计算机支持下协同工作的心理学研究

计算机支持下协同工作（ｃｏｍｐｕｔｅｒｓｕｐｐｏｒｔｅｄｃｏｏｐｅｒａｔｉｖｅｗｏｒｋ,简称ＣＳＣＷ）是计算机科学和认知科学的新兴交叉研究领域,主要研究在高技术支持下的群体协作。ＣＳＣＷ中蕴含着大量的心理学研究问题。心理学家需要更好地理解群体协作的性质以评估新技术是否与群体协作相适应,其研究成果会有助于理解如何构建技术和哪些技术可能成功。本文首先从分析ＣＳＣＷ的领域维度入手,然后讨论与之相关的一些重要的心理学研究问题,最后简要介绍国外在该领域进行的研究工作     

Some deterministic models of concept identification

It is shown that deterministic models can compete effectively with stochastic models in summarizing concept identification behavior. Three groups of deterministic models are examined. Examination of individual learners' trial by trial behavior in a concept experiment shows: (1) One person exhibited behavior consistent with a Hypothesis Permutation (HP) model despite being a nonlearner who showed no evidence of improvement over a period of 24 trials. However, when all 50 persons studied in each of two treatment groups were examined, only 22 members of one group and 10 of the other showed no inconsistencies with deterministic local consistency assumptions. (2) Certain deterministic computer programs could find at least one satisfactory order for predicting all responses by 18 of the 22 consistent solvers and 6 of the 10 consistent solvers, respectively, in the two groups just mentioned. For these 24 persons, then, a less restrictive deterministic model is adequate than for the others. (3) Those 38 original members of the first treatment group who met a stringent learning criterion were compared with respect to predictions generated by stochastic and mathematized deterministic models. One deterministic model (RSS-U 9-state) is in some respects the best of the models examined, but this success is a partial reflection of estimating eight parameters from the data.     

EFFECTS OF CONTEXTUAL COMPETENCE ON SOCIAL INITIATIONS

The frequency of social initiations and satisfaction with interactions in three dyads, each consisting of 1 student with disabilities and 1 nondisabled peer, were assessed under two alternating conditions: Condition 1 assessed the interactions around a set of four trained computer games, and Condition 2 assessed interactions when students were playing a set of four untrained computer games. Training was conducted with a multiple baseline design across participants and was followed by social interaction probes using an alternating treatments design. The results indicated greater frequencies of social initiations by 5 of 6 participants, higher degrees of game satisfaction by all participants, and equal or higher degrees of peer satisfaction by 5 of 6 participants when playing trained games in comparison to untrained games.     

Treating Childhood Social Anxiety Disorder With Virtual Environments and Serious Games: A Randomized Trial

Disseminating efficacious psychological treatments remains a challenge for researchers and clinicians. In the case of social anxiety disorder (SAD), Social Effectiveness Therapy for Children (SET-C) has been demonstrated as an efficacious intervention, but elements of the protocol, such as peer generalization sessions, remain challenging to conduct in typical clinical settings. To address this need, we developed an artificially intelligent, web-based application, Pegasys-VR™, designed to replace peer generalization sessions and enhance homework compliance. The feasibility of Pegasys-VR™ was tested in a randomized controlled trial in comparison to SET-C. The results indicated that both programs were equally efficacious in decreasing anxiety and improving social skill in social encounters. Sixty-three percent (63%) of children treated with SET-C and 60% treated with Pegasys-VR™ did not meet diagnostic criteria for SAD at posttreatment. Pegasys-VR™ is a feasible, efficacious, and dissemination-friendly element of a comprehensive treatment program for social anxiety disorder in children.     

An expanded model for perceptual visual single object recognition system using expectation priming following neuroscientific evidence

Under numerous circumstances, humans recognize visual objects in their environment with remarkable response times and accuracy. Existing artificial visual object recognition systems have not yet surpassed human vision, especially in its universality of application. We argue that modeling the recognition process in an exclusive feedforward manner hinders those systems’ performance. To bridge that performance gap between them and human vision, we present a brief review of neuroscientific data, which suggests that considering an agent’s internal influences (from cognitive systems that peripherally interact with visual-perceptual processes) recognition can be improved. Then, we propose a model for visual object recognition which uses these systems’ information, such as affection, for generating expectation to prime the object recognition system, thus reducing its execution times. Later, an implementation of the model is described. Finally, we present and discuss an experiment and its results.     

What do computer models of cognition explain: a reply to Gobet

The differences between Gobet’s views and ours call attention to some points concerning the argumentative status of computational models. If we have two fundamentally different models which reasonably accurately simulate a phenomenon, we must ask, what is the argumentative status of the models in psychological terms. Moreover, if it is possible to present different models of same phenomena, what is the general argumentative power of models in psychology? As the kind of differences between our views and the ones of Gobet’s are common in modelling, we briefly call attention to these foundational issues in our paper.     

Video game violence: A review of the empirical literature

The popularity of video games, especially violent video games, has reached phenomenal proportions. The theoretical line of reasoning that hypothesizes a causal relationship between violent video-game play and aggression draws on the very large literature on media violence effects. Additionally, there are theoretical reasons to believe that video game effects should be stronger than movie or television violence effects. This paper outlines what is known about the relationship between violent video-game playing and aggression. The available literature on virtual reality effects on aggression is discussed as well. The preponderance of the evidence from the existing literature suggests that exposure to video-game violence increases aggressive behavior and other aggression-related phenomena. However, the paucity of empirical data, coupled with a variety of methodological problems and inconsistencies in these data, clearly demonstrate the need for additional research.     

Justice and Game Advantage in Sporting Games

This paper is a case study of what Jon Elster calls "local justice"; particular schemes of justice which, on a relatively autonomous basis, are designed and implemented by institutions and practices to meet particular preferences and goals. The paper suggests an interpretation of the role of justice in sporting games. First, a framework for examinations of schemes of local justice is suggested. Second, norms are suggested that express the requirements that have to be met in order to consider a sporting game as just. The discussion shows that sports are characterized by a particular blend of meritocratic justice in which goods and burdens are distributed according to performance, and a non-meritocratic distribution through which goods and burdens arise as matters of chance. The essay concludes by arguing that the optimal blend of meritocratic justice and chance results in the realization of not merely fair sporting games, but of exciting and good games as well.