Naslov: | Student data mining solution - knowledge management system related to higher education institutions |
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Avtorji: | ID Natek, Srečko (Avtor) ID Zwilling, Moti (Avtor) |
Datoteke: | http://www.sciencedirect.com/science/article/pii/S0957417414002462
RAZ_Natek_Srecko_i2014.pdf (787,93 KB) MD5: 9C3BF7CB59174B70B03A3711302D5411
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Jezik: | Angleški jezik |
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Vrsta gradiva: | Znanstveno delo |
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Tipologija: | 1.01 - Izvirni znanstveni članek |
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Organizacija: | MFDPŠ - Mednarodna fakulteta za družbene in poslovne študije
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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. |
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Ključne besede: | data mining, knowledge management system, student's success rate, data mining for small data set, higher education institutions, educational data mining |
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Status publikacije: | Objavljeno |
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Verzija publikacije: | Objavljena publikacija |
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Leto izida: | 2014 |
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Št. strani: | str. 6400-6407 |
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Številčenje: | Vol. 41, iss. 14 |
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PID: | 20.500.12556/ReVIS-767 |
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UDK: | 004.8:378 |
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ISSN pri članku: | 0957-4174 |
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COBISS.SI-ID: | 12870561 |
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DOI: | 10.1016/j.eswa.2014.04.024 |
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Datum objave v ReVIS: | 19.02.2016 |
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Število ogledov: | 8329 |
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Število prenosov: | 329 |
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