Detecting students-at-risk in computer programming classes with learning analytics from students’ digital footprints

Different sources of data about students, ranging from static demographics to dynamic behavior logs, can be harnessed from a variety sources at Higher Education Institutions. Combining these assembles a rich digital footprint for students, which can enable institutions to better understand student b...

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Vydáno v:	User modeling and user-adapted interaction Ročník 29; číslo 4; s. 759 - 788
Hlavní autoři:	Azcona, David, Hsiao, I-Han, Smeaton, Alan F.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Dordrecht Springer Netherlands 01.09.2019 Springer Nature B.V
Témata:	At risk students Computer programming Computer Science Demographics Digital computers Feedback Footprints Higher education institutions Management of Computing and Information Systems Multimedia Information Systems Prediction models Students User Interfaces and Human Computer Interaction Learning analytics Educational data mining Predictive modelling Computer Science Education Peer learning Machine learning
ISSN:	0924-1868, 1573-1391
On-line přístup:	Získat plný text
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