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Autor/inn/enZhang, Mingyu; Ma, Jian; Liu, Zhiying; Sun, Jianshan; Silva, Thushari
TitelA Research Analytics Framework-Supported Recommendation Approach for Supervisor Selection
QuelleIn: British Journal of Educational Technology, 47 (2016) 2, S.403-420 (18 Seiten)Infoseite zur Zeitschrift
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN0007-1013
DOI10.1111/bjet.12244
SchlagwörterSupervisors; Supervisor Supervisee Relationship; Supervisory Methods; Social Networks; Outcome Based Education; Qualitative Research; Evaluation Methods; Cognitive Style; Selection Criteria; Student Research; Researchers
AbstractIdentifying a suitable supervisor for a new research student is vitally important for his or her academic career. Current information overload and information disorientation have posed significant challenges for new students. Existing research for supervisor identification focuses on quality assessment of candidates, but ignores indirect relevance with candidate supervisors' previous students, social network connections and their thinking styles. This paper presents a comprehensive student-centric approach based on research analytics framework for finding and recommending supervisors for new students. In particular, it integrates multiple measurements from three dimensions, i.e., "relevance," "connectivity" and "quality." A prototype system was developed to support student-supervisor recommendations on a research social network platform (i.e., www.ScholarMate.com). The results of user-based evaluations demonstrate that our proposed approach generates more satisfactory recommendations as compared with that of all baseline methods. (As Provided).
AnmerkungenWiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2020/1/01
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