Collaborative learning tasks involve interaction between multiple participants, who thus need to maintain some degree of mutual understanding. The process by which this is accomplished is termed grounding. The way in which collaboration, grounding and learning take place is largely determined by the task, the situation and the tools available. This paper discusses relations between grounding, collaboration and learning, drawing on research from two main areas: the Language Sciences and Cultural-Historical Activity Theory ("CHAT"). We build a unifying perspective of mutual understanding mediated by material and semiotic tools that can be used for analysis as well as for design of collaborative learning tasks, especially those that are carried out via computer-mediated communication. We illustrate the perspective with reference to a particular computermediated collaborative learning situation in the domain of physics. 1. Introduction Collaborative learning is a complex phenomenon that c...

Conversations involve all sorts of verbal activities beyond those strictly related to the performance of the task at hand. Among other things, the participants in a conversation have to make sure they both understand what's going on, to manage turn taking, and to keep each other informed about their progress in achieving their task. The participants share information about the status of all of these processes; this suggests that the view of the conversational score they share is rather more complex than assumed in previous accounts. We proposed a preliminary formalization of this more complex view of the conversational score in previous work; in this paper we revise that earlier model, and use our theory of the conversational score to give a partial specification of the effect of the dialogue acts included in the DRI classification.

this article, we want to get a formal grip on the way in which context influences the behaviour of presuppositions. Before we describe how we intend to do this, let us first describe the notion of context we are interested in. There are various uses of the term `context'. Bunt (1995) characterizes context as all those factors which are relevant to the understanding of communicative behaviour, and he goes on to distinguish five major dimensions: the linguistic context, the semantic context, the physical context, the social context and the cognitive context. For presuppositions in general, and for bridging in particular, the following seem most relevant: the linguistic context, as this will contain the antecedents from which a bridge has to be constructed, and the cognitive context, which according to Bunt includes the attentional state and the world knowledge of an interlocutor. Throughout this article we will therefore focus on the linguistic and the cognitive context. The resulting, global picture is as follows: an interpreter tries to understand a sentence in some context \Gamma. This context contains representations of the preceding discourse (the linguistic context) as well as background knowledge (the cognitive context). The interlocutor assumes that parts of her context are, to some extent, public. That is, they form what the interlocutor assumes to be the common ground. In this article, we are particularly interested in how interlocutors use the context to come to an understanding of the current sentence, and how they can adjust their context on the fly, so to speak, when the current sentence calls for such an adjustment. This brings out the extreme flexibility of context in natural language communication: speaker and hearer constantly attempt to align their repr...

Abstract: We describe a model for resolution of belief conflicts by argumentation in agent interactions, based on aspects of dialogic logic, speech act theory and belief systems research. This is part of a long term project on the relations between argumentation and cognitive change in collaborative problemsolving interactions. A set of communicative acts for argumentative interaction is defined, based on viewing them as multifunctional with respect to argumentation and interaction control. We concentrate on defining different intra- and inter-personal conflict situations, in terms of agents ' mental states, and specify the communicative acts that are relevant within each of them. An illustrative example of an argumentation sequence is presented and discussed in relation to the model. Our main claims are that the dialectical and rhetorical dimensions of argumentation need to be situated within a more general interactional framework, and that resolution of belief conflicts can give rise to increased coherence in agents ' epistemic states.

The effects of utterances such as cue phrases, keep-turn markers, and grounding signals cannot be characterized as changes to a shared record of the propositions under discussed: the simplest (and arguably most natural) way of characterizing the meaning of these utterances is in terms of a theory in which the conversational score is seen as a record of the discourse situation, or at least of the speech acts that have been performed. The problem then becomes to explain how discourse entities are accessible. We consider three hypotheses about the dynamics of a speech act-based theory of the conversational score, and argue that they could be implemented with relatively minor modifications to the technical tools already introduced in theories such as Compositional DRT.

In this chapter we present the DenK project, a long-term effort where the aim is to build a generic cooperative human-computer interface combining multiple input and output modalities. We discuss the view on human-computer interaction that underlies the project and the emerging DenK system. The project integrates results from fundamental research in knowledge representation, communication, natural language semantics and pragmatics, and object-oriented animation. Central stage in the project is occupied by the design of a cooperative and knowledgeable electronic assistant that communicates in natural language and that has internal access to an application domain which is presented visually to the user. This electronic `Cooperative Assistant' has an information state that is represented in a rich form of type theory, a formalism that enables us to model the inherent cognitive dynamics of a dialogue participant.

This paper presents an environment for the design and implementation of an Intelligent Tutoring System based on a multimodal dialogue interface and user modelling. The system exploits existing web-based on-line courses and superimposes a rhetorical structure as the underlying model for the course content. In addition, the learner profile is based on the notion of stereotypical ascription, while a multi-agent architecture supports the coordination of multiple interaction modalities.

This paper addresses the problem of understanding the mechanisms by which learning takes place as a result of collaboration between agents. We compare dialogue operators and machine learning operators with a view to understanding how the knowledge that is co-constructed in dialogue can be learned in an individual agent. Machine Learning operators make knowledge changes in a knowledge space; dialogue operators are used to represent the way in which knowledge can be co-constructed in dialogue. We describe the degree of overlap between both sets of operators, by applying learning operators to an example of dialogue. We review several differences between these two sets of operators: the number of agents, the coverage of strategical aspects and the distance between what one says or hears and what one knows. We discuss the interest of fusing dialogue and learning operators in the case of person-machine cooperative learning and multi-agent learning systems.

Collaborative learning tasks involve interaction between multiple participants, who thus need to maintain some degree of mutual understanding. The process by which this is accomplished is termed grounding. The way in which collaboration, grounding and learning take place is largely determined by the task, the situation and the tools available. This paper discusses relations between grounding, collaboration and learning, drawing on research from two main areas: the Language Sciences and Cultural-Historical Activity Theory ("CHAT"). We build a unifying perspective of mutual understanding mediated by material and semiotic tools that can be used for analysis as well as for design of collaborative learning tasks, especially those that are carried out via computer-mediated communication. We illustrate the perspective with reference to a particular computermediated collaborative learning situation in the domain of physics. 1.

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