Dear all,
The University of Oxford Quant SIG Seminar Series resumes next Monday (April 30) for Trinity term. The schedule for this term promises to be just as interesting as the last, with presentations from established academics and students alike. For the first meeting this term (Monday, 30 April), we welcome Andrea Canales (DPhil candidate, Department of Sociology, Oxford University) presenting on the following topic:
Does teaching affect student’s chances of completing a degree at British Universities?
(please see abstract below for more detail)
This promises to be a very interesting talk, and an excellent beginning to this term's Quant SIG. As usual the Quant SIG will meet in Seminar Room J from 12:15pm-2pm, Department of Education, 28 Norham Gardens, Oxford OX2 7PY.
If you do not have access to the building, please contact Patrick Alexander ([log in to unmask]) to arrange access.
Best wishes,
Patrick Alexander
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ABSTRACT:
Abstract
This paper examines the effects of teaching (student-faculty ratio, learning resources and satisfaction with teaching quality) on student’s chances of completing a degree at British Universities.
I employ three data sources to conduct the empirical analyses . First, I use student-level longitudinal data provided by the Higher Education Statistic Agency (HESA), which contains information about student’s academic progression at British Universities throughout years. I also employ institutional-aggregated level data drawn from the National Student Survey (NSS), which provides information about student’s satisfaction with teaching quality at universities in the UK. Finally, I employ institutional information provided by HEFCE and HESA about universities’ learning resources (faculty and books) and infrastructure.
A series of factorial analyses were carried out with the questions from the National Student Survey (NSS), in order to determine how many dimensions composed student’s evaluation of teaching quality. Three dimensions were identified as central aspects of teaching quality: teaching organization, teaching feedback and learning resources. Once these dimensions were identified, multilevel binomial regression analyses (random intercepts) were used to determine the main effects of teaching and institutional variables on student’s attainment. Random coefficient models with cross level interactions were also conducted to analyze how these institutional aspects vary across different groups of students.
Overall, the analyses revealed that institutional aspects –those related to conventional characteristics and teaching aspects- contribute to explain some institutional variation in the student’s chances of degree completion. Likewise, the results confirmed that conventional features such as institutional selectivity or type of university have greater significance on student’s attainment than teaching aspects. The effect of teaching is rather small and varies across different student’s populations.
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