Adaptive learning recognizes that each student learns at her own pace and in her own way. The user information sub-Ontology to describe user’s basic information, the user preference sub-Ontology to describe user’s preference information, user performance sub-Ontology to describe user’s performance information along with the user competency Ontology to describe user’s learning skills were established respectively.
In terms of education, physical equipment goes hand in hand with curricular support necessary to foster a conducive learning environment for children with CP. For instance, a child with CP may be required to learn the basic motor and communication skills before starting school.
The researchers further write that no system or tool can “replace careful attention and timely interventions by a well-trained teacher who understands how children learn mathematics.” The alert teacher assesses how well students understand the concepts and processes being studied and provides instruction that helps them to thoroughly master each step before moving on to the next.
Secondly, the features of domain knowledge was studied; as the complexity and diversity of domain knowledge and the lack of ontology engineering technology for domain experts make it difficult to develop domain ontology, the method to establish ontology based on knowledge engineering was proposed; the method to extract domain knowledge concepts, define concepts hierarchical structure and construct the relationship models were presented.
Math Games Are Effective Tools For Adaptive Learning
The sixth of our series of ten articles on cerebral palsy (CP) looks at the range of aids and other adaptive equipment that help people with CP to move about and communicate effectively. This paper, which based on semantic learning web, semantically described domain knowledge and user pattern using Ontology technology, presented the architecture of ontology-based adaptive e-learning system (OntoAES) , provided the platform for knowledge acquiring and sharing, and also provided learners with effective learning services based on personal knowledge spaces and preferences.
As a student progresses through a course, IDL’s Adaptive Learning Server continuously collects data on the student’s performance, steering the student into the learning style that best fits him or her and ensuring that every student masters the material.
Firstly, various theory models of teaching and learning processes were studied; the definition and description of learning behaviors in those theory models were analyzed; based on different characteristics of the learning behaviors, the features and requirements of the adaptive e-learning process was studied in order to provide the theory architecture and behavior model for the adaptive e-learning system; how to present knowledge space was studied, domain knowledge model and user knowledge space model were established.
As information increases explosively, the diversity and heterogeneity of knowledge in different domains make it difficult to represent and share knowledge. Based on analysis of user learning behavior records, the analysis and definition of the potential learning resource relation pattern based on users’ use of log, the relation model and user preference model were acquired through information extraction and data mining technologies.
These include symbol boards that rely on eye-gazing or pointing rather than … Read More..Continue Reading