Within UK higher education the renewed attention to learning and teaching is an impetus for change. Advances in
information technology create new space for learning beyond the traditional classroom lecture format. New
initiatives are creating networked teaching materials for shared use across institutions. But little is known about the
readiness of teachers and students to take advantage of these resources for teaching and study. Are universities
providing the support needed for using these networked resources in classrooms, computer labs, and independent
study?
An academic Task Force on the use of numeric data in learning and teaching has issued a report on the barriers
faced by teachers and students to using national data services across a number of disciplines, including but not
limited to the social sciences. The enquiry focused on numeric data, which involves a higher number of skills to use
than many other types of information resources. Results were analysed from a national survey of teaching
departments in universities, and seven case studies of real-life teaching scenarios in both post- and undergraduate
classes in several disciplines. The Task Force contributed views from their own significant experience of teaching in
academia as well.
The project is part of a national development programme on learning and teaching funded by the JISC (Joint
Information Systems Committee). Its unique focus within the set of projects is on the value of introducing statistical
data such as area census statistics, sample survey datasets, and economic trend data to the educational experience
of students, particularly when students actively take part in analysing the data, and practice drawing conclusions
from empirical evidence.
The enquiry found that despite established use of quantitative secondary analysis of national datasets in research,
a number of issues make its use in teaching and students’independent study difficult, and therefore rare. Whilst
print tables and graphs are often used by lecturers in teaching empirical subjects, statistical files requiring ‘hands-
on’ computer analysis are not commonly built into the teaching design, except in methods courses. Yet these are
transferable skills needed by today’s graduates to enter the professions or advanced study.
Only one-quarter of survey respondents who said they used data in the classroom had considered using the
nationally funded academic data services provided by the Data Archive (at Essex), MIMAS (at Manchester), or
EDINA (at Edinburgh) as a source of the data used in their teaching. The survey uncovered a number of barriers
experienced by teachers in the use of these services, namely a lack of awareness of relevant materials, lack of
sufficient time for preparation, complex registration procedures, and problems with the delivery and format of the
datasets available. These problems were elaborated in open-ended comments by respondents and in the case
studies of current teaching practice.
A compounding problem is the lack of local support for teachers who would like to incorporate data analysis into
substantive courses. A majority of the survey respondents said that the level of support for data use in their own
institutions was ad-hoc. Peer support was more common than support from librarians and computing service staff,
and over one-third received no support whatever. The top three forms of local support needed were data discovery/
locating sources, helping students use data, and expert consultation for statistics and methods (for staff).
The Task Force analysed the results of the sur vey and the experiences expressed in the case studies and issued
recommendations for UK higher education, summorised below:
1. A broad initiative is recommended to promote subject-based statistical literacy for students, coupled with
tangible support for academic teaching staff who wish to incorporate empirical data into substantive courses.
2. The development of high-quality teaching materials for major UK datasets must be funded adequately, in order
to provide salience to subject matter and demonstrate relevant methods for coursework.
3. The national data services need to improve the usability of their datasets for learning and teaching.
4. A more concerted and co-ordinated promotion of the national data services could then follow, which is
responsive to user demand.
5. Universities should develop IT strategies that include data services and support for staff and students, and
integration of empirical datasets into learning technologies
