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Pregled bibliografske jedinice broj: 1084886

Machine learning model for detecting high school students as candidates for drop-out from a study program


Pašić, Đani; Kučak, Danijel
Machine learning model for detecting high school students as candidates for drop-out from a study program // MIPRO 2020 43rd International Convention / Skala, Karolj (ur.).
Rijeka, 2020. str. 1384-1388 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


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Naslov
Machine learning model for detecting high school students as candidates for drop-out from a study program

Autori
Pašić, Đani ; Kučak, Danijel

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
MIPRO 2020 43rd International Convention / Skala, Karolj - Rijeka, 2020, 1384-1388

Skup
43rd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2020)

Mjesto i datum
Opatija, Hrvatska, 28.09.2020. - 02.10.2020

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
machine learning ; logistic regression ; higher education student ; student retention

Sažetak
Transition from high school to university is not successful for all students. Before enrolling in a program, the Admission Office tries to help those students to decide whether that program is best suited for them. They do so by using collected empirical data. The challenge is to classify which students would successfully finish the program and which would not. The students who are most likely not to finish the program successfully should be warned that their decision is not necessarily the best decision for them, and they should consider some other possibilities. This paper proposes one possible criterion for the given challenge: we will develop a machine learning model with the collected data from high schools which the students have attended prior to Algebra and calculate the probability of not finishing the program successfully. Students who would be classified by the model as unsuccessful will receive recommendation for another study program.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti



POVEZANOST RADA


Ustanove:
Visoko učilište Algebra, Zagreb

Profili:

Avatar Url Danijel Kučak (autor)

Avatar Url Đani Pašić (autor)

Poveznice na cjeloviti tekst rada:

ieeexplore.ieee.org www.researchgate.net

Citiraj ovu publikaciju:

Pašić, Đani; Kučak, Danijel
Machine learning model for detecting high school students as candidates for drop-out from a study program // MIPRO 2020 43rd International Convention / Skala, Karolj (ur.).
Rijeka, 2020. str. 1384-1388 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Pašić, Đ. & Kučak, D. (2020) Machine learning model for detecting high school students as candidates for drop-out from a study program. U: Skala, K. (ur.)MIPRO 2020 43rd International Convention.
@article{article, author = {Pa\v{s}i\'{c}, \DJani and Ku\v{c}ak, Danijel}, editor = {Skala, K.}, year = {2020}, pages = {1384-1388}, keywords = {machine learning, logistic regression, higher education student, student retention}, title = {Machine learning model for detecting high school students as candidates for drop-out from a study program}, keyword = {machine learning, logistic regression, higher education student, student retention}, publisherplace = {Opatija, Hrvatska} }
@article{article, author = {Pa\v{s}i\'{c}, \DJani and Ku\v{c}ak, Danijel}, editor = {Skala, K.}, year = {2020}, pages = {1384-1388}, keywords = {machine learning, logistic regression, higher education student, student retention}, title = {Machine learning model for detecting high school students as candidates for drop-out from a study program}, keyword = {machine learning, logistic regression, higher education student, student retention}, publisherplace = {Opatija, Hrvatska} }

Časopis indeksira:


  • Scopus





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