Plateaus,Dips, and Leaps: Where to Look for Inventions and Discoveries During Skilled Performance

The framework of plateaus, dips, and leaps shines light on periods when individuals may be inventing new methods of skilled performance. We begin with a review of the role performance plateaus have played in (a) experimental psychology, (b) human–computer interaction, and (c) cognitive science. We then reanalyze two classic studies of individual performance to show plateaus and dips which resulted in performance leaps. For a third study, we show how the statistical methods of Changepoint Analysis plus a few simple heuristics may direct our focus to periods of performance change for individuals. For the researcher, dips become the marker of exploration where performance suffers as new methods are invented and tested. Leaps mark the implementation of a successful new method and an incremental jump above the path plotted by smooth and steady log–log performance increments. The methods developed during these dips and leaps are the key to surpassing one's teachers and acquiring extreme expertise.     

路径转弯对语篇空间情境模型建构的影响

采用回指解决方法, 通过3个实验探讨了路径转弯对空间情境模型建构的影响机制。实验1和实验2的结果表明, 读者在建构含有路径转弯的语篇时, 在一定范围内出现了路径转弯效应。总体趋势为当语篇的空间描述简单(转弯次数<2)时, 目标句的阅读时间会随着转弯次数的增多而增长, 但当语篇的空间描述复杂(转弯次数>2)时, 不仅不再出现路径转弯效应, 反而出现了该效应的反转现象。实验3借助眼动仪监测, 运用语篇与主人公行走路线同步动态呈现模式, 让被试实时追随主人公行走路线, 控制转弯次数和路径距离, 以当前位置与回指地点间的直线距离为自变量, 探究读者在空间描述复杂时建构空间情境模型的心理机制。实验结果表明当阅读空间描述简单的语篇时, 读者建构的空间情境模型是路线型的, 通过逆向搜索的方式进行回指解决; 当语篇的空间描述较为复杂时, 读者倾向于建构地图型空间情境模型, 以俯视的视角通过空间搭桥寻找空间最短直线距离进行回指解决。     

基于多传感器数据的航空管制员情境意识的计算

航空管制人员保持良好的情境意识是确保空中交通以安全、高效方式运行的必要条件。如果在管制员工作过程中, 能准确监测其情境意识状态, 并在情境意识丧失前给予及时告警, 那么将会极大地提高管制绩效和减少空中两机相撞的概率。目前, 国外评价管制员情境意识的方法虽然不少, 但这些方法基本都是诊断性质和回溯性质的, 无法对管制员的情境意识进行监测或预警。管制员的情境意识受个体差异、任务等多种因素的影响, 同时, 其也可以由某些指标来表征, 如某些作业绩效指标和生理指标。为了能够实现对航空管制员情境意识的准确监控及告警, 拟通过雷达管制模拟实验、心理测量、专家评定等方法采集多传感器数据, 分别建立基于表征指标和基于影响变量的情境意识计算模型, 并比较其预测性能。该研究结果可为管制员情境意识的实时监测提供支持。     

时间情景模型提取过程的实质初探:激活与抑制

采用扇效应技术和负启动实验范式探讨时间情景模型提取过程的实质。实验材料为18个"某人在某时间做某事"的句子,结果发现,实验条件下目标句的反应时显著长于控制条件下目标句的反应时,而两种条件下启动句的反应时无显著差异,出现了显著的负启动效应。这表明,在时间情景模型提取过程中,不仅激活了目标情景模型和与之相关的情景模型,而且对同时激活的相关的情景模型进行了抑制,支持长时记忆提取的抑制观。     

文本阅读中的信息整合研究

文本阅读中的信息整合研究是当前文本阅读研究的热点问题,在这一问题上,虽然当前研究已经达成了一些基本共识,但仍然存在着建构主义理论、最低限度假设和记忆基础文本加工理论这三种理论争议。本文详细介绍了这三种理论争议的主要观点和实验证据,特别是重点分析了三种理论争议的最新发展,在此基础上对未来的研究趋势进行了展望。     

对肿瘤患者输血的思考

就肿瘤患者输血相关的几个问题进行探讨,提出如何权衡输血对肿瘤患者的有益作用与危害,在肿瘤患者输血中如何进行自体输血及血液替代品的应用,从而推进我国输血医学的发展。     

An improved learning algorithm for random neural networks based on particle swarm optimization and input-to-output sensitivity

Extreme learning machine (ELM) for random single-hidden-layer feedforward neural networks (RSLFN) has been widely applied in many fields in the past ten years because of its fast learning speed and good generalization performance. But because traditional ELM randomly selects the input weights and hidden biases, it typically requires high number of hidden neurons and thus decreases its convergence performance. It is necessary to select optimal input weights and hidden biases to improve the convergence performance of the traditional ELM. Generally, the single-hidden-layer feedforward neural networks (SLFN) with low input-to-output sensitivity will cause good robustness of the network, which may further lead into good generalization performance. Moreover, particle swarm optimization (PSO) has no complicated evolutionary operators and fewer parameters need to adjust, and is easy to implement. In this study, an improved ELM based on PSO and input-to-output sensitivity information is proposed to improve RSLFN’s convergence performance. In the improved ELM, PSO encoding the input to output sensitivity information of the SLFN is used to optimize the input weights and hidden biases. The improved ELM could obtain better generalization performance as well as improve the conditioning of the SLFN by decreasing the input-to-output sensitivity of the network. Finally, experiment results on the regression and classification problems verify the improved performance the proposed ELM.     

家校合作对青少年学业成绩的影响：一个有调节的中介模型

本研究基于广州市基础教育质量监测项目,以2380名初中生及其家长为被试,构建一个有调节的中介模型,考察了家校合作对青少年学业成绩的影响机制。研究发现：（1）家校合作对青少年学业成绩具有显著的正向预测作用;（2）在家校合作对青少年学业成绩的影响中,亲子沟通发挥了部分中介作用;（3）独生状况调节了家校合作→亲子沟通→学业成绩的后半段,即相对于非独生子女而言,独生子女亲子沟通对学业成绩的促进作用更为显著。