1 / 14

Background

The effectiveness of remedial education- addressing enhancement in student performance and retention in a post-1992 university Giorgio Di Pietro Westminster Business School DEE annual conference London School of Economics 6 September 2011

nicholas-sherman
Télécharger la présentation

Background

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. The effectiveness of remedial education- addressing enhancement in student performance and retention in a post-1992 university Giorgio Di Pietro Westminster Business School DEE annual conference London School of Economics 6 September 2011 I would like to acknowledge the financial support received by the Economics Network of the Higher Education Academy

  2. Background The UK higher education system has undergone significant expansion in recent decades. Alongside the benefits of this rapid expansion, there are also some concerns. One of these concerns is that a large number of students accepted into higher education institutions are unprepared for this level of study. There is great evidence that the chances of obtaining a degree are significantly reduced for students that start university with inadequate academic skills.

  3. Background-cont Typically colleges and universities set up remedial courses in an attempt to address the problem of accepting unprepared students into higher education. These courses are specifically designed for first-year students and aim to help bridging the gap between students’ knowledge and the requirements for their degree courses. Despite its growing importance, there is little evidence about the effectiveness of remedial courses. This is due to the paucity of data as well as to the difficulty of accounting for selection into remedial education.

  4. Objective of the paper This project aims at analysing the effectiveness of a math remedial course adopted by a single School of a post-1992 university. It uses a regression discontinuity (RD) design in an attempt to address the problem related to selection into remedial education. The RD design exploits the discontinuity induced by rules used for the assignment to remedial courses.

  5. Data The attention is focused on three cohorts of first-year students between the academic years 2007-2008 and 2009-2010. The total number of students is 1,521. Of these approximately 33.3% have failed the diagnostic test and hence have been assigned to a math remedial course. The effectiveness of remedial education is measured against student performance on a math-based module that is compulsory for both remedial and non-remedial students. I consider two indicators of student performance on this module: 1) a binary variable that takes the value 1 if the student has successfully completed the module, and 0 otherwise; 2) the overall score (out of 100) received by the student on the module.

  6. Differences in observable characteristics between remedial and non-remedial students In line with the findings obtained by similar studies (see, for instance, Attewell et al., 2006), remedial students are more likely to be older, more likely to come from an ethnic minority group and more likely to have a low socio-economic background relative to non-remedial students.

  7. RD Design • We focus our attention on students who either barely failed or barely passed the math diagnostic test. The basic idea of the RD design is to compare the average performance of these two groups of students on the compulsory math-based module. • These groups of students are assumed to have the same observable (and unobservable) characteristics.

  8. Difference in observable characteristics between remedial and non-remedial students within a 2- point interval around the cut-off on the math diagnostic test ** indicates statistical significance at 5%;

  9. *** indicates statistical significance at 1%

  10. ** indicates statistical significance at 5%; *** indicates statistical significance at 1%

  11. *** indicates statistical significance at 1%

  12. ** indicates statistical significance at 5%; *** indicates statistical significance at 1%

  13. Conclusions Our empirical analysis suggests that remediation does not matter! This result is consistent with that obtained by Lagerlöf and Seltzer (2009) who use data from a pre-1992 university. Other two findings (not shown in this presentations) are: 1) Timing of remediation does not matter either 2) Remediation does not affect the performance of students on other compulsory first-year modules

More Related