TITLE

A Decision Support Tool for Inferring Further Education Desires of Youth in Sri Lanka

AUTHOR(S)
Firdhous, M.F.M; Jayasundara, Ravindi
PUB. DATE
June 2011
SOURCE
International Journal of Advanced Computer Science & Application;Jun2011, Vol. 2 Issue 6, p28
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
This paper presents the results of a study carried out to identify the factors that influence the further education desires of Sri Lankan youth. Statistical modeling has been initially used to infer the desires of the youth and then a decision support tool has been developed based on the statistical model developed. In order to carry out the analysis and the development of the model, data collected as part of the National Youth Survey has been used. The accuracy of the model and the decision support tool has been tested by using a random data sets and the accuracy was found to be well above 80 percent, which is sufficient for any policy related decision making.
ACCESSION #
64877944

 

Related Articles

  • Data Mining for Education Decision Support: A Review. Suhirman; Zain, Jasni Mohamad; Herawan, Tutut // International Journal of Emerging Technologies in Learning;2014, Vol. 9 Issue 6, p4 

    Management of higher education must continue to evaluate on an ongoing basis in order to improve the quality of institutions. This will be able to do the necessary evaluation of various data, information, and knowledge of both internal and external institutions. They plan to use more efficiently...

  • KNOWLEDGE CONFLICTS RESOLVING IN THE MULTI-AGENT DECISION SUPPORT SYSTEM USING MULTI-STAGE CONSENSUS DETERMINING. Sobieska-Karpińska, Jadwiga; Hernes, Marcin // Business Informatics / Informatyka Ekonomiczna;2012, Vol. 3 Issue 25, p182 

    The present paper describes using a multi-stage consensus algorithm to knowledge conflicts resolving in multi-agent decision support systems. The problem of knowledge conflict between agents, structure of decision, profile and criteria of consensus determining are presented in the first part of...

  • Pruning Based Interestingness of Mined Classification Patterns. Al-Hegami, Ahmed // International Arab Journal of Information Technology (IAJIT);Oct2009, Vol. 6 Issue 4, p336 

    Classification is an important, problem in data mining. Decision tree induction is one of the most common techniques that are applied to solve the classification problem. Many decision tree induction algorithms have been proposed based on different attribute selection and pruning strategies....

  • Decision Support System for Medical Diagnosis Using Data Mining. Kumar, D. Senthil; Sathyadevi, G.; Sivanesh, S. // International Journal of Computer Science Issues (IJCSI);May2011, Vol. 8 Issue 3, p147 

    The healthcare industry collects a huge amount of data which is not properly mined and not put to the optimum use. Discovery of these hidden patterns and relationships often goes unexploited. Our research focuses on this aspect of Medical diagnosis by learning pattern through the collected data...

  • Adaptation of a Cluster Discovery Technique to a Decision Support System. Mogharreban, Namdar; Koohang, Alex // Interdisciplinary Journal of Information, Knowledge & Management;2006, Vol. 1, p59 

    This paper reports on the implementation of a cluster discovery technique to a decision support system. The model is a multi-criteria multi-alternative decision environment. The decision support reported here is a diagnostic system. Adaptive Resonance Theory 1 (ART1), which is a cluster...

  • Decision-making: Theory and practice. Turpin, S. M.; Marais, M. A. // Orion;2004, Vol. 20 Issue 2, p143 

    This paper compares a number of theoretical models of decision-making with the way in which senior managers make decisions in practice. Six prominent decision-makers were interviewed about their own decision-making style, as well as their use of decision support technology. Significant variation...

  • Harvesting Information from a Library Data Warehouse. Su, Siew-Phek T.; Needamangala, Ashwin // Information Technology & Libraries;Mar2000, Vol. 19 Issue 1, p17 

    Presents a study that seeks to apply data warehousing and data mining technologies in the development of a Library Decision Support System to aid the library management's decision making. Local environment; Library data sources; System architecture; Data cleansing and extraction; Graphical user...

  • DECISION SUPPORT SYSTEM FOR SEISMIC RISKS. Somodevilla, María J.; Priego, Angeles B.; Castillo, Esteban; Pineda, Ivo H.; Vilariño, Darnes; Nava, Angélica // Journal of Computer Science & Technology (JCS&T);2012, Vol. 12 Issue 2, p71 

    This paper focuses on prediction and prevention of seismic risk through a system for decision making. Data Warehousing and OLAP operations are applied, together with, data mining tools like association rules, decision trees and clustering to predict aspects such as location, time of year and/or...

  • Leveraging the Geospatial Advantage. Butler, Ben; Bailey, Andrew // Wildfire;Mar/Apr2013, Vol. 22 Issue 2, p10 

    The article reports on the use of geospatial data in the Wildland Fire Decision Support System (WFDSS) to modify strategic decisions on wildland fires. It states that the use of such data ensures that resources, infrastructure and the risk exposure of firefighters are included in planning and...

Share

Read the Article

Courtesy of THE LIBRARY OF VIRGINIA

Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics