
06649305
a
2016f.00406
Curley, Nuala
Meehan, Maria
The challenge of collecting useful qualitative data on students' visits to a mathematics support centre at a university in Ireland.
Adams, G. (ed.), Proceedings of the British Society for Research into Learning Mathematics (BSRLM). Vol. 35, No. 1. Proceedings of the day conference, St. Patrick's College, Dublin, Ireland, February 28, 2015. London: British Society for Research into Learning Mathematics (BSRLM). 2530 (2015).
2015
London: British Society for Research into Learning Mathematics (BSRLM)
EN
C95
D75
university teaching
educational research
learning problems
remedial teaching
mathematics support centre
basic mathematical problem areas
data collection
collaborative work with tutors
evidence based approach
http://www.bsrlm.org.uk/IPs/ip351/BSRLMIP35105.pdf
Summary: Since September 2009, the Mathematics Support Centre (MSC) in University College Dublin (UCD) has kept an electronic record of each student visit to the Centre. By September 2013 there had been 21,200 visits and an analysis of the qualitative data, specifically the tutors' comments on students' difficulties, was planned to identify the mathematical topics and concepts that were causing persistent difficulties. However we found the nature of the data collected lacked the detail to allow the analysis to take place. We realized that in order to identify the mathematical topics with which students experience difficulty, firstly we needed to identify the nature of the data we required and to do this rigorously and secondly, to work with the tutors to find ways in which they could identify this data and record it efficiently. We describe our efforts, and those of the tutors, over the last eighteen months to collect this data. In September 2014, we commenced our data recording proper. This involved eight weeks of intensive collaborative work with the tutors to ensure the quality and authenticity of the data collected. During this period there were 2,012 visits to the MSC. We also present a preliminary analysis of the most prevalent mathematical topics that are emerging from this eightweek data collection.