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Detecting students-at-risk in computer programming classes with learning analytics from students’ di...

Detecting students-at-risk in computer programming classes with learning analytics from students’ di...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2214668927

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

About this item

Full title

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

Publisher

Dordrecht: Springer Netherlands

Journal title

User modeling and user-adapted interaction, 2019-09, Vol.29 (4), p.759-788

Language

English

Formats

Publication information

Publisher

Dordrecht: Springer Netherlands

More information

Scope and Contents

Contents

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 behaviour and to better prepare for guiding student...

Alternative Titles

Full title

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

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_journals_2214668927

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2214668927

Other Identifiers

ISSN

0924-1868

E-ISSN

1573-1391

DOI

10.1007/s11257-019-09234-7

How to access this item