible split of each covariate. Obtaining these likelihood ratios (...) is computationally demanding. As a remedy, we propose to guide the construction of SEM trees by a family of score-based tests that have recently been popularized in psychometrics. These score-based tests monitor fluctuations in case-wise derivatives of the likelihood function to detect parameter differences between groups. Compared to the likelihood-ratio approach, score-based tests are computationally efficient because they do not require refitting the model for every possible split. In this paper, we introduce score-guided SEM trees, implement them in semtree, and evaluate their performance by means of a Monte Carlo simulation. (shrink)

Research into the roots of ideological extremism has traditionally focused on the social, economic, and demographic factors that make people vulnerable to adopting hostile attitudes toward outgroups. However, there is insufficient empirical work on individual differences in implicit cognition and information processing styles that amplify an individual’s susceptibility to endorsing violence to protect an ideological cause or group. Here we present original evidence that objectively assessed cognitive inflexibility predicts extremist attitudes, including a willingness to harm others, and sacrifice one’s life (...) for the group. Across two samples (N = 1,047) from the United Kingdom and United States, structural equation models demonstrated that cognitive inflexibility predicted endorsement of violence to protect the national ingroup, which in turn predicted a willingness to die for the group. These statistical models accounted for an average of 31.4% of the variance in willingness to die for the group, after accounting for demographic variables. Furthermore, cognitive inflexibility was related to greater confidence in the decision to sacrifice one’s life in an ingroup trolley problem scenario. Analysis of participants’ performance on the cognitive tasks revealed that cognitive rigidity – distinctly from other aspects of cognition – was specifically implicated as a cognitive antecedent of extremist attitudes. Implications for the study of radicalization and identity fusion throug... (shrink)

Flow prediction in a vegetated channel has been extensively studied in the past few decades. A number of equations that essentially differ from each other in derivation and form have been developed. Because the process is extremely complex, getting the deterministic or analytical form of the process phenomena is too difficult. Hybrid neural network model is particularly useful in modeling processes where an adequate knowledge of the physics is limited. This hybrid model is presented here as a complementary tool to (...) model channel flow–vegetation interactions in submerged vegetation conditions. The hybrid model is used to overcome the local minima limitations of a feed-forward neural network. The prediction capability of model has been found to be better than past empirical predictors. The model developed herein showed significantly better results in several model performance criteria compared with empirical models. (shrink)

With the increasing use of mobile devices and new technologies, electronic payments, such as near field communication mobile payments, are gaining traction and gradually replacing the currency-based cash payment methods. Despite multiple initiatives by various parties to encourage mobile payments, adoption rates in developing countries have remained low. The purpose of this research is to explore the prime determinants of NFC mobile-payment adoption intention and to develop a model of mobile payment adoption that includes perceived risk as one of the (...) major elements by extending the UTAUT2 theory components. An online survey was used to acquire data from 370 NFC mobile payments users for the current study. To validate the components and their correlations, structural equation modelling was implemented. According to the findings, performance expectancy, hedonic motivation, social influence, and facilitating conditions have substantial impacts on the consumers’ intentions to adopt NFC mobile payments. Effort expectancy and PR were reported to have no considerable effects on the adoption intention. In addition, INFC is revealed to be a major mediator between the associations of the actual adoption of NFC mobile payment with PE, HM, and SI. The findings of the study would assist providers and marketers in better understanding of the consumers’ behavior, designing effective marketing strategies to enhance the consumers’ positive intentions, and achieving the mass adoption of NFC mobile payments in different environmental contexts. (shrink)

This study tested a structural model of cognitive-emotional explanatory variables to explain performance in mathematics. The predictor variables assessed were related to students’ level of development of early mathematical competencies (EMCs), specifically, relational and numerical competencies, predisposition toward mathematics, and the level of logical intelligence in a population of primary school Chilean students (n = 634). This longitudinal study also included the academic performance of the students during a period of four years as a variable. The sampled students (...) were initially assessed by means of an Early Numeracy Test (ENT), and, subsequently, they were administered a Likert-type scale to measure their predisposition toward mathematics (EPMAT) and a basic test of logical intelligence (TILE). The results of these tests were used to analyse the interaction of all the aforementioned variables by means of a structural equations model. This combined interaction model was able to predict 64.3% of the variability of observed performance. Preschool students' performance in EMCs was a strong predictor for achievement in mathematics for students between 8 to 11 years of age. Therefore, this paper highlights the importance of EMCs and the modulating role of predisposition toward mathematics. Also, this paper discusses the educational role of these findings, as well as possible ways to improve negative predispositions toward mathematical tasks in the school domain. (shrink)

A vast stream of empirical work has revealed that coach and athlete leadership are important determinants of sport teams’ functioning and performance. Although coaches have a direct impact on individual and team outcomes, they should also strive to stimulate athletes to take up leadership roles in a qualitative manner. Yet, the relation between coach leadership behavior and the extent of high-quality athlete leadership within teams remains underexposed. Based on organizational justice theory and the social identity approach, the present research (...) tested whether perceived justice of the coach positively predicts the quality of athlete leadership. Furthermore, we examined the role of group dynamic processes within this relation. Belgian volleyball and basketball players were asked to rate the justice of their coach, their team identification, the task cohesion, and the athlete leadership quality in the team. Structural equation modeling indicated that coaches’ perceived justice positively predicted the quality of athletes’ leadership, and that this relation was established through three intermediate steps. These results suggest that fair coach behavior does not only bridge the gap between leadership and followership, it also has the potential to improve the quality of athletes’ leadership within sport teams. More specifically, findings suggest that coaches’ perceived justice cultivates a shared social identity characterized by high levels of players’ identification with their team, which in turn increased their perceptions of the team’s task cohesion. Finally, this increased task cohesion encouraged the athlete leaders to demonstrate high-quality leadership. (shrink)

Decision Making Competence (DMC) reflects individual differences in rational responding across several classic behavioral decision-making tasks. Although it has been associated with real-world risk behavior, less is known about the degree to which DMC contributes to specific components of risk attitudes. Utilizing a psychological risk-return framework, we examined the associations between risk attitudes and DMC. Italian community residents (n = 804) completed an online DMC measure, using a subset of the original Adult-DMC battery (A-DMC; Bruine de Bruin, Parker, & Fischhoff, (...) 2007). Participants also completed a self-reported risk attitude measure for three components of risk attitudes (risk-taking, risk perceptions, and expected benefits) across six risk domains. Overall, greater performance on the DMC component scales were inversely, albeit modestly, associated with risk-taking tendencies. Structural equation modeling results revealed that DMC was associated with lower perceived expected benefits for all domains. In contrast, its association with perceived risks was more domain-specific. These analyses also revealed stronger indirect effects for the DMC  expected benefits  risk-taking than the DMC  perceived risk  risk-taking path, especially for risk behaviors that may be considered more antisocial in nature. These results suggest that DMC performance differentially impacts specific components of risk attitudes, and may be more strongly related to the evaluation of expected value of the given behavior. (shrink)

As Active Mining is a new concept among data mining and/or knowledge discovery in databases communities, in order to validate the effectiveness, it is important to carry out empirical studies using practical data. Based on the concept of Active User Reaction, this paper develops a causal model from liver function test data in a medical domain. To develop the model, we have set a problem to predict the values of ICG test from given observation data and experts' background knowledge. We (...) therefore employ a framework of meta-learning and structural equation modeling. In this paper meta-learning means learning about mined results from multiple data-mining techniques. Structural equation modeling enables us to describe flexible models from background knowledge. The construction of the causal model contains two phases: meta-learning and the model building. The meta-learning phase utilizes both the linear regression and the neural network as data mining techniques, then examines the predictability on the given data set. Mining models are n-folded learned from the training data set. Each of the prediction accuracy of the mining models is compared using with the testing data. On the model building phase, we use structural equation modeling to develop a causal model based on results of meta-learning and background knowledge. We again compare the accuracy of the causal model with each of the mining models. Consequently we have developed the causal model, which is comprehensible and have good predictive performance, via the meta-learning phase. Through the empirical study, we have got the conclusion that the framework of meta-learning is effective in data mining in a difficult medical domain. (shrink)

This article argues that corporate social responsibility may contribute to product differentiation in export markets and thus improve export performance. We test this argument by observing a period of decreasing export competitiveness in a leading emerging economy. Using a large-scale survey design with 252 questionnaires completed by mediumand large-sized Brazilian exporters, we used structural equations modelling to test our hypotheses. The results suggest that CSR product differentiation predicts export performance better than product quality differentiation and almost as well (...) as product innovation differentiation. Multi- group analysis further revealed that the positive and significant effect of CSR product differentiation on export performance is likely to be contingent on the number and type of countries that are targeted. Our study contributes to the literature on CSR and export performance by developing and empirically validating a model that explains under which conditions CSR-based product differentiation may lead to improved export performance. (shrink)

This article argues that corporate social responsibility (CSR) may contribute to product differentiation in export markets and thus improve export performance. We test this argument by observing a period of decreasing export competitiveness in a leading emerging economy (Brazil). Using a large-scale survey design with 252 questionnaires completed by medium- and large-sized Brazilian exporters, we used structural equations modelling to test our hypotheses. The results suggest that CSR product differentiation predicts export performance better than product quality differentiation and (...) almost as well as product innovation differentiation. Multi-group analysis further revealed that the positive and significant effect of CSR product differentiation on export performance is likely to be contingent on the number and type (developing vs. developed) of countries that are targeted. Our study contributes to the literature on CSR and export performance by developing and empirically validating a model that explains under which conditions CSR-based product differentiation may lead to improved export performance. (shrink)

This study examines the extent to which enabling and controlling uses of management control systems moderate the relationship between environmental innovation strategy and organizational performance. Partial least squares structural equation modeling is used to analyze survey data collected from top managers in 175 manufacturing and services sectors representing multinational and local organizations operating in Sri Lanka. We find that while the enabling use of MCS positively moderates the relationship between environmental innovation strategy and organizational performance, in contrast, (...) the controlling use of MCS negatively moderates the relationship. We compare the results for the manufacturing and services sectors. As predicted, we find a significant positive moderating impact of the enabling use of MCS in both manufacturing and services sectors. However, contrary to our expectations, we find no significant moderating impact for both sectors for the controlling use of MCS. We conclude that environmental innovation strategy per se does not lead to performance improvements; however, the extent to which organizations use enabling and controlling MCS determines the relationship. We provide theoretical insights and practical implications concerning the importance of strategic alignment between managerial controls, environmental innovation strategy, and organizational performance. (shrink)

The present study aimed to examine the relations between physical self-concept, intrinsic and extrinsic motivation as well as physical performance of 1,082 children aged 7–8 years. The central objective of this study was to contrast a mediation model assuming physical self-concept as a mediator of the relations between both types of motivation and physical performance to a mediation model assuming both types of motivation as mediators of the relations between physical self-concept and physical performance. Physical self-concept and (...) both types of motivation were measured by using self-reported questionnaires, while physical performance was measured with 10 motor skill tests. All tests were carried out during regular school hours (8–12 A.M.) by qualified test personnel. Beyond correlation analyses, structural equation modeling (SEM) was performed to find evidence for the predictive relations between the variables under study. Results showed that physical self-concept was significantly positively related to both types of motivation and physical performance (allp< 0.001). In contrast, results of SEM revealed that only physical self-concept (p< 0.001) and intrinsic motivation (p< 0.05) were significantly positively linked to physical performance. Furthermore, physical self-concept proved to significantly mediate the relations of both types of motivation to physical performance (p< 0.001), while only intrinsic motivation, but not extrinsic motivation, proved to significantly mediate the relation between physical self-concept and physical performance (p< 0.05). These results suggest that school-based or extracurricular interventions targeted at improving younger children's physical performance only by means of an increased level of physical activity or by external factors without supporting children's physical self-concept and intrinsic motivation may have less or no effects on their physical performance. (shrink)

The purpose of this study was twofold: to validate the College Teachers’ Academic Frustration Tolerance Questionnaire and the College Teachers’ Academic Performance Questionnaire and to explore the relationship between frustration tolerance and academic performance among college teachers. A total of 25 experts were recruited to modify and validate both questionnaires, and the results showed that the questionnaires had good content validity. Exploratory factor analysis provided further evidence supporting the reliability of the CTAFT and the CTAP, suggesting that the (...) instruments are reliable and valid. Confirmatory factor analysis showed that frustration tolerance affected academic performance, which could best be modeled in the three dimensions of Affect, Preferred Difficulties, and Action. A total of 450 college teachers from each faculty of both universities were then recruited to explore the significant positive correlation between academic frustration tolerance and academic performance. The results from the structural equation model suggested that AC and PD combined significantly predicted academic performance. To our knowledge, this is the first study to explore the relationship between college teachers’ academic frustration tolerance and academic performance in China. (shrink)

Through empirical studies or laboratory tests, previous studies have shown that sport-confidence, attention, and emotion regulation are key factors in archery performance. The present study aims to further identify the effects and pathways of sport-confidence, attention, and cognitive reappraisal on real-world archery performance by constructing a hypothesized model to provide a basis for scientific training of athletes to improve sport performance. A survey design was utilized on a sample of 61 athletes from the Chinese National Archery Team (...) to test the model. The measurement and hypothesized models were tested using partial least squares structural equation modeling. The results indicate that the model fit well and explained 33.6% of the variance in archery performance. Sport-confidence and attention were important predictive indicators of archery performance, while the relationship between cognitive reappraisal and archery performance showed considerable complexity. We conclude that the development of sport-confidence and attention of archery athletes should be strengthened, but athletes who use cognitive reappraisal in archery competition should be mindful of its potential appropriation of cognitive resources and should be directed to improve sport-confidence or develop a positive orientation to arouse excitement. (shrink)

This paper proposes a nonlinear autoregressive neural network method for the investment performance evaluation of state-owned enterprises. It is different from the traditional method based on machine learning, such as linear regression, structural equation, clustering, and principal component analysis; this paper uses a regression prediction method to analyze investment efficiency. In this paper, we firstly analyze the relationship between diversified ownership reform, corporate debt leverage, and the investment efficiency of state-owned enterprises. Secondly, a set of investment efficiency evaluation (...) index system for SOE was constructed, and a nonlinear autoregressive neural network approach was used for verification. The data of A-share state-owned listed companies in Shanghai and Shenzhen stock exchanges from 2009 to 2018 are taken as a sample. The experimental results show that the output value from the NARNET is highly fitted to the actual data. Based on the neural network model regression analysis, this paper conducts a descriptive statistical analysis of the main variables and control variables of the evaluation indicators. It verifies the direct impact of diversified ownership reform on the investment efficiency of SOE and the indirect impact on the investment efficiency of SOE through corporate debt leverage. (shrink)

This study examined the relationship between two types of mathematical flexibility – potential flexibility, which indicates individuals’ knowledge of multiple strategies and strategy efficiency, and practical flexibility, which refers to individuals’ flexible performances when solving math problems. Both types of flexibility were assessed in the domain of linear equation solving. Furthermore, two types of beliefs – self-efficacy and use of flexible cognition – were investigated as potential moderators between potential and practical flexibility. 121 8th grade students from China took (...) part in this study. Results indicate that potential flexibility positively predicted practical flexibility. Additionally, self-efficacy and use of flexible cognition might moderate the relationship between these two types of flexibility, suggesting that potential flexibility may lead to different degrees of practical flexibility depending on different levels of beliefs. Implications of these findings for research on mathematical flexibility and for educational practice are discussed. (shrink)

The present research seeks to utilize Implicit Theories of Intelligence and Achievement Goal Theory to understand students’ intrinsic motivation and academic performance in mathematics in Singapore. 1,201 lower-progress stream students, ages ranged from 13 to 17 years, from 17 secondary schools in Singapore took part in the study. Using structural equation modeling, results confirmed hypotheses that incremental mindset predicted mastery-approach goals and, in turn, predicted intrinsic motivation and mathematics performance. Entity mindset predicted performance-approach and performance-avoidance (...) goals. Performance-approach goal was positively linked to intrinsic motivation and mathematics performance; performance-avoidance goal, however, negatively predicted intrinsic motivation and mathematics performance. The model accounted for 35.9% of variance in intrinsic motivation and 13.8% in mathematics performance. These findings suggest that intrinsic motivation toward mathematics and achievement scores might be enhanced through interventions that focus on incremental mindset and mastery-approach goal. In addition, performance-approach goal may enhance intrinsic motivation and achievement as well, but to a lesser extent. Finally, the study adds to the literature done in the Asian context and lends support to the contention that culture may affect students’ mindsets and adoption of achievement goals, and their associated impact on motivation and achievement outcomes. (shrink)

Equal opportunity requires that persons be selected for desirable positions on the basis of their qualifications. To assess an applicant's qualifications, we must both predict how well he would perform if chosen, and compare his projected performance with that of his rivals. Since we lack direct access to future performance, all such predictions must be based on some past– or present-tense information about the applicants, together with some relevant supporting information. But is any and every way of predicting (...) performance acceptable? Or are some methods of predicting improper even if they are more accurate than any available alternatives? And, if some methods of predicting are improper, which ones are these, and why? (shrink)

Linguistic and non-linguistic pattern learning have been studied separately, but we argue for a comparative approach. Analogous inductive problems arise in phonological and visual pattern learning. Evidence from three experiments shows that human learners can solve them in analogous ways, and that human performance in both cases can be captured by the same models. We test GMECCS, an implementation of the Configural Cue Model in a Maximum Entropy phonotactic-learning framework with a single free parameter, against the alternative hypothesis that (...) learners seek featurally simple algebraic rules. We study the full typology of patterns introduced by Shepard, Hovland, and Jenkins (), instantiated as both phonotactic patterns and visual analogs, using unsupervised training. Unlike SHJ, Experiments 1 and 2 found that both phonotactic and visual patterns that depended on fewer features could be more difficult than those that depended on more features, as predicted by GMECCS but not by rule-seeking. GMECCS also correctly predicted performance differences between stimulus subclasses within each pattern. A third experiment tried supervised training to elicit simple rule-seeking phonotactic learning, but cue-based behavior persisted. We conclude that similar cue-based cognitive processes are available for phonological and visual concept learning, and hence that studying either kind of learning can lead to significant insights about the other. (shrink)

Shifts of attention within working memory based on retroactive (retro-) cues were shown to facilitate performance in working memory tasks. Although posterior asymmetries in the EEG, such as the contralateral delay activity (CDA), have been used to study the active storage of lateralized working memory representations, results on the relation of such asymmetric effects to retro-cue benefits remain inconclusive. We recorded EEG in a retro-cue working memory task with lateralized items and a continuous performance response. Following either a (...) selective or neutral retro-cue, participants adjusted the orientation of a central memory probe to the cued item. Selective retro-cues elicited an early posterior contralateral negativity (PCN), anterior directing attention negativity (ADAN) and a later modulation of CDA indicating that active storage was concentrated on the cued information. By dividing all trials into three within-condition performance quantiles, we could further show that high working memory accuracy was associated with a sustained increase of the CDA effect following the retro-cue. These results suggest that focusing resources on the active storage of relevant representations is an important factor regarding retro-cue benefits in working memory tasks. (shrink)

The study investigated psychometric properties of the Sport Motivation Scale-6, assessing intrinsic regulation, four extrinsic regulation constructs, and amotivation among athletes competing at a regional and national level. In particular, we tested the factorial structure of SMS-6, its short-term stability, and the associations of SMS-6 constructs with self-efficacy, self-esteem, motivational climate, and satisfaction with sport performance. Participants were 197 athletes, representing team and individual disciplines. The measurement was repeated at the three-week follow-up. Results yielded support for the six first-order (...) factor structure. More autonomous forms of motivation were related to higher levels of self-efficacy, performance satisfaction, and taskoriented motivational climate in sport organizations. Sequential multiple mediation analysis showed that the association between general self-efficacy and performance satisfaction at a follow-up was mediated by introjected regulation and personal-barrier self-efficacy. (shrink)

In the last 10 years, emotional intelligence has become a current issue of research in psychology, and there are indicators to consider that emotional intelligence should be analyzed to help the coach to behave effectively during competitions. According to Boardley’s (2018) revised model of coaching efficacy, coaches’ emotional intelligence is predictive of their efficacy beliefs, which, in turn, is predictive of coaching behavior. However, little is known about the mediating effects of coaching efficacy dimensions on the relationships between (...) coach’s emotional intelligence and reactive behaviors in competitive settings. Thus, the purpose of this study is to examine mediating effects of coaching efficacy dimensions on the relationship between emotional intelligence and coaches’ reactive behaviors during a game using a multimethod approach. Participants were 258 coaches of youth football players aged 9 to 17 years old. Observations in situ using Coaching Behavior Assessment System were carried on 258 football games during two seasons. At the end of each game, coaches completed the Wong and Law Emotional Intelligence Scale and the Coaching Efficacy Scale. Structural equation modelling analyses revealed that motivation efficacy and character building mediated the relationship between regulation of emotion and positive and negative coaches’ reactions during game. Specifically, motivation efficacy mediated the association between regulation of emotion and positive coaches’ reactions, and the relationship between regulation of emotion and negative coaches’ reactions were mediated by motivation efficacy and character building. In addition, coaching level moderated the relationships between emotional intelligence, self-efficacy and coaches’ reactive behaviors. Findings of the present study showed that coaching efficacy dimensions (i.e., motivation efficacy and character building) that have the capacity to influence their confidence in ability to affect the psychological mood and positive attitude of athletes, transfer the effects of emotional intelligence (i.e., regulation of emotion) on coaches’ verbal reactions during a youth soccer game. Specifically, a coach who feels competent to regulate their own emotions would perceive high beliefs of efficacy to motivate and to build character of their athletes, and this insight has an impact on their positive verbal reactions in response to athletes’ performances. (shrink)

The purpose is to solve the problem that the current research on the impact of the microstructure of mental elasticity and its constituent factors on the development of the mental elasticity of children is not comprehensive, and the traditional artificial analysis method of mental problems has strong subjectivity and low accuracy. First, the structural equation model is used to study the microstructure of poor children's mental elasticity, and to explore the structural relationship and functional path between the mental elasticity (...) of children and the self-efficacy of their mental health, psychological anxiety, and attachment. Second, a prediction model of mental problems of children in plight based on the backpropagation neural network is constructed. Finally, middle schools in the representative areas of Northwest China are selected as the research unit. The relevant research data are collected by issuing questionnaires, and the data set is constructed to verify the performance of the model. The experimental results show that the average prediction errors of the BPNN model and the support vector regression model are 1.87 and 5.4, respectively. The error of BPNN is 65.4% lower than that of SVR, so BPNN has a better performance. The prediction results of the test set show that the actual error and the relative error of the BPNN model are controlled in the range of 0.01, and the prediction accuracy is high. The structural equation model has a high fitting degree. The results of the questionnaire analysis show that attachment, self-efficacy, and psychological anxiety exert a significant direct impact on mental elasticity. This exploration aims to conduct a micro investigation on the relationship among the three core variables in the resilience research of children in plight, and analyze their resilience, to provide a theoretical basis for the resilience intervention design of vulnerable groups. (shrink)

Purpose Online education can facilitate inclusive societal development. In emerging countries with low investment per capita in school and universities, it helps students overcome infrastructure constraints to continue their learning and reach their full potential, and it helps educational institutes to save costs and improve quality of learning. This study aims to develop and empirically evaluate a conceptual model for predicting digital loyalty (DL) among participants in online accounting courses, as a key lever to execute an inclusive societal development agenda (...) and ensure sustainability of education in an emerging country. Design/methodology/approach The study used quantitative primary data collected from survey questionnaires administered to 167 respondents in India and employed partial least squares structural equation modelling (PLS SEM) to analyse the data. Findings We observed that perceived learning (PL) significantly mediated the relationship between learning performance (LP) and digital loyalty to an online accounting programme. Research limitations/implications Students’ attitudes and preferences have changed remarkably in recent years. Online education encourages participants to complete their courses, learn new and relevant skills, improve their quality of life and recommend online education to others. This facilitates an inclusive, open society with opportunities for all. The results of this study have certain implications. First, as a novel extension of Abrantes et al.’s (2007) work, the DL construct added a new key dimension to the model. Second, the use of PLS Predict introduced methodological rigour to measures such as R2 and blindfolding processes, improving the understanding of the PLS Predict algorithm’s application to prediction studies. Practical implications The study established PL as a mediating variable in the associations between LP and DL and between pedagogical affect (PA) and DL. These findings have practical implications for course design and execution programmes in educational institutes, especially those aiming to democratise education and ensure inclusivity. Online education service providers should focus on equipping students with updated, cross-functional and integrated skills. Originality/value Online education can foster an inclusive and open society by overcoming the twin limitations of geographical distance and infrastructure constraints resulting from scarce learning resources, especially in emerging markets, such as India. The study makes an original contribution by collecting participant data for online accounting courses in India to establish clearly the antecedents of DL. This study empirically demonstrates the role of LP as the most significant antecedent of PL and DL. (shrink)

Exercise plays an important role in the process of socialization among young people and children by providing a context in which children can be exposed to the existing rules and values of society. However, the increasing news of unethical behaviors reported in competitive scenarios led the public to suspect the view “sports shape great characters.” To investigate the issue and explore potential influencing factors, the study examined the relationship among athletes’ perfectionism, achievement goals, and sports ethics based on the achievement (...) goal theory. A total of 243 young athletes were recruited. The multidimensional perfectionism, achievement goals, and sports ethics were measured by a battery of questionnaires. A direct effect model that did not include mediation variables and a mediation effect model that included mediation variables were analyzed by structural equation modeling. Results indicated that perfectionistic strivings may positively predict sports ethics, whereas perfectionistic concerns may negatively predict sports ethics. Mastery approach and mastery avoidance may positively predict sports ethics, whereas the performance approach and performance avoidance may negatively predict sports ethics. Achievement goals may partially mediate the relationship between perfectionism and sports ethics. Perfectionistic strivings may negatively predict sports ethics through performance approach and positively predict sports ethics through mastery approach. Perfectionistic concerns may negatively predict sports ethics through performance avoidance and positively predict sports ethics through mastery avoidance. To prevent athletes from using unethical behaviors, strategies should be developed to reduce perfectionistic concerns and increase their perfectionistic strivings. (shrink)

Wireless sensor networks have been spawning many new applications where cooperative state estimation is essential. In this paper, the problem of performing cooperative state estimation for a discrete linear stochastic dynamical system over wireless sensor networks with a limitation on the sampling and communication rate is considered, where distributed sensors cooperatively sense a linear dynamical process and transmit observations each other via a common wireless channel. Firstly, a novel dynamic variance-based triggering scheme is designed to schedule the sampling of each (...) sensor and the transmission of its local measurement. In contrast to the existing static variance-based triggering scheme, the newly proposed DVTS can lead to the larger average intertrigger time interval and thus fewer total triggering number with almost approximate estimation accuracy. Second, a new Riccati equation of the prediction variance iteration for each estimator is obtained, which switches dynamically among the modes related to the variance of the previous step and the recently received measurements from other sensors. Furthermore, the stability issue is also mainly investigated. Finally, simulation results show the effectiveness and advantage of the proposed strategy. (shrink)

It is usually taken as given that consciousness involves superior or more elaborate forms of information processing. Contemporary models equate consciousness with global processing, system complexity, or depth or stability of computation. This is in stark contrast with the powerful philosophical intuition that being conscious is more than just having the ability to compute. I argue that it is also incompatible with current empirical findings. I present a model that is free from the strong assumption that consciousness predicts superior (...) class='Hi'>performance. The model is based on Bayesian decision theory, of which signal detection theory is a special case. It reflects the fact that the capacity for perceptual decisions is fundamentally limited by the presence and amount of noise in the system. To optimize performance, one therefore needs to set decision criteria that are based on the behaviour, i.e. the probability distributions, of the internal signals. One important realization is that the knowledge of how our internal signals behave statistically has to be learned over time. Essentially, we are doing statistics on our own brain. This ‘higherorder’ learning, however, may err, and this impairs our ability to set and maintain optimal criteria for perceptual decisions, which I argue is central to perception consciousness. I outline three possibilities of how conscious perception might be affected by failures of ‘higher-order’ representation. These all imply that one can have a dissociation between consciousness and performance. This model readily explains blindsight and hallucinations in formal terms, and is beginning to receive direct empirical support. I end by discussing some philosophical implications of the model. (shrink)

In football it was recently demonstrated, that patterns of motivational constructs in young talented football players are relatively stable in early adolescence, and are associated with specific performance related outcomes (Zuber, Zibung, & Conzelmann, 2015). The aim of the present study was to check whether the motivational patterns found in youth elite football also re-emerge in ice hockey, showing similar relations to performance. 135 young male ice hockey talents (MAge = 17.26, SD = 1.24) playing on the highest (...) and second highest level of their age group were questioned about five motivational constructs. Six months later, their coaches rated their players’ current game performance. The results demonstrated a very high similarity of the patterns in ice hockey with the ones earlier found in football. In terms of the transition to performance levels, the highly intrinsically achievement-oriented players were rated by their coaches as belonging to the top-level players significantly more often (OR = 2.6), whereas the non-achievement-oriented failure-fearing players show a higher chance to be rated as part of the lowest performance group (OR = 3.8). The results indicate the importance of achievement motivation for performance in ice hockey also, and this generalizability thus provides relevant clues which are important for consideration in national programs for talent identification across several sports. (shrink)

Experimental engineering models have been used both to model general phenomena, such as the onset of turbulence in fluid flow, and to predict the performance of machines of particular size and configuration in particular contexts. Various sorts of knowledge are involved in the method - logical consistency, general scientific principles, laws of specific sciences, and experience. I critically examine three different accounts of the foundations of the method of experimental engineering models (scale models), and examine how theory, practice, and (...) experience are involved in employing the method to obtain practical results. Models of machines and mechanisms can be (and generally are) involved in establishing criteria for similar phenomena, which provide guidance in using events to model other events. Conversely, models of phenomena such as events that model other events can be (and generally are) involved in experimentation on models of machines. I conclude that often it is not more detailed models or the more precise equations they engender that leads to better understanding, but rather an insightful use of knowledge at hand to determine which similarity principles are appropriate in allowing us to infer what we do not know from what we are able to observe. (shrink)

Insight problem solving was investigated with the matchstick algebra problems developed by Knoblich, Ohlsson, Haider, and Rhenius (1999). These problems are false equations expressed with Roman numerals that can be made true bymoving one matchstick. In a first group participants examined a static two-dimensional representation of the false algebraic expression and told the experimenter which matchstick should be moved. In a second group, participants interacted with a three-dimensional representation of the false equation. Success rates in the static group for (...) different problem types replicated the pattern of data reported in Knoblich et al. (1999). However, participants in the interactive group were significantly more likely to achieve insight. Problem-solving success in the static group was best predicted by performance on a test of numeracy, whereas in the interactive group it was best predicted by performance on a test of visuo-spatial reasoning. Implications for process models of problem solving are discussed. (shrink)

An important task in mathematical sciences is to make quantitative predictions, which is often done via the solution of differential equations. In this paper, we investigate why, to perform this task, scientists sometimes choose to use numerical methods instead of analytical solutions. Via several examples, we argue that the choice for numerical methods can be explained by the fact that, while making quantitative predictions seems at first glance to be facilitated by analytical solutions, this is actually often much easier with (...) numerical methods. Thus we challenge the widely presumed superiority of analytical solutions over numerical methods. (shrink)

The growing threat of terrorism has increased the importance of aviation security and the work of airport security officers (screeners). Nonetheless, airport security research has yet to focus on emotional exhaustion and job satisfaction as major determinants of screeners’ job performance. The present study bridges this research gap by applying the job demands–resources (JD−R) model and using work–family conflict (WFC) as an intervening variable to study relationships between work characteristics (workload and supervisor support), emotional exhaustion, and job satisfaction in (...) 1,127 screeners at a European airport. Results of structural equation modeling revealed that (a) supervisor support as a major job resource predicted job satisfaction among screeners; (b) workload as a major job demand predicted their emotional exhaustion; and (c) WFC proved to be a promising extension to the JD–R model that partially mediated the impact of supervisor support and workload on job satisfaction and emotional exhaustion. Theoretical and practical implications are discussed. (shrink)

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behaviour change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behaviour change scale. Structural equation modelling examined three progressive (...) models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behaviour change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behaviour change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behaviour change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behaviour change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behaviour change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behaviour change. The discussion critically examines these findings in relation to dual-processing frameworks. This includes considering the limitations of current operationalisations and recommendations for future research that align outcomes and subsequent work more closely to specific dual-process models. (shrink)

When Christiaan Huygens prepared the 1686/1687 expedition to the Cape of Good Hope on which his pendulum clocks were to be tested for their usefulness in measuring longitude at sea, he also gave instructions to Thomas Helder to perform experiments with the seconds-pendulum. This was prompted by Jean Richer's 1672 finding that a seconds-pendulum is 1 1/4 lines shorter in Cayenne than in Paris. Unfortunately, Helder died on the voy¬age, and no data from the seconds-pendulum ever reached Huygens. He nevertheless (...) did receive data from his clocks on the return-voyage from the Cape of Good Hope to Texel. When he first calculated the ship's course according to these data, it appeared to have gone straight through Ireland. He then tried introducing a correction to the data, based on an idea he had previously entertained as a possible explanation of Richer's finding: he corrected the observed time to com¬pen¬sate for a reduction in the effect of gravity from the Poles to the Equator resulting purely from the Earth's rotation. His newly calculated course convinced him that this rotational effect is the sole source of any variations in gravity with latitude. This paper examines Huygens's correc¬tions to the data and his reasoning from the new course to the conclusion that nothing else causes a variation in gravity. In the process, we show that Huygens had cogent empirical reasons to reject Isaac Newton's theory of universal gravity, which predicted a some¬what larger variation in gravity. (shrink)