On the Social Rational Mirror: Learning E-commerce in a Web-Served Learning Environment

Nóbrega, Germana M. da; Cerri, Stefano A.; Sallantin, Jean

doi:10.1007/3-540-47987-2_9

Cited by 5 publications

(4 citation statements)

References 5 publications

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“…One exception, quite known by us, consists of DaN o obrega (2002), DaN o obrega et al (2002), and DaN o obrega et al (2003). These, however, limited the explanation of the conceptual foundations to the toy domain of arches and the experimentation to a reduced subset of concepts in the domain of law.…”

Section: Interactive Knowledge Construction In the Collaborative Builmentioning

confidence: 96%

Interactive Knowledge Construction in the Collaborative Building of an Encyclopedia

Lemoisson

Cerri

2005

Applied Artificial Intelligence

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Section: Interactive Knowledge Construction In the Collaborative Builmentioning

confidence: 96%

Interactive Knowledge Construction in the Collaborative Building of an Encyclopedia

Lemoisson

Cerri

2005

Applied Artificial Intelligence

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“…In this framework, social supervized learning basically follows the same protocol as co-building of ontologies, the particular point is that the group feeds the learner with examples in order to let him make the correct abductions. A more extensive discussion of this kind of learning can be found in [7] [8].…”

Section: Interactive Constructionmentioning

confidence: 99%

Constructive Interactions

Lemoisson¹,

Cerri²,

Mahe³

et al. 2003

Electronic Workshops in Computing

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The new paradigm of "knowledge construction using experiential based and collaborative learning approaches" is an outstanding opportunity for interdisciplinary research. This document is an attempt to introduce and exemplify as much as possible using the lexicon of "social sciences", considerations and tools belonging to "artificial intelligence" (e.g.: the machine learning tradition). In the paper we first draw a conceptual framework for rational agents in conversational interaction; then we use this framework for describing the processes of co-building ontologies, co-building theories, social interactive learning ... as examples of constructive interactions ; finally we give a brief description of a few AI methods and tools which might help-or perhaps be unavoidable in order to ensure the success of the interactive process.

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“…Within the server PhiInEd, two phases of a course are currently taken into account, namely, Planning and Running [15]. Figure 11 illustrates the characters taking part in these phases, along with the actions performed and the possible relations to each other.…”

Section: Instantiating Phi-calculus Into a Web-served Learningmentioning

confidence: 99%

“…Expecting to confirm our assumption (that the answer is positive), we have decided to expose real learners to the method. In order to support the learner's work, we have implemented a Webŋserved LE, called PhiInEd [15,13]. From a widespread perspective, the work on PhiInEd can be seen as an attempt to validate the model Phi-calculus when this latter meets the cause of Human Learning.…”

Section: Introductionmentioning

confidence: 99%

A contradiction-driven approach to theory formation: conceptual issues, pragmatics in human learning, potentialities

Nóbrega¹,

Cerri²,

Sallantin³

2003

J. Braz. Comp. Soc.

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Abstract.In Educational literature, Discovery Learning appears as an approach in which the learner builds up his/her own knowledge by performing experiments within a domain and inferring/increasing rules as a result. Such a constructivist approach has been largely exploited in the design of computational artefacts with learning purposes, the so-called Discovery Learning Environments (DLEs). One known feature of such environments is the autonomy degree required for students to succeed while handling a domain. Additionally, DLEs designers are often challenged to get students actually engaged. Such questions are on the basis of our concerns with the design and usage of particular DLEs, within which learning events occur as a consequence of contradiction detection and overcoming, during human/machine cooperative work. In this paper, we present an artificial agent capable of handling such a contradiction-driven approach of learning, by highlighting the exchanges that the agent should promote with a human learner. The conceptual model supporting the agent's design relies on the scientific rationale, particularly the empirical approach guided by the theory-experiment confrontation. We shall reinforce the interest of the model for the design of DLEs by presenting its exploitation in a real learning situation in Law. Also, we suggest potential instantiations of the model elsewhere than in Human Learning.

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On the Social Rational Mirror: Learning E-commerce in a Web-Served Learning Environment

Cited by 5 publications

References 5 publications

Interactive Knowledge Construction in the Collaborative Building of an Encyclopedia

Interactive Knowledge Construction in the Collaborative Building of an Encyclopedia

Constructive Interactions

A contradiction-driven approach to theory formation: conceptual issues, pragmatics in human learning, potentialities

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