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Students' concept of models: An epistemological and ontological perspective

David F. Treagust, Gail Chittleborough and Thapelo L. Mamiala
Science and Mathematics Education Centre
Curtin University of Technology
Scientific models are used routinely in science classes to help explain scientific concepts, however it is frequently assumed that students are aware of the role, limitations and purpose of the particular model being used. This paper reports on the results of a pencil and paper questionnaire given to 250 students from Year 8 to Year 11 to gain some insight into students' understanding of the role of models in science. The results provided evidence that many students have a good understanding of the role of models in science with respect to the representational nature of models, the changing nature of models and the multiplicity of models. All items in the instrument support the assertion that the students gain a better understanding of the role of models in science as they learn more about science. Some Year 11 students provided evidence of having a developing scientific epistemology that is most encouraging. The results have led to the suggestion of a categorisation scheme to be used with scientific models to highlight some of their properties to students. The schema provides an ontological interpretation and understanding of the model concept by students.

Introduction

Models have been described as bridges or links between the known and the unknown (Hardwick, 1995) that form an integral part of the building of the students' personal framework for new knowledge. Literature does provide evidence of the value of models in improving understanding of the scientific concept being taught (Acquistapace, 1997; Huddle, White, & Rogers, 2000; Harrison & Treagust, 1998). A model is a broad term that can include a multitude of representations. Our study has focused on scientific models; however students do not always differentiate between scientific models and models in general, so we include all definitions of models in our discussion. Gilbert and Boulter (1995) describe a model 'as an intermediary between the abstractions of theory and the concrete actions of experiment' (p. 54). For students to understand the nature and role of models it is necessary for them to have an understanding of what a model is (Gilbert, 1997). Grosslight, Unger, Jay, & Smith, (1991) reported that a secondary students' understanding of the model concept is naive and slow to develop.

Background

Models and modeling play a significant role within the process of science. Students' overall view of science, their epistemology, evolves from their experiences, their background knowledge and their understanding of how scientific ideas have developed over time. Gilbert (1997) has recommended a more authentic treatment of the process of science with teachers being educated to use models in a more scientific way. Studies have frequently recommended the development of students' modelling skills through the use of models and multiple models. A model has at its core an analogical relation that needs to be constructed and understood by the learner (Duit & Glynn, 1995). In this way, the metaphorical nature of models is often underestimated (Bhushan & Rosenfeld, 1995; Barnea, 1997).

The significant difference between students' understanding of models and that of experts has highlighted the inadequate understanding that some students have of the model concept (Kozma & Russell, 1997; Moreira & Greca, 1995; Grosslight et al., 1991; Ingham & Gilbert, 1991). Inadequacies include the student focusing on the surface features of the model, being unable to transfer from one model to another easily, and not being able to identify the features of a model (Kozma & Russell, 1997). Obviously experts' constructs are beyond that of students however transitional constructs can be developed to bridge the gap. Models play an important role in this process. Treagust and Harrison (1999) recognized that explaining difficult and complex concepts to students in a meaningful way is an onerous task and teachers need sound pedagogical content knowledge and a repertoire of strategies to achieve this. Models can serve as one type of tool to be used in this challenge. Gilbert (1997) has proposed that teachers should be encouraged to use models in a more scientific way to help improve students' perceptions of models.

A model can be a physical object, explanation or idea that is a representation of the real thing. In the learning process, models are proven teaching aids that provide analogous representations (Gilbert & Osborne, 1980). The model requires the learner to identify the analogue (the model) with the target (reality) (Gilbert & Boulter, 1995). Without the learner making this connection, the model has no value. As students use models discerningly, appreciating their limitations, links are formed between the analogue and the target, and each learner constructs a personal mental model for the concept. Gilbert has distinguished models according to their role: a currently accepted theory in a coherent form is often called a consensus model; in generating an image in the learners' mind, the image is often called a mental model; and the expression of learners' personal understanding is often called the expressed model (Gilbert & Boulter, 1995). These are descriptions of general model schema, being more than just different types of models. These complimentary model types interact to play a unique and significant role in the learner's construction of new knowledge. Modelling occurs both in science and in science education (Duit & Glynn, 1995). Are they the same? Do students treat them the same? This is a dilemma that has implications for the way in which students regard and classify scientific models and teaching models.

The common method of classifying models is according to their type, form and method of use (Gilbert & Osborne, 1980; Grosslight et al., 1991). Harrison and Treagust (2000) distinguished 10 different analogical model types: scale models, pedagogical analogical models, iconic and symbolic models, mathematical models, theoretical models, maps, diagrams and tables, concept-process models, simulations, mental models and synthetic models. This classification scheme incorporated a schema for general models and specific model types. In contrast to this is a scheme by Gobert and Clement (1994) that used the categories of structural, functional and spatial to classify specific models. Buckley, Boulter and Gilbert (1997) have presented a framework to classify models according to their 'attributes'. Three aspects are considered: Is the model static or dynamic? Is the model deterministic or stochastic? Is the model material or symbolic? At an alternative ontological level Gilbert, Boulter and Rut herford (1998) describe four different models: a consensus model- an accepted model, tested by scientists and socially agreed upon; a teaching model- a model used to help explain something, an expressed model- the personal expression of the students understanding of the phenomena in speech, actions or writing and a mental model- the personal internal understanding of the phenomena. All the typologies described are equally valid and all very valuable, but they occupy different ontological levels.

The attributes of a model are important, firstly in enabling learners to recognise the strengths and limitations of the particular model, secondly as a method of classifying the model, and thirdly in recognising the level of representation at which the model is presented. Without realising, we classify and sort everything we encounter using our own personal criteria and framework. In teaching, it is necessary to introduce students to a scientific framework, which may or may not be at conflict to their personal framework. The use of classification keys, categorising criteria, sorting methods etc provides the students with a new logical method of sorting information. Any classification scheme that is imposed or introduced to students must be logical and acceptable and may cause the diverse ideas of students to be accommodated and channeled into the new schema.

Research has shown that students have a naive understanding of the role of models in science (Grosslight et al., 1991). This result is not surprising considering that models are used extensively, often without elaboration of their role, the symbolic nature, their limitations and their strengths. The passive use of models leaves the student with the perception of models as descriptors, whereas the active use of models can develop the perception of models as interpretive and predictive tools. For model-based reasoning to be successfully implemented, Stephens, McRobbie, and Lucas (1999) confirmed that students' need to have a good knowledge of the model and be familiar with the connections between the model and the target.

Students' understanding of the dynamic processes of science develops over time through historical examples, scientific method used in experimental work, their general knowledge and personal experiences. Students' epistemologies of science refer to their understanding of how scientific ideas are built up, including their knowledge about the process of knowing about scientific knowledge (Simpson & Weiner 1989). Models play a significant role in the development of scientific ideas. Songer & Linn (1991) categorized students' views of science as: static beliefs, dynamic beliefs and mixed beliefs. The dynamic beliefs group viewed science as 'understandable, interpretive and integrated with many activities around them' (p. 769), whereas the static beliefs group held unproductive beliefs viewing 'science knowledge as static, memorization intensive and divorced from everyday lives' (p.769). The mixed beliefs group, which applies to the majority of students, had some views of each of the other two groups. A student's epistemological understanding is constantly developing, so imposing a label is not always helpful. Despite this, Songer and Linn's categories highlight some qualities that are developing in students as their understanding of scientific knowledge matures. A student's view of models, their type, role and position in the process of science can provide some insight into students' epistemological beliefs.

Considering the complexity, depth and the simplicity that a model may have, it is important for students to use models with a more informed approach. With this in mind, this study surveyed students about their understanding of models to gain a more accurate assessment of this understanding.

Method

The instrument My Views of Models in Science, VOMS, was used to understand students' ideas about models. Responses were obtained from 242 students from three different schools and across four Year levels, 8, 9, 10 and 11. All schools were coeducational, with two being state high schools and one being a private college. The Year 8, 9 and 10 students were studying general science and the Year 11 students had chosen to study chemistry. The students sampled had no specific teaching abut models, however the chemistry students had used chemical models in their classes. The 6 items in the instrument evolved from Aikenhead's (1992) Views of Science - Technology - Society item bank of questions. Each item required students to choose between two alternative statements about scientific models, thus forcing them take a definitive stance in response to the question. For example, given the statement, 'Models and modelling in science are important in understanding science', students were asked to choose whether models are representations of ideas or how things work, or are accurate duplicates of reality. The Year 11 students were also required to provide a reason for their choice. Students' identification was coded with a four digit numbering system indicating school, class, and individual. The responses were recorded and the Statistical Package for Social Scientists (SPSS) (Coakes & Steed, 1996) was used to analyse the quantitative data. Statistical differences were investigated with respect to gender, age and school. ANOVA tests were performed on all items in the survey to identify any differences between different Year levels; t-tests were used to identify any gender differences. The VOMS instrument has a Cronbach alpha reliability of 0.83 indicating that the results of the items are consistent throughout the instrument.

Results

The percentage responses to the instrument, My Views of Models in Science (VOMS), are presented in Table 1.

Table 1: Results of the instrument: My Views on Models and Modelling in Science (n= 248)

StatementTotal %
n=248
% for each Year group
11
n=74
10
n=90
9
n=32
8
n=52

1)Models and modelling in science are important in understanding science. Models are:
a)
b)
representations of ideas or how things work
accurate duplicates of reality
79
21
91
9
77
23
66
34
75
25
2)Scientific ideas can be explained by:
a)
b)
one model only - any other model would simply be wrong.
one model - but there could be many other models to explain the ideas
12
88
3
97
8
92
16
84
31
70
3)When scientists use models and modelling in science to investigate a phenomenon, they may:
a)
b)
use only one model to explain scientific phenomena.
use many models to explain scientific phenomena.
11
89
9
91
12
88
6
94
13
87
4)When a new model is proposed for a new scientific theory, scientists must decide whether or not to accept it. Their decision is:
a)
b)
based on the fact s that support the model and the theory.
influenced by their personal feelings or motives.
73
27
77
23
79
21
69
31
60
40
5)The acceptance of a new scientific model:
a)
b)
requires support by a large majority of scientists
occurs when it can be used successfully to explain results
14
86
6
94
15
85
21
79
15
84
6)Scientific models are built up over a long period of time through the work of many scientists, in their attempts to understand scientific phenomenon. Because of this scientific models:
a)
b)
will not change in future years.
may change in future years.
17
83
15
85
12
87
19
81
29
71

The responses on the VOMS instrument (Table 1) showed that a large majority of students (>70%) view models as a representation of ideas or how things work (item 1); that there could be many other models to explain ideas (item 2); that models are used to explain scientific phenomena (item 3); that a model is based on the facts that support the theory (item 4); a model is accepted when it can be used successfully to explain results (item 5); and that a model may change in future years (item 6).

An independent t-test performed on the six items found that only item 5 was statistically significantly different (p < 0.05) in respect of gender. In that item, the female students have responded more positively, demonstrating a more scientifically sophisticated view of models. An ANOVA analysis on the results for each item with respect to Year level showed statistically significant differences (p < 0.05) between the Year levels for item 1 and item 2 (see Table 2). For both items there was an increase in the number of students choosing the more scientifically valid response with age.

Table 2: ANOVA Analysis of each Item with respect to Year Level

Item numberdfSum of squaresMean squareFSignificance

Item 1Between groups
Within groups
Total
3
238
241
1.2
38.53
40.25
0.57
0.16
3.55

0.01*

Item 2Between groups
Within groups
Total
3
239
242
2.60
23.70
26.30
0.87
0.10
8.73

0.00**

Item 3Between groups
Within groups
Total
3
237
240
0.14
23.05
23.20
0.05
0.10
0.49

0.69

Item 4Between groups
Within groups
Total
3
235
238
1.40
45.92
47.32
0.47
0.20
2.39

0.07

Item 5Between groups
Within groups
Total
3
237
240
0.64
27.84
28.48
0.21
0.18
1.81

0.15

Item 6Between groups
Within groups
Total
3
238
241
0.98
33.7
34.71
0.33
0.14
2.30

0.08


* Indicates significant differences at the .05 level.
** Indicates significant differences at the .01 level.

Students' understanding of three conceptions about models are further discussed, with item 1 of the instrument examining the idea of models as representations, item 2 and 3 looking at the multiplicity of models and items 4, 5 and 6 probing the dynamic nature of models.

Models as representations

There were significant differences across the year groups with 23%, 34%, and 25% of Year 8, 9 and 10 general science students respectively and only 9% of the Year 11 Chemistry students describing a model as an accurate duplicate of reality. This result compares to those reported by Grosslight et. al. (1991) where even higher percentages of students (about 50%) believed that 'the model should be exact, smaller or proportional' (p. 810). The difference between the age groups is significant and provides good evidence that older and more experienced students have a better understanding of the roles of models and the diversity of model types. Chemistry in particular makes extensive use of models. Many scientific models are not exact, in fact with the more abstract concepts, imprecise models are used because reality is too difficult, even impossible to duplicate. There is a dilemma for some students in accepting the lack of precision of some models. The reasons given to support the answer in item 1 that models are representations include 'helps us to explore things too small to see''(1511), "How atoms look is a theory, no one has actually seen them" (3611), "Science is too complicated, it can't be an accurate duplicate of reality" (2911), and "They are how we want to think things behave or look like. However, they aren't accurate as there are many exceptions" (3411). "Although I understand that the models aren't the real thing, it does make it easier to see how a molecule may work" (7212) " they only help us to gain an idea of how something should look and how it behaves etc" (6912). These comments reflect the complexity of the model concept and the subtle differences in students' interpretations. In contrast, reasons given to support the alternative response that models are accurate duplicates of reality include: "proven and tested that it is accurate" (3211)"; "because that is how they are represented in the chemistry text book" (2811) and "atlas" (5512).

The multiplicity of models

Items 2 and 3 examine the coexistence of multiple models, revealing that almost 90% of students agree that many models can be used to explain scientific phenomena. When considering the importance of using more than one model, students supported their choice by saying, "There can be several models that work because no one actually knows what is correct" (7212); "to see things from different perspectives" (4512); "different models of the same thing may be used to emphasise and show in detail certain aspects" and "phenomena are things we try to understand and it may take various models to make clear the phenomena and how it works " (3111). Despite this very high response there is still a significant difference between the Year groups (see Table 2) with 31% of Year 8 students agreeing that 'one model only' is a preferable. This result supports the assertion that older and more experienced students have a better understanding of the roles of models and the diversity of model types as suggested in the previous section.

The dynamic nature of models

Items 4, 5 and 6 deal with the changing nature of models, with 73% of students believing that a model is accepted on the facts that support it and the theory; 86% agreeing that a model is accepted when it can explain results and 83% believing that scientific models will change in the future. The differences between the groups are quite marked in Item 4 with 40% of 8 students believing that scie ntists are 'influenced by their personal feelings or motives' compared with 23% of Year 11 students. Similarly with item 5, 29% of Year 8 students believe 'scientific models will not change in future years' whereas only 17% of Year 11 students support this idea (see table 1). The consistency in the differences between year groups for items 4, 5 and 6 supports the assertion that the students are gaining a better understanding of the role of models as they learn more about science.

The reasons given to support the concept of the dynamic nature of models included "facts may change due to technology" (2211),"they have been proven wrong in the past, so what we are learning now might all be non-existent or wrong"(3611) and " As we generate a greater understanding of subjects we will be better able to create increasingly 'correct' models" (3111). These responses (see Table 3) referred to scientific models with respect to their role in the scientific world and the scientific process and link the scientific model to the broader perspective of scientific changes. These responses provide evidence that a few students are developing a broader view of science, a dynamic perspective as Songer and Linn (1991) described. This epistemological perspective is not usually taught directly, but more often indirectly, through example. The responses (see Table 3) of the Year 11 students given as justification for their choice provide evidence of a wide range of understandings.

Table 3: A sample of Year 11 student responses given to support their choice in the instrument

Item 1: Concept: Model as a representation
7212Although I understand that the models aren't the real thing, it does make it easier to see how a molecule works
5512(Choosing models are accurate duplicates of reality) eg. 'atlas'
4712In science no one has ever seen an atom. Chemistry or science are all based on theory so they must be ideas and representations
3912The models can never be accurate duplicates of reality because reality is too complicated. You simply have to try and understand how things work
3712We use models to create a visual image that we can work with to test out ideas
2911Science - too complicated can't be accurate duplicates of reality
3111I think the purpose of models is to represent an idea or real thing in more understandable contexts, not simply be a replica
2211Model is not always accurate, but it gives ideas how things work and visualise and create image in the mind

Items 2 and 3: Concept: Multiple models
2911Too many exceptions; one model can't cover everything
eg. light ---> particles ---> waves/rays ??
3011There are different ways of showing things, ie. different model shapes and formulae, etc
3511Many models are required to explain various aspects of the phenomena
3111Different models of the same thing may be used to emphasise and show in detail certain aspects
3912Ideas are so big they can be divided into many smaller areas, which can be represented by a model.

Items 4, 5 and 6: Concept: The Dynamic Nature of Models
3011Even though things don't have heaps of support they may still be right
0811New ideas develop long after our passing
2111Scientists may think that they are smart and know everything but not really
3311When it (the model) is right, it will be accepted by a large majority of scientists
3611They (scientists) have been proven wrong in the past, so what were learning now might all be non-existent and wrong.
3111As we generate a greater understanding of subjects we will be better able to create increasingly "correct" models
3511As new knowledge comes to hand, pre-existing knowledge may be considered as invalid.
4612Facts are objective and are rarely disputed
4612Once a model can be utilised to demonstrate a theory it is acceptable
4712Change in technology makes the impossible, possible, theories today may be proven wrong in future years!
5512If a new scientific model is not accepted by the majority of scientists, it won't be used- even if it does successfully explain results.
5712If a new model can't be used properly that for what they created it- it is useless
7312Science has not yet developed to its full potential and most likely never will this is because there are always new things to discover
6512It has already been proven that scientific models will change as understanding increases and technology develops models may be incorrect or not up to date as they should be.
6312New and improved ideas are thought of everyday - changing the way we apply ourselves to tasks as technology and understanding becomes more advanced.
6512If scientists don't support a new scientific model then it won't be accepted by others and therefore would not be used.
6412Without support then you can't succeed other scientists have to prove your model is valid.

A sophisticated argument provided by three students (6412, 6512, 5512, see Table 3) for Item 5 justifying that the acceptance of a new model goes beyond the valid belief of the model needing to successfully explain results. Student 5512 explains that, 'if a new scientific model is not accepted by the majority of scientists, it won't be used - even if it does successfully explain results'. Student 6412 responds: 'Without support then you can't succeed, other scientists have to prove your model is valid". A developing/mixed epistemology is commonly exhibited in the comments such as 'It has already been proven that scientific models will change as understanding increases and technology develops, models may be incorrect or not up to date as they should be' (6512). In this way, the comments presented in Table 3 show the links between models and the student's understanding of the process of science.

Discussion

The results of this study are encouraging with the majority of students having a scientifically acceptable understanding of the model concept and the level of understanding is improving with increasing year levels. However, the study also identifies some students' weaknesses and misunderstandings that have been used as a basis for identifying what students need to know about models. Misunderstandings include: a model being an exact copy; there being only one possible model for a particular phenomenon which is unchangeable; and the value of a model being determined by scientists opinions.

In trying to make the role and meaning of 'models' clearer to students, particular criteria can be addressed. The framework presented in Figure 1 highlights the variety of models and their unique positions in the students' learn ing. Students' ideas of models originate from their experiences that are usually associated with scale models like toy planes, computer simulations, drawings or plans and symbols. Students begin to group these experiences using their own criteria. The three conceptions of models identified by the instrument can be used to develop a typology of models targeting the common mis-understandings that students have shown in this area: 1. Models as representations - refers to the purpose of a model and the accuracy of a model;. 2. The multiplicity of models - refers to the mode of the representation, and 3. The dynamic nature of models - refers to the permanency of models. A typology based on these three conceptions highlights the attributes of particular models by investigating four characteristics:

  1. What is the purpose of the model? For example is it a teaching model, an explanatory model, a predictive model, a mental model, a theoretical model, an analogical model, a scale model, a simulation, etc. More than one response may be correct.

  2. How accurate is the model? Is the representation an exact replica or scale model of the target? Is it imprecise or impressionistic?

  3. The mode of representation- referring to the physical nature of the representation eg visual, concrete, symbolic, verbal, 2 or 3 dimensional?

  4. The permanency of the model. Is this representation accepted as fact? Is it just an idea?
The diversity of the model concept is presented in Figure 1 where four different model concepts are represented: Teaching models, Scientific models, Mental models and Expressed models. The scheme crosses several ontological levels of categorisation of models so can be used to assess teaching models as well as scientific models, mental models and expressed models.

Figure 1

Figure 1: Teaching models, Scientific models, Mental models and Expressed models

The basic input and output classification is simple in explaining how the four different model concepts relate to the learning process while ontological and epistemological aspects of students' understanding can also be layered onto this scheme. Through teaching we are endeavoring to change, develop or modify students' thinking and understanding to a more scientifically acceptable way. The analysis here focuses on the students' understanding of the model concept only, without considering the actual scientific concepts and knowledge that the models are being used to explain, thus revealing the complexities of the learning process.

Conclusion

The VOMMS instrument has provided evidence that many students have a good understanding of the role of models in science with respect to the representational nature of models, the changing nature of models and the multiplicity of models. Areas of concern included the idea that a model is an exact copy; there being only one possible model for a particular phenomenon which is unchangeable; and the value of a model being determined by scientists' opinions. All items in the instrument supported the assertion that that the students are gaining a better understanding of the role of models as they learn more about science. Some Year 11 students provided evidence of having a developing scientific epistemology that is most encouraging.

The term model and its use in science are wide and varied. Identification of particular characteristics of models and the recognition of different model concepts may improve students understanding of the type, role and position of models in the process of Science. It is proposed that the students' epistemological and ontological frameworks can be challenged and enhanced by the active use of models.

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Treagust, D. F., Treagust, G. Chittleborough, Mamiala, T.L. (in press). Students' understanding of the role of scientific models in learning science. International Journal of Science Education.

Authors: David F. Treagust, Gail Chittleborough and Thapelo L. Mamiala
Science and Mathematics Education Centre
Curtin University of Technology, Perth, Western Australia.

Correspondence: Gail Chittleborough
Email: G.Chittleborough@curtin.edu.au
Phone: +61 8 9266 7924 Fax: +61 8 9266 2503
Science and Mathematics Education Centre, Curtin University of Technology
GPO Box U1987, Perth WA 6845, Australia

Please cite as: Treagust, D. F., Chittleborough, G. and Mamiala, T. L. (2001). Students' concept of models: An epistemological and ontological perspective. Proceedings Western Australian Institute for Educational Research Forum 2000. http://www.waier.org.au/forums/2001/treagust.html


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