Students' concept of models: An epistemological and ontological perspective
David F. Treagust, Gail Chittleborough and Thapelo L. MamialaScience and Mathematics Education Centre
Curtin University of Technology
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Students' concept of models: An epistemological and ontological perspectiveDavid F. Treagust, Gail Chittleborough and Thapelo L. MamialaScience and Mathematics Education Centre Curtin University of Technology |
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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.
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 Rutherford (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.
| Statement | Total % 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 facts 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.
| Item number | df | Sum of squares | Mean square | F | Significance | |
| Item 1 | Between groups Within groups Total | 3 238 241 | 1.2 38.53 40.25 | 0.57 0.16 | 3.55 | 0.01* |
| Item 2 | Between groups Within groups Total | 3 239 242 | 2.60 23.70 26.30 |
0.87 0.10 | 8.73 | 0.00** |
| Item 3 | Between groups Within groups Total | 3 237 240 | 0.14 23.05 23.20 |
0.05 0.10 | 0.49 | 0.69 |
| Item 4 | Between groups Within groups Total | 3 235 238 | 1.40 45.92 47.32 |
0.47 0.20 | 2.39 | 0.07 |
| Item 5 | Between groups Within groups Total | 3 237 240 | 0.64 27.84 28.48 | 0.21 0.18 | 1.81 | 0.15 |
| Item 6 | Between 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.
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.
| Item 1: Concept: Model as a representation | |
| 7212 | Although 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' |
| 4712 | In science no one has ever seen an atom. Chemistry or science are all based on theory so they must be ideas and representations |
| 3912 | The models can never be accurate duplicates of reality because reality is too complicated. You simply have to try and understand how things work |
| 3712 | We use models to create a visual image that we can work with to test out ideas |
| 2911 | Science - too complicated can't be accurate duplicates of reality |
| 3111 | I think the purpose of models is to represent an idea or real thing in more understandable contexts, not simply be a replica |
| 2211 | Model 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 | |
| 2911 | Too many exceptions; one model can't cover everything eg. light ---> particles ---> waves/rays ?? |
| 3011 | There are different ways of showing things, ie. different model shapes and formulae, etc |
| 3511 | Many models are required to explain various aspects of the phenomena |
| 3111 | Different models of the same thing may be used to emphasise and show in detail certain aspects |
| 3912 | Ideas 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 | |
| 3011 | Even though things don't have heaps of support they may still be right |
| 0811 | New ideas develop long after our passing |
| 2111 | Scientists may think that they are smart and know everything but not really |
| 3311 | When it (the model) is right, it will be accepted by a large majority of scientists |
| 3611 | They (scientists) have been proven wrong in the past, so what were learning now might all be non-existent and wrong. |
| 3111 | As we generate a greater understanding of subjects we will be better able to create increasingly "correct" models |
| 3511 | As new knowledge comes to hand, pre-existing knowledge may be considered as invalid. |
| 4612 | Facts are objective and are rarely disputed |
| 4612 | Once a model can be utilised to demonstrate a theory it is acceptable |
| 4712 | Change in technology makes the impossible, possible, theories today may be proven wrong in future years! |
| 5512 | 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. |
| 5712 | If a new model can't be used properly that for what they created it- it is useless |
| 7312 | Science has not yet developed to its full potential and most likely never will this is because there are always new things to discover |
| 6512 | 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. |
| 6312 | New and improved ideas are thought of everyday - changing the way we apply ourselves to tasks as technology and understanding becomes more advanced. |
| 6512 | If scientists don't support a new scientific model then it won't be accepted by others and therefore would not be used. |
| 6412 | Without 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.
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' learning. 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:
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.
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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| 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 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/archives/forums/2001/treagust.html |