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Improving science education in Europe - Survey: 'Students' images of science'

This study was designed to provide information about the images of science drawn upon by science students during labwork. By ‘images of science’ we mean the profile of ideas about the epistemology and sociology of science used by individuals in specific contexts for specific purposes. In the case of labwork, students draw upon images of science to explain the purposes of empirical investigation, relationships between data and knowledge claims, and relationships between knowledge claims and experimental design, analysis and interpretation of data. As individuals are viewed as having a number of images of science that might be deployed in a given situation, no attempt was made to classify individual students as thinking in a particular way. Rather, findings from the study have been used to identify ways of thinking used by large numbers of students in a variety of situations.

Labwork might well develop students’ conceptual understanding or their skills in planning investigations, or their aptitudes at using standard laboratory procedures in carrying out investigations. Many students in teaching laboratories often work with knowledge claims already agreed as reliable within the scientific community. For example, they may be involved in work to illustrate accepted theories or to apply accepted theory in specific contexts. Their ideas about how that knowledge came to be viewed as reliable may well influence their labwork. For all these reasons, participation in labwork involves students in drawing upon epistemological understanding.

In order to investigate the epistemological understanding that students might draw upon during labwork, responses were collected to 5 written survey questions from 661 students in the participating countries. These questions focused upon students’ views on the nature of the data collected during labwork, links between data and knowledge claims in labwork, and the ways in which decisions are made about data collection and drawing conclusions during labwork.

Three ‘images of science’ appeared to by used by significant numbers of students in a variety of contexts. These were:
- A ‘data-focused view’, in which students appeared to view the process of data collection as a simple one of description of ‘the real world’. For example, 12% of the university students in the sample stated that the best estimate of a value from a set of measured data should correspond to a measured value, and 28% of university students suggested that the process of proposing a relationship between two variables was a simple matter of following a routine algorithm to join measured points.

- A ‘radical relativist view’, in which students appeared to view the process of drawing conclusions as so problematic that it is never possible to select one explanation as being better than another one. For example, 16% of university students suggested that it is up to individual scientists to decide how to interpret a given data set as there is no way of determining between two contrasting views.

- A ‘theory and data linked view’, in which theory, data and methodological aspects of labwork are viewed as inter-related, each in principle being able to influence the other.

From this, it appears that many students are likely not to recognise the epistemological basis of routine algorithmic procedures used for data handling during labwork, such as estimating values from sets of data and drawing lines and curves through measured data points. In some cases, this is likely to lead to students taking inappropriate actions during their labwork learning (such as assuming that computers can solve problems of data analysis, not recognising the need for scientists to instruct computers how to handle data according to specific requirements determined by theoretical considerations). Findings from this study suggest that individual students draw from a range of images of science in acting in various situations. For many students, it may therefore be necessary to introduce ideas about the epistemological basis of routine algorithms for data analysis, as well as to give students experience and practice at applying this reasoning in a variety of appropriate labwork contexts.

It also appears that many students are likely to see knowledge claims as emerging directly from the logical analysis of data, not recognising how particular theories and models help to shape scientists’ ways of evaluating and interpreting data. This may lead to inappropriate behaviour during labwork, such as students not recognising how theory might be drawn upon during experimental design, analysis and interpretation, or students appearing likely to draw strong conclusions from investigations carried out in labwork, based on inconclusive evidence.

Reported by

Universite de Paris-Sud XI
Rue Georges Clemenceau
91405 Orsay
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