数学焦虑个体近似数量加工的神经机制:一项EEG研究

近似数量加工是对大数目物体数量在不依赖逐个数数前提下的估计。行为学研究提示高数学焦虑人群近似数量加工能力下降, 但神经机制未明。本研究探讨高数学焦虑个体近似数量加工的神经机制, 比较高低数学焦虑脑电活动的差异:(1)行为上无显著组间差异; (2)高数学焦虑组的P2p成分波幅增加; (3) δ频段ERS及β频段ERD无显著数量比例效应, 而低数学焦虑组在上述指标的数量比例效应显著。本研究为高数学焦虑人群近似数量加工能力下降提供了电生理学的证据。     

How Experts Adapt Their Gaze Behavior When Modeling a Task to Novices

Domain experts regularly teach novice students how to perform a task. This often requires them to adjust their behavior to the less knowledgeable audience and, hence, to behave in a more didactic manner. Eye movement modeling examples (EMMEs) are a contemporary educational tool for displaying experts’ (natural or didactic) problem-solving behavior as well as their eye movements to learners. While research on expert-novice communication mainly focused on experts’ changes in explicit, verbal communication behavior, it is as yet unclear whether and how exactly experts adjust their nonverbal behavior. This study first investigated whether and how experts change their eye movements and mouse clicks (that are displayed in EMMEs) when they perform a task naturally versus teach a task didactically. Programming experts and novices initially debugged short computer codes in a natural manner. We first characterized experts’ natural problem-solving behavior by contrasting it with that of novices. Then, we explored the changes in experts’ behavior when being subsequently instructed to model their task solution didactically. Experts became more similar to novices on measures associated with experts’ automatized processes (i.e., shorter fixation durations, fewer transitions between code and output per click on the run button when behaving didactically). This adaptation might make it easier for novices to follow or imitate the expert behavior. In contrast, experts became less similar to novices for measures associated with more strategic behavior (i.e., code reading linearity, clicks on run button) when behaving didactically.     

家庭社会经济地位对数学成绩的影响:亲子沟通和学业自我效能感的链式中介模型

采用“中国学校课程教学调查项目”中1811名八年级学生及其家长作为样本进行调查,探讨家庭社会经济地位与数学成绩的关系,考察亲子沟通和学业自我效能感的作用机制。结果显示:(1)家庭社会经济地位显著正向影响数学成绩;(2)亲子沟通、学业自我效能感在家庭社会经济地位与数学成绩之间起部分中介作用;(3)亲子沟通、学业自我效能感在家庭社会经济地位与数学成绩之间具有链式中介作用。     

Empathic accuracy and cognitions during conflict: An in‐depth analysis of understanding scores

Empathic accuracy research indicates that partners achieve only moderate success at reading each other's thoughts. The current study identifies specific patterns of online thought that contribute to empathic inaccuracy during conflict interactions. Married/cohabiting partners completed a conflict interaction and reported their own thoughts during video‐assisted recall of the interaction, also inferring the thoughts of the other partner. Content analysis of these online thoughts demonstrated a high degree of mindfulness about the process of communication, along with a perspective bias, in which partners tended to construe their own communication as constructive and the other partner's communication as avoidant and confrontational. Specific mind‐reading errors linked to both the thematic content and affective tone of online thought predicted lower overall empathic accuracy.     

Do infants have a sense of numerosity? A p‐curve analysis of infant numerosity discrimination studies

Research demonstrating that infants discriminate between small (e.g., 1 vs. 3 dots) and large numerosities (e.g., 8 vs. 16 dots) is central to theories concerning the origins of human numerical abilities. To date, there has been no quantitative meta‐analysis of the infant numerical competency data. Here, we quantitatively synthesize the evidential value of the available literature on infant numerosity discrimination using a meta‐analytic tool called p‐curve. In p‐curve the distribution of available p‐values is analyzed to determine whether the published literature examining particular hypotheses contains evidential value. p‐curves demonstrated evidential value for the hypotheses that infants can discriminate between both small and large unimodal and cross‐modal numerosities. However, the analyses also revealed that the published data on infants’ ability to discriminate between large numerosities is less robust and statistically powered than the data on their ability to discriminate small numerosities. We argue there is a need for adequately powered replication studies to enable stronger inferences in order to use infant data to ground theories concerning the ontogenesis of numerical cognition.     

The effects of secondary tasks that involve listening and speaking on young adult drivers with traits associated with autism spectrum disorders: A pilot study with driving simulation

A driver’s license is key to independence for many young adults, including those with autism spectrum disorders (ASDs). However, individuals with ASDs may face special challenges when learning to drive. If effective driver training is to be devised for this demographic, it is important to determine the nature of these challenges. Driving inherently requires multitasking (e.g. steering, speed maintenance, navigation, hazard detection) and drivers are routinely obligated to combine driving with the demands of listening and responding to others, as occurs during driving lessons. Given that individuals who display traits associated with ASDs may have special difficulties with secondary tasks and especially those that involve socialization, we examined the effects of secondary tasks that involve listening and responding to questions while driving. We compared performance when simply driving (the control condition), driving while listening (the audiobook condition), and driving while listening and speaking (the prompt: answer condition). The autism spectrum quotient (AQ:Baron-Cohen, Wheelwright, Skinner, Martin, & Clubley, 2001), a commonly used self-report questionnaire intended to measure traits associated with ASDs in research, was used to identify young drivers with more and fewer traits related to ASDs in a community sample, (None had a clinical diagnosis of ASD.) Consistent with studies of drivers clinically diagnosed with ASDs, we found that high AQ scorers reported greater mental and physical demand, effort, and frustration when driving, and showed more moment-to-moment variability in lane position and hazard reaction compared to low AQ scorers as measured in a driving simulator. Differences between the low and high scorers were typically largest when secondary tasks were imposed, but the predicted interaction between drive condition and AQ group only emerged in terms of steering variability.     

Effects of training and display content on Level 2 driving automation interface usability

IntroductionLevel 2 driving automation features, such as adaptive cruise control (ACC) combined with lane centering, primarily communicate their operating statuses through the instrument cluster. It remains unclear how interface-specific training and display content influence the ability to understand Level 2 activity in production vehicles.MethodsEighty participants viewed videos recorded from the driver’s point of view in a variety of driving scenarios with Level 2 activity displayed in the instrument cluster of a 2017 Mercedes-Benz E-Class. Half viewed one of two instrument cluster layouts (simple or complex), and half received an orientation to the interface before the experiment. After each video, they were asked about the scenario they had just seen. We then examined what information in the displays participants used to identify Level 2 activity and the usability of the displays.ResultsTraining improved recognition accuracy of when lane centering was temporarily inactive and understanding of why it was inactive. Neither training nor display content affected the ability to recognize when ACC had adjusted the vehicle’s speed or detected a vehicle ahead, or when ACC initially did not detect a lead vehicle and understanding of why it had not detected it. Both factors influenced which sources of information participants used to determine Level 2 activity. Recognition accuracy of system activity improved when participants used valid sources of information. Training, but not display content, improved lane centering usability, but not ACC usability.DiscussionBasic training improves detection of notifications that potentially require further driver action, but not of those that display persistent status information. Training does not result in full understanding of all system notifications or functional limitations, which reinforces the need for intuitive, salient communication about system behavior and its limitations.     

The impact of navigation system display size and environmental illumination on young driver mental workload

Driver distraction is a major cause of road crashes and has a great influence on road safety. In vehicles, one of the common distracting sources is navigation systems (NSs). The navigation system (NS) can distract the driver due to following directions and reading the provided information through its display. These tasks take the driver’s attention from the primary task of driving and may cause poor driving performance, increasing the risk of crashes. In this paper, the effect of the environment (i.e., urban areas and rural areas), the navigation system display (NSD) size, environmental illumination, and gender on young drivers between the ages of 18 and 29 years mental workload was investigated using a simulated driving experiment. To evaluate each driving condition, the NASA-TLX (NASA Task Load Index) workload assessment tool, and a distraction evaluation element, were introduced and used to assess the overall workload, the workload subscales and the distraction by the NSD. The assessment showed a higher perceived overall workload for urban areas and night driving as compared to a rural areas and daytime driving. Moreover, the results showed a greater perceived distraction by the NSD in urban areas compared to driving in rural areas. The subjects also felt distracted when using the small NS compared to using the large NS. The study concluded that urban areas driving, and night driving creates higher perceived workload than rural areas and daytime driving. Furthermore, small NSD leads to more perceived distraction than large NSD while driving. The NSD designers may utilize this research findings to optimize NSD designs to improve driving safety, performance and comfort. Moreover, this study contributes to our understanding of the effect of the NSD size on driving workload and distraction.     

Evaluating agents’ trustworthiness within virtual societies in case of no direct experience

A great deal of effort has been made to introduce trust models to assess trustworthiness within virtual societies. The great majority of them makes extensive use of direct experience as the main source of information, considering recommendation/reputation and inferential processes just later, as a secondary mechanism to refine trust assessment. In this kind of networks, unfortunately, direct experience might not always represent the best solution to assess trustworthiness. In fact, their highly dynamic structure promotes an increase of the average number of interconnections among agents. This in turn negatively affects the degree of knowledge the agents possess about each specific individual, i.e. direct experience. To date, however, it has not been said much about how to face these situations.It is fundamental to find an effective approach for trust assessment even in lack of direct experience, which is the central focus of this research. By the means of a multi-agent social simulation, we consider the situation in which an agent can just access indirect knowledge for trust assessment, namely recommendations of specific individuals or whole categories of individuals. Then, we compare the efficiency of these two approaches in order to identify when it is more convenient to rely on the first or on the second one. As expected, our results confirm that the dynamic nature of these networks strongly affects the role of categories. We modeled this feature introducing the “turnover” in the simulations, whereby the higher is the turnover the more convenient it is relying on categories. Besides this confirmatory result, our simulations highlight the higher degree of robustness of categories in the presence of unreliable recommenders. Such a result is even more significant if there is no available information about how reliable the recommenders are.The results we obtained are in accordance with the current literature and can be of important interest for the development of this sector.