Comparing in-the-moment skill coaching effects from tailored versus non-tailored acceptance and commitment therapy mobile apps in a non-clinical sample

Mobile apps are promising for teaching how to practice psychological skills in high-risk and in vivo momentary situations, but there has been minimal research on the immediate effects of app-based skill coaching on mental health in-the-moment. This study analyzed the mobile app data in a non-clinical sample of 39 adults participating in a larger randomized controlled trial, with participants randomized to an acceptance and commitment therapy (ACT) mobile app that tailors skill coaching based on in-the-moment variables (n = 17) or an app that provides randomly selected skill coaching (n = 22). Data were collected before and after each ACT skill coaching session on proximal outcome (depression, anxiety, and engagement in meaningful activity) and ACT process variables. Multilevel models indicated significant immediate improvements on average following ACT skill coaching sessions on all proximal outcome and ACT process variables, although with relatively small effects ranging between 0.17 and 0.27 SD units change. Larger immediate pre-to-post effects from ACT coaching sessions were found for anxiety, experiential avoidance, and cognitive fusion in the tailored app versus random app condition. Overall, results suggest that an ACT app can have immediate, in-the-moment effects on psychological functioning, which may be enhanced by tailoring skills to current context.     

双因子模型MCAT中多级评分项目选题策略的比较

双因子模型假设测验考察一个一般因子和多个组因子,符合很多教育和心理测验的因素结构。“维度缩减”方法将参数估计中多维积分计算化简为多个迭代二维积分,是双因子模型的重要特征。本文针对考察多级评分项目的计算机化自适应测验,首先推导双因子等级反应模型下Fisher信息量的计算,然后推导“维度缩减”方法在项目选择方法中的应用,最后在低、中、高双因子模式题库中比较D-优化方法、后验加权Fisher信息D优化方法(PDO)、后验加权Kullback-Leibler方法(PKL)、连续熵(CEM)和互信息(MI)方法在能力估计的相关、均方根误差、绝对值偏差和欧氏距离的表现。模拟研究表明：(1)双因子模式越强,即一般因子和组因子在项目上的区分度的差异越小,一般因子估计精度降低,组因子估计精度增加,整体能力的估计精度提高;(2)相同实验条件下,连续熵方法的测量精度最高,PKL方法的能力估计精度最低,其它方法的测量精度没有显著差异。     

A reinforcement learning approach to personalized learning recommendation systems

Personalized learning refers to instruction in which the pace of learning and the instructional approach are optimized for the needs of each learner. With the latest advances in information technology and data science, personalized learning is becoming possible for anyone with a personal computer, supported by a data-driven recommendation system that automatically schedules the learning sequence. The engine of such a recommendation system is a recommendation strategy that, based on data from other learners and the performance of the current learner, recommends suitable learning materials to optimize certain learning outcomes. A powerful engine achieves a balance between making the best possible recommendations based on the current knowledge and exploring new learning trajectories that may potentially pay off. Building such an engine is a challenging task. We formulate this problem within the Markov decision framework and propose a reinforcement learning approach to solving the problem.     

超越传统：动态进化心理学研究进展

立足于基本适应目标与决策原则的功能分析,致力于心理过程多维度的动态考察,动态进化心理学在坚持适应主义原则基础上,将基因与经验、环境同时纳入心理发展解释框架,更为彻底地贯彻了有机体与环境交互作用观,在一定程度上克服了传统进化心理学的局限。但由于忽略社会实践的作用,它所展示的更多的是生物学意义上的人的发展图景,对心理过程的动态分析亦难以挣脱形而上学的桎梏。     

To Weight or Not to Weight? Balancing Influence of Initial Items in Adaptive Testing

It has been widely reported that in computerized adaptive testing some examinees may get much lower scores than they would normally if an alternative paper-and-pencil version were given. The main purpose of this investigation is to quantitatively reveal the cause for the underestimation phenomenon. The logistic models, including the 1PL, 2PL, and 3PL models, are used to demonstrate our assertions. Our analytical derivation shows that, under the maximum information item selection strategy, if an examinee failed a few items at the beginning of the test, easy but more discriminating items are likely to be administered. Such items are ineffective to move the estimate close to the true θ, unless the test is sufficiently long or a variable-length test is used. Our results also indicate that a certain weighting mechanism is necessary to make the algorithm rely less on the items administered at the beginning of the test. This research was partially supported by the NSF Grants SES0241020 and SES0613025. The authors thank the Editor, Associate Editor and two anonymous reviewers for their comments and suggestions. Send further information to Hua-Hua Chang, Department of Psychology, 603 E. Daniel Street, M/C 716, Champaign, IL 61820.     

生存加工：一种独特而强大的记忆编码程序

记忆是进化的产物。生存是人类面临的首要问题, 在进化过程中生存压力可能塑造了记忆的有关特征。生存加工比控制条件使信息有更好的记忆表现, 产生稳定的记忆优势, 这就是所谓的记忆生存优势效应。而传统的编码程序, 如图式加工、关系加工、一致性、精细加工、努力程度、情绪激活、熟悉度、新异性及自我参照等, 均不能解释生存优势。因此, 生存加工很可能是一种新的独特而强大的记忆编码程序。最后文章指出未来研究应重视生存加工的神经机制、跨文化、儿童群体及错误记忆等方面的研究。     

分布式群体在动态系统控制决策中的内隐学习

采用计算机网络模拟技术,考察分布式群体在动态系统控制决策过程中对系统规则的内隐学习效应及其迁移。结果表明,在决策者的显性规则知识量极少且没有增加的情况下,决策绩效随决策进程适应性提高。决策者所能报告的规则知识量与决策绩效的相关也不显著。同时,当决策任务目标转换时,决策的高绩效得以维持。这表明群体决策者能对动态系统规则进行内隐学习,且能正迁移到类似的决策情景中。研究进一步指出,群体决策行为的动态适应与内隐过程有关。     

视觉障碍儿童适应行为特点的研究

本研究用儿童适应行为量表对5－12岁的视障儿童和正常儿童适应行为进行比较研究,结果发现：视障儿童的年龄与适应行为发展之间存在着明显的相关,而正常儿童不存在这种相关。同时,视障缺损程度不同影响儿童适应行为的发展;虽然没有发现性别因素引起视障儿童适应行为的差异,但在社会责任和劳动技能的适应行为中,女孩的表现略优于男孩。     

自我知觉积极偏向的理论解释和意义分析

许多研究者注意到了人在进行自我知觉时的积极偏向,并提出各种观点对其进行解释和论证;许多实证研究也从不同侧面揭示了这种乐观偏向的适应意义。本文对相关内容进行了综合和梳理,介绍了自我增强的动机、自尊的需要和实现趋向等理论观点;并概括出这一积极偏向在提高行为动机和成就表现、消除不良情绪以及增进身心健康和社会适应等方面所具有的积极作用。