The Application Of Repertory Grid Analysis In Eliciting Conceptual Frameworks And Classificatory Knowledge Of Biological Natural Kinds Concepts
University of Dublin, Ireland
Supervisor: Dr. Philip S.C. Matthews
Concepts give structure and order to the world around us. However, many learners are impeded by the perceived difficulty of concepts presented to them, and as a result of the mode of presentation. Students’ conceptual structures have been studied at length in science education in the hope of remediating impediments to learning. Despite much research in conceptual development, and prior conceptions in particular, relatively little has focused on the structures of biological concepts and less again on biological concepts that are natural kinds. This work describes four empirical studies concerning biological natural kind concepts that involve using repertory grid analysis (RGA) as a tool for investigating the structures of representations of these concepts and how students classify them. RGA possesses a powerful set of tools, which a researcher may utilise in order to examine the structures of conceptual frameworks, as concept mapping also claims to do. Modern RGA is computer-based tool and models of conceptual structures can be represented in graphical form. Protocols were used to compare the conceptual frameworks of a group of individuals, and conceptual change can be monitored in a rigorous way that is not possible with customary concept mapping techniques. Convenience samples of senior primary and post-primary students were used in the Republic of Ireland, Northern Ireland and Valencia; two qualified biologists were retained to provide a base-line comparison. The studies consisted of tasks whereby students were presented with sets of stimuli (the first study which used words, and the others used graphics): (i) one set of five equids and the concept ‘goat’; (ii) two sets of six equids (consisting of examples drawn from the following three categories: extant, extinct and imaginary); (iii) a large set of mammals; and (iv) five sets of dicotyledonous plant families. Grids of rankings were elicited from the students’ interaction with the stimuli and these were subjected to mathematical procedures such as principal components analysis and cluster analysis. In the first introductory study it was found that RGA could be used to represent the conceptual structures of science learners. Perceptually similar concepts were clustered together and outlying concepts formed separate groups. In-between concepts such as hybrids were dealt with in an idiosyncratic way, i.e., the students constructed their own understanding of how these ‘fitted-in’ and where to make the appropriate ‘cuts’ in the array of living things before them. The elicited grids in the case of the mammals were be ‘averaged’ and compared (either between individuals or between groups which could include the qualified biologists or not); whereas in the studies on equids and dicotyledons visual networks were produced, called ‘socionets’. Those produced for the students in the equid and dicotyledonous family studies demonstrated a commonality in the way these concepts were represented at a given limit but differences were noted over the time frame investigated (five year groups in the case of equids) and differences between the N. Ireland and Valencia groups were noted in the case of the dicotyledons study. Some students could be denoted as ‘consensual’ i.e., they had the greatest number of links whereas others shared very little with their peers or the experts in terms of their ability to represent the concepts provided, i.e., they were ‘isolated’ in their conceptual structures. Those socionets produced for in the mammals study displayed cultural or folkbiological understanding of the mammals rather than using their formal biological understanding. These findings point to the rich reality of the students’ understanding of the living world and therefore how practitioners can investigate such understanding using RGA.
McCloughlin, T.J.J. (2008) The Application Of Repertory Grid Analysis In Eliciting Conceptual Frameworks And Classificatory Knowledge Of Biological Natural Kinds Concepts. Unpublished PhD thesis. University of Dublin, Trinity College.