ERIC Number: EJ1077706
Record Type: Journal
Publication Date: 2015-Nov
Abstractor: As Provided
Reference Count: N/A
Developing a Dynamic Inference Expert System to Support Individual Learning at Work
Hung, Yu Hsin; Lin, Chun Fu; Chang, Ray I.
British Journal of Educational Technology, v46 n6 p1378-1391 Nov 2015
In response to the rapid growth of information in recent decades, knowledge-based systems have become an essential tool for organizational learning. The application of electronic performance-support systems in learning activities has attracted considerable attention from researchers. Nevertheless, the vast, ever-increasing amount of information is creating management problems regarding the efficiency and accuracy of knowledge retrieval. This study aims to develop a dynamic inference expert system (DIES) to solve these problems. DIES integrates web technology, knowledge management, Extensible Markup Language (XML) and C Language Integrated Production System (CLIPS) to facilitate the convenience of knowledge retrieval and the efficiency of learning at work. The advantages of XML include scalability, sharing, easy readability and the ability to enhance the efficient management of knowledge-based systems. In DIES, organizational knowledge is automatically generated as machine-readable language and knowledge description, using CLIPS as a rule-conduction tool to develop specific organizational knowledge bases. A data source consisting of 22 participants from different industries was employed to examine the effectiveness of DIES. Results indicate that participants intend to apply DIES within their industries, with a 95% probability of attaining above-average satisfaction.
Descriptors: Workplace Learning, Knowledge Management, Management Systems, Artificial Intelligence, Learning Activities, Inferences, Efficiency, Accuracy, Technology Uses in Education, Internet, Programming Languages, Information Retrieval, Scaling, Reliability, Shared Resources and Services, Readability, Probability, Intention, Satisfaction, Statistical Analysis
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
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