Scientific external representations (ERs), such as diagrams, images, pictures, graphs and
animations are considered to be powerful teaching and learning tools, because they assist
learners in constructing mental models of phenomena, which allows for the comprehension
and integration of scientific concepts. Sometimes, however, students experience difficulties
with the interpretation of ERs, which· has a negative effect on their learning of science,
. . including biochemistry. Unfortunately, many educators are not aware of such student
difficulties and make the wrong assumption that what they, as experts, consider to be an
educationally sound ER will necessarily promote sound. learning and understanding among
novices. On the contrary, research has shown that learners who engage in the molecular
biosciences can experience considerable problems interpreting, visualising, reasoning and
learning with ERs of biochemical structures and processes, which are both abstract and often
represented by confusing computer-generated symbols and man-made markings.
The aim of this study was three-fold. Firstly, to identify and classify students' conceptual and
reasoning difficulties with a selection of textbook ERs representing· IgG structure and
function. Secondly, to use these difficulties to identify sources of the difficulties and,
therefore, factors influencing students' ability to interpret the ERs. Thirdly, to develop a
model of these factors and investigate the practical applications of the model, including
guidelines fOf improving ER design and the teaching and learning with ERs. The study was
conducted at the University of KwaZulu-Natal, South Africa and involved a total of 166
second and third-year biochemistry students. The research aims were addressed using a p,ostpositivistic
approach consisting of inductive and qualitative research methods. Data was
collected from students by means of written probes, audio- and video-taped clinical
interviews, and student-generated diagrams.
Analysis of the data revealed three general categories of student difficulties, with the
interpretation of three textbook ERs depicting antibody structure and interaction with antigen,
termed the process-type (P), the. structural-type (S) and DNA-related (D) difficulties.
Included in the three general categories of difficulty were seventeen sub-categories that were
each classified on the four-level research framework of Grayson et al. (2001) according to
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how much information we had about the nature ofeach difficulty and, therefore, whether they
required further research. The incidences of the classified difficulties ranged from 3 to 70%,
across the student populations and across all three ERs. Based on the evidence of the
difficulties, potential sources of the classified difficulties were isolated. Consideration of the
nature of the sources of the exposed difficulties indicated that at least three factors play a
major role in students' ability to interpret ERs in biochemistry. The three factors are:
students' ability to reason with an ER and with their own conceptual knowledge (R),
students' understanding (or lack thereof) of the concepts of relevance to the ER (C), and the
mode in which the desired phenomenon is represented by the ER (M).
A novel three-phase single interview technique (3P-SIT) was designed to explicitly
investigate the nature of the above three factors. Application of3P-SIT to a range of abstract
to realistic ERs of antibody structure and interaction with antigen revealed that the. instrument
was extremely useful for generating data corresponding to the three factors.. In addition;
analysis of the 3P-SIT data showed evidence for the influence ofone factor on another during
students' ER interpretation, leading to the identification of a further four interactive factors,
namely the reasoning-mode (R-M), reasoning conceptual (R-C), conceptual-mode (C-M) and
conceptual-reasoning-mode (C-R-M) factors. The Justi and Gilbert (2002) modelling process
was employed to develop a model of the seven identified factors. Empirical data generated
using 3P-SIT allowed the formulation and validation of operational definitions for the seven
factors and the expression of the model as a Venn diagram,
Consideration ofthe implications of the model, yielded at least seven practical applications of
the model, including its use for: establishing whether sound or unsound interpretation,
learning and visualisation of an ER has occurred; identifying the nature and source of any
difficulties; determining which of the factors of the model are positively or negatively
influencing interpretation; establishing what approaches to ER design and teaching and
learning with ERs will optimise the interpretation and learning process; and, generally
framing and guiding researchers', educators' and authors' thinking about the nature of students'
difficulties with the interpretation of both static and animated ERs in any scientific context.
In addition, the study demonstrated how each factor of the expressed model can be used to
inform the design of strategies for remediating or preventing students' difficulties with the
interpretation of scientific ERs, a target for future research. / Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2005.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:ukzn/oai:http://researchspace.ukzn.ac.za:10413/5484 |
| Date | January 2005 |
| Creators | Schonborn, Konrad Janek. |
| Contributors | Anderson, Trevor Ryan., Grayson, Diane J. |
| Source Sets | South African National ETD Portal |
| Language | en_ZA |
| Detected Language | English |
| Type | Thesis |
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