“Applications of Expert System for Quality Assessment in Higher Education”- with respect to Students Perspective.

MUKUND A. KULKARNI

Abstract


ABSTRACT

The Higher Education for any country is a important area since the students would turn into good or bad citizens in a sort span of time when they complete the higher education. The policy of the higher education should be such that it is inclusive, student centric and trace on quality of the teaching and learning. The Paper highlights on use of advanced software’s and tools in the form of expert systems to improve the quality in higher education.

The Quality of Education being offered in institutions of Higher Education is a question being debated widely. With the growing cost of Higher Education in India, the question has become specially pertinent for all its stakeholders – students to policymakers alike. This paper attempts to look into expert system  as a techno-management tool for redressing their concerns. Various probable avenues are discussed where expert system could make an impact on the existing Indian Higher Education system. For example by affecting the overall quality of Higher Education in India and in addition making it more stakeholder friendly. An insight about the priorities assigned to various IT based KM interventions in different areas of Indian Higher Education System is suggested  based on the inputs from a cross-section of Indian Academia. Adoption of the proposed system shall not only improve the “Quality of Service (QoS)” but also decrease the economics of Higher Education in India. It will directly affect the society as a whole.

It is the expert system that is able to automate QMS. An expert system is a self-teaching system. Authors offer to organize the knowledgebase of the expert system for QMS from several levels differing by a degree of detailed elaboration of the information. They describe briefly the knowledgebase structure of the expert system.

Keywords: Information Technology, Knowledge Management, Indian Higher Education, Quality factors , Expert System , Inference Engine

 


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ISSN : 2251-1563