Explanation modelling and competence management

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, Montréal ioan.rosca@licef.teluq.uquam.ca INSCIT’2006, Merida, 27 October 2006

2. Summary 1 From information to knowledge: competences 2 From learning to explanation as competence operators 3 Difficulties in modeling explanations 4 Principle observations about the explanation phenomena 5 Consequences :pedagogical competences, posture indexation, matching services 6 Competence indexation for the emergent mode 7 Concretization for adapting orchestration mode 8 Competence optimization problems

3. 1 Information, knowledge, competence • 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 • 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) • concept refinement (decomposition) : notional subspace S organised on a norm Ns: • (1c) kS= [Ns, s(k1, k2…kn)] • 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]wherebki=0/1 if p knows/doesn’t know ki 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)

4. 2 From learning to explanation Subject 15 3 learning: activities as competence operators i-f c1i c1f c2i c2f c3i c3f M 100% mastership measured competences explain explain explain f 0% 13 6 14 ka kb kc kd ke i effects of explanation on various learners Ci? Cf? 5 i k knowledge refining competences Expert Novice k1 f k3 k2 7 12 k1.3 k1.2 2 k1.1 k3.1 1 k3.2 k1.3.1 k1.3.2 11 10 8 participate dialog consult consult 9 Instrument Ci Cf Ci,Cf 4 learning topologies a simple model for explanation

5. 3 Modeling explanations (www.ioanrosca.com/educatie/these) involved domains aspect space personal projects ITS, AI, CBT, CAL, CSCL, CSCW, DSS ARITM, CPElectro, MAT (training and education experiences- Romania) computers, telecommunications Metamorph, Stereopresentation ( adaptable multimedia composition) communication science NOVEX,SAFARI (expert- computer- novice action and decision sharing) action,negotiation system theory multimedia EASE (retrieval and matching) language explanation unitary model ? logics rhetoric NUAC(services management on INTERNET) semiotics diagrams information science ADISA (planning instructional systems) sciences of education MOT,GEFO (orchestrating pedagogical procedures) methodology, epistemology view filters TELOS (facilitating semantic and technical interoperation between knowledge management sites) psychology and cognitive science paradigms interests methods sociology, human development studies language criteria

6. 4 Principles • Knowledge as a communicational system. We obtain a systemic meaning of "knowledge“extending 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. • 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 . • 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.

7. The wide specter of "assistance". The concept of "assistance" - covers a large range of significations ("information“, "clarifications“, “guiding”, “teaching”, ”supporting”, "equipping“ etc.) The advanced "support" systems allow the combination of these possibilities. 5 Orientations and propositions • Distributed intelligence and synaptic tele-informational systems. The intrinsic qualities of a human assistant (appropriate, available and well-disposed) are difficult to mechanize. The posture of information "emitter" is multipliable (through the diffusion of the conceiver's "message"), but that of a learner "listener" or interactive partner- much harder. But prior to cooperating or communicating, the partners must equip, find and agree themselves. The synaptic "matching" infrastructure, based on the computer network, can provide contact, contract and management services, forming a "synaptic" (matching) infrastructure for the collective brain's physiology • Competence conditions and matching services for resource retrieval or concretisation (3a) (c1 <= c2 si m1<=m2), usable for selecting resources on emergent mode (3b) c(p/r,k)>=c(a/i,k), for concretisations of abstract actor a by participants p on planned mode (3c1) e1<=c<o<=e2 or d1<=c<o<=d2 – a support element is sufficient (3c2) e1<c<d1<e2<o<=d2 – the assistant can lead the learner in the document efficiency range • Explicative capacities and pedagogical indexation. In order to observe the competence equilibrium around pedagogical operations, I have organised the competences space of a person P on "postures": (knowK, aimK, explainK(x,y), describeK(x,y), recommendK(x,y), evaluateK(x,y))- where the parenthesis show a predicate depending on the detained (x) or aimed (y) "mastering level" of the person to which P could explain directly (transmit by a document, evaluate, recommend etc) the knowledge k. The indexation of explicative documents poses similar problems to that of referencing support persons. They can be partially considered the author's representative towards the expected user (minus the interactivity limitations). That is why I have also characterises their explicative potential by (c1,c2) increases.

8. 6 Referencing and retrieving for emergent activities 2 find, choose 3 use (index) 2 find, choose 3 use (dialog) record search engine record search engine Participants Knowledge reference system K recordset recordset k p descriptors descriptors use rec rec 1 declare explicative competence exp 1 declare knowledge 4 react 4 react 3 use (participate) 2 find, choose 3 use (consult) 2 find, choose record search engine record search engine Documents Operations recordset ped recordset d o descripteurs descriptors rec rec 1 declare explicative potential 1 declare explicative potential 4 react 4 react

9. 7 Adapting orchestrations persons p2 p1 author knowledge referencesystem operations Function editor objects o1 o2 ob1 ob2 ob3 compose model resources repositories ps rs a primary procedure support resource Function adaptor support person adapter person directories concretise elements function operations directories a1 abstract actors a2 e meta-procedure of functional cycle user analyst i1 o1 i2 o2 i3 abstract instruments is1 as2 record react finds and executes Function executor Function analyser b abstract procedure model px py ob x ob x ob y ob z a1 a2 a1 a2 o1 o2 e1 e2 is1 as2 executed operation is1 as2 rs x rs x ps x ps x c model with concretised elements d secondary procedure based on function execution

10. O E d n e O c2 E c1 E O O D A e f1 E E E f2 O O O D A D A D A e e a d E E E O O O R D A D A D A ? d a a d e e E E a state changes for Toeda topology b global allocation problem O o D A D A d a d a 8 Competence optimization