THE FUNCTIONS OF ASSESSMENT: IMPLICATIONS FOR SELECTION AND DEVELOPMENT OF DEVICES FOR ASSESSING REPERTOIRES IN CLINICAL,EDUCATIONAL, AND OTHER SETTINGS

An attempt is made to identify the many different functions that assessment of an individual's repertoire can serve. Implications of these functions for the character of and evidence about assessment devices are suggested. The functions fall into two general groups, those which influence decisions regarding an individual learner, and those which influence policy, program development, and scientific knowledge. The first group of functions is presented in a rough chronological sequence such that they form a “behavioral assessment funnel,” beginning with functions involving broad-band assessment to identify likely persons and skill areas, and narrowing to the precise pinpointing, monitoring, and follow-up functions. The contribution of behavior analysis and behavior therapy to assessment methodology in this sequence is identified as well as the areas where more traditionally conceived methods are still useful. The second group of functions and behavioral contributions to it are then discussed.     

INTERACTIONS BETWEEN TEACHER GUIDANCE AND CONTINGENT ACCESS TO PLAY IN DEVELOPING PREACADEMIC SKILLS OF DEVIANT PRESCHOOL CHILDREN1

Token-mediated access to play and snacks was made contingent on completion of academic tasks in the Baseline Experiment. This contingency produced stable completion rates that were subsequently doubled, and then tripled, for four deviant children in a special preschool. A reversal design demonstrated that the contingency was functional in maintaining the children's rates of task completion. The Guidance Experiment examined the role of a social event, teacher guidance, in the acquisition of task-completion skills, in a multiple-baseline-across-tasks design (with reversals). The analysis demonstrated that teacher guidance was an important supplement to the token-mediated contingency in establishing significant increases in task completions for a second group of three deviant children in the special class. The importance of teacher guidance was related to the difficulty level of the children's tasks.     

Losing My Religion as a Natural Experiment: How State Pressure and Taxes Led to Church Disaffiliations between 1940 and 2010 in Germany

The sociological literature has produced a remarkably consistent picture of the quantitative patterns of religious disaffiliations in Western countries. This article argues, and demonstrates, that strong changes in a social context may lead individuals to disaffiliate rapidly, leading to very different aggregate effects from those in the “western model.” We use the unique situation of the separation of Germany from 1949 to 1989 and its subsequent reunification as a “natural experiment” to show just how much the relationships routinely found can be disrupted under changed conditions. The state socialist “treatment” affected religious disaffiliations in East Germany profoundly as it (a) made disaffiliations 10 times more probable in the East than in the West in the 1950s and 1960s, (b) shielded East German church members from factors that led to mass disaffiliations in the West in the late 1960s and early 1970s, (c) reversed the education‐disaffiliation link in the East, thus making disaffiliation more likely among the less educated, and (d) led to an especially strong increase in disaffiliations in the East right after the reunification     

Do early birds share their worms? How prosocial behaviour and empathy vary across the day

Social behaviours have been proposed to follow circadian patterns across the course of the day, but empirical support is mixed. As a within-subject test of circadian effects on everyday behaviour, we conduct an experience-sampling study with a near-representative population of 285 Americans (7405 observations). Prosocial behaviour and empathy were both somewhat more frequent in the morning (d = 0.08). However, these non-linear patterns only described morning-type participants; evening-types had consistent (and lower) rates of prosocial behaviour and empathy across time-of-day. These patterns were explained by morning-types reporting more social opportunities earlier in the day. These findings suggest that small, within-subject diurnal effects on social behaviour occur in daily life, and that some circadian effects may be driven by situation selection.     

Quitters would not prosper: Examining the relationship between online assessment performance and assessment attrition behavior

Hiring managers are often hesitant to implement online assessments over concerns that higher‐quality candidates are more likely to quit lengthy assessment batteries than lower‐quality candidates. In this paper, we present the results of two studies that collectively challenge this assumption. In Study 1, data from 327,517 job‐seekers spanning eight hiring contexts showed that assessment performance was negatively associated with subsequent assessment attrition behavior. In Study 2, we replicated this pattern of effects in two additional samples comprising 1,844,604 applicants for hourly associate positions, and 18,937 applicants for nursing positions. Collectively, these findings suggest that some degree of attrition may ultimately benefit, rather than harm, organizations using prehire assessments.     

自然数码奇象记忆法记忆复杂数字的神经机制

本研究采用学习-再认范式和复杂数字记忆材料,考察自然数码奇象记忆法相对于机械记忆法在记忆提取上的优势及神经机制。行为结果表明,自然数码奇象记忆法比机械记忆法的再认准确率更高。事件相关电位分析结果显示,再认提取阶段奇象记忆条件下诱发的N400和N700波幅显著更低,这说明奇象记忆提取更容易。在自然数码奇象记忆条件下,正确再认旧数字诱发的前额区、左顶枕叶区及中顶枕叶区N700成分与使用自然数码奇象记忆有关。本研究表明,采用自然数码奇象记忆可以减少或跨越语义加工,从而提高个体对材料的记忆效率。     

Decision-making bioinspired model for target definition and “satisfactor” selection for physiological needs

Every person, from an early age, has to make decisions to resolve situations that arise in life. In general, different people make different decisions in the same situation, since decision-making takes into account different factors such as age, emotional state, experience, among others. We can make decisions about situations that we classify as: more important than others, routine, unexpected, or trivial. However, making the correct decision(s) in a timely manner for these situations is one of the most complex and delicate challenges that human beings face. This is due to the arduous mental process required to be carried out. Providing such behavior to a virtual entity is possible through the use of Cognitive Architectures (CAs). CAs are an approach for modeling human intelligence and behavior. This paper presents an functional bioinspired computational decision-making model to satisfy the physiological needs of hunger and thirst. Our proposal considers as black boxes other cognitive functions that are part of a general CA (named Cuäyöllötl or brain in Nahuatl). In the proposed case study, it is proved that the decision-making process plays an essential role in determining the objective and selecting the object that satisfies the established need.     

Detecting anonymous attacks in wireless communication medium using adaptive grasshopper optimization algorithm

Intrusion Detection Systems (IDSs) is a system that monitors network traffic for suspicious activity and issues alert when such activity is revealed. Moreover, the existing IDSs-based methods are based on outdated attacks that unable to identify modern attacks or malicious trends. For this reason, in this study we developed a new multi-swarm adaptive grasshopper optimization algorithm to utilize adaptation mechanism in a group of swarms based on fuzzy logic to protect against sophisticated attacks. The proposed (MSAGOA) technique has the capability of global optimization and rapid convergence that are used to attain optimal feature subsets to identify attack types on IDS datasets. In the MSAGOA technique, learning engine as Extreme learning Machine, Naive Bayes, Random Forest and Decision Tree is applied as a fitness function to select the highly discriminating features and to maximize classification performance. Afterward, select the best classifier which works as a fitness function in our approach to measure the performance in terms of accuracy, detection rate, and false alarm rate. The simulations are performed on three IDS datasets such as NSL-KDD, AWID-ATK-R, and NGIDS-DS. The experimental results demonstrated that MSAGOA method has performed better and obtained high detection rate of 99.86%, accuracy of 99.89% in NSL-KDD and high detection rate of 98.73%, accuracy of 99.67% in AWID-ATK-R and detection rate of 89.50%, accuracy of 90.23% in NGIDS-DS. In addition, the performance is compared with several other existing techniques to show the efficacy of the proposed approach.