Behavioral variability in an evolutionary theory of behavior dynamics

McDowell’s evolutionary theory of behavior dynamics (McDowell, 2004) instantiates populations of behaviors (abstractly represented by integers) that evolve under the selection pressure of the environment in the form of positive reinforcement. Each generation gives rise to the next via low‐level Darwinian processes of selection, recombination, and mutation. The emergent patterns can be analyzed and compared to those produced by biological organisms. The purpose of this project was to explore the effects of high mutation rates on behavioral variability in environments that arranged different reinforcer rates and magnitudes. Behavioral variability increased with the rate of mutation. High reinforcer rates and magnitudes reduced these effects; low reinforcer rates and magnitudes augmented them. These results are in agreement with live‐organism research on behavioral variability. Various combinations of mutation rates, reinforcer rates, and reinforcer magnitudes produced similar high‐level outcomes (equifinality). These findings suggest that the independent variables that describe an experimental condition interact; that is, they do not influence behavior independently. These conclusions have implications for the interpretation of high levels of variability, mathematical undermatching, and the matching theory. The last part of the discussion centers on a potential biological counterpart for the rate of mutation, namely spontaneous fluctuations in the brain's default mode network.     

On initial item selection in cognitive diagnostic computerized adaptive testing

There has recently been much interest in computerized adaptive testing (CAT) for cognitive diagnosis. While there exist various item selection criteria and different asymptotically optimal designs, these are mostly constructed based on the asymptotic theory assuming the test length goes to infinity. In practice, with limited test lengths, the desired asymptotic optimality may not always apply, and there are few studies in the literature concerning the optimal design of finite items. Related questions, such as how many items we need in order to be able to identify the attribute pattern of an examinee and what types of initial items provide the optimal classification results, are still open. This paper aims to answer these questions by providing non‐asymptotic theory of the optimal selection of initial items in cognitive diagnostic CAT. In particular, for the optimal design, we provide necessary and sufficient conditions for the Q ‐matrix structure of the initial items. The theoretical development is suitable for a general family of cognitive diagnostic models. The results not only provide a guideline for the design of optimal item selection procedures, but also may be applied to guide item bank construction.     

Do Smarter People Employ Better Decision Strategies? The Influence of Intelligence on Adaptive Use of the Recognition Heuristic

Within the adaptive toolbox approach, it has repeatedly been shown that, on average, people tend to adapt their decision strategies to the decision context. Building upon these results, we investigated whether individuals systematically differ in their ability to successfully adapt to the situation when applying the fast‐and‐frugal recognition heuristic (RH). In decisions between recognized and unrecognized choice objects, individuals can base their choices solely on recognition, as predicted by the RH, or they can use further knowledge retrieved from memory. Since intelligence has been conceived as the ability to successfully adapt to different situations, we expected intelligence to influence the degree of adaptive use of the RH. To test this hypothesis, we first re‐analyzed data that referred to a decision domain for which RH‐use is known to perform well. As expected, individual RH‐use increased with general intelligence. Next, we designed an experiment addressing individual RH‐use in two new decision domains, one domain for which RH‐use was less effective than knowledge‐use and another domain for which both strategies were about equally effective. In addition, we tested whether fluid or crystallized intelligence best predicts adaptive use of the RH. RH‐use was found to decrease with fluid but not crystallized intelligence when RH‐use was less effective than use of further knowledge. In contrast, there was no significant association between either type of intelligence and RH‐use when none of the two strategies was optimal. We conclude that adaptive use versus non‐use of the RH is moderated by fluid intelligence. Copyright © 2017 John Wiley & Sons, Ltd.     

Computational modeling of organisational learning by self-modeling networks

Within organisational learning literature, mental models are considered a vehicle for both individual learning and organizational learning. By learning individual mental models (and making them explicit), a basis for formation of shared mental models for the level of the organization is created, which after its formation can then be adopted by individuals. This provides mechanisms for organizational learning. These mechanisms have been used as a basis for an adaptive computational network model. The model is illustrated by a not too complex but realistic case study.     

L’accompagnement à la recherche d’un emploi : enjeux,modèles,et perspectives de recherche

What is at stake in the process of elaborating support to provide job seekers with personal advice, both theoretically and practically speaking? All through a review of papers, this article focuses on different theoretical schemes in the process of helping jobseekers to get back to work, but it also details the currently existing support devices and analyses their effects. Eventually it concentrates on the main psychological features taken into account in the process of counseling. As a conclusion, this article examines the perspectives and the consequences of molding and shaping personal counseling for jobseekers from a research angle.     

题库优化设计的回顾与展望

题库优化设计是指在题库建立前确定一份最佳的题库开发蓝图,使题库更好地服务于组卷。目前,在线性计算机化测验的情景下,题库优化设计方法主要包括：线性规划法、成本函数法;在计算机适应性测验（CAT）情境下,题库设计方法主要包括：影子测验设计法、p-优化设计法。文中首先介绍这些优化设计法的基本思路、具体步骤与相关的应用研究,然后评述当前题库设计研究的局限,指出未来的可能研究方向。     

认知诊断CAT中项目曝光控制方法的比较

项目曝光率关系到题库建设和测验安全,是计算机化自适应测验(Computerized Adaptive Testing, CAT)需要考虑的重要问题。在认知诊断 CAT 情形下,首先基于传统 CAT 中 a-分层方法的思想提出按项目信息量对题库分层的分层多阶段(Stratified Multistage, SM)选题方法;然后将 SM 方法与项目合格(Item Eligibility, IE)方法相结合得到SMIE方法。在此基础上,开展模拟研究比较SM、IE、SMIE、最大修正优先指标(Maximum Modified Priority Index, MMPI)方法、限制阈值(Restrictive Threshold, RT)方法和限制进度(Restrictive Progressive, RPG)方法的选题表现。总体上,它们的测量精度从高到低依次为IE、SM、SMIE、RT、RPG和MMPI方法;项目曝光分布均匀性的优劣次序为MMPI、RPG、SMIE、RT、SM和IE方法;SMIE和RT方法能较好地平衡测量精度和项目曝光均匀性要求。     

Coping profiles characterize individual flourishing,languishing, and depression

Abstract

According to the broaden-and-build theory of positive emotions, negative emotions narrow one's thought–action repertoire. In contrast, positive emotions have a broadening effect, expanding cognitive capacity, increasing potential coping strategies that come to mind, and enhancing decision-making, reaction, and adaptation to adversity. Fredrickson and Losada determined that a positivity ratio – the ratio of experienced positive to negative emotions – at or above 2.9 promotes human flourishing. A ratio below 2.9 is indicative of languishing individuals, whereas a ratio below 1.0 is a marker of depression. This study examined whether adaptive and maladaptive coping profiles differentiated those who flourish, languish, or are depressed in two convenience samples – military spouses (n =367) and public school teachers (n=267). Results were consistent with the theoretical predictions, as coping profiles of the groups differed significantly, with flourishing individuals favoring adaptive coping strategies more than those who were languishing or depressed. Conversely, depressed individuals reported greater use of maladaptive coping strategies than those who were languishing or flourishing. These results provide further empirical support for the mathematical model of Fredrickson and Losada, as the set of positivity criteria were predictive of coping profiles in two samples where successful coping and adaptation are important.     

Children's self-reported coping strategies: The role of defensiveness and repressive adaptation

Abstract

This study examined differences in self-reported coping strategies across children classified according to Weinberger et al.'s (1979) adaptive style paradigm. Consistent with the larger literature, it was hypothesized that repressors (i.e. characterized by high self-reported defensiveness and low self-reported distress) would endorse fewer behaviorally and cognitively avoidant coping strategies than other adaptive style groups. Participants included 134 children, ranging in age from 10 to 13 (M=11.26, sd=.59), who completed measures of defensiveness, trait anxiety, and coping. Consistent with the hypotheses, results indicated significantly lower endorsement of avoidant coping strategies, and significantly higher endorsement of approach-oriented strategies among repressors, but no significant differences across adaptive style groups for other forms of coping. Results indicate that, consistent with other indicators of psychological functioning, the measurement of coping strategies is subject to the effects of socially desirable responding. Further, results provide evidence that measures of coping may be contaminated by items reflecting adjustment problems.