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Using Fourier coefficients in time series analysis for student performance prediction in blended learning environments
Expert systems, 33 (2016), 2; 189-200. https://doi.org/10.1111/exsy.12142
Gamulin, Jasna; Gamulin, Ozren; Kermek, Dragutin

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Gamulin, J., Gamulin, O. i Kermek, D. (2016). Using Fourier coefficients in time series analysis for student performance prediction in blended learning environments. Expert systems, 33. (2), 189-200. doi: 10.1111/exsy.12142

Gamulin, Jasna, et al. "Using Fourier coefficients in time series analysis for student performance prediction in blended learning environments." Expert systems, vol. 33, br. 2, 2016, str. 189-200. https://doi.org/10.1111/exsy.12142

Gamulin, Jasna, Ozren Gamulin i Dragutin Kermek. "Using Fourier coefficients in time series analysis for student performance prediction in blended learning environments." Expert systems 33, br. 2 (2016): 189-200. https://doi.org/10.1111/exsy.12142

Gamulin, J., Gamulin, O. i Kermek, D. (2016) 'Using Fourier coefficients in time series analysis for student performance prediction in blended learning environments', Expert systems, 33(2), str. 189-200. doi: 10.1111/exsy.12142

Gamulin J, Gamulin O, Kermek D. Using Fourier coefficients in time series analysis for student performance prediction in blended learning environments. Expert systems [Internet]. 2016. [pristupljeno 27.12.2024.];33(2):189-200. doi: 10.1111/exsy.12142

J. Gamulin, O. Gamulin i D. Kermek, "Using Fourier coefficients in time series analysis for student performance prediction in blended learning environments", Expert systems, vol. 33, br. 2, str. 189-200, 2016. [Online]. Dostupno na: https://urn.nsk.hr/urn:nbn:hr:211:534638. [Citirano: 27.12.2024.]

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Podaci o radu
Naslov (engleski)Using Fourier coefficients in time series analysis for student performance prediction in blended learning environments
AutorJasna Gamulin
AutorOzren Gamulin
MBZ: 178974
AutorDragutin Kermek
Autorova ustanovaSveučilište u Zagrebu
Fakultet organizacije i informatike
Znanstveno / umjetničko
područje, polje i grana		DRUŠTVENE ZNANOSTI
Informacijske i komunikacijske znanosti
Sažetak (engleski)
In this work, it is shown that student access time series generated from Moodle log files contain information sufficient for successful prediction of student final results in blended learning courses. It is also shown that if time series is transformed into frequency domain, using discrete Fourier transforms (DFT), the information contained in it will be preserved. Hence, resulting periodogram and its DFT coefficients can be used for generating student performance models with the algorithms commonly used for that purposes. The amount of data extracted from log files, especially for lengthy courses, can be huge. Nevertheless, by using DFT, drastic compression of data is possible. It is experimentally shown, by means of several commonly used modelling algorithms, that if in average all but 5–10% of most intensive and most frequently used DFT coefficients are removed from datasets, the modelling with the remained data will result with the increase of the model accuracy. Resulting accuracy of the calculated models is in accordance with results for student performance models calculated for different dataset types reported in literature. The advantage of this approach is its applicability because the data are automatically collected in Moodle logs.
Ključne riječi (engleski)
Jezikengleski
Vrsta publikacijeZnanstveni rad - Izvorni znanstveni rad
Status objaveObjavljen
Vrsta recenzijeRecenziran - međunarodna recenzija
Verzija publikacijeObjavljena verzija rada (izdavačev PDF)
Naslov časopisaExpert systems
Brojčani podacivol. 33, br. 2, str. 189-200
p-ISSN0266-4720
DOIhttps://doi.org/10.1111/exsy.12142
URN:NBNurn:nbn:hr:211:534638
Datum objave publikacije2016
URL dokumentahttp://bib.irb.hr/823277
URL dokumentahttp://onlinelibrary.wiley.com/doi/10.1111/exsy.v33.2/issuetoc
Vrsta resursaTekst
Prava pristupaOtvoreni pristup
Uvjeti korištenjaIkona licence Zaštićeno autorskim pravom.
Datum i vrijeme pohrane2017-09-21 10:04:10