What could be My Next Job? Using Flat Information Structures to Generate Creative Future Career Ideas

In a dynamic labor market, it is important to help people combine information and generate creative solutions to cope with complex career challenges. In the present research, we apply the theory of information structure to creative career idea generation and hypothesize that flat information structures—that is, structures in which the information is disorganized—are more conducive to creativity than hierarchical information structures—that is, structures in which information is organized in higher‐order categories. In two experimental studies, participants had to combine career information related to self and work preferences that was presented either in flat or hierarchical structures. We found that flat information structures, compared with hierarchical information structures, led to future career ideas that were more creative on average. Our results suggest that cognitive flexibility explains the effect of information structure on the creativity of career ideas. Theoretical implications and suggestions for career management practices are discussed.     

Brief Cognitive-Behavioral Therapy for Suicidal Inpatients

Suicide risk is elevated in psychiatric patients following discharge from inpatient care. Despite this vulnerability, there has been limited research investigating suicide prevention protocols that take into account the unique system characteristics of this setting (e.g., short lengths of stay, crisis stabilization treatment model, multidisciplinary team coordination). Cognitive-behavioral therapy (CBT) has demonstrated efficacy for improving suicide risk in outpatients, but has not been validated with inpatients. The current study was a treatment development and pilot feasibility open trial that modified brief cognitive-behavioral therapy (BCBT) for an inpatient setting (BCBT-I). Key treatment modifications included administering up to 10 sessions (depending on patient length of stay), daily, and in a standardized order, with core crisis management skills introduced during the first three sessions. In addition, coordination with the inpatient treatment team was included in BCBT-I implementation. Six adult inpatients with a recent suicide attempt enrolled and completed an average of 4.67 BCBT-I sessions (SD = 1.36). The treatment was highly acceptable (Client Satisfaction Questionnaire total score M = 3.49, SD = 0.73). Pre- to posttreatment effect sizes demonstrated improvements in suicidal ideation (d = 0.97), depression (d = 1.33), and suicidal implicit associations (d = 1.28). All but one of the participants (83%) completed follow-up assessments 1-, 2-, and 3-months postdischarge. Over follow-up, two participants reported suicidal ideation (both without intent), and none reported suicide attempts, preparatory acts or behaviors, or nonsuicidal self-injury. This study provided preliminary evidence supporting the feasibility of CBT to treat suicidal inpatients. Future research is needed to validate BCBT-I in a larger, randomized controlled trial to determine whether BCBT-I reduces suicide risk beyond that afforded by inpatient treatment alone.     

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.     

Cogmic space for narrative-based world representation

Representing a world or a physical/social environment in an agent’s cognitive system is essential for creating human-like artificial intelligence. This study takes a story-centered approach to this issue. In this context, a story refers to an internal representation involving a narrative structure, which is assumed to be a common form of organizing past, present, future, and fictional events and situations. In the artificial intelligence field, a story or narrative is traditionally treated as a symbolic representation. However, a symbolic story representation is limited in its representational power to construct a rich world. For example, a symbolic story representation is unfit to handle the sensory/bodily dimension of a world. In search of a computational theory for narrative-based world representation, this study proposes the conceptual framework of a Cogmic Space for a comic strip-like representation of a world. In the proposed framework, a story is positioned as a mid-level representation, in which the conceptual and sensory/bodily dimensions of a world are unified. The events and their background situations that constitute a story are unified into a sequence of panels. Based on this structure, a representation (i.e., a story) and the represented environment are connected via an isomorphism of their temporal, spatial, and relational structures. Furthermore, the framework of a Cogmic Space is associated with the generative aspect of representations, which is conceptualized in terms of unconscious- and conscious-level processes/representations. Finally, a proof-of-concept implementation is presented to provide a concrete account of the proposed framework.     

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.     

人们何以能够“舍生取义”?基于保护性价值观认知神经机制的解释

保护性价值观是一种拒绝与其他任何价值相互交易, 尤其拒绝与经济价值进行交易的观念。近些年来的认知神经科学研究证据表明, 人们之所以可以为了坚守保护性价值观, 表现出“舍生取义”的行为(如对抗利益诱惑甚至放弃生命), 一方面在于保护性价值观是以一种道义主义的绝对规则方式进行表征和建构的, 这使得人们较少进行利弊权衡; 另一方面, 由于保护性价值观与自我和道德认同过程紧密相关, 使得其被主观赋予了最高价值。未来研究中, 可以在借鉴保护性价值观的研究范式基础上, 开展对中国人核心价值观的实证研究探讨, 关注其文化差异问题, 并进行正确价值观的干预和正确引导的应用实践研究。     

公平规范执行中内群体偏爱的心理发展机制

如何揭示群体规范和公平价值在个体心理发展中的作用机理, 提升儿童-青少年在群际互动当中的公平感知与规范执行, 是教育心理领域的关键问题。公平规范执行中内群体偏爱现象是近年来的研究热点之一, 然而先前研究存在以下不足：1)大多采用问卷法, 易受社会赞许性的影响, 存在言行不一致的情况; 2)大多采用情景实验, 聚焦社会互动的最终行为输出端, 无法实时有效地把握社会决策的动态进程; 3)脑成像研究仍以fMRI技术为主, 侧重于评估认知加工潜在的脑区激活模式及各脑区间的功能连接, 缺乏对群际公平规范执行中大脑激活动态模式的精确把握。针对这些不足, 本项目从资产分配情景出发, 以儿童和青少年为研究对象, 联合运用认知、行为、眼动和电生理等多层次测评手段, 对公平规范执行中内群体偏爱的发生过程进行认知解析, 探讨认知控制和心智化在其间的关键作用机制及其心理发展轨迹。研究结果将服务于中小学管理中的德育教育, 引导与培养学生的公正感与行为。     

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。