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Science Education at the Nexus of Theory and Practice

Science Education at the Nexus of Theory and Practice

Yew-jin and Aik-Ling National Institute of Education, Singapore

SENSE PUBLISHERS ROTTERDAM / TAIPEI

A C.I.P. record for this book is available from the Library of Congress.

ISBN: 978-90-8790-420-3 (paperback) ISBN: 978-90-8790-421-0 (hardback) ISBN: 978-90-8790-422-7 (e-book)

Published by: Sense Publishers, P.O. Box 21858, 3001 AW Rotterdam, The Netherlands

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All Rights Reserved © 2008 Sense Publishers No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work.

TABLE OF CONTENTS

Preface

ix SECTION A: CONCEPTS, CONCEPTUAL CHANGE & SCIENCE

1.

Concepts, Conceptual Change & Science Yew-Jin Lee and Aik-Ling Tan

1

2.

The Role of Multiple Representations in Learning Science: Enhancing Students’ Conceptual Understanding and Motivation David F. Treagust

7

3.

Making Sense of a, b, c’s of Science: A Dialectic Between Everyday and Scientific Conception Jennifer Yeo, Seng-Chee Tan and Kok-Sing Tang

25

4.

Science Misconceptions in the Service of Conceptual Change: Intervention Studies with Preservice Primary Teachers Joseph P. Riley, Malcolm B. Butler, Toh Kok Aun and Yap Kueh Chin

45

5.

Cultivating Thinking and Comprehension: A Practical Model Taha Massalha and Rachel Abadi

65

6.

Experiments For Challenging Topics in Pre-University Physics Foong See Kit, Lim Chim Chai, Ho Shen Yong, Darren Wong and Loganantham Kuppan

81

7.

Getting the Point: Chemical Concepts in Action Shien Chue, Yew-Jin Lee and Kim Chwee Daniel Tan

111

8.

Standards of Judging Online Information, Searching Strategies, & Learning Outcomes from Online Inquiry Science Activities Chin-Chung Tsai

135

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SECTION B: SCIENCE TEACHER DEVELOPMENT & LEARNING 9.

Science Teacher Development & Learning Yew-Jin Lee and Aik-Ling Tan

155

10.

An Evidential Reasoning Approach to Analysis of Teaching Practices using a Web-based Video Analysis Tool Lynn A. Bryan, Arthur Recesso and Eulsun Seung

159

11.

Preparing Students For Examination: A Divided View Between Teachers’ And Students’ Conceptions Of Good Science Teaching Benny Hin Wai Yung, Siu Ling Wong, Man Wai Cheng, Fei Yin Lo and Derek Hodson

181

12.

Teacher Questioning In Science Classrooms: What Approaches Stimulate Productive Thinking? Christine Chin

203

13.

Generating ‘Knowledge of Practice’ through Collaborative Action Research Karen Goodnough and Pamela Osmond

219

14.

Authority and Transmission versus Knowledge Building: Dilemmas in Learning Science Aik-Ling Tan and Seng-Chee Tan

239

SECTION C: ACCESS TO SCIENCE, ACCESSIBLE SCIENCE 15.

Access to Science, Accessible Science Yew-Jin Lee and Aik-Ling Tan

253

16.

Proposals for Core Nature of Science Content in Popular Books on the History and Philosophy of Science William F. McComas

259

17.

Science Education and the ESL Learner Judith Morris and David Treagust

271

18.

Visual Journeys into Critical Place-based Science Education Steve Alsop and Sheliza Ibrahim

291

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19.

Empathy in Participative Thinking: The Discourse of Physics Classrooms in an Age of Globalization SungWon Hwang and Wolff-Michael Roth

303

20.

A 5-year-old’s Initiation into Scientific Ways of Knowing Yong Jae Joung

317

21.

Physics for Four Year Olds Lynn Chapman and David E. Quinn

333

22.

Learning Science in Informal Settings Wolff-Michael Roth

359

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PREFACE

From 22 to 24 November 2006, Singapore hosted her first international conference devoted to science education––Science Education: What Works. Organized jointly by the National Institute of Education, the Ministry of Education, and the Science Teachers’ Association of Singapore, the event attracted over 400 participants from 18 countries. Feedback from participants was enthusiastic and the organizers were gratified to hear of more than one request that it be conducted yearly, rather than tri-annually as planned. As with most conferences, the networking and sharing opportunities that occurred were the most valuable outcomes. It is in this same spirit that this book attempts to concretize that wisdom that was circulating during the conference: the chapters here represent some of the more rigorous, cuttingedge, and exciting research by plenary speakers and presenters that we as editors felt would be of interest to fellow science educators. Our chosen title, Science Education at the Nexus of Theory and Practice, is evocative and reflects the chief tension in the field of education: How do I link theory and practice? This is a fundamental question that has been asked by countless teachers and academics of whatever vintage yet it resists easy answers. We do not pretend to be able to supply something here that would completely satisfy everybody because the issues are multifaceted (see Carr & Kemmis, 1986). Instead, we showcase 19 partial answers, albeit all carefully argued and reasoned, that can help bridge this gulf between theory and practice across three substantive areas: concepts, conceptual change and science learning; science teacher development and learning; and access to science, accessible science. And because we felt that these themes deserve greater elaboration and discussion than what space in this Preface could afford, the editors have decided to engage in (written) dialogue before each of the three sub-sections that follow. We anticipate raising troublesome and troubling issues that might otherwise be glossed over in more typical introductory formats. Arguably, whether there are others ways of grouping these chapters or whether a chapter slants towards reporting practical solutions or concocting new theories is perhaps less important than the message that they collectively express––theory and practice need each other for neither is prior. As Stuart Hall, a noted scholar of culture once said, their constant bickering and interplay enables knowledge to be pushed forward, which we likewise hope reading this book will amply achieve. Readers might recall that the title of the conference, Science Education: What Works, sounds problematic, if not pretentious; a vulgar carry-over from presageprocess-product eras that failed to perpetuate nothing except school failure and disinterest in science. Nothing could be further from the truth for what the organizers wanted to celebrate was the appearance of success not so much a hunt for universal formulas to be indiscriminately applied. To us this perspective seems to be reasonable and if any lessons learnt here can be transferred across different contexts, so much the better. Unlike those that argue ‘why what works doesn’t ix

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work’ in educational research (Smeyers & Depaepe, 2006), we are inclined towards optimism, with many accompanying ‘AND’s (Deleuze & Parnet, 2002). Rather than one destination during this critical phase of planetary survival, there should be multiple goals and pathways in science education that ‘work.’ At the very least, we envisage that these chapters will provoke others to put whatever has been offered to the test in the classroom. What is the point of research if it does not invite this? We acknowledge that there are no guarantees––so frustratingly characteristic of research in the human sciences––but this certainly helps to complete one more piece in the puzzle and to avoid those binary and reductive applications of research that entice us all (Rose, 2006). Whether you are approaching this book as a classroom teacher or a science education researcher, we hope that it catalyzes reflection upon your current practices such that you can act on them in a transformative manner. Our insights of the many issues and dilemmas in science education have been greatly enriched by our own reading of these chapters. Finally, this project would not be possible without the support of the many authors and our colleagues at the National Institute of Education. We would like to specially thank Professors Sing-Kong Lee, Leo Tan, Paul Teng, and Shirley Lim for their support and encouragement during the organization of the conference. We would also like to express our gratitude to Professor Wolff-Michael Roth for his editorial advice during the preparation of this book. Yew-Jin Lee & Aik-Ling Tan Singapore January 2008. REFERENCES Deleuze, G., & Parnet, C. (2002). Dialogues II (H. Tomlinson & B. Habberjam, Trans.). New York: Continuum. Carr, W., & Kemmis, S. (1986). Becoming critical: Education knowledge and action research. Lewes: Falmer Press. Rose, M. (2006). The Spencer foundation. Retrieved December 1, 2007, from http://www.spencer.org/ publications/Grant_Analysis/Rose.htm Smeyers, P., & Depaepe, M. (Eds.). (2006). Educational research: Why ‘what works’ doesn’t work. Dordrecht: Springer.

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1. CONCEPTS, CONCEPTUAL CHANGE & SCIENCE SECTION A

Aik-Ling: This section focuses on an area that has a long-standing history and one which has contributed a great deal to policy and curricula reform (Anderson, 2007). Conceptual change research––almost synonymous with science education research during the last twenty years––seeks to understand how learners grasp various ideas and concepts from a psychological or developmental perspective. It is therefore fitting that Treagust opens our book by examining how analogies, models, diagrams, and multimedia software can be best appropriated for the learning of science. Reviewing some of his past work in these areas, I appreciated the limitations of text to represent the complexities of science and scientific concepts although my own research focus now is on how talk is used in constructing learning experiences in the classroom. Yew-Jin: I’ve had little research experience with analogies and models but I do hear about the excitement that these tools are generating among learning scientists and science educators. When I was a high school biology teacher I recall, without knowing much about the theories behind them, how analogies often helped students overcome a mental roadblock so to speak. Likening the immune system to a fortress or the transport system to highways and roads did assist in the visualization process although I’ve also seen how some teachers got so carried away with using unfamiliar analogs that the lesson backfired as Treagust had warned. It’s this whole idea of using multiple pathways of looking at the same thing––they all add up. Treagust is careful in reminding us about their shortcomings too; for example even when diagrams were used as active tools, not all university students in his study with Chittleborough experienced improvements in chemistry. Similarly, the possession of modelling abilities at this advanced stage of education should not be assumed. Aik-Ling: Your chapter with Chue and Tan appears to be an extension of what Treagust talked about––using models, diagrams and analogies to illustrate chemical bonding. What do you think is the value of examining gestures performed by the instructor as compared with the traditional way of examining conceptual learning? Again, I realise how limiting is the examination of only talk (in the classroom) as windows to student cognition. Yew-Jin: You’re right, Aik-Ling! In the chapter by Treagust, his concern was the role of multiple representations in learning science. What happens now if these same representations are concocted on the fly without conscious effort and using one’s hands as well? What if we are told that these patterns of hand Y.-J. Lee, & A.-L. Tan (eds.), Science education at the Nexus of Theory and Practice, 1–6. © 2008 Sense Publishers. All rights reserved.

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movements that we call gestures are the visible expressions of thought including those related to scientific thinking (McNeill, 1992)? I believe all these have implications for learning which all educators and not just science teachers ought to know about. What do you think? Aik-Ling: Hmmm...from casual conversations with teachers, they do not think very much about their gestures when they are talking or even during teaching. In fact, some of them are not even aware that that they are gesturing. Often the participants claim that their intentions of the gestures are not what analysts make them out to be! Personally, I think that it is a complex situation here–– on the one hand, gestures are to be read and interpreted by the recipient and on the other hand, they may not be read according to the intentions of the person! Yew-Jin: You bring out an important point: Gesture production is below the level of consciousness. Thus, I imagine if you asked a person after-the-fact what he or she ‘meant’ by the previous gesture that was performed, I’m quite sure you’ll get all sorts of answers. This is because the act of asking and getting an answer now becomes an accounting process, a topic to be rhetorically managed, which is inherent in all interviewing situations. It’s the same thing when we ask somebody, “What did you mean when you said that?” I believe it’s difficult to know such things conclusively for we do not plan which word follows another when we speak and likewise gestures accompany speech without people thinking about their formation. All interlocutors have is what is presented in real-time be it gestures or talk. For most times, it is sufficient although I do acknowledge that if audiences come from different cultural backgrounds or experiences, some meanings from gestures might be lost or wrongly understood. However, in our chapter, this did not seem to be an issue for the teachers and students as they worked through the chemistry course together. Aik-Ling: Yeo, Tan, and Tang’s work stems from a different theoretical lens as compared to Treagust and Chue, Lee, and Tan but its focus on language and how students build up their knowledge and language of science is down my alley. Although I recognise the limitations of merely analysing talk, it is nevertheless very powerful and insightful for an observer to ‘see’ what is going on inside the heads of the learner. After all, ‘talk’ is ‘thought’ which is made visible to the listener. Yew-Jin: Not forgetting that gestures are a ‘language’ too, a genuine system of signifiers… Aik-Ling: Right, the way Yeo, Tan, and Tang analysed the shuttling between everyday and technical language provides information on the ‘journey’ which learners go through as they move from everyday lived experiences towards more scientific and abstract ones. What is probably novel here is that this analysis occurred in an online platform where we have no information on the learners’ facial expression, tone of voice, gestures or the sequence in which the ‘talk’ took place.

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SECTION A

Yew-Jin: For most researchers who work in these fields, discursive or conversational analyses are the methods of choice to ascertain conceptual change. What you said is correct, we often don’t really have very much extraneous information, which might be absolutely critical in deciphering how people learn. On the other hand, capturing data this way is so convenient compared to how we normally do it using tape or videorecorders. This is a compromise that has to be thought through carefully. Coming back to your earlier point, I think Yeo, Tan, and Tang emphasize that the flow between abstract and everyday concepts is dialectical; neither is prior but both require each other. This reminds me so much of something I wrote before about how people learn scientific knowledge in the workplace (Lee & Roth, 2005). I know it sounds very odd but people apprehend phenomena through lived, bodily experience first. Yet, in order to comprehend the former on a deeper level, reflection is also necessary and this is where technical abstraction comes in to illuminate those initial experiences. Therefore, the cycle continues on and on. Did you find anything like this in your work in local classrooms Aik-Ling? Aik-Ling: I have not done much work where students and teachers reflect on their learning but from my analyses of classroom talk and sharing these findings with teachers, I realise that teachers lack the ‘official’ language to talk about their own practices (lived experiences). Once they acquire the language to talk about their experiences however, it makes more sense to them! It’s dialectical indeed. Take, for example, the standard Initiation, Response and Evaluation (IRE) sequence which is so familiar. Teachers practice it all the time in the classroom but are not aware that they are doing it because they do not have a language to ‘talk’ about it. Once they have learnt the term and its characteristics, teachers can better make sense (and question, critique, modify) of their practice in the light of their new knowledge. The same goes for students (learners of science). Once they learn scientific terms, they can start (re-)interpreting their lived experiences through a scientific lens. Similarly, having a scientific lens will help them to ‘see’ things that they would have otherwise miss! For example, before I learnt about the concept of Doppler effect, I did not give second thought to the diminished volume of the siren of the ambulance as it sped pass me. Once I learnt about Doppler effect, I started to ‘hear’ the difference in volume as planes fly by, as motor cycles speed past me! Yew-Jin: That’s very interesting! So, from the encounter with the Doppler concept, you (re-)applied it in various situations and found it consistent as an explanation of the concrete phenomena. By doing so, you were building up more and more ‘confirmatory’ cases in your understanding of this particular scientific concept. This brings me to the chapters by Foong et al. and Riley et al. Both are concerned with physics education although the former presents a series of experiments for what they call ‘challenging topics’ and the latter tries to uncover some misconceptions among preservice teachers through survey and discussion methods. One point which both groups of authors 3

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stressed is that students need time to talk about the phenomena, to get familiar with the experimental set-up, and to be familiar with the science concepts being tested. Unfortunately, this resource of time is something teachers never have enough of thus resulting in situations where experiments and teacher-led demonstrations often fail to live up to their potential (Roth, McRobbie, Lucas, & Boutonné, 1997). Indeed, I’d like to suggest that even the use of dataloggers, which are supposed to minimize the tedium of data collection and analysis do not necessarily live up to expectations given the vast distance between real-world settings and school science (Roth & Lee, 2006). This separation is not normally bridged in school because of severe time constraints. Aik-Ling: As fun and interesting as Foong et al. have rigged their experiments from household equipment, I cannot help but wonder why and how misconceptions have such deep roots in learners, even after going through higher levels of learning. I personally have misconceptions which I hold very firmly and some of them arose because I learnt them through inaccurate and inappropriate analogies––as highlighted by Treagust in his chapter about the dangers of misuse of analogies! Furthermore, Riley et al. said that while peer discussions were effective when carefully planned, they were still insufficient for completely removing misconceptions. Yew-Jin: Sure, and they reported that some students asked for more follow-up laboratory work to verify or test their hypothesis after these discussions. I think this is moving along the right track although we know how the curriculum hurries everybody along the school year in an attempt to gain coverage, not mastery. Aik-Ling: One of my weakest areas of knowledge in science is on the movement and behaviour of heavenly bodies. That is one of the reasons why I find reading Massalha and Abadi’s chapter so challenging. They presented a model of teaching for this rather abstract topic, ensuring that the preconception of the learners are taken into account and that there was reflection built in after the teaching activity. This is probably important lest we end up like the graduates in the popular Harvard graduation video where the top graduates carried with them misconceptions about season formation and day and night! Yew-Jin: I strongly feel that some of the past research on science misconceptions were misguided, at least the teaching implications arising from those kinds of research programs. Meaning that rather than attributing to kids some kind of deficiency or inadequacy, why not appreciate that speaking and thinking in those ‘incorrect’ ways are quite natural forms of human sense-making (Macbeth, 2000)? Science after all is a very ‘unnatural’ way of understanding the world, an entirely different language game if you may that requires a long period of training. Looking at the notorious persistence of misconceptions confirms that other than a specialized group of elites, the average person is not part of this community. Now, recent manifestations of misconceptions research is more sophisticated (e.g., diSessa, 2006) and takes into consider4

SECTION A

ation that cognition is also very much social, which I feel is a step in the right direction (Settlage & Goldston, 2007). Aik-Ling: I agree with you. ‘Incorrect’ ways of explaining can be and probably has great potential as starting points for learning. Rather then telling the students that they are wrong, getting them to compare and talk about differences between their conceptions and what is commonly acceptable as science gives a way to see how scientific concepts and knowledge are derived (Bereiter, Scardemalia, Cassell, & Hewitt, 1997). In order to facilitate this process, students can be presented with the opportunities to search for information and to analyse these information as presented in Tsai’s chapter. Although Tsai did not focus on multimedia software in the learning of science, determining how students judge, search, and learn using online information has been a neglected area. His use of the Navigation Flow Map was ingenious for it allows the plotting of the exact sequence of web searches and other behaviors otherwise hidden to researchers. Overall, I think his work reminds us to teach students adequate online searching skills lest they are lost as to what they are inquiring on the Internet! Yew-Jin: That is true but the study also showed that over time, these skills can improve; the students revisited different websites for information rather than only sticking to a few, dug deeper into certain sites, and displayed metacognitive expertise in deciding what and how to search. We are also told that these kinds of behaviors were highly correlated with certain epistemological perspectives (e.g., those who were less reliant on authoritative sources), which is perhaps to be expected as we will see in later chapters. If students can therefore be given time to discuss their searching strategies and results among themselves, this can result in more fruitful online learning experiences according to Tsai. REFERENCES Anderson, C. W. (2007). Perspectives on science learning. In S. K Abell & N. G. Lederman (Eds.), Handbook of research on science education (pp. 3–30). Mahwah, NJ: Lawrence Erlbaum Associates. Bereiter, C., Scardamalia, M., Cassells, C., & Hewitt, J. (1997). Postmodernism, knowledge building, and elementary science. Elementary School Journal, 97, 329–340. diSessa, A. J. (2006). A history of conceptual change research: Threads and fault lines. In R. K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (pp. 265–281). New York: Cambridge University Press. Lee, Y.-J., & Roth, W.-M. (2005). The (unlikely) trajectory of learning in a salmon hatchery. Journal of Workplace Learning, 17, 243–254. Macbeth, D. (2000). On an actual apparatus for conceptual change. Science Education, 84, 228–264. McNeill, D. (1992). Hand and mind: What gestures reveal about thought. Chicago: University of Chicago Press. Roth, W.-M., McRobbie, C. J., Lucas, K. B., & Boutonné, S. (1997). Why may students fail to learn from demonstrations? A social practice perspective on learning in physics. Journal of Research in Science Teaching, 34, 509–533.

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LEE & TAN Roth, W.-M., & Lee, Y.-J. (2006). Computers and cognitive development at work. Educational Media International, 43, 331–346. Settlage, J., & Goldston, M. J. (2007). Prognosis for science misconceptions research. Journal of Science Teacher Education, 18, 795–800.

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DAVID F. TREAGUST

2. THE ROLE OF MULTIPLE REPRESENTATIONS IN LEARNING SCIENCE Enhancing Students’ Conceptual Understanding and Motivation

INTRODUCTION

All representations such as models, analogies, equations, graphs, diagrams, pictures and simulations can be exhibited in verbal, mathematical, visual and/or actional-operational modes. These different types of representations have been used to enhance conceptual understanding and a considerable amount of research has been conducted to investigate the effect of a single and multiple representations on learning. Using different representations and different modes of teaching can make difficult scientific concepts more intelligible to students by increasing the likelihood of progressing towards more sophisticated conceptual learning according to the concept learning model. Learning in this way that is more intelligible, plausible and fruitful can also lead to increased motivation to study science. In this chapter, I discuss studies involving multiple representations that examine science concept learning and motivation using analogies (Treagust, Harrison, Venville, & Dagher, 1996), modeling (Chittleborough & Treagust, 2007), diagrams (Chittleborough & Treagust, 2006) and multimedia (Tsui & Treagust, 2003, 2004). Firstly, I present some important background issues about the functions of multiple representations and levels of representation. BACKGROUND

In discussing the functions of multiple representations, Ainsworth (1999, p. 131) states that ‘a common justification for using more than one representation is that it is more likely to capture a learner’s interest and, in so doing, play an important role in promoting conditions for effective learning.’ Ainsworth’s research primarily involves computers and multimedia but multiple representational learning environments are ubiquitous and exist when there is no technology in the classroom. The first function of multiple representations is to contain complementary information or support complementary cognitive processes. Examples of this function are when different representations such as tables or graphs provide equivalent information; for some learners one mode of representation is more easily assimilated than the other. The implication is that in classes, teachers should present to students different representations that express equivalent information because each makes salient different aspects of the situation. According to Ainsworth Y.-J. Lee, & A.-L. Tan (eds.), Science Education at the Nexus of Theory and Practice, 7–23. © 2008 Sense Publishers. All rights reserved.

THE ROLE OF MULTIPLE REPRESENTATIONS

(1999, p. 137) ‘where learners are given the opportunity to use multiple external representations, they may be able to compensate for any weaknesses associated with one particular strategy by switching to the other.’ There are rarely situations where a single representation, such as tabulated data, is effective for all tasks. The second function of multiple representations is that they can help learners develop a better understanding of a conceptual domain by using one representation to constrain their interpretations of a second representation. For example, learners may be presented with a familiar analogy to support their interpretation of a physical phenomenon of which they are less familiar and which is more abstract. The third function of multiple representations is that they can lead to a deeper understanding of concepts that may include promoting an abstraction, encouraging generalisation, and teaching the relation between representations. For example, domain knowledge may be extended when learners know how to interpret a velocity time graph to know whether or not a body is accelerating and can subsequently extend their knowledge to present tables and acceleration-time graphs. In addition to these three functions of multiple representations, science education researchers have classified the levels of representation used in biology topics like genetics and in chemistry as 1) macroscopic representations that describe the phenotype of organisms and the bulk properties of tangible and visible phenomena in the everyday experiences of learners when observing changes in the properties of matter, such as colour changes, pH of aqueous solutions, and the formation of gases and precipitates in chemical reactions; 2) submicroscopic (or molecular) representations that provide explanations at the genotype of the organism at the genetic level and for matter at the particulate level as being composed of atoms, molecules and ions; and 3) symbolic representations that involve the use of letters, symbols, formula and equations, as well as drawings, diagrams, models and computer animations to symbolise matter. USING ANALOGIES IN SCIENCE TEACHING & LEARNING

In investigating the role that analogies play in conceptual understanding of science, a constructivist view of the learning process has deliberately been taken. This view asserts that learners construct their own knowledge, using their existing knowledge, and thereby are able to view the world in ways that are coherent and useful to them. In the process of this knowledge construction, learners develop patterns of beliefs manifested as alternative conceptions about science which are influenced by social experiences. These alternative conceptions often differ significantly from the generally accepted views of the concept under consideration. Further, these ideas are surprisingly resistant to change after traditional instruction. Science teachers who communicate ideas and concepts in their classrooms using analogies are in good company. Many important discoveries in science have been made in this manner; for example, Johannes Kepler developed concepts of planetary motion from the workings of a clock, Christian Huygens used water wave motion to understand light phenomena, and Kekulé developed the idea of the 8

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benzene ring from a dream about a serpent biting its own tail. A key question for science education researchers and science teachers to investigate is whether students can economically and repeatedly employ these same analogical reasoning skills to understand a new concept or phenomenon. Wong (1993) answered such a question when teacher education students created their own analogies to explain three air pressure phenomena. Over the past two decades, a body of research has been built up in science education about the potential of analogies in science teaching and learning and how specific aspects of analogies can be used to engender interest and motivation to help students understand the science they are learning in school (see for example, Aubusson, Harrison, & Ritchie, 2006). An analogy is a process of identifying similarities between two concepts. The familiar concept is called the analog and the unfamiliar science concept is called the target. For the simple analogy ‘electric current through a wire is like water flowing through a pipe,’ electric current through a wire is the target concept and water flowing through a pipe is the analog. When using an analogy in science teaching, teachers should select an appropriate student-world analog to assist in explaining the science concept. The analog and target share attributes that allow a relationship to be identified and contribute to the concept being taught; however, there are features of the analog which are unlike the target, and these can cause impaired learning if incorrectly matched, as well as confusion and reduced interest in the topic. Advantages of Using Analogies in Science Teaching Analogies are believed to help student learning by providing visualisation of abstract concepts, by helping compare similarities of the students’ real world with new concepts, and by increasing students’ interest in the topic being studied and thereby increasing motivation. Concrete analogs facilitate understanding of the abstract concept by pointing to the similarities between objects or events in the students’ world and the phenomenon under discussion. Refraction of light as it passes obliquely from a less dense medium such as air into a denser medium such as glass is a particularly abstract physics concept often taught at the Year 10 level. A common analogy for refraction of light, as discussed later, comprises a small cart on wheels, painted with luminous paint moving at an angle from a smooth surface, the laboratory bench, to a rough surface, a piece of carpet. Analogies can be motivational in that, as the teacher uses ideas from the students’ real world experience, a sense of intrinsic interest can potentially be generated. From a teaching perspective, the use of analogies can enhance conceptual change learning since the analogies open new perspectives. Research has shown that the effectiveness of analogical instruction can be improved by training students in analogical reasoning. Indeed, several authors nominate analogies as candidates for generating dissonance between children’s science and scientists’ science. Analogies are believed to enhance students’ understanding by providing visualisation of abstract concepts, by helping compare similarities of the students’ real world with the new concepts, and by increasing students’ motivation. In 9


addition, teachers’ use of analogies creates an increased awareness on the part of the teacher to take students’ prior conceptions into consideration in teaching and has the potential for the content to be more interesting for the students. By becoming more aware of students’ conceptions, differences between students’ ideas and those of the teacher become more evident (see also Harrison & Treagust, 2006). Potential Problems when Using Analogies in Science Teaching Despite their advantages and usefulness, analogies can cause incorrect or impaired learning depending on the analog-target relationship. If the teacher uses an analog that is unfamiliar to the learner, development of understanding through the analogy is prevented. The use of analogies in science teaching does not always produce the intended effects, especially when students take the analogy too far and are unable to separate it from the content being learned. Some students only remember the analogy and not the content under study. There are also possible problems with using analogies from a developmental perspective. One of the major differences between concrete operational thought and formal operational thought described by Piaget is that people who are at the formal operational level are able to disembed concepts from particular contexts and apply the abstract form of the concept over many contexts. This is the essence of analogical thought and students at the concrete operational level, according to this developmental perspective, are unable to do this. It can be argued, therefore, that although analogies may be more useful to students who primarily function at the concrete operational level, analogical reasoning may be limited. Students already functioning at a formal operational level may have an adequate understanding of the target and the inclusion of an analogy might add unnecessary information or ‘noise.’ Unshared attributes between analog and target are often a cause of misunderstanding for learners who attempt to transfer or map unshared attributes from the analog to the target. No analog shares all its attributes with the target, or by definition, it would become an example; therefore, every analogy breaks down somewhere. For instance, when electric current in wires is compared to water flowing in pipes, some students could conclude that electricity will leak out of a switched-on power point that has no plug in it. There is real world evidence to dispute this idea but this analogy has often been criticised because it perpetuates the idea that electricity is matter with volume and space. Although it may be clear to the teacher that all the attributes of analog and target are not shared, some students try to transfer most, or all, of the analog structure onto the target content and then describe the target content with direct reference to analog features. Many teachers with whom we have spoken, realised that despite the advantages and usefulness of analogies, the use of this teaching tool can cause incorrect or impaired learning related to the analog-target relationship. Consequently, the use of analogies does not always produce the intended effects. In brief, some of the constraints of using analogies are analog unfamiliarity, the particular stage of 10

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cognitive development of the learner and the incorrect transfer of features between target and analog. The features of the target and analog that are not shared are often a cause of misunderstanding for the learners when they attempt to transfer them. Rather than using the analog attributes as a guide for drawing conclusions concerning the target, students occasionally incorporate parts, or all, of the analog structure into the target content. One of the results of this incorrect transfer is that when students are questioned concerning the nature of the target content, they will answer with direct reference to analog attributes. When analogies are used during classroom instruction, discussion should take place to assist in defining the limitations of the analogy. Working with a competent and interested group of teachers who participated in our research, we developed a teaching strategy called the FAR Guide consisting of three phases called Focus, Action, and Reflection (FAR) that can be used in lesson preparation by teachers (Treagust, Harrison, & Venville, 1998; Harrison & Treagust, 2006). Dana and her Understanding of Refraction Working with an experienced teacher who was teaching Year-10 optics, we set out to assess the efficacy of using an analogy for refraction of light that comprised a small cart on wheels, painted with luminous paint moving at an angle from a smooth surface, the laboratory bench, to a rough surface a piece of carpet (Treagust, Harrison, Venville, & Dagher 1996). The analogy is that the small cart changes direction when it meets a different surface as does light when it enters a transparent medium of different density, such as glass, from air. We hypothesised that the analogical instruction would provide useful avenues for engendering students’ interests as well as conceptual change. Indeed, we found that the analogy enabled the majority of the class to provide plausible evidence for their understanding of optical refraction phenomena. An interview with Dana, illustrates the type of learning which can occur following this mode of analogical instruction. When interviewed using a series of practical demonstrations about the behaviour of light, Dana was vague and unenthusiastic as the first four questions were discussed and did not volunteer any physics explanation, however simple, to account for refraction. When discussing the fourth question concerning her observations and explanations of a pencil standing half immersed in a clear liquid, Dana was unable to explain the observations. However, when prompted by the interviewer about an analogy that she had been taught three months earlier, Dana’s answers to this and subsequent ray tracing problems (glass block and prism) were probably the best we saw of the 40 students. When scoring the interview protocol as a regular physics test, Dana’s scored full marks, and this from a student whom the teacher placed in the bottom 25% of the class and who failed the Optics unit. The tape-recording of the interview adds another facet to this story. Until the advent of the analogy, Dana was quietly spoken and disinterested. When the analogy was recalled, she became enthusiastic and talkative about the questions in the interview. We believe that Dana’s responses did show evidence of enhanced conceptual understanding as she 11


made connections between the analogy and the behaviour of light when changing media. Dana did not merely memorise the analogical event, but applied the ideas from it to the new phenomena. This connection was fruitful for her in that after she became dissatisfied with her first attempt on the fourth interview question, she corrected her drawing and then accurately answered the glass block and prism questions. Furthermore her language tone indicated a keen interest in her own learning. THE MODELLING ABILITY OF NON-MAJOR CHEMISTRY STUDENTS

Models provide a description of real phenomena in terms of something else with which the learner is more familiar and can be referred to as analogical models. Models are commonly used to provide links to familiar concepts and provide a foundation on which students can build new ideas (Justi & Gilbert, 2006). These considerations are in line with a constructivist approach to teaching in which the students’ prior knowledge is the foundation on which to build further knowledge. Nevertheless, research has shown that students may view models in different ways and this has implications for teaching with models. According to Grosslight, Unger, Jay, and Smith (1991), students can be classified at three levels according to their modelling ability. Level 1 Modellers view models as toys or simple copies of reality and students believe there is a general one-to-one correspondence between model and reality. Level 2 Modellers recognise that a specific purpose governs the way a model is constructed and students understand that a model does not have to correspond with reality but that the focus is on aspects of the model and reality. Level 3 Modellers realise that models are used to develop and test ideas and do not depict reality and that students can construct and manipulate diverse multiple models without being perturbed by their differences. Research has shown that many secondary students view models only as copies of the scientific phenomena and their understanding of the role of models frequently is seen as being simplistic (Treagust, Chittleborough, & Mamiala, 2003). Even university students have limited experience with models (Ingham & Gilbert, 1991). Teachers’ level of understanding of models also has been described as limited because they have a simplified understanding of models and modelling in science (Van Driel & Verloop, 1999). The use of concrete models and pictorial representations has been shown to be beneficial to students’ understanding of chemical concepts (Coll, 2006; Harrison & Treagust, 1996). However, the extensive and accepted process of using models has made the model appear as ‘fact’ to many teachers and students. Frequently, students do not differentiate between models and they do not regard models differently from the observed characteristic that the model is trying to explain. For example, teachers do not emphasise the representational nature when referring to the formula CH4 saying that it is methane, whereas to state that CH4 represents a methane molecule would be more accurate. This lack of emphasis reinforces the dilemma of some students viewing models only as copies of the scientific phenomena. While it is assumed that students understand the representational 12

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nature and the analogical relations within the scientific language, the strengths and limitations of each model need to be discussed so that students can assess its accuracy and merit. Indeed, identifying the criteria that are used to categorise models may improve students’ understanding of models (Chittleborough & Treagust, 2005). Modelling Ability and Understanding In a study involving the role of multiple representations and modelling ability, we were interested to examine how the modelling ability of first year university students, who were taking an introductory chemistry course, influenced their use of models and their ability to understand chemical concepts in terms of the macroscopic, submicroscopic and symbolic representations (Chittleborough & Treagust, 2007). Data were collected in focus groups, questionnaires, worksheets and interviews with volunteers. The results showed that university students’ modelling ability is not necessarily an innate skill and that students need to be taught how to model. Students need to be able to recognise the target and source and the instruction needs to provide learning opportunities to build students’ confidence with the model as well as show the potential of the model to be applied to solving problems. With general models, there can be a number of analogs (i.e., a number of models) but they link to only one real target. When considering chemical models, links are formed between an analog and the target where the analog is a symbolic representation (of which there may be many different types) which links with two real targets––the submicroscopic level (target 1) and the macroscopic level (target 2). The symbolic representations are analogs of the macro and sub-microscopic levels which are the targets. The duality of models in chemistry is a significant difference to general models that textbooks do not always highlight. Initially, the symbolic representation is used to provide conceptual insight into the abstract sub-microscopic level; however, students are expected to also link the symbolic representation to the macroscopic level. So, for example, the ball-andstick model for methane is obviously a model of the sub-microscopic nature of the molecule providing students with a visual impression of the arrangement of the atoms in the molecule at the nanoscale. But students also are expected to associate the ball-and-stick model of methane with its macroscopic qualities, i.e., it is a gas, an organic compound consisting of one carbon and four hydrogen atoms, which is reactive and flammable. So symbolic chemical representations––or models––have links to both the sub-microscopic level and the macroscopic level of chemical representation of matter. The modelling ability is a measure of the students’ ability to make both links simultaneously. The data from this study emphasised the need for students to: use the models for explaining, predicting, or describing in order to be able to learn from them; build up a foundation through memorisation to improve modelling skills; understand what each component of the model represents; and distinguish different scales of representation and use them appropriately, e.g., subatomic versus molecular. 13


Students cannot use the chemical representations unless they appreciate their modelling characteristics. Obviously, the students’ modelling ability is critical to the successful use of the chemical representations and it can be fostered and developed. A student’s level of modelling is not fixed or predetermined. The research showed that students’ modelling ability can be developed through instruction and practice and generally, for the majority of students, as modelling skills improved so did their understanding of chemical concepts. Generally, the students’ background knowledge influenced their modelling ability and as modelling skills improved so did students’ understanding of chemical concepts. The skill of modelling improved through practice with models and different representations and through the continued use of multiple models students gradually developed personal mental models for the sub-microscopic level. Three students are perhaps typical of this group studying introductory chemistry. Narelle had no previous chemical knowledge and no consideration about the concept of representation; Alistair had studied grade 11 and 12 chemistry, had not taken final examinations but had an understanding of the submicroscopic level; and Leanne had not studied chemistry in high school. Narelle initially had no consideration for the sub-microscopic level of matter, was classified as a Level 1 modeller and had no criteria for classifying a variety of molecular diagrams of elements and compounds. Narelle was confused with two and three dimension drawings as well as molecular, atomic and sub-atomic levels. Alistair could describe how atoms are arranged in a sample of copper and was described as a level 2 modeller. Leanne had never studied chemistry before and had difficulty understanding the representational nature of models and diagrams and was classified as Level 1 modeller. As might be expected, students with superior modelling ability made better use of models and achieved a higher level of understanding of chemical concepts. Modelling has been shown to be a necessary skill for understanding chemistry at the sub-microscopic level. The results of this study highlighted the importance of using models for explaining, predicting or describing; understanding what each component represents and understanding the scale of the representation. Students with no chemical background tended to learn chemistry using only the macroscopic and symbolic levels of representation. The results confirm previous research that the sub-microscopic level is the most poorly understood of the three levels of chemical representation. It was not always appreciated by students that the chemical models form links to two real targets: the sub-microscopic level and the macroscopic level. DIAGRAMS AS REPRESENTATIONS

A chemical diagram is a representation in one or more of a multitude of forms such as a schematic, illustrative or symbolic representation. Scientific diagrams are generally labelled diagrams, often drawn to a scale, providing an accurate representation. The significant characteristics of chemical diagrams are in the visual impact, provided by both the macroscopic and sub-microscopic levels that 14

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can enhance the development of mental models. A chemical diagram can have one or more of a multitude of purposes, namely for explanation, description, instruction, to provide a mental picture or to provide multiple representations. A multi-modal teaching approach provides learners with the opportunity to synthesise their own mental model. The value of a diagram in making the link with an abstract concept depends on it being consistent with the learners’ needs and being pitched at the learners’ level of understanding. Diagrams can have more than just illustrative purposes, expanding the purpose of diagrams to model construction and reasoning (Gobert & Clement, 1999). In this way, chemical diagrams serve as significant teaching tools; however, the value depends on the students’ understanding of the diagram. While the characteristics and purpose of diagrams are important, the way the diagram is used in the instruction is equally important. Flow charts, Venn diagrams, Vee-diagrams and concept maps are examples of diagrams in which students diagrammatically represent their understanding. These diagrams are pedagogically powerful because students have to actively construct the representation of their understanding and strategies for using these active diagrams are well documented. By contrast, diagrams of laboratory equipment are passive diagrams, presenting information to students. These traditional diagrams are consistent with transmissionstyle pedagogy when it is assumed that no specific teaching strategy is needed to ensure student understanding. In a study by Chittleborough and Treagust (2006), chemical diagrams were intentionally introduced into the pre-laboratory exercises in an introductory university course to improve the teaching of chemistry based on the assumption that students would be better prepared for the laboratory activities through using and interpreting chemical diagrams of the chemical equipment used in the experiments. The desired outcome was for students to be better prepared for laboratory sessions and improve their ability to understand experiments. By making students use diagrams in an active manner––that requires interpretation–– students’ should become more familiar with diagrams and their understandings of chemical diagrams should be improved. These outcomes are dependent on the diagrams being beneficial learning tools and on the students being able to fully understand the diagrams. Students had to complete online pre-laboratory exercises before each of the 11 laboratory classes. In designing the pre-laboratory exercises, chemical diagrams of the laboratory equipment were included with the aim of improving familiarity with equipment, understanding how the equipment functioned, and improving the explanations of chemical phenomena. For example, the aim of a diagram of a distillation apparatus was not only to show the function of the equipment but to explain how this occurred and for the student to develop a mental model of the sub-microscopic liquid-vapour-liquid states. Consequently, the students were required to interpret diagrams in order to complete the exercises. The online prelaboratory exercises provided immediate feedback to the student on their response and provided them with an opportunity to redo the exercise if their response was

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incorrect. The students performed experiments that commonly used equipment that was portrayed in the diagrams. Of the 122 students enrolled in the introductory first-year university chemistry course, 17 students volunteered to be interviewed about the chemical diagrams. The interviews were conducted individually and in groups, depending on students’ availability. Some students are more comfortable being interviewed in a group situation and there is evidence from the data that they listened and learnt from each other during the interview. Each interview took approximately one hour. Students were interviewed about their understanding of the diagrams of laboratory equipment that they had encountered in the pre-laboratory exercises. In the interview, students were asked to relate these diagrams to their laboratory experience, for example: What does the diagram show? What is happening to the mixture in the distilling flask? Has the image supported what you already know? The number of students completing the interviews ranged from 15 to 17 due to pressures of time and other commitments. In reporting the results pseudonyms are used. The transcripts were coded using N-Vivo in terms of relevant aspects of students’ understanding. An associate acted as an independent researcher, crosschecking the coded categories and the coded text to verify coding accuracy. Direct and indirect questions were used to examine students’ understanding of both the chemical content and their own learning. The interview responses provided data about the students’ perspective of their understanding of the chemical content and of the way they are interpreting and using the diagram to learn. While all the students interviewed were able to describe the diagram or concept in the diagram, not all students understood the chemical diagrams as well as would be expected at this tertiary level of education. There was a large variation in students’ level of understanding even within the small interview sample group. This was unexpected. It was attributed to the limited background knowledge of the student, unfamiliarity with the nature of chemical drawings and the lack of practice in interpreting chemical diagrams. Students’ interview responses revealed limitations in several skills that are advantageous to develop when learning chemistry, Firstly, there was a lack of ability to ‘picture’ or talk about the sub-microscopic level which influenced students’ ability to interpret diagrams at the sub-microscopic level. Students with limited chemical background commonly interpreted the chemical diagrams at a macroscopic level seeing only the laboratory equipment. Secondly, there was a lack of ability to attend to the details of the diagram even though throughout the interviews students were challenged to interpret diagrams more critically. Thirdly, there was a lack of ability to use chemical terminology accurately. The students’ verbal responses that used everyday language and chemical phrases carelessly contrasted with the precise and limited nature of chemical vocabulary with which many of these students were not familiar. The study highlighted the difficulties experienced by students with little or no chemical background knowledge who have not had the opportunity to develop these necessary skills. It seems evident that visual aids such as chemical diagrams should be used in conjunction with rich verbal and written forms to tackle this issue. Chemical diagrams should suit the intended purpose. So for setting up 16

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laboratory equipment a diagram that accurately portrays the actual laboratory equipment may help students better understand the physical set-up of the experiment at the macroscopic level but it may not help them to understand the changes that are occurring at the sub-microscopic level. For explanatory purposes, diagrams need to relate the levels of chemical representation or the particular concept. Throughout the interviews, additional inscriptions on the diagrams proved to be beneficial to students’ understanding. Using the complementary diagrams of the macroscopic, sub-microscopic and symbolic levels of representation, as in a chemical equilibrium diagram, showed the connection with experimental experience. These complementary diagrams reinforced the idea of connecting both the macroscopic and the symbolic diagrams that aided understanding of the submicroscopic level. The results of this study could be used to inform pedagogical content knowledge about teaching with chemical diagrams. Students did not always interpret diagrams correctly, even though they did answer online pre-laboratory questions on the diagrams, suggesting that there is a need for strategies that would promote active interaction with diagrams. Consistent with a constructivist approach, these suggested strategies require the students to demonstrate their understanding and receive feedback. In this way, the diagram becomes an active tool rather than a passive tool for learning. The results of this study confirm the research literature claims of the importance of visualisation tools in learning. This research adds to the current research by identifying the importance of drawings in promoting an understanding of the submicroscopic level of matter by helping students to develop personal mental models of that level. The data showed that some students did not interpret or use the diagrams correctly and highlighted the importance of students actively using diagrams and having the necessary skills to use and interpret chemical diagrams correctly. In this way, the data support Gilbert’s notion of metavisualisation and the need to use diagrams actively and metacognitively. Overall, the research showed that: – All students interviewed appreciated that chemical diagrams of laboratory equipment are useful for setting up laboratory equipment and for explaining particular chemical phenomena. – Students’ level of understanding of a chemical diagram varied greatly. – The connections between the diagrams of the macroscopic level (equipment), the sub-microscopic level (molecular) and the symbolic level (equations) were not always apparent to students. – Students’ understanding was not necessarily improved with the use of diagrams; – Diagrams could also introduce misconceptions. In brief, despite ensuring that these were active diagrams rather than passive diagrams, the students’ use of diagrams did not guarantee better understanding of chemical concepts.

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USING MULTIMEDIA IN SCIENCE TEACHING & LEARNING

Science teachers and science educators are increasingly using technology to supplement their teaching. For example, a variety of computer programs have been used over the past two decades to enhance student learning of genetics. Multiple representations in the latest educational software have provided new learning opportunities for high school students. What is different is that these multiple representations are now dynamically linked in interactive multimedia programs such as BioLogica (Concord Consortium, 2001) which is an exemplar of such programs for learning introductory genetics. In BioLogica, a student can select or make changes in graphic or text objects and observe the results according to the laws of Mendelian genetics using for example, fictitious Dragons. The resulting screens concurrently display genotype, phenotype and symbolic representations of the genetics cross. Unlike other less interactive simulation programs, Biologica allows students to manipulate objects of genetics represented at different levels of biological organization⎯DNA, genes, chromosomes, gametes, cells, organisms, and pedigrees⎯and observe their behaviour constrained by the Mendelian model of genetics and molecular/cellular mechanism. All the levels of representations are linked so that changes in one level are reflected in all the other levels. Activity scripts mediate learners’ interaction with the hypermodel through a sequence of challenges, monitor their progress, and provide them with feedback and helpful hints as they work through the activities. However, for students to benefit from the interactions with the multiple representations, they need to be engaged in mindful learning. The multiple representations and the tools for manipulating these representations in BioLogica are designed to provide students with a challenging and interactive environment for learning genetics across the multiple levels of organisation. For example, in the Monohybrid activity, a student first predicts the offspring phenotypes, does a simulation of a cross, visualises the process and results, and then explains his/her reasoning on the screen. The student is then presented with challenges and some embedded assessment questions and a realworld human genetics problem to solve. Classroom Studies Using Biologica Few studies about genetics learning have focused on motivation of students and their perceptions while learning with technology. Thick and rich descriptions alongside online test results and the teacher’s outcomes-based assessment records of most of the participating students, have allowed us to better understand the complexity of the interactions between students and the computer while learning genetics. While the small sample imposed limitations on the findings from this case study, analysis within and across other ongoing case studies should eventually provide a more holistic and coherent understanding of these issues. From two case studies by Tsui and Treagust (2003; 2004), many students found BioLogica intrinsically motivating as they interacted with the multiple 18

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representations of BioLogica in various ways. To both the students and the teacher, instant feedback and visualization, two salient features of the multiple representations, appeared to make BioLogica intrinsically motivating which is likely to develop a better understanding of their own reasoning processes. The first source of evidence about BioLogica activities engendering motivation was from the voices of five students and the teacher. Their perceptions were interpreted in terms six themes, namely, instant feedback, flexibility, visualisation, control, fantasy and challenge. The following quotes from verbatim transcripts of the interviews illustrate these features of the motivational aspects of the BioLogica activities. BioLogica provided instant feedback to the students while solving problems as is illustrated by this discussion between Eric and Laurie: [When you used BioLogica] you can see if you are right or not. Because, well, if you’re thinking [about a] Punnett square… crossing something over, you’re not sure if you’re right or not [but] on the computer you can actually see if you are right. Laurie’s response to what Eric said was as follows: Yeah, ‘cause the questions you answered in class [about] genetics the teacher doesn’t actually check them. So you might answer all those questions and like they’re all wrong when you come to the test. But there [BioLogica] it tells you if you’re right or wrong. So, you can make it right). This aspect of student motivation appeared to have lived up to the teacher’s expectations before the genetics course as he said in the first interview “BioLogica is a good method to show the [students] instantly what happens.” BioLogica gave students flexibility by allowing them to pace their learning progress in response to their keyboard actions so that students can work at their own pace and go back to check their answers during the activities. This flexibility of BioLogica is illustrated by the following dialogue involving Laurie and Nelson: You might understand the first bit and the last bit the teacher says but you might not understand all the bits in between. While with BioLogica you can go back if you forget because you are going at your own pace. In the classroom sometimes you [are] either working faster than most people or sometimes slower so um... if you are working in class you have to stop and wait for more things to do or if you are slow you can’t keep up. But because you are doing it at your own pace you learn more and get more things done. Visualization, which involves linked visual-graphical representations in BioLogica, may deepen students’ understanding of the connection between representations and concepts that require multilevel thinking. In particular, visualization can help students make meaningful connections between processes and their observable outcomes. Laurie’s comments in the first interview after she had completed two BioLogica activities, namely, Introduction and Meiosis are typical of other responses about the visualisation nature of BioLogica: 19


It’s good with the Dragons because with humans you don’t notice much change, but with the Dragons it’s a total change. So you understand eventually why they have different traits. Nelly also had similar comments about visualization: I think it’s fun because of the Dragons. Because you actually see that way how everything is different, like all the different cells [gametes], how they change all the time. It depends on which one is put together. Similarly, Eric explained how visualization had helped his understanding: You can actually watch the processes and it helps you understand more. So like, it’s a lot easier to follow. Because you can watch it slowly…yes. BioLogica promoted feelings of control on the part of the learner using computers instead of reading a textbook or listening to the teacher. Ada and Mark talked about their experience in two different interviews as follows: Instead of just doing it [genetic crosses] out of a book or just being told it, you get to actually see it and decide yourself and see the outcome of it. Sometimes when I didn’t understand something on Biologica I had to ask Mr. Anderson but that didn’t happen very often because it was really well explained on the computers. Sometimes when a person’s talking they can’t [use a] word in a way [that] you can relate to. So sometimes it was easier to understand [with BioLogica] than listening to a teacher. BioLogica evoked in students mental images of situations not actually existing. In particular, the fictitious Dragons are different from the humans that the students see every day. When asked why they liked the Dragons, Matthew and Eric had their fantasies as follows: Because they [the Dragons] have got the variation between them and the [other] species. They have a wide variety between them, whether they were on land or sea or whatever. Yeah, because it [a Dragon] is made up; it’s not real; it makes it more fun; like if you had humans on the computer, it’s a bit boring because you see them every day. So you can do it with some animals and stuff like that, it’s more interesting. BioLogica provided some interactive challenging problems with the Dragons. Ada and Matthew tried to talk genetics like scientists during their interviews: Well the BioLogica work [activity] I don’t know what it’s called, exactly, like the way that you had to pick which cells were chosen to make the new offspring. The dominant and recessive genes showed whether they actually had that characteristics or not. And that was just easier to understand.

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Well in one of the problems I think you had to make a certain type of Dragon with certain characteristics so I had to select certain chromosomes that [were] dominant or recessive genes to be used as gametes to make a new Dragon. So that was interactive there. Overall, the above comments with the six themes indicated that students found the BioLogica Dragons intrinsically motivating. The interview data were consistent with the classroom observations which indicated that the BioLogica activities became an important motivator in student learning of genetics when they were interspersed between Mr Anderson’s normal teacher-directed presentations. Particularly, instant feedback and visualization appeared to play the most salient roles in connecting motivation to learning for understanding as typified by Laurie’s remark: “Yeah. In the class it gets boring so you stop listening. But when it’s fun you take everything in and understand more.” Knowing of the benefits of multimedia is essential but teachers wishing to integrate multimedia such as BioLogica into their teaching to improve student learning do need additional time to familiarise themselves with the software and to make adequate preparation to gain feedback from log files analysis and formative assessment results. However, once these skills are developed, collaboration between science teachers and science educators and science education researchers will be useful in providing more learning opportunities for students using BioLogica. CONCLUSIONS

The examples above have illustrated how multiple representations such as analogies, models, diagrams and multimedia software have been used in science teaching and learning. In a numbers of instances, when students were not able to understand a concept, being presented with an analogy, a model, diagram or interactive simulations provided opportunities for learning and at the same time provided increased interest in the concept being investigated. These different representations have been shown to help learners understand the target concept in terms of the underlying features of the concept at a deeper level and help make connections between concepts that were otherwise not easily comprehended. As noted in the research on students’ use of active diagrams, even with the clear intention of improving students’ learning, developing connections between the diagrams of the macroscopic level (equipment), the sub-microscopic level (molecular) and the symbolic level (equations) were not always apparent to students. REFERENCES Ainsworth, S. E. (1999). The functions of multiple representations. Computers & Education, 33, 131–152. Aubusson, P. J., Harrison, A. G., & Ritchie, S. M. (2006). Metaphor and analogy in science education. Dordrecht: Springer. Chittleborough, G., & Treagust, D. F. (2005, April). Criteria that students use to classify models. Paper presented at the annual meeting of the National Association for Research on Teaching, Dallas, TX.

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THE ROLE OF MULTIPLE REPRESENTATIONS Chittleborough, G., & Treagust, D. F. (2006, April). The descriptive and explanatory nature of chemical diagrams does not guarantee understanding. Paper presented at the annual meeting of the National Association for Research on Teaching, San Francisco, CA. Chittleborough, G., & Treagust, D. F. (2007). The modeling ability of non-major chemistry students and their understanding of the submicroscopic level. Chemistry Education Research and Practice, 8, 274–292. Coll, R. K. (2006). The role of models, mental models and analogies in chemistry teaching. In P. J. Aubusson, A. G. Harrison, & S. M. Ritchie (Eds.), Metaphor and analogy in science education (pp. 65–77). Dordrecht: Springer. Concord Consortium. (2001). BioLogica. Retrieved October 8, 2001, from http://biologica.concord.org Gobert, J. D., & Clement, J. J. (1999). Effects of student–generated diagrams versus student-generated summaries on conceptual understanding of causal and dynamic knowledge of plate tectonics. Journal of Research in Science Teaching, 36, 39–53. Grosslight, L., Unger, C., Jay, E., & Smith, C. (1991). Understanding models and their use in science: Conceptions of middle and high school students and experts. Journal of Research in Science Teaching, 28, 799–822. Harrison, A. G., & Treagust D. F. (1996). Secondary students’ mental models of atoms and molecules: Implications for teaching chemistry. Science Education, 80, 509–534. Harrison, A. G., & Treagust D. F. (2006). Teaching and learning with analogies: Friend or foe? In P. J. Aubusson, A. G. Harrison, & S. M. Ritchie (Eds.), Metaphor and analogy in science education (pp. 11–24). Dordrecht: Springer. Ingham, A. I., & Gilbert, J. K. (1991). The use of analogue models by students of chemistry at higher education level. International Journal of Science Education, 13, 203–215. Justi, R., & Gilbert, J. K. (2006). The role of analog models in the understanding of the nature of models in chemistry. In P. J. Aubusson, A. G. Harrison, & S. M. Ritchie (Eds.), Metaphor and analogy in science education (pp. 119–130). Dordrecht: Springer. Treagust, D. F., Chittleborough, G., & Mamiala, T. L. (2003). The role of sub-microscopic and symbolic representations in chemical explanations. International Journal of Science Education, 25, 1353–1368. Treagust, D. F., Harrison, A. G., Venville, G. J., & Dagher, Z. (1996). Using an analogical teaching approach to engender conceptual change. International Journal of Science Education, 18, 213–229. Treagust, D. F., Harrison, A. G., & Venville, G. J. (1998). Teaching science effectively with analogies: An approach for pre-service and in-service teacher education. Journal of Science Teacher Education, 9, 85–101. Tsui, C.-Y., & Treagust, D. F. (2004). Motivational aspects of learning genetics with interactive multimedia. The American Biology Teacher, 66, 277–285. Tsui, C.-Y., & Treagust, D. F. (2003). Genetics reasoning with multiple external representations. Research in Science Education, 33, 111–135. Van Driel, J. H., & Verloop, N. (1999). Teachers knowledge of models and modelling in science. International Journal of Science Education, 21, 1141–1153. Wong, E. D. (1993). Self-generated analogies as a tool for constructing and evaluating explanations of scientific phenomena. Journal of Research in Science Teaching, 30, 367–380.

David F.Treagust Curtin University of Technology, Australia Email: [email protected] David Treagust is Professor of Science Education at Curtin University of Technology in Perth, Western Australia and teachers courses in Campus-based and International programs related to teaching and learning science. He taught 22

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secondary science for 10 years and his research interests are related to understanding students’ ideas about science concepts, and how these ideas contribute to conceptual change and can be used to enhance the design of curricula and teachers’ classroom practice.

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