Efficient Data Mining Technique in Higher Education System: Analysis with Reference to Madhya Pradesh

Predicting the academic performance of students is very challenging due to large volume of data in the educational institutions database. Data mining techniques are implemented to predict students' academic performance in many institutions. Because of predicting students' performance, it will help teachers and institutions to decide strategies to teach to the students who are weak in studies and also they can define different strategies who are good in studies so that these students can perform better, So, aim of this paper is to study such a data mining technique which will help us to predict students' academic performance in advance.

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On the Need to Adopt a Strategic Planning Document «Strategy for the Development of the Higher Education System in the Russian Federation for the Period up to 2030»

Administrative Consulting ◽

10.22394/1726-1139-2020-6-123-135 ◽

2020 ◽

pp. 123-135

Author(s):

R. A. Amirov

Keyword(s):

Higher Education ◽

Strategic Planning ◽

Russian Federation ◽

Education System ◽

System Analysis ◽

Higher Education System ◽

Strategy System ◽

The Russian Federation ◽

Implementation Of The Strategy

The purpose: the article substantiates the importance of the country’s adoption of the strategic planning document «Strategy for the development of the higher education system in the Russian Federation for the period up to 2030».Materials and methods: the research uses theoretical and empirical methods, logical and system analysis, methods of description, prediction and expert assessments. The theoretical basis of the research is the method of strategic management developed by the famous economist, doctor of economic sciences, professor, foreign member of the Russian Academy of Sciences V. L. Kvint.Results: the analysis of numerous definitions of the concept and essence of strategy existing in the scientific literature is carried out, and a number of key positions in its definition are highlighted. Justifications are given for the criteria for developing strategies, using the example of the Strategy for the development of the country’s higher education system for the long term. The features of developing a strategy for the development of higher education are defined, and the hierarchy of levels of the strategy system is presented in relation to the strategy for the development of domestic higher education.Discussion: the strategy proposed for adoption should reflect the state and prospects of development of the higher education system, with the definition of Russia’s position in the world educational space, current challenges and threats facing higher education, identify strategic priorities, goals and objectives, mechanisms and stages of implementation of the strategy, propose scenarios for the development of the higher education system, identify sources of resources for the implementation of the strategy, expected results and monitoring of its implementation.Conclusion: it is noted that various state programs, national, Federal and priority projects, and action plans related to the development of the higher education system are being developed and approved in the country. However, there is no key strategic planning document — the Strategy for the development of the higher education system in Russia for the long term (for example, until 2030). In this regard, it is very relevant to develop and adopt this strategy, which undoubtedly takes into account the historically established traditions and features of the national higher school.

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Evaluation of the Pulse and Temperature of Higher Education System through Modeling and Data Mining

10.1109/dsins54396.2021.9670609 ◽

2021 ◽

Author(s):

Jiahao Liu ◽

Yutai Gao ◽

Yue Zhuo ◽

Jian Zu

Keyword(s):

Higher Education ◽

Data Mining ◽

Education System ◽

Higher Education System

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Rough Set Theory and Fuzzy Logic Based Warehousing of Heterogeneous Clinical Databases

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems ◽

10.1142/s0218488517500167 ◽

2017 ◽

Vol 25 (03) ◽

pp. 385-408 ◽

Cited By ~ 4

Author(s):

R. Saravana Kumar ◽

G. Tholkappia Arasu

Keyword(s):

Data Mining ◽

Fuzzy Logic ◽

Set Theory ◽

Rough Set ◽

Rough Set Theory ◽

Second Phase ◽

Data Mining Technique ◽

Mining Technique ◽

Clinical Databases ◽

Efficient Data

Large amounts of data about the patients with their medical conditions are presented in the Medical databases. Analyzing all these databases is one of the difficult tasks in the medical environment. In order to warehouse all these databases and to analyze the patient’s condition, we need an efficient data mining technique. In this paper, an efficient data mining technique for warehousing clinical databases using Rough Set Theory (RST) and Fuzzy Logic is proposed. Our proposed methodology contains two phases – (i) Clustering and (ii) Classification. In the first phase, Rough Set Theory is used for clustering. Clustering is one of the data mining techniques for warehousing the heterogeneous data bases. Clustering technique is used to group data that have similar characteristics in the same cluster and also to group the data that have dissimilar characteristics with other clusters. After clustering the data, similar objects will be clustered in one cluster and the dissimilar objects will be clustered under another cluster. The RST can be reduced the complexity. Then in the second phase, these clusters are classified using Fuzzy Logic. Normally, Classification with Fuzzy Logic is generated more number of rules. Since the RST is utilized in our work, the classification using Fuzzy can be done with less amount of complexity. The proposed approach is evaluated using various clinical related databases from heart disease datasets – Cleveland, Switzerland and Hungarian. The performance analysis is based on Sensitivity, Specificity and Accuracy with different cluster numbers. The experimentation results show that our proposed methodology provides better accuracy result.

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