From Implicit Theories to Creative Achievements: The Mediating Role of Creativity Motivation in the Relationship between Stereotypes,Growth Mindset,and Creative Achievement

Research has demonstrated that implicit theories of creativity are crucial in shaping an individual’s behavior and real‐life decisions toward being creative. The present study proposed and examined the underlying mechanisms of how two kinds of implicit theories—the growth mindset of the creative self and the stereotype of creative others—are associated with creative achievements through the mediating role of creativity motivation. Participants were 606 undergraduate students who were enrolled in an education major in two universities in China. Overall, the study found that Chinese students held a positive image toward a creative student, regarding him or her as highly competent, warm, and popular. Student perceptions of a creative other were positively related to their growth mindset of creativity. Moreover, results verified both the mediating role of creativity motivation on growth mindset, as well as the effect of positive stereotyping of the creative other on students’ creative achievement. These findings point to promising creativity motivation strategies including the cultivation of a malleable view of creativity and of creative role models, that may, in turn, promote creative achievement by encouraging students to do, learn, and accomplish new things.     

初中生友谊质量与孤独感的变化轨迹:一项多元潜变量增长模型分析

为考察初中生友谊质量与孤独感的变化轨迹及两者间的关系,采用关系网络问卷、孤独感量表对西安市的875名初中生（M=12.73±0.18;男生494名）进行三年追踪测量,使用多元潜变量增长模型进行分析。结果发现：（1）初中三年,中学生的友谊质量逐渐提高,孤独感水平逐渐下降;（2）初一时的友谊质量和孤独感水平存在显著的个体差异,初中三年期间二者的发展速度也存在个体差异;（3）初一时的友谊质量可显著预测初一时的孤独感水平（β=-1.77,p<0.001）及随后的发展速度（β=0.20,p<0.05）;（4）男生的孤独感水平初始值高于女生,友谊质量的初始值则低于女生;高SES个体孤独感的起始值高于低SES个体。本研究结果揭示了初中三年期间个体友谊质量与孤独感的动态变化关系及友谊质量对孤独感的预测作用,对改善青少年孤独感的现状有一定的现实指导意义。     

Dynamics Versus Development in Numerosity Estimation: A Computational Model Accurately Predicts a Developmental Reversal

Perceptual judgments result from a dynamic process, but little is known about the dynamics of number-line estimation. A recent study proposed a computational model that combined a model of trial-to-trial changes with a model for the internal scaling of discrete numbers. Here, we tested a surprising prediction of the model—a situation in which children's estimates of numerosity would be better than those of adults. Consistent with the model simulations, task contexts led to a clear developmental reversal: children made more adult-like, linear estimates when to-be-estimated numbers were descending over trials (i.e., backward condition), whereas adults became more like children with logarithmic estimates when numbers were ascending (i.e., forward condition). In addition, adults’ estimates were subject to inter-trial differences regardless of stimulus order. In contrast, children were not able to use the trial-to-trial dynamics unless stimuli varied systematically, indicating the limited cognitive capacity for dynamic updates. Together, the model adequately predicts both developmental and trial-to-trial changes in number-line tasks.     

Performance of Mental Health Counselors in Integrated Primary and Behavioral Health Care

Integrated primary and behavioral health care (IPBH) is becoming a preferred mode of service delivery in the United States. Integrated care includes the participation of medical and mental health professionals, such as mental health counselors. The clinical outcomes of these professionals need to be studied to determine their effectiveness in such settings. We examined the performance of 10 mental health counselors on the clinical outcome of 1,747 clients treated in an IPBH center. Analyses using growth curve modeling and pre‐post test design revealed that mental health counselors were effective overall, but they differed in client dropout rates and efficiency in reducing clients' initial symptoms. We used the analyses to rank order counselors based on their effectiveness. Counselors who were the most effective varied in their efficiency but demonstrated the lowest client dropout rates. Implications for future research and counseling practice were discussed.     

Adaptations in driver deceleration behaviour with automatic incident detection: A naturalistic driving study

Traffic congestion and crash rates can be reduced by introducing variable speed limits (VSLs) and automatic incident detection (AID) systems. Previous findings based on loop detector measurements have revealed that drivers reduce their speeds while approaching traffic congestion when the AID system is active. Notwithstanding these behavioural effects, most microscopic traffic flow models assessing the impact of VSLs do not describe driver response accurately.This study analyses the main factors that influence driver deceleration behaviour while approaching traffic congestion with and without VSLs. The Dutch VSL database was linked to the driver behaviour data collected in the UDRIVE naturalistic driving study. Driver engagement in secondary tasks and glance behaviour were extracted from the video data. Linear mixed-effects models predicting the characteristics of deceleration events were estimated.The results show that the maximum deceleration is high when approaching a slower leader, when driving at high speeds and short distance headways, and close to the beginning of traffic congestion. The minimum time headway is short when driving at high speeds and changing lanes. Certain drivers showed higher decelerations and shorter time headways than others. Controlled for these main factors, smaller maximum decelerations were found when the VSLs were present and visible, and when the gantries were within close proximity. These factors could be incorporated into microscopic traffic simulations to evaluate the impact of AID systems on traffic congestion more realistically. Further research is needed to clarify the link between engagement in secondary tasks, glance behaviour and deceleration behaviour.     

Trust and intention to use autonomous vehicles: Manufacturer focus and passenger control

Autonomous Vehicle (AV) research has focused on public acceptance of and intention to use AVs, with trust emerging as important to these variables. Research on AV trust has centered on trust in vehicle performance. However, trust evaluation may include AV manufacturers and developers, and regulation pertaining to AVs; thus, we expand our measurement of trust to include beliefs based on manufacturers and regulation. In this experiment, we manipulate information regarding manufacturer focus (i.e., an emphasis on standards, regulations, and research (SRR) versus speed to market) to determine its effect on trust. When information focused on SRR, we found higher levels of trust in AV performance and in manufacturers, compared to when it focused on speed to market. In addition, information regarding passenger control (i.e., the ability to take over for the vehicle and to determine privacy settings) was manipulated to yield either high or low passenger control conditions. Behavioral Intention (BI) to use AVs was lowest when speed to market was emphasized and when passenger control was low. Furthermore, trust was tested as a mediator between perceived risk and BI. Trust in AV performance partially mediated the relationship between perceived AV performance risk and BI. In addition, trust in AV regulation partially mediated the relationship between AV privacy/security risk and BI. Researchers should continue to examine trust beyond the AV itself to encompass trust in manufacturers and regulations. Those designing and marketing AVs should carefully consider decisions that influence manufacturer/developer reputation and passenger control due to their effect on intention to use AVs.     

Learning algorithm for an intelligent decision making system based on multi-agent neurocognitive architectures

The paper presents the formalism of an intelligent decision-making system based on multi-agent neurocognitive architectures, which has an architectural similarity to the human brain. An invariant of the organizational and functional structure of the intellectual decision-making process based on the multi-agent neurocognitive architecture is developed. An algorithm for teaching intelligent decision-making systems based on the self-organization of the invariant of multi-agent neurocognitive architectures is presented. Using this algorithm, an intelligent agent was trained and the architecture of the learning process was built on the basis of an invariant of neurocognitive architecture. Further research is related to training an intelligent agent in more complex behavior and expanding the capabilities of an intelligent decision-making system based on multi-agent neurocognitive architectures.     

Modeling talent development pathways in alpine ski racers

We explore developmental pathways to excellence in sub-elite adolescent alpine ski racing by exploring athletes' engagement in practice activities that characterize sport specialization and/or diversification. Moreover, we extend previous research by using more refined linear mixed-effects models to examine changes in practice and performance data over time rather than relying on the less sensitive repeated measures ANOVAs typically used in previous research. Altogether, 174 individuals (M = 15.9 yrs, women = 91) from professional development academies in the United States completed a sport-specific Practice History Questionnaire (PHQ). We recorded national rankings in technical events to assess performance. Mixed-effects models indicated that hours in ski-related activities generally increased over time (linear β = 1.38, p's < 0.001), except time spent in play, which decreased over time (β = 102.8, p = 0.002). Performance rankings also improved over time (β = 30.99, p < 0.001), with more time spent in ski-activity associated with greater rates of improvement, particularly in younger skiers (β = 9.77, p's < 0.001). The effects were largely driven by time spent in coach-led group practice (β = 2.16, p < 0.001). Overall, an earlier age of first engagement was associated with better rankings (β = −15.40, p = 0.024), and accumulating more hours in other sports was also associated with greater rates of performance improvement (β = −8.87, p = 0.014). Sub-elite alpine ski racers engage early in the sport, with higher-ranked athletes spending more time in ski-specific practice, particularly group practice, during development. However, these athletes generally continued to participate in other sports across development, providing greater support for the early engagement hypothesis rather than early specialization per se.     

多级评分认知诊断模型述评

认知诊断评估旨在探讨个体内部的知识掌握结构,并提供关于学生优缺点的详细诊断信息,以促进个体的全面发展。当前研究者已开发了大量0-1评分的认知诊断模型,但对于多级评分认知诊断模型的研究还比较少。本文对已有的多级评分认知诊断模型进行了归纳,介绍了模型的假设,计量特征以及适用范围,为实际应用者和研究者在多级评分认知诊断模型的比较和选用上提供借鉴和参考。最后,对未来关于多级评分诊断模型的研究方向进行了展望。     

这不是我想象中的工作！不合规任务对新员工工作投入的影响

本研究基于情绪的认知评价理论,探讨了不合规任务对新员工工作投入的动态影响机制。通过收集分析71名新员工连续5个工作日的追踪数据发现,不合规任务会诱发新员工的不愉快情绪,进而影响其工作投入,工作成长观能够有效缓冲这一负面影响。以上结论拓宽了不合规任务的影响后果,并为如何干预不合规任务给新员工带来的消极影响提供了启示。