The path through e-learning: FAD and e-learning. The third generation of the e-learning: the Learning Objects.
Introduction to the logic systems. Truth and provability in a model.
Characteristics of the propositional and predicative logic. Natural deduction for propositional logic. How to represent facts in predicative logic.
Introduction to XML. The validation process of an XML document.
Characteristics of the Resource Description Frameworks for knowledge representation.
- on line slides
- XML on line manual http://xml.html.it/guide/leggi/58/guida-xml-di-base/, paragraphs 1-8
Learning Objectives
Introduction to the e-learning: an overview on the new methods for the creation of the Learning Objects. The characteristics and the perspectives of the semantic web are pointed out.
The student has to understand the basic processes of logic reasoning together with the concepts of truth and provability and how to use automatic reasoning to produce knowledge.
Some hints about the new perspectives of the semantic web are furnished.
Finally, the student understand how to produce and modify Learning Objects using XML.
Prerequisites
none
Teaching Methods
lessons with examples and exercises. PC sessions if possible
Further information
none
Type of Assessment
test and oral examination
Course program
FAD and e-learning. How to personalize on line learning.
The third generation of the e-learning: Learning Objects (LO). The metadati.
The SCORM standard and its troubles. LO repository. Searching inside Merlot repository.
How to write metadati. Introduction to XML. Validation process for XML documents.
The semantic web. Knowledge based agent. Knowledge representation languages: syntax and semantics.
Truth and provability. Valuation of a formula inside a model. Automatic inference process.
The logic systems. Propositional and Predicative logics.
Propositional logic: syntax and well formed formulas. Semantics of the propositional logic. Truth tables. Inference rules. Deduction trees.
Predicative logic: Syntax and semantics. How to represent facts in the predicative logic.
How to represent knowledge using Resource Description Frameworks (RDF).
RDF Data Model: resources, properties and statements. Knowledge graphs.
RDF Schema: how to use blank nodes. Reification. Hints about classes.