Explanation modelling and competence management Ioan Rosca, PhD. in educational technology telecommunication, computer, information and instructional systems.

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    17-Dec-2015

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  • Slide 1
  • Explanation modelling and competence management Ioan Rosca, PhD. in educational technology telecommunication, computer, information and instructional systems engineer researcher and conceptual architect at LICEF, Teleuniversity, Montral ioan.rosca@licef.teluq.uquam.ca INSCIT2006, Merida, 27 October 2006
  • Slide 2
  • Summary 1 From information to knowledge: competencesFrom information to knowledge: competences 2 From learning to explanation as competence operatorsFrom learning to explanation as competence operators 3 Difficulties in modeling explanationsDifficulties in modeling explanations 4 Principle observations about the explanation phenomenaPrinciple observations about the explanation phenomena 5 Consequences :pedagogical competences, posture indexation, matching servicesConsequences :pedagogical competences, posture indexation, matching services 6 Competence indexation for the emergent modeCompetence indexation for the emergent mode 7 Concretization for adapting orchestration modeConcretization for adapting orchestration mode 8 Competence optimization problemsCompetence optimization problems
  • Slide 3
  • 1 Information, knowledge, competence from information to knowledge embodied in persons and reflected in documents- involved in material-cognitive processes from live knowledge to reified concept spaces; natural language discourses and structured knowledge domains (text and hypertext collections, thesaurus and dictionaries, classifications, relational databases, declarative languages, notional graphs, ontologies) competences: descriptions of someone (p) relation (R) relative to concepts (k) : (2a) cR(p,k)=[MR,m(MR)], MR- mastering scale for R (0-1, 0-10, 0-100, A-F etc.) ; m(MR)-measure on this scale (2b) cR[](p,k)= [R, M, mr1, mr2..] in the case of vectors of relations R[], as Bloom abilities: Rbloom[]= [observeK, understandK, applyK, analyseK, synthesiseK, evaluateK] (2c) cS(p,K) = [S(k1, .kn), M, mk1, mk2.mkn]- for decomposed knowledge kS, for example for a binary scale M=B= 0/1: (2d) cSb(p,K)=[S,B,bk1,bk2.bkn] where bki=0/1 if p knows/doesnt know ki concept identification: reference systems and semantic coordinates (UKL -universal knowledge locator) (1a) kd=[Nk, d(Nk), a(d)] (Nk organisation norm, d(Nk) domain organised on Nk norm, a(d) internal address of k in d) (1b) kD= [kd1, kd2] - multi-referenced knowledge concept refinement (decomposition) : notional subspace S organised on a norm Ns: (1c) kS= [Ns, s(k1, k2kn)] For the general case (2e) cRS(p,k)=)= [M, m(ri,kj) R, S] or, using some global competence calculus formulas: (2f) c(p,k)=[M,m(M)]=f (m(r1),m(r2))=g (m(k1),m(k2))=h( m(ri,kj) R, S)
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  • 2 From learning to explanation learning topologies participateconsultdialog Ci Cf Ci,Cf consult a simple model for explanation NoviceExpert Instrument Subject 12 3 4 5 6 7 8 9 10 11 12 13 14 15 i f kakbkckdke M 0% 100% learning: activities as competence operators i-fmastership measured competences c1i c1f explain Ci? Cf? c2i c2f explain c3i c3f explain effects of explanation on various learners k k1 k2 k3 k1.1 k1.2 knowledge refining competences i k1.3 k1.3.1 k1.3.2 k3.1 k3.2 f
  • Slide 5
  • 3 Modeling explanations (www.ioanrosca.com/educatie/these) ? explanation unitary model aspect space sociology, human development studies computers, telecommunications methodology, epistemology sciences of education information science diagrams semiotics rhetoric multimedia action,negotiation system theory logics ITS, AI, CBT, CAL, CSCL, CSCW, DSS psychology and cognitive science communication science language paradigms language interests criteria view filters involved domains methods ARITM, CPElectro, MAT (training and education experiences- Romania) Metamorph, Stereopresentation ( adaptable multimedia composition) NOVEX,SAFARI (expert- computer- novice action and decision sharing) NUAC(services management on INTERNET) TELOS (facilitating semantic and technical interoperation between knowledge management sites) MOT,GEFO (orchestrating pedagogical procedures) personal projects ADISA (planning instructional systems) EASE (retrieval and matching)
  • Slide 6
  • 4 Principles Bipolarity of explanation. Explanation phenomenon is based on the cognitive consonance lived by a human pair. Synchronous or asynchronous, sonorous, textual or graphical, direct or remote, realized through communication, resource sharing or co-operation, exploiting the physical interaction through objects and the innate or cultivated human communication capacities (language etc.)- the explicative relationship between an "expert" and a "novice" is essentially a bipolar phenomenon, based on the collaboration between two free-will centres. Knowledge as a communicational system. We obtain a systemic meaning of "knowledgeextending the phenomenology vision about the unity of the (observed object observing subject) pair, taking into account the shared character of knowledge and including, in a single whole, the represented subject, the representing symbol and the human pair using the representation to communicate on the subject. Person in society: cognitive duality. The individual cognitive metabolism interferes with that of the community- in which it is "situated". The communication between two persons can be seen as a relation between two distinct cognitive systems, but also as a manifestation of the cognitive physiology of the species' system, ensuring spiritual evolution, through knowledge propagation. Structure/process duality: existence/transformation, adaptation/evolution, ontogenesis/phylogenesis. The physical and conceptual entities, tied by relationships, create systemic units and determine their behavior (physiology). Conversely, the physical and cognitive processes sediment structures (entities and relations). A complete systemic vision must reveal the existence- becoming duality, using "structures in processes" models. Conservation and change: circular relationships between "model" and "reality". The reality must be observed and understood (modeled)- even if we wish to conserve it. A reciprocal influences loop is blend between "reality" and "model" (accentuated- when the phenomena's "model" is used as an instrument by the participants)- with major behavioral consequences. A such "reality-model" system has its global physiology.
  • Slide 7
  • 5 Orientations and propositions Competence conditions and matching services for resource retrieval or concretisation (3a) (c1

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