1,944 research outputs found
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Combining Analyses of Cognitive Processes, Meanings, and Social Participation: Understanding Symbolic Representations
We propose three analytic representations of collaborative problem solving. Activity nests, a generalization of goal-subgoal trees, represent functional decompositions of task activity into components, using nesting to indicate operations that satisfy task functions. Semiotic networks, an extension of semantic networks, represent meanings as refers-to relations between symbolic expressions and other signifiers, and relations in situations and situation types, along with general relations between these meanings. Contribution Vagrants, an adaptation of contribution trees (Clark & Schaefer, 1989), represent how turn sequences collectively achieve task components. W e developed these representations to analyze how pairs of middle-school students constructed tables to represent quantitative properties of a simple physical device that models linear functions. Variations between activity nests of dififerent pairs support an explanation of activity in terms of attimement to constraints and to affordances and abilities, rather than following procedures. The semiotic networks support a hypothesis that task components are completed through accomplishing alignments of refers-to relations.which is a generalization of goal satisfaction. Similarities between the contribution diagrams support a general pattern that we call the turn structure of collaborative operations, in which task information is recognized and task operations are initiated, performed, and accepted. Interaction is organized into this structure in order to support mutually aligned intentions, understandings, actions, and agreements
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Managing Disagreement in Intellectual Conversations: Coordinating Interpersonal and Conceptual Concerns in the Collaborative Construction of Mathematical Explanations
This paper reports research into how mathematical explanations are constructed during conversation based on videotapes of pairs of student math teachers collaboratively writing explanations in geometry. In particular, we analyzed how disagreements about parts of their explanations were managed in these conversations. In contrast to research on disagreement in everyday conversation, explanation disagreements were more likely to overlap with preceding turns and to be stated baldly without prefaces, token agreements or qualifications. However, the observed frequencies of different kinds of disagreements were not consistent with a model favoring explicit substantive disgreement either. Instead, it is proposed that both the interpersonal concerns that would motivate a preference for agreement and the conceptual concerns for a quality explanation that would motivate a preference for substantive disagreement are being managed by participants. Disagreements are co-constructed, and conversants are seen to jointly employ complex devices for introducing and managing disagreement across turns that can satisfy both kinds of concerns with much less conflict betweeen them than might have been expected
Conservation of information-processing capacity in paired-associate memorizing
Data that impose constraints on hypotheses regarding the role of temporal variables in memorizing are reviewed, including results that apparently disconfirm Greeno's (1967) time-sharing hypothesis. An alternative hypothesis is proposed, in which it is assumed that S occasionally attenuates his rate of processing information for memory, with the probability of attentuation being relatively high when the item being presented is still in short-term memory as a result of a recent presentation.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/32693/1/0000060.pd
Matrix analysis of identifiability of some finite markov models
Methods developed by Bernbach [1966] and Millward [1969] permit increased generality in analyses of identifiability. Matrix equations are presented that solve part of the identifiability problem for a class of Markov models. Results of several earlier analyses are shown to involve special cases of the equations developed here. And it is shown that a general four-state chain has the same parameter space as an all-or-none model if and only if its representation with an observable absorbing state is lumpable into a Markov chain with three states.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45730/1/11336_2005_Article_BF02291365.pd
Attentional biases for food stimuli in external eaters: Possible mechanism for stress-induced eating?
External eaters reportedly increase snack intake when stressed, which could be due to an attentional shift towards food stimuli. Attentional biases for food stimuli were tested in high and low external eaters in stress and control conditions, using a computerised Stroop. A significant interaction was observed between external eating group and condition for snack word bias. This suggested that low external eaters have a greater bias for snack words when unstressed and that stressed, high external eaters have a greater bias for snack words than stressed, low external eaters, which could contribute to stress-induced snack intake in high external eaters
An analysis of some conditions for representing N state Markov processes as general all or none models
Recently Markov learning models with two unidentifiable presolution success states, an error state, and an absorbing learned state, have been suggested to handle certain aspects of data better than the three state Markov models of the General All or None model type. In attempting to interpret psychologically, and evaluate statistically the adequacy of various classes of Markov models, a knowledge of the relationship between the classes of models would be helpful. This paper considers some aspects of the relationship between the class of General All or None models and the class of Stationary Absorbing Markov models with N error states, and M presolution success states.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45728/1/11336_2005_Article_BF02290602.pd
Combining Cytotoxic and Immune-Mediated Gene Therapy to Treat Brain Tumors
Glioblastoma (GBM) is a type of intracranial brain tumor, for which there is no cure. In spite of advances in surgery, chemotherapy and radiotherapy, patients die within a year of diagnosis. Therefore, there is a critical need to develop novel therapeutic approaches for this disease. Gene therapy, which is the use of genes or other nucleic acids as drugs, is a powerful new treatment strategy which can be developed to treat GBM. Several treatment modalities are amenable for gene therapy implementation, e.g. conditional cytotoxic approaches, targeted delivery of toxins into the tumor mass, immune stimulatory strategies, and these will all be the focus of this review. Both conditional cytotoxicity and targeted toxin mediated tumor death, are aimed at eliminating an established tumor mass and preventing further growth. Tumors employ several defensive strategies that suppress and inhibit anti-tumor immune responses. A better understanding of the mechanisms involved in eliciting anti-tumor immune responses has identified promising targets for immunotherapy. Immunotherapy is designed to aid the immune system to recognize and destroy tumor cells in order to eliminate the tumor burden. Also, immune-therapeutic strategies have the added advantage that an activated immune system has the capability of recognizing tumor cells at distant sites from the primary tumor, therefore targeting metastasis distant from the primary tumor locale. Pre-clinical models and clinical trials have demonstrated that in spite of their location within the central nervous system (CNS), a tissue described as \u27immune privileged\u27, brain tumors can be effectively targeted by the activated immune system following various immunotherapeutic strategies. This review will highlight recent advances in brain tumor immunotherapy, with particular emphasis on advances made using gene therapy strategies, as well as reviewing other novel therapies that can be used in combination with immunotherapy. Another important aspect of implementing gene therapy in the clinical arena is to be able to image the targeting of the therapeutics to the tumors, treatment effectiveness and progression of disease. We have therefore reviewed the most exciting non-invasive, in vivo imaging techniques which can be used in combination with gene therapy to monitor therapeutic efficacy over time
Interpretation of the two-stage analysis of paired-associate memorizing
Four groups were run with response difficulty and stimulus difficulty varied factorially. A two-stage Markov model fit the data adequately. The parameter associated with the first stage depended on stimulus difficulty as well as response difficulty, refuting an interpretation of the first stage as response learning. The learning parameters associated with the second stage seemed to depend only on stimulus difficulty. The results suggest that the first stage of learning involves storage of the stimulus-response pair in memory, and the second stage involves learning to retrieve the item reliably.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/32746/1/0000115.pd
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