Year: 2003
Type: preprint
Abstract: A number of studies have been conducted which use the Bloom taxonomy to improve teaching and learning.However, to our knowledge, neither the Bloom taxonomy nor any other established learning taxonomy has been used as a basis to develop a quantifiable tool that will enable teachers to analyse the cognitive process embedded in the objectives and assessment of a subject, as well as provide a methodology to assess alignment of those objectives with the assessment tasks.This paper presents the development of such a quantifiable tool.We discuss the assumptions, method and potential benefits of the outlined approach and in particular its value in providing a mechanism for comparison between subjects, both over time for a given subject and between subjects.The approach has been applied to a specific example in the education system of a profession, the Institute of Actuaries of Australia.The approach is not mathematically difficult to develop.The model requires a number of parameters to be specified.Once these parameters are specified then the methodology is robust.Adjustments to results are made by explicit adjustments to the parameters and not the methodology.A key consequence of this is that once the methodology is accepted, results and any changes can be explicitly tracked and the causes unambiguously identified.In environments where subjective opinion may be pronounced, such an approach raises the level and quality of discussion significantlyfrom 'shooting the messenger' to 'addressing the message'.We also comment on the potential for extensions of this work.In an economic and educational environment where teachers are being held more accountable for the attainment of promised learning outcomes for their students the development of the tool proposed here is potentially powerful and widely applicable.
Authors: Julian D. Gribble, Lois Meyer, Anna Jones
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W594705921