Optimizing the Distributed Learning System with Accuracy Driven Dynamic Communication Frequency

2021 ◽  
Author(s):  
Fengyuan Yang ◽  
Tao Wei ◽  
Yuchen Huang ◽  
Jianhong Feng
Keyword(s):  
Distributed Learning ◽  
Learning System ◽  
Communication Frequency

An evaluation of a distributed learning system

2001 ◽  
Vol 43 (2) ◽  
pp. 105-116 ◽  
Author(s):  
Peter M. Lawther ◽  
Derek H.T. Walker
Keyword(s):  
Distributed Learning ◽  
Learning System

scholarly journals A Cognitive Style Perspective to Handheld Devices: Customization vs. Personalization

2016 ◽  
Vol 17 (1) ◽  
Author(s):  
Chen-Wei Hsieh ◽  
Sherry Y. Chen
Keyword(s):  
Cognitive Style ◽  
Test Scores ◽  
Empirical Studies ◽  
Cognitive Styles ◽  
Distributed Learning ◽  
Learning System ◽  
Handheld Devices ◽  
Digital Learning ◽  
Post Test ◽  
Similar Task

<p>Handheld devices are widely applied to support open and distributed learning, where students are diverse. On the other hand, customization and personalization can be applied to accommodate students’ diversities. However, paucity of research compares the effects of customization and personalization in the context of handheld devices. To this end, we developed a customized digital learning system (CDLS) and personalized digital learning system (PDLS), which were implemented on the handheld devices and tailored to the needs of students with diverse cognitive styles. Furthermore, we conducted two empirical studies to examine the effects of cognitive styles on the use of the CDLS and PDLS. More specifically, Study 1 identified the preferences of each cognitive style group, which were employed to develop the PDLS in Study 2, which investigated how students with different cognitive styles react to the CDLS and the PDLS.  The results from these two studies showed that student in the CDLS and those in the PDLS obtained similar task scores and post-test scores. However, Serialists with the PDLS could more efficiently complete the tasks than those with CDLS. Additionally, Holists more positively perceived the PDLS than Serialists.</p>

An Interoperable Model for the Intelligent Content Object Based on a Knowledge Ontology and the SCORM Specification

2017 ◽  
Vol 56 (5) ◽  
pp. 723-749 ◽  
Author(s):  
Xin-Hua Zhu ◽  
Tian-Jun Wu ◽  
Hong-Chao Chen
Keyword(s):  
Domain Knowledge ◽  
Reference Model ◽  
Distributed Learning ◽  
Learning System ◽  
Tutoring Systems ◽  
Object Based ◽  
Run Time ◽  
Program Interface ◽  
Content Object ◽  
Knowledge Ontology

Based on the sharable content object concept of advanced distributed learning, an ontology-based intelligent content object (ICO) that can automatically reason and be reused is proposed. Then, by extending the advanced distributed learning or sharable content object reference model (SCORM) specification, an interoperable model for the ICO is developed; it involves (a) adding an ontological model of general domain knowledge for intelligent tutoring systems to the SCORM specification and encapsulating the design details of the heterogeneous knowledge ontologies, (b) adding a hierarchical data structure for the current ontology element to the communication data model in the run-time environment of the SCORM specification, (c) extending the application program interface in the run-time environment of the SCORM specification to enable the ICO to query various knowledge ontologies in a consistent way, and (d) adding an Ontology section to the content aggregation model in the SCORM specification to ensure that the same ICO can be associated with different knowledge ontologies. The proposed model extends the SCORM-based courseware model from a multimedia-based structured courseware to the intelligent courseware based on a knowledge ontology and can significantly improve the overall intelligence of the learning system along the lines of the specification, thereby providing a reference for the future development of the SCORM specification.

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