回忆任务对合作抑制和错误修剪的调节——情绪效价和编码水平的影响

前人在项目回忆条件的合作记忆研究中记录到明显的合作抑制和错误修剪,背景提取条件的相关研究尤显不足;同时,情绪效价和编码水平对两类现象调节的研究尚未涉及。为此,本文在两个实验中采用经典合作记忆研究范式,以不同情绪效价的词汇为实验材料并以词汇在学习阶段的呈现颜色为背景展开研究。实验1和实验2分别在学习阶段采用了深编码和浅编码任务,回忆阶段则均含项目回忆(回忆已学词汇)和背景提取(回忆词汇在学习阶段的呈现颜色)两种任务。采用深编码条件的实验1的结果显示,项目回忆比背景提取条件的合作抑制更强、错误修剪更弱,回忆任务与词汇情绪效价交互影响合作抑制强度;采用浅编码条件的实验2则发现错误修剪在两种任务间的差异不显著。两实验的联合分析显示,回忆任务与编码水平交互影响合作抑制和错误修剪强度。上述结果表明:回忆任务对合作抑制和错误修剪的调节支持双重加工模型;回忆任务与情绪效价对合作抑制强度的交互影响支持权衡说,且与双重加工模型相吻合;回忆任务与编码水平交互影响合作抑制和错误修剪强度。     

现代社会伦理秩序的发生路径

“自发生成论”和“理性创设论”是传统道德哲学关于社会伦理秩序生成的两种理论模式。“自发生成论”认为,伦理道德不是纯粹人类理性设计的产物,而是人类行为实践的自然结果;“理性创设论”认为,伦理道德是人类自觉建构的结果,是人类理性创设的产物。这两种理论模式都以抽象的人性为其理论基础,无法合理解释个体与类之间的伦理关系。基于现实伦理实体的“创生拓展”应成为现代社会伦理秩序的发生路径。     

等级反应模型下计算机化自适应测验选题策略

计算机化自适应测验(CAT)中的选题策略,一直是国内外相关学者关注的问题。然而对多级评分的CAT的选题策略的研究却很少报导。本研究采用计算机模拟程序对等级反应模型(Graded Response Model)下CAT的四种选题策略进行研究。研究表明：等级难度值与当前能力估计值匹配选题策略的综合评价最高;在选题策略中增设 “影子题库”可以明显提高项目调用的均匀性;并且不同的项目参数分布或不同的能力估计方法都对CAT评价指标有影响     

精加工推理中的文章结构清晰度效应

本研究旨在探讨文章结构清晰度对读者在阅读时所构建的精加工推理的水平和阶段的影响。研究采用让被试阅读后做推理测试题的方法 ,通过分析其答题成绩得出的结果表明 :文章的结构越清晰 ,越有利于读者在阅读的过程中进行精加工推理。     

Biodata Validity Decay and Score Inflation with Faking: Do Item Attributes Explain Variance Across Items?

Rating scales were developed to assess the biodata dimensions offered by Mael (1991). Biodata items assessing conscientiousness were administered under honest-responding and faking-good conditions. Item attributes were examined to determine their value in predicting item validity for honest respondents and item validity for faking respondents. Analyses were also conducted to determine whether the degree of item faking was related to item attributes. Item attributes associated with item validity for honest respondents are not the same as the item attributes indicative of item validity for the faking respondents. We suggest that this makes it very difficult to develop a biodata questionnaire which will be equally valid for both honest and faking respondents.     

Persistence of stereotypic behavior: examining the effects of external reinforcers

Basic research has shown that behavioral persistence is often positively related to rate of reinforcement. This relation, expressed in the metaphor of behavioral momentum, has potentially important implications for clinical application. The current study examined one prediction of the momentum metaphor for automatically reinforced behavior. Participants were 3 children who had been diagnosed with an autism spectrum disorder and who engaged in stereotypic behavior maintained by automatic reinforcement. Results suggested that stereotypic behavior was more resistant to disruption following periods of access to preferred stimuli delivered on a variable-time schedule than following periods without access to preferred stimuli. The implications of these findings for the treatment of automatically reinforced behavior are discussed.     

义务教育阶段学业质量监测题库建设的理论与实践

义务教育阶段学业质量监测是学生学业质量评价的重要方式,在当前国内外教育质量评价领域中发挥着极为重要的作用.加强学业质量监测的题库建设,则是促进学业质量监测工具的命制与实施从经验型向科学化迈进的必由之路.本文在对义务教育阶段学业质量监测题库的性质和功能进行阐述的基础上,重点探讨了学业质量监测题库建设的理论基础、基本流程和关键环节,并进一步分析指出了当前题库建设中有待深入研究的问题.     

药物成瘾者相关线索反应的自动化用药行为特征及其消退

采用ERP技术考察海洛因成瘾者相关线索下的用药行为的性质和神经机制, 在此基础上结合虚拟现实技术(VR)和途径偏向矫正训练(AAT), 探究基于“相关线索-习惯性用药”联结的自动化用药行为的动作消退、替代训练的有效性。研究发现, (1)相比对照线索, 成瘾者在相关线索下的反应时更长, N1波幅更小, N1潜伏期更短; 相比对照组被试, 成瘾者在相关线索下的行为任务的正确率更低, 反应时更长, N1波幅更小; N1波幅的组间组内差异和潜伏期的组内差异主要集中在中央区。(2)结合VR技术的途径偏向矫正训练后, 训练组被试的生理指标和途径偏向系数显著降低, 且显著低于对照组被试; 追踪测试中, 训练组被试的分数显著低于对照组。这表明相关线索下成瘾者的用药行为具有自动化、无意识的性质, 感觉运动区N1的异常活动是其神经机制之一。VR提取用药动作记忆-AAT消退替代训练, 可以有效削弱或消退成瘾者的成瘾动作倾向, 而且训练效果持续性较好, 可达到减少或停止现实情境中的用药和复吸行为的目的。     

Nested diagnostic classification models for multiple-choice items

This study proposes and evaluates a diagnostic classification model framework for multiple-choice items. Models in the proposed framework have a two-level nested structure which allows for binary scoring (for correctness) and polytomous scoring (for distractors) at the same time. One advantage of these models is that they can provide distractor information while maintaining the statistical properties of the correct response option. We evaluated parameter recovery through a simulation study using Hamiltonian Monte Carlo algorithms in Stan. We also discussed three approaches to implementing the proposed modelling framework for different purposes and testing scenarios. We illustrated those approaches and compared them with a binary model and a traditional nominal model through an operational study.