Repozitorij samostojnih visokošolskih in višješolskih izobraževalnih organizacij

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Naslov:Student data mining solution - knowledge management system related to higher education institutions
Avtorji:Natek, Srečko (Avtor)
Zwilling, Moti (Avtor)
Jezik:Angleški jezik
Vrsta gradiva:Znanstveno delo
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:MFDPŠ - Mednarodna fakulteta za družbene in poslovne študije
Opis:Higher education institutions (HEIs) are often curious whether students will be successful or not during their study. Before or during their courses the academic institutions try to estimate the percentage of successful students. But is it possible to predict the success rate of students enrolled in their courses? Are there any specific student characteristics, which can be associated with the student success rate? Is there any relevant student data available to HEIs on the basis of which they could predict the student success rate? The answers to the above research questions can generally be obtained using data mining tools. Unfortunately, data mining algorithms work best with large data sets, while student data, available to HEIs, related to courses are limited and falls into the category of small data sets. Thus, the study focuses on data mining for small student data sets and aims to answer the above research questions by comparing two different data mining tools. The conclusions of this study are very promising and will encourage HEIs to incorporate data mining tools as an important part of their higher education knowledge management systems.
Ključne besede:data mining, knowledge management system, student's success rate, data mining for small data set, higher education institutions, educational data mining
Leto izida:2014
UDK:004.8:378
ISSN pri članku:0957-4174
OceCobissID:171291 Povezava se odpre v novem oknu
COBISS_ID:12870561 Povezava se odpre v novem oknu
DOI:10.1016/j.eswa.2014.04.024 Povezava se odpre v novem oknu
Število ogledov:4740
Število prenosov:197
Datoteke:URL http://www.sciencedirect.com/science/article/pii/S0957417414002462
.pdf RAZ_Natek_Srecko_i2014.pdf (787,93 KB)
 
Nadgradivo:Expert systems with applications
Pergamon
Oxford, 1990
 
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
  
Skupna ocena:(1 glas)
Vaša ocena:Ocenjevanje je dovoljeno samo prijavljenim uporabnikom.

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