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.     

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.     

State‐Trace Analysis: Dissociable Processes in a Connectionist Network?

Some argue the common practice of inferring multiple processes or systems from a dissociation is flawed (Dunn, 2003). One proposed solution is state‐trace analysis (Bamber, 1979), which involves plotting, across two or more conditions of interest, performance measured by either two dependent variables, or two conditions of the same dependent measure. The resulting analysis is considered to provide evidence that either (a) a single process underlies performance (one function is produced) or (b) there is evidence for more than one process (more than one function is produced). This article reports simulations using the simple recurrent network (SRN; Elman, 1990) in which changes to the learning rate produced state‐trace plots with multiple functions. We also report simulations using a single‐layer error‐correcting network that generate plots with a single function. We argue that the presence of different functions on a state‐trace plot does not necessarily support a dual‐system account, at least as typically defined (e.g. two separate autonomous systems competing to control responding); it can also indicate variation in a single parameter within theories generally considered to be single‐system accounts.     

Simulating single word processing in the classic aphasia syndromes based on the Wernicke-Lichtheim-Geschwind theory

The Wernicke-Lichtheim-Geschwind (WLG) theory of the neurobiological basis of language is of great historical importance, and it continues to exert a substantial influence on most contemporary theories of language in spite of its widely recognized limitations. Here, we suggest that neurobiologically grounded computational models based on the WLG theory can provide a deeper understanding of which of its features are plausible and where the theory fails. As a first step in this direction, we created a model of the interconnected left and right neocortical areas that are most relevant to the WLG theory, and used it to study visual-confrontation naming, auditory repetition, and auditory comprehension performance. No specific functionality is assigned a priori to model cortical regions, other than that implicitly present due to their locations in the cortical network and a higher learning rate in left hemisphere regions. Following learning, the model successfully simulates confrontation naming and word repetition, and acquires a unique internal representation in parietal regions for each named object. Simulated lesions to the language-dominant cortical regions produce patterns of single word processing impairment reminiscent of those postulated historically in the classic aphasia syndromes. These results indicate that WLG theory, instantiated as a simple interconnected network of model neocortical regions familiar to any neuropsychologist/neurologist, captures several fundamental "low-level" aspects of neurobiological word processing and their impairment in aphasia.     

Optimisation of phase ratio in the triple jump using computer simulation

The triple jump is an athletic event comprising three phases in which the optimal proportion of each phase to the total distance jumped, termed the phase ratio, is unknown. This study used a whole-body torque-driven computer simulation model of all three phases of the triple jump to investigate optimal technique. The technique of the simulation model was optimised by varying torque generator activation parameters using a Genetic Algorithm in order to maximise total jump distance, resulting in a hop-dominated technique (35.7%:30.8%:33.6%) and a distance of 14.05 m. Optimisations were then run with penalties forcing the model to adopt hop and jump phases of 33%, 34%, 35%, 36%, and 37% of the optimised distance, resulting in total distances of: 13.79 m, 13.87 m, 13.95 m, 14.05 m, and 14.02 m; and 14.01 m, 14.02 m, 13.97 m, 13.84 m, and 13.67 m respectively. These results indicate that in this subject-specific case there is a plateau in optimum technique encompassing balanced and hop-dominated techniques, but that a jump-dominated technique is associated with a decrease in performance. Hop-dominated techniques are associated with higher forces than jump-dominated techniques; therefore optimal phase ratio may be related to a combination of strength and approach velocity.     

The Motivational Pull of Video Games: A Self-Determination Theory Approach

Four studies apply self-determination theory (SDT; Ryan & Deci, 2000) in investigating motivation for computer game play, and the effects of game play on well-being. Studies 1–3 examine individuals playing 1, 2 and 4 games, respectively and show that perceived in-game autonomy and competence are associated with game enjoyment, preferences, and changes in well-being pre- to post-play. Competence and autonomy perceptions are also related to the intuitive nature of game controls, and the sense of presence or immersion in participants’ game play experiences. Study 4 surveys an on-line community with experience in multi-player games. Results show that SDT’s theorized needs for autonomy, competence, and relatedness independently predict enjoyment and future game play. The SDT model is also compared with Yee’s (2005) motivation taxonomy of game play motivations. Results are discussed in terms of the relatively unexplored landscape of human motivation within virtual worlds.     

Treatment for anxiety disorders: Efficacy to effectiveness to implementation

Anxiety disorders are common, costly and debilitating, and yet often unrecognized or inadequately treated in real world, primary care settings. Our group has been researching ways of delivering evidence-based treatment for anxiety in primary care settings, with special interest to preserving the fidelity of the treatment while at the same time promoting its sustainability once the research is over. In this paper, we describe the programs we have developed and our directions for future research. Our first study evaluated the efficacy of CBT and expert pharmacotherapy recommendations for panic disorder in primary care, using a collaborative care model of service delivery (CCAP). Symptom, disability and mental health functioning measures were superior for the intervention group compared to treatment as usual both in the short term and the long term, although also more costly. In our ongoing CALM study, we have extended our population to include panic disorder, social anxiety disorder, generalized anxiety disorder and posttraumatic disorder, while at the same time utilizing clinicians with limited mental health care experience. In addition to pharmacotherapy management, we developed a computer-assisted CBT that guides both novice clinician and patient, thereby contributing to sustainability once the research is over. We have also incorporated a measurement based approach to treatment planning, using a web-based tracking system of patient status. To date, the computer-assisted CBT program has been shown to be acceptable to clinicians and patients. Clinicians rated the program highly, and patients engaged in the program. Future directions for our research include dissemination and implementation of the CALM program, testing potential alternations to the CALM program, and distance delivery of CALM.     

Computing the uncomputable; or,The discrete charm of second-order simulacra

We examine a case in which non-computable behavior in a model is revealed by computer simulation. This is possible due to differing notions of computability for sets in a continuous space. The argument originally given for the validity of the simulation involves a simpler simulation of the simulation, still further simulations thereof, and a universality conjecture. There are difficulties with that argument, but there are other, heuristic arguments supporting the qualitative results. It is urged, using this example, that absolute validation, while highly desirable, is overvalued. Simulations also provide valuable insights that we cannot yet (if ever) prove.