Quantitative research has always
been a challenging topic in my teaching of research methods. Quite a number of
my students are innately disinclined to deal with numbers and find statistical
analysis uninteresting and even unnerving. So every time I cover quantitative research,
I always start with this quote from Earl Babbie’s The Practice of Social
Research:
““Empirical research is first and
foremost a logical rather than a mathematical operation. Mathematics is merely
a convenient and efficient language for accomplishing the logical operations inherent
in quantitative data analysis. This textbook is not intended to teach you
statistics or torture you with them. Rather, I want to sketch out a logical
context within which you might learn and understand statistics.”
It is important that students understand
statistics are just a means to an end – a tool that we can use to help us accomplish
our research objective by making sense of quantitative data. In my teaching, I
focus primarily on the conceptual understanding of statistics. Students are
expected to master what the frequently used statistical measures are, when to
use them, for what types of variables and what kinds of analytic objectives, and
don’t have to worry about the computational process. They can explore that on
their own – there are many tutorials on YouTube.
At this year’s SCELC Research Day, I gave a
workshop on quantitative data analysis, and this “conceptual understanding”
strategy seemed to have worked well. We had interesting discussions around the
tables and it’s great to see how the librarians planned to use the statistics
covered in the workshop in the analysis of their existing data sets. I just
wish there were more time for us to do some hands on exercises. Nonetheless, it
was a great experience talking about research methods with librarians, as always.
Formalized Curiosity 