Computer-Driven Instructional Design with INTUITEL
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Adaptive Learning Environments
adaptive learning systems
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Age Group_Uncategorized
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B01=Kevin Fuchs
B01=Peter A. Henning
Category1=Non-Fiction
Category=JNMT
Category=JNU
Category=JP
Category=UMZ
Category=UY
Cc
Computer Technology
COP=Denmark
Delivery_Pre-order
educational ontologies
eq_bestseller
eq_computing
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
HTTP Header
Hypercube Model
IMS Learn Design
instructional technology
Intelligent Tutoring Systems
Language_English
Learner Update
Learning Pathways
Learning Portal
Learning Style Theories
Message Id
ontology-based learning pathway guidance
PA=Not yet available
pedagogical knowledge modeling
Pedagogical Ontology
personalized e-learning
Price_€20 to €50
PS=Forthcoming
Query Builder
Reasoning Engine
Recommendation Rewriter
Rest Interface
semantic metadata annotation
softlaunch
Spatio Temporal Databases
Spatio Temporal Trajectories
Technology Enhanced Learning
Term Artificial Intelligence
Time Dependent Vector
Turing Machine
User Id
XML Document
Product details
- ISBN 9788770044349
- Weight: 300g
- Dimensions: 156 x 234mm
- Publication Date: 21 Oct 2024
- Publisher: River Publishers
- Publication City/Country: DK
- Product Form: Paperback
- Language: English
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INTUITEL is a research project that was co-financed by the European Commission with the aim to advance state-of-the-art e-learning systems via addition of guidance and feedback for learners. Through a combination of pedagogical knowledge, measured learning progress and a broad range of environmental and background data, INTUITEL systems will provide guidance towards an optimal learning pathway. This allows INTUITEL-enabled learning management systems to offer learners automated, personalised learning support so far only provided by human tutors INTUITEL is - in the first place - a design pattern for the creation of adaptive e-learning systems. It focuses on the reusability of existing learning material and especially the annotation with semantic meta data. INTUITEL introduces a novel approach that describes learning material as well as didactic and pedagogical meta knowledge by the use of ontologies. Learning recommendations are inferred from these ontologies during runtime. This way INTUITEL solves a common problem in the field of adaptive systems: it is not restricted to a certain field. Any content from any domain can be annotated. The INTUITEL research team also developed a prototype system. Both the theoretical foundations and how to implement your own INTUITEL system are discussed in this book.
