- From: Owen Ambur <Owen.Ambur@verizon.net>
- Date: Wed, 25 May 2022 22:52:58 -0400
- To: public-aikr@w3.org
- Cc: Kranthi Kiran <kranthi@thoughtflow.io>
- Message-ID: <21a52994-a967-e0c1-74ff-31cb7110c4e3@verizon.net>
The goals and objectives implicit in Paquette's wall of text are now available in StratML format at https://stratml.us/drybridge/index.htm#GOML4LE I'm copying Kranthi because MOT reminds me of his ThoughtFlow application and I am looking forward to learning how it might be applied in support of the vision of the StratML standard: A worldwide web of intentions, stakeholders, and results. Owen On 5/24/2022 10:33 PM, Paola Di Maio wrote: > Not new, but v good read, > I plan to leverage some concepts > > > Graphical Ontology Modeling Language for Learning Environments > GILBERT PAQUETTE* > https://www.researchgate.net/publication/228639039_Graphical_ontology_modeling_language_for_learning_environments > > In the last fifteen years, our main goal has been to synthesize and > combine > various forms of graphical representations that are useful for educational > modeling and knowledge management, using an integrated graphical formal- > ism. We have shown that very different kinds of representation, conceptual > maps, flowcharts, decision trees and others, can all be modeled more > precise- > ly, using the MOT graphic language based on typed objects (concept, proce- > dures, principles, facts) as well as few typed links. With this set of > primitive > graphic symbols, it has been possible to build very different graphic > models, > from simple taxonomies to ontologies, more or less complex learning > designs, > delivery process, decision systems, and methods. > Recent developments have led to two specialisations of the graphic lan- > guage. The first one is a powerful, yet simple graphic language to build > ontologies for a knowledge domain. The second one enables to model learn- > ing designs and scenarios in a standardized and computable way. The > associ- > ation between both kinds of models specifies the central part of a > learning > environment at the design phase, and enables its delivery to learners > and edu- > cators. In the final section, I assert that knowledge representation > for educa- > tion should be graphic, user-friendly, general, scalable, declarative, > standard- > ized and computable. Adiscussion of these criteria conclude
Received on Thursday, 26 May 2022 02:53:17 UTC