Artificial intelligence-enabled prediction model of student academic performance in online engineering education

Online education has been facing difficulty in predicting the academic performance of students due to the lack of usage of learning process, summative data and a precise prediction of quantitative relations between variables and achievements. To address these two obstacles, this study develops an ar...

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Vydáno v:	The Artificial intelligence review Ročník 55; číslo 8; s. 6321 - 6344
Hlavní autoři:	Jiao, Pengcheng, Ouyang, Fan, Zhang, Qianyun, Alavi, Amir H.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Dordrecht Springer Netherlands 01.12.2022 Springer Springer Nature B.V
Témata:	Academic achievement Analysis Artificial Intelligence CAI Computation Computer assisted instruction Computer Science Data Distance learning Education Engineering Engineering education Engineering schools Evolutionary computation Genetic algorithms Genetics Internet Knowledge acquisition Learning Online education Performance evaluation Performance prediction Prediction models Predictions Students Teaching Variables Online engineering education Higher education Online learning Artificial intelligence Collaborative learning Prediction model
ISSN:	0269-2821, 1573-7462
On-line přístup:	Získat plný text
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