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A methodology that supports the analysis, the design and the delivery planning of a learning system, integrating the concepts, the processes and the principles of instructional design, software engineering and cognitive
210 Knowledge modeling principles212 Knowledge model214 Target competencies310 Learning units content 410 Learning instruments content 610 Knowledge and competency management
Instructional Modeling
220 Instructional principles222 Learning events network224 Learning units properties320 Instructional scenarios322 Learning activities properties420 Learning instruments properties620 Actors and group management
Materials Modeling
230 Media principles 330 Development infrastructure 430 Learning materials list 432 Learning materials models 434 Media elements 436 Source documents630 Learning system / resource management
Delivery Modeling
240 Delivery principles242 Cost-benefit analysis340 Delivery planning440 Delivery models442 Actors and user’s materials444 Tools and telecommunication446 Services and delivery locations540 Assessment planning640 Maintenance / quality management
IMS-LD is a progress in eLearning specifications– Some IMS-LD scenarios cannot be expressed in
SCORM– IMS-LD is more general, favors innovative methods
Assigning optional objectives and prerequisites according to the IMS RDCEO specification (IMS 2002) is not enough– Consistency checking is not supported between levels nor
between the content of learning activities and resources, and the actors’ competency
– Knowledge in learning resources is not described – Actor’s knowledge and competencies is only indirectly defined
through educational objectives Need for a qualitative structural representation of
knowledge in activities, but also a quantitative one
To say that somebody needs to acquire a certain knowledge is insufficient
A skills’ taxonomy based on different viewpoints : instructional objectives, generic tasks/processes, meta-knowledge Expandable taxonomy from general to
specific Ordering skills from simple to complex Integrating domains of multiple
Components of a Function Components of a Function must reach competence must reach competence equilibrium . equilibrium . Ex: Learning resources (persons, Ex: Learning resources (persons, documents and tools) must enable documents and tools) must enable learners to progress from an entry learners to progress from an entry level to a target level required by the level to a target level required by the activity.activity.
Components of a Function Components of a Function must reach competence must reach competence equilibrium . equilibrium . Ex: Learning resources (persons, Ex: Learning resources (persons, documents and tools) must enable documents and tools) must enable learners to progress from an entry learners to progress from an entry level to a target level required by the level to a target level required by the activity.activity.
1. Tree organization of the knowledge referential: – allows competence inheritance from parent node to children– reduce significantly the mechanisms of competence
analysis and management. 2. Must be completed by relational logic to sustain
more refined mechanism of conceptual matching. 3. Ontology referencing is insufficient without mastery
levels– prevent coarse granulation of sense– weak semantic management services.
4. Quantitative measures to weight ability on knowledge – level scale to be reasonably simple, manageable – levels correspondomg to clearly identify cognitive processes– to be materialized as a learning design
1. Tree organization of the knowledge referential: – allows competence inheritance from parent node to children– reduce significantly the mechanisms of competence
analysis and management. 2. Must be completed by relational logic to sustain
more refined mechanism of conceptual matching. 3. Ontology referencing is insufficient without mastery
levels– prevent coarse granulation of sense– weak semantic management services.
4. Quantitative measures to weight ability on knowledge – level scale to be reasonably simple, manageable – levels correspondomg to clearly identify cognitive processes– to be materialized as a learning design