From Current Students
A Lecture on Quantitative Approach (by Dr. Ryo Sasaki, IDCJ)
MFUNGO, Bahati Deusdetus (Tanzania)
The world might be said to be made up of that which is relatively measurable and that which is relatively immeasurable. Different schools of thinking place different levels of emphasis on the very measurable and the very immeasurable. This is what has been the prodigious debate between qualitative and quantitative approaches. Some people believe that there is a gamut between quantitative and qualitative data definition and collection. Having this in his mind Dr Ryo Sasaki made a brief lecture on quantitative approach at Meiji University especially for the Class of Research Method 2 organized by Dr. Aki Yonehara, afterwards having again a Brown Bag Seminar at International Student Lounge.
Dr. Sasaki is a senior researcher at International Development Centre of Japan (IDCJ). On the said day he unveiled the exquisite stories of ‘Quantitative approach’ in the field of Program Evaluation. Since Program Evaluation is the systematic assessment of the operation and/or outcomes of a program or policy, compared to a set of explicit or implicit standards, he gave examples of outcome/impact evaluation reports taken from different countries. Five basic designs for impact evaluation were introduced, namely, Simple before-after, Interrupted time series, Generic control, Matched control and Randomized controlled trial. In fact these designs were presented from the so called simple to the rigorous one. Thanks to JICA as most of the reports were made under their command.
Basically I was very overwhelmed with this topic bearing in mind the fact that program evaluation has been a course that I have been interested to deal with. With different examples, I got to know some of the criteria that should be put into account before an individual decides for a certain design of evaluation. To know weaknesses and strengths of every single design again was of a paramount importance to me. Indeed, the lecture has built a strong faith in me especially on how to run the rigorous statistical analysis, hoping to apply it in my future career.