dc.contributor.advisor |
Mabsout, Ramzi Jr |
dc.contributor.author |
Khachan, Amani Jr |
dc.date.accessioned |
2020-09-22T13:00:46Z |
dc.date.available |
2020-09-22T13:00:46Z |
dc.date.issued |
9/22/2020 |
dc.identifier.uri |
http://hdl.handle.net/10938/21922 |
dc.description |
Pierre Mouganie
Hossein Radmard |
dc.description.abstract |
Building student career identity is central to the mission of higher education. Career decisions are taken at young ages and involve both immediate and long-term costs and benefits. Previous work on nudging interventions in higher education had targeted students’ matriculation, retention and academic involvement. This paper explores the potential of college career services in employing nudging and machine learning to influence and support students with their career identity build-up process, which in turn would impact their success and commitment. |
dc.language.iso |
en |
dc.subject |
Nudging |
dc.subject |
Machine Learning |
dc.subject |
Learning Analytics |
dc.subject |
Employability |
dc.subject |
Career Development Learning |
dc.subject |
Career Identity |
dc.title |
Can Nudging and Machine Learning Improve the Effectiveness of University Career Services? |
dc.type |
Thesis |
dc.contributor.department |
Department of Economics |
dc.contributor.faculty |
Faculty of Arts and Sciences |
dc.contributor.institution |
American University of Beirut |