Deep Learning Questions Can Help Selection of High Ability Candidates for Universities

Autor/inn/en	Mellanby, Jane; Cortina-Borja, Mario; Stein, John
Titel	Deep Learning Questions Can Help Selection of High Ability Candidates for Universities
Quelle	In: Higher Education: The International Journal of Higher Education and Educational Planning, 57 (2009) 5, S.597-608 (12 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0018-1560
DOI	10.1007/s10734-008-9164-y
Schlagwörter	College Admission; College Applicants; College Entrance Examinations; Prediction; Academic Achievement; Private Schools; Public Schools; Culture Fair Tests; Foreign Countries; United Kingdom (England) + Suchen Sie Ihr Suchwort? Hochschulzugang; Hochschulzulassung; Zulassung; College applications; Studienbewerber; Aufnahmeprüfung; Vorhersage; Schulleistung; Private school; Privatschule; Public school; Öffentliche Schule; Ausland
Abstract	Selection of students for places at universities mainly depends on GCSE grades and predictions of A-level grades, both of which tend to favour applicants from independent schools. We have therefore developed a new type of test that would measure candidates' "deep learning" approach since this assesses the motivation and creative thinking that we look for in university students. We recruited 526 applicants to Oxford University and gave them a short commentary test and a learning style questionnaire. Specific deep learning approach questions correlated with results in the new test, and both predicted whether the candidate subsequently obtained a place at Oxford. Furthermore high scores on one open-ended commentary question, demanding arguments in favour of a case, produced a greater than 70% chance of obtaining a first class degree at the end of their course irrespective of the candidates' type of school attended or GCSE scores. Candidates from State schools scored as well as those from Independent schools in both tests. Thus our test seemed to index candidates' potential to succeed at a highly selective university, and might usefully be added to current selection procedures for such universities. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10