Building complexity in chemistry through images

Cover image: © Getty Images First published 2023 by Routledge 4 Park Square, Milton Park, Abingdon, Oxon OX14 4RN and by Routledge 605 Third Avenue, New York, NY 10158 Routledge is an imprint of the Taylor & Francis Group, an informa business © 2023 selection and editorial matter, Margaret A.L. Blackie, Hanelie Adendorff and Marnel Mouton; individual chapters, the contributors The right of Margaret A.L. Blackie, Hanelie Adendorff and Marnel Mouton to be identified as the authors of the editorial material, and of the authors for their individual chapters, has been asserted in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data A catalog record has been requested for this book ISBN: 978-0-367-51869-1 (hbk) ISBN: 978-0-367-51870-7 (pbk) ISBN: 978-1-003-05554-9 (ebk) DOI: 10.4324/9781003055549 Typeset in Galliard by SPi Technologies India Pvt Ltd (Straive) Contents List of figures List of tables List of contributors 1 Enacting Legitimation Code Theory in science education vii x xi 1 MARGARET A.L. BLACKIE, HANELIE ADENDORFF, AND MARNEL MOUTON PART I Academic Support in Science 2 Becoming active and independent science learners: Using autonomy pathways to provide structured support 19 21 KAREN ELLERY PART II Physical Sciences 3 Improving assessments in introductory Physics courses: Diving into Semantics 39 41 CHRISTINE M. STEENKAMP AND ILSE ROOTMAN-LE GRANGE 4 Building complexity in Chemistry through images 63 ZHIGANG YU, KARL MATON, AND YAEGAN DORAN 5 Using variation in classroom discourse: Making Chemistry more accessible BRUNO FERREIRA DOS SANTOS, ADEMIR DE JESUS SILVA JÚNIOR, AND EDUARDO FLEURY MORTIMER 82 vi Contents 6 Radiation Physics in theory and practice: Using Specialization to understand ‘threshold concepts’ 103 LIZEL HUDSON, PENELOPE ENGEL-HILLS, AND CHRIS WINBERG PART III Biological Sciences 7 Interdisciplinarity requires careful stewardship of powerful knowledge 127 129 GABI DE BIE AND SIOUX MCKENNA 8 Advancing students’ scientific discourse through collaborative pedagogy 148 MARNEL MOUTON, ILSE ROOTMAN-LE GRANGE, AND BERNHARDINE UYS 9 Using Autonomy to understand active teaching methods in undergraduate science classes 169 M. FAADIEL ESSOP AND HANELIE ADENDORFF PART IV Mathematical Sciences 191 10 A conceptual tool for understanding the complexities of mathematical proficiency 193 INGRID REWITZKY 11 Supporting the transition from first to second-year Mathematics using Legitimation Code Theory 206 HONJISWA CONANA, DEON SOLOMONS, AND DELIA MARSHALL PART V Science Education Research 225 12 Navigating from science into education research 227 MARGARET A.L. BLACKIE Index 241 4 Building complexity in Chemistry through images Zhigang Yu, Karl Maton, and Yaegan Doran Introduction Images are common in Chemistry. Photographs, diagrams, graphs and charts are widely used to represent Chemistry knowledge and form a crucial component of the texts through which students learn that knowledge. A key feature of images is the complexity of meanings they express, as different degrees of complexity are needed in different learning stages (Dimopoulos et al. 2003, Kapıcı and Savaşcı-Açıkalın 2015, Pintó and Ametller 2002). For example, Figure 4.1 includes two images from Chemistry textbooks designed for secondary school curriculum in New South Wales (NSW), Australia. The image on the top is from a Year 7 textbook discussion of states of matter and shows an ‘everyday’ phenomenon: ice melting to become liquid water. The epistemological meanings expressed are relatively simple. In contrast, the image on the bottom is from a Year 11 textbook and illustrates the working mechanism of a ‘Daniell cell,’ a type of electrochemical cell that converts chemical energy into electrical energy. The diagram presents multiple technical elements and processes that are key to the energy conversion. The complexity of the diagram can be illustrated by unpacking the meanings being expressed into a written description. The experimental set-up includes three main components: cathode, anode and salt bridge. The cathode is ‘copper’ in the right beaker and shown gaining copper cations (denoted by circles labelled ‘Cu2+’ moving to circles labelled ‘Cu’) from the electrolyte (represented by blue liquid). Since copper cations are positively charged, their addition makes the cathode positively charged. The anode is ‘zinc’ in the left beaker, which is shown releasing zinc anions (denoted by circles labelled ‘Zn’ moving to circles labelled ‘Zn2+’) into the electrolyte (purple liquid). As zinc metal loses positively charged cations, the anode is negatively charged. The ‘salt bridge’ is a filter paper soaked in a solution of potassium nitrate (KNO3), which connects the left and right beakers. Its function is to help maintain the electrical neutrality within the internal circuit. In the image, the nitrate anions (circles labelled ‘NO3-’) move towards the left beaker while the potassium cations (circles labelled ‘K+’) move to the right beaker to maintain an electrical neutrality in the two electrolytes. In addition to these key technical elements, the image also involves several technical DOI: 10.4324/9781003055549-6 64 Zhigang Yu et al. Figure 4.1 Melting ice cubes (top); the electrode reactions in a Daniell cell (bottom). (top) (reproduced with permission from Shutterstock); (bottom) drawing after Chan et al. 2018: 391 processes. The two electrodes are associated with two chemical reactions, shown here by labels of chemical equations: the cathode undergoes a reduction reaction ‘Cu2+(aq) + 2e− → Cu(s)’ and the anode undergoes an oxidation reaction ‘Zn(s) → Zn2+(aq) + 2e−.’ A third technical process is the movement of electrons from the anode to the cathode (denoted by circles labelled ‘e−’ moving from ‘zinc’ to ‘copper’) forming ‘electric current.’ These processes are overlaid on the elements. In short, the image condenses a significant number of technical meanings from Chemistry. As the two images from Chemistry textbooks for Years 7 and 11 illustrate, there is considerable difference in the complexity of the knowledge expressed through the years of secondary schooling. This rise in complexity of images is, we shall show, a feature of progression through the years of secondary school Chemistry. Yet, there remains little understanding of how images Building complexity in Chemistry through images 65 embody the complexity of Chemistry knowledge. To date, studies have tended to describe images in Chemistry in terms of the kinds of referents they involve. Johnstone (1991), for example, classifies Chemistry knowledge in terms of three levels: ‘macro’ or what can be seen, touched and smelled; ‘submicro’ or atoms, molecules, ions, etc.; and ‘symbolic’ or symbols, formulas, equations, etc. Gilbert (2005) develops this schema into a model of three types of representation in Chemistry: macroscopic, submicroscopic and symbolic. From this perspective, the top image in Figure 4.1 is ‘macroscopic’ and the bottom image is a hybrid of ‘macroscopic’ (the apparatus), ‘submicroscopic’ (atoms, cations, and electrons) and symbolic (chemical equations and formulas). This influential model of chemical representations usefully highlights the breadth of referents that may be included in images, but it does not capture the varying levels of complexity these images present, which is our concern here. Another approach to images in science education examines the degree of ‘specialization’ of content expressed (note that this is not ‘Specialization’ from Legitimation Code Theory). For example, Dimopoulous et al. (2003) distinguish three types of images in science: ‘realistic’ (images that represent reality according to human optical perception), ‘conventional’ (graphs, maps, flowcharts, molecular structures constructed according to the technoscientific conventions) and ‘hybrids’ (images that include elements from both the other two types). They argue that ‘conventional’ images correspond to strong, ‘hybrids’ to moderate, and ‘realistic’ to weak levels of ‘specialization.’ That is, ‘conventional’ images express the most techno-scientific knowledge, whereas ‘realistic’ images convey ‘everyday’ knowledge. The three categories of images offer a broad sense of differences in images’ degree of what they term ‘specialization,’ which implies differences in the complexity of knowledge. However, it does not systematically capture complexity. For example, an image of a chemical apparatus may be ‘realistic’ but also express relatively complex technical knowledge. Thus, a model is required for describing different degrees in the complexity of meanings expressed by images. A fruitful avenue for exploring complexity is through the Semantics dimension of Legitimation Code Theory (LCT). Semantics explores knowledge practices in terms of their context-dependence and complexity (Maton 2011, 2013, 2014, 2020). It has proven useful in analyzing a diverse range of practices, including academic writing (Brooke 2017, Clarence 2017, Kirk 2017), musical performance (Richardson 2020, Walton 2020) and dance (Lambrinos 2020). This chapter will focus on the concept of semantic density, which examines the complexity of meanings, and will extend this growing body of work to embrace images. To ‘see’ the complexity of knowledge expressed by the images used for building Chemistry knowledge, we will establish a model that makes explicit different levels of complexity in images based on data from Chemistry textbooks designed for the secondary school 66 Zhigang Yu et al. curriculum in NSW, Australia. This model is what is termed in LCT a translation device (Maton and Chen 2016) for relating different strengths of semantic density to images from the textbooks. This device will then be enacted to explore how complexity changes through secondary education and to begin to reveal the roles that images play in organizing Chemistry knowledge. Our analysis will suggest that images play a variety of roles, with some connecting knowledge to ‘everyday’ phenomena and others more concerned with building connections among theoretical ideas. It also suggests that across the years of secondary schooling, at least in textbooks for NSW, images embody a growing range of semantic density. That is to say that, while images in each year maintain a connection to the everyday world, they reach up towards increasingly complex and technical meanings from the field of Chemistry. Seeing complexity in images: semantic density Semantic density (SD) refers to the degree of complexity of meanings or practices (Maton 2014). Semantic density can be stronger or weaker along a continuum of strengths, where the stronger the semantic density (SD+), the more complex the meanings and the weaker the semantic density (SD−), the simpler the meanings. Put another way, the more relations with other meanings enjoyed by a practice, the stronger its semantic density (Maton and Doran 2017). These meanings may be epistemological, such as formal definitions and empirical referents, or axiological, such as affective, aesthetic, ethical, moral or political meanings (Maton 2014). In this chapter, we focus on epistemological meanings and so discuss epistemic–semantic density or ‘ESD.’ For example, ‘salt’ in everyday usage refers to small white crystals often used to add flavour to food – a relatively small number of relations among epistemological meanings, such as its flavour, shape and uses. In contrast, as a technical word in the field of Chemistry, ‘salt’ refers to a compound produced by the reaction of an acid with a base and involves relations with numerous chemical concepts, such as cations, anions and ionic bonds, which themselves relate to a large number of other meanings. Thus, in Chemistry, the term ‘salt’ is situated within a relatively complex constellation of epistemological meanings that imbues the term with relatively strong epistemic– semantic density.1 As we discussed in the introduction, to analyze the role of the complexity of knowledge expressed by images in building Chemistry knowledge, a model is needed to reveal different degrees of complexity. We begin by outlining such a model as a translation device (Maton and Chen 2016) or series of categories for identifying different strengths of epistemic–semantic density in images used in NSW secondary school Chemistry textbooks. We then enact this translation device to explore the complexity of images in Chemistry textbooks through secondary school. Building complexity in Chemistry through images 67 A model of complexity in images used for teaching chemistry Chemistry uses a range of images, even when representing the ‘same’ phenomenon. Figure 4.2, for example, presents two images that represent water, from textbooks aimed at Year 7 (left) and Year 11 (right) of secondary school. The left image comprises water flowing out from the tap into the cup, a depiction of a relatively commonplace activity that shows the physical state and the colour of water. The right image represents water in terms of the intermolecular force among its molecules, using the symbols ‘O’ and ‘H’ to indicate atoms within the molecules, solid lines between ‘O’ and ‘H’ to represent covalent bonds and a dashed line to represent hydrogen bonding between the water molecules. As our descriptions suggest, the images express different levels of complexity: the left image embodies weaker epistemic– semantic density than the right image, which involves a more complex constellation of meanings and thus stronger epistemic–semantic density. As shown in Table 4.1, the variation in epistemic–semantic density we touch on here is the first distinction in the model between more complex (stronger ESD) and simpler (weaker ESD) images. It is marked by whether images depend for their meanings on the complex constellation of meanings associated with Chemistry, termed technical images, or do not, which we term here everyday images.2 The right image in Figure 4.2 is a technical image that makes explicit multiple meanings within the domain of Chemistry, for example, atoms, partial charges and hydrogen bonding. The left image is an Figure 4.2 Fresh water in a cup (left); hydrogen bonding between water molecules (right). ((left) reproduced with permission from Shutterstock) Table 4.1 A translation device for the epistemic–semantic density of images in secondary school chemistry textbooks ESD Types Subtypes ++ technical conglomerate compact events entities −− everyday 68 Zhigang Yu et al. everyday image that shows water without indicating a more complex constellation of epistemological meanings. (Although a trained chemist could read into this image a large number of Chemistry-specific meanings, the image itself does not rely on the complex constellation of Chemistry to convey meaning). Secondary school Chemistry textbooks use both everyday and technical images throughout year levels to build knowledge. Everyday images often present things and phenomena in the physical world that can be connected to specialist Chemistry knowledge, while technical images often build theoretical understandings of these things and phenomena. Subcategories of technical images This is but a first level of delicacy. Both everyday and technical images exhibit a range of variations in complexity – as shown in Table 4.1. Focusing first on technical images, Figure 4.3 comprises examples from a Year 7 textbook (left), illustrating the compressibility of air, and a Year 11 textbook (right), presenting the structure of water molecules. The left image shows that the process of pushing a piston (the grey stick) compresses air in cylinders (in the right side of the piston), which in turn accelerates the motion of molecules (balls with shades). The image as a whole is categorized as technical as it relies on the constellation of Chemistry to make sense. It expresses the knowledge that pressure influences the thermal motion of molecules. However, its various components are not themselves ‘technical’: the balls, arrows, walls, etc., do not express knowledge from the constellation of Chemistry individually. It is only when combined into the image as a whole that the ‘technical’ meaning is expressed. In contrast, the right image in Figure 4.3 is categorized as technical whose components themselves are also ‘technical’ in nature. This image is a structural formula that presents the molecular make-up of water: ‘O’ and ‘H’ represent oxygen and hydrogen atoms, respectively, and solid lines denote single covalent bonds. The image as a whole is categorized as technical as it expresses meanings from the constellation of Chemistry, for example, geometry of water molecules, and the components are ‘technical’ as they resonate out to numerous meanings in Chemistry, such as lone electrons and shared electrons. Thus, while both are categorized as technicals, the Year 11 image embodies stronger Figure 4.3 Compressibility of air (left); a structural formula of water molecules (right). ((left) reproduced with permission from Oxford University Press) Building complexity in Chemistry through images 69 epistemic–semantic density than the Year 7 image: both the (right) image as a whole and its components are integrated within the complex constellation of meanings that constitutes Chemistry. This offers a distinction within technical images: whether an image involves components that depend for their meanings on complex constellations of epistemological meanings. Those that do are termed technical-conglomerates; those where only the image as whole depends on a complex constellation are termed technical-compacts (see Table 4.1). In Figure 4.3, the left image is categorized as compact – as a whole, it depends on meanings from a wider constellation to express that pressure influences the thermal motion of molecules, but its components do not themselves each express chemical meanings. The right image is categorized as conglomerate: both the image as a whole and its components (‘O’ and ‘H,’ for example) express chemical meanings. Though we have limited the device presented in Table 4.1 to two levels of delicacy, for simplicity, further distinctions are possible. For example, Figures 4.4 and 4.5 are both conglomerates but represent differences in the complexity of the knowledge they express. Both the images as wholes and their components express chemical meanings. However, Figure 4.5 involves considerably more components that express Chemistry meanings than Figure 4.4. The structural formula of methane molecules (Figure 4.4) involves only two technical components: the chemical symbols representing atoms and the lines representing covalent bonds. In contrast, in Figure 4.5, the two pathways, ‘green’ and ‘brown’ (the original is in colour), are themselves technical as they show a series of organic reactions to the target product, ibuprofen molecules. The components within each pathway also express Chemistry meanings. For example, the structural formula of ibuprofen presents its molecular structure. In addition to atoms and covalent bonds, structural formulas in Figure 4.5 involve a group of special technical components: functional groups. For example, the structural formula of ibuprofen molecules includes a carboxylic group (-COOH), which determines that ibuprofen molecules are a type of carboxylic acid. Then within these functional groups are the atoms and the covalent bonds themselves (C, H, – etc.). Thus, further distinctions can be made within conglomerates if required. We shall draw on this in our analysis but do not require a third level here for other subcategories. Figure 4.4 A structural formula of methane molecules. 70 Zhigang Yu et al. Figure 4.5 Two pathways for the production of ibuprofen. (drawing after Chan et al. 2019: 364) Subcategories of everyday images As summarized in Table 4.1, we can distinguish between different kinds of everyday images used in Chemistry textbooks. This often involves using everyday images for presenting things or phenomena as they appear to the naked eye. Such images often offer an orientation to the phenomena explained by Chemistry as they appear in commonplace settings. A second level of delicacy is illustrated by Figure 4.6. The left image shows the inside of a box of matches, while the right image displays a burning match. Both are everyday images but vary in complexity. The left image shows entities: the box and matches. The right image shows both an entity and an event: the burning of a match. The left image thus displays weaker epistemic–semantic density than the right image, which includes a process. We can thereby distinguish between: everyday-entity images (ESD– –) that present entities only and everyday-event (ESD–) images that also express events or actions. Building complexity in Chemistry through images 71 Figure 4.6 A pile of matches (left); a burning match (right). ((left) reproduced with permission from Shutterstock; (right) reproduced with permission from Shutterstock) Distinctions among images and knowledge-building The distinction between different kinds of everyday and technical images allows us to ‘see’ the potential for knowledge-building offered by the sequencing of images in Chemistry textbooks. Using the model outlined above, we can see how the ‘same’ Chemistry phenomenon can be imaged with varying degrees of complexity. For example, all three images in Figure 4.7 represent combustion of carbon; the left and middle images are from Year 10, and the right is from Year 11. The top image presents combustion of carbon through an everyday-event image (ESD–): a pile of wood is burning at a campsite to provide light and warmth for people. The left image presents combustion of carbon through a technical-compact image (ESD+) that describes energy change during the reaction. The vertical axis shows energy levels of chemical species and the horizontal axis indicates reaction time. The line graph shows that, as the reaction goes on, energy decreases from a higher level to a lower level. The image as a whole relates to the chemical concept of exothermic reaction, which explains why the burning of wood in the left image can release heat and warm people. With stronger epistemic–semantic density, the middle image provides a theoretical explanation for the physical phenomenon presented in the left image. The knowledge of energy change during combustion of carbon is then further elaborated in Year 11 through a technicalconglomerate image (ESD++), shown in the right image in Figure 4.7. This is an energy level diagram for the formation of carbon dioxide from carbon and oxygen via carbon monoxide. The diagram shows two pathways to the formation of carbon dioxide, in which the overall enthalpy change involved is the same. The image as a whole is ‘technical’ as it expresses meanings from the constellation of Chemistry: combustion of carbon to form carbon dioxide involves two stages and releases heat. Within the diagram, the components also express ‘technical’ meanings. The arrows that lead ‘C(s) + O2(g)’ to ‘CO(g) + ½ O2(g)’ and ‘C(s) + O2(g)’ to ‘CO2(g)’ represent incomplete and complete combustion of carbon, respectively, and are meanings from the constellation of Chemistry. With even stronger epistemic–semantic density, the 72 Zhigang Yu et al. Figure 4.7 A campfire (top); energy change during combustion of carbon (left); an energy level diagram for the formation of carbon dioxide from carbon and oxygen carbon monoxide (right). ((top) reproduced with permission from Shutterstock; (right) drawing after Chan et al. 2018: 486) right image expresses more complex Chemistry knowledge of the combustion of carbon. Though the three images in Figure 4.7 represent the ‘same’ phenomenon, they present differing degrees of complexity of meaning. The everyday image presents a ‘common-sense’ or experiential version of the phenomenon and the technical images offer increasingly complex theoretical understandings. When sequenced together, they offer the possibility for connecting simpler meanings to a greater range of meanings from the constellation of Chemistry, increasing the complexity of the knowledge being expressed. To explore how images are used in Chemistry textbooks, we shall enact the translation device (Table 4.1) to analyze images from Chemistry textbooks designed for the secondary school curriculum in NSW, Australia. Changing complexity of images in chemistry textbooks Chemistry textbooks tend to use images with a range of different levels of complexity both within and across year levels. To explore this variation, we will use the translation device for epistemic–semantic density to examine Chemistry textbooks designed for secondary schooling in NSW, Australia. Here we analyze six textbooks: Oxford Insight Science Year 7 (Zhang et al. 2013), Oxford Insight Science Year 8 (Zhang et al. 2014a), Oxford Insight Science Year 9 (Zhang et al. 2014b), Oxford Insight Science Year 10 (Zhang Building complexity in Chemistry through images 73 et al. 2015), Pearson Chemistry Year 11 (Chan et al. 2018) and Pearson Chemistry Year 12 (Chan et al. 2019). It should be noted that our analysis of images excludes the accompanying text in the textbooks; our focus here is on what images themselves express in terms of complexity of knowledge, rather than their multimodal interactions with verbal text. The curriculum of secondary school Chemistry in NSW includes six years that are categorized into three stages: Stage 4 (Years 7 and 8), Stage 5 (Years 9 and 10) and Stage 6 (Years 11 and 12). Our analysis focuses on one topic that appears in all three stages: chemical reactions. We shall show that while epistemic–semantic density increases across the stages, weaker epistemic– semantic density images are present throughout. Thus, rather than a progression from simpler to more complex images, the textbooks retain simpler images and add more complex images. That is, simpler images are not confined to an early stage of secondary schooling and left behind once technical Chemistry knowledge has been established. Rather, a connection to the ‘everyday’ and experiential is kept from Year 7 to Year 12. In sum, they represent a growing range of epistemic–semantic density. We suggest that this offers textbooks the possibility of modelling moves between simpler ‘everyday’ or common-sense knowledge and more complex theoretical Chemistry knowledge throughout secondary school. Stage 4: From everyday-entities to technical-compacts Figure 4.8 shows the simplest and the most complex images found in the textbooks for Stage 4 (Year 7 and 8) in relation to chemical reactions. They are from consecutive pages of the same textbook. The left image shows a rusted car, illustrating a common issue for objects made of iron: rust. This is an everyday-entity image that expresses relatively weak epistemic–semantic density (ESD−−). In contrast, the right image shows a diagram of six test tubes containing different environments: air, water, oil, boiled water, salt solution and dry salt. In these test tubes, iron nails are placed to observe their respective speed of rusting. This diagram thus also illustrates ‘rusting’ but Oil Rubber stopper Air Nail Water Oil Boiled Salt water solution Dry salt Figure 4.8 A rusted car (left); a diagram of a rusty nail experimental set-up (right). ((left) reproduced with permission from Shutterstock; (right) reproduced with permission from Oxford University Press) 74 Zhigang Yu et al. with a technical-compact image that expresses stronger epistemic–semantic density (ESD+). The six test tubes include different environments with distinct concentrations of air, which indicates that the key variable influencing rusting of iron is oxygen. With this range of epistemic–semantic density (from ESD−− to ESD+), the images in Stage 4 offer imagic means to everyday phenomena and build relatively theoretical understanding underpinning them (though not as technical as is possible: ESD+ rather than ESD++). Stage 5: From everyday-entities to technical-conglomerates Figure 4.9 shows the simplest and the most complex images in relation to chemical reactions found in textbooks for Stage 5 (Years 9 and 10). Similarly to Stage 4, there is an everyday-entity image that expresses relatively simple meanings (ESD−−): on the left image in Figure 4.9, showing two segments of orange. This is illustrating a food that has weak acidity and reactivity and thus is edible. In contrast to Stage 4, however, the kind of technical images included in textbooks are of greater complexity: technical-conglomerate images (ESD++). The right image of Figure 4.9 illustrates the formation of sodium chloride through an ‘equation diagram.’ The overall diagram shows that a sodium chloride (Na+ and Cl−) is formed by a sodium atom (Na) donating an electron to a chlorine atom (Cl) (shown by the dashed arrow combined with an ‘e−’). In addition, the components – the individual diagrams showing atomic structure of the atoms and ions – are technical. One aspect of the key technical information expressed by the atomic structure diagram is that a sodium atom has only one electron in its outer shell and a chlorine atom has seven. A sodium atom and a chlorine atom thus tend to lose and gain one electron, respectively, to achieve their stable status. This technical-conglomerate means that epistemic–semantic density of images in Stage 5 reaches higher than in Stage 4: it reaches further into complexity. However, as shown by the left image, images expressing simpler meanings are retained: everyday-entity images (ESD−−). Thus, images in Stage 5 span a greater range of epistemic–semantic density (from ESD−− to ESD++) than those found in Stage 4 (from ESD−− to ESD+). Figure 4.9 Two segments of orange (left); the formation of sodium chloride. ((left) reproduced with permission from Shutterstock; reproduced with permission from Oxford University Press) Building complexity in Chemistry through images 75 Stage 6: From everyday-entities to technical-superconglomerates Stage 6 takes a further step into complexity. The textbooks continue to include everyday-entity images but now include far more technicalconglomerate images and introduce particularly strong technical-conglomerates or, for want of a better term for the moment, superconglomerates. The range of epistemic–semantic density of images is illustrated by Figure 4.10. The left image is an everyday-entity (ESD−−) that shows batteries and is used in the textbook to illustrate the application of electrochemical reactions in an ‘everyday’ setting. The right image is a technical-superconglomerate. It shows the formation of a secondary amide through a condensation reaction between ethanoic acid and methylamine. The diagram as a whole is ‘technical’ as it shows a Chemistry reaction integrated within the domain of Chemistry. Each side of the arrow is also ‘technical.’ The left includes diagrams known as structural formulas for both ethanoic acid and methylamine, while the right includes structural formulas for water and a secondary amide. These components each in turn include multiple other ‘technical’ components. For example, in the structural formula of ethanoic acid, the group ‘–COOH’ represents the functional group carboxyl, while ‘–CH3’ represents the methyl group, with each of these further including technical components: the symbols ‘C,’ ‘O,’ and ‘H’ represents atoms, while the lines ‘—’ and ‘ ’ denote single and double covalent bonds. This image thus expresses multiple levels of technical meaning – more than that shown by the most complex images of Stages 4 or 5. This represents significantly stronger epistemic–semantic density. Such images occur regularly in Stage 6 and thus push the complexity of the knowledge expressed through images to much greater heights. A greater range of complexity Textbooks for all three Stages of NSW secondary schooling employ everydayentity images (ESD−−) to show ‘everyday’ phenomena. However, as illustrated in Figure 4.11, there is an expansion in the degree of complexity of other images as the years progress, increasing the semantic range of images. As Figure 4.11 suggests, the knowledge expressed by the images in the textbooks studied maintains connections with the common-sense ‘everyday’ or Figure 4.10 Batteries (left); a diagram showing the formation of a secondary amide through a condensation reaction between ethanoic acid and methylamine (right). ((left) reproduced with permission from 123RF.com) 76 Zhigang Yu et al. Figure 4.11 A widening range of images’ epistemic–semantic density across stages. phenomenal world but reaches towards increasing levels of complexity in Chemistry knowledge. As we have emphasized, this is not simply an ascent into greater complexity but rather into a greater range of complexity. We conjecture that this growing range of epistemic–semantic density may play a significant role in building Chemistry knowledge through secondary schooling. In terms of Johnstone’s (1991) Chemistry triplet (macro, micro and symbolic), the simplest images in each stage tend to express macroscopic knowledge (what can be sensed) and present things or phenomena as they appear in everyday settings. As the epistemic–semantic density range grows, the most complex images tend to express microscopic knowledge (diagrams of atoms, molecules and structures) in Stage 5 and symbolic knowledge (symbolic graphs and diagrams) in Stage 6. In the field of Chemistry education, it has been widely argued that to be successful students need to move among different types of Chemistry knowledge (Gabel 1993, Johnstone 1993, Chittleborough et al. 2005). The widening range of epistemic–semantic density of images in textbooks analyzed here suggests that this move, particularly when shifting from macroscopic knowledge to symbolic knowledge, involves successful mastery of the increasing range of complexity of the knowledge expressed by images. Integrating complexities through composite images This range of complexity is not simply found in comparing images – it may also be expressed within images. To explore this, we introduce another form of images: composites. These are images that bring together different degrees of complexity of knowledge. For example, Figure 4.12 is an image that brings together two levels of complexity representing water and ice. The photograph on the left shows ice floating on water, a common-sense phenomenon we could see in ‘everyday’ life. The two diagrams, in contrast, provide a chemical explanation at a microscopic level for the phenomenon: ice floats on the water because the water molecules form a crystal lattice in which the molecules are spaced more widely apart than in liquid water. This arrangement of water molecules means ice is less dense than liquid water. Building complexity in Chemistry through images 77 These everyday and technical images embody two levels of complexity and are incorporated into one composite. A composite image can be distinguished by considering two attributes. First, the image presents strong boundaries between its composite parts.3 These boundaries tend to be shown by elements which create dividing lines that disconnect constituent parts of the image or by blank spaces that form ‘gutters’ or gaps between images. Both signify that there are constituent parts being brought together. In Figure 4.12, the circles which centre around the molecule models separate the photo and the two diagrams. Viewed individually, each of these constituent images makes sense on their own. Second, the constituent images of a composite embody different levels of complexity. As mentioned above, Figure 4.12 comprises images exhibiting two levels of complexity: the photograph of a cup of water and ice embodies weaker epistemic– semantic density (an everyday-entity), and the diagrams of water molecules embody relatively strong epistemic–semantic density (technical-conglomerate). By way of contrast, Figure 4.13 neither distinguishes constituents nor involves different levels of complexity. Though it may look as if it contains multiple components, they do not have strong boundaries around each other nor embody distinct strengths of epistemic–semantic density. Figure 4.12 Ice is less dense than liquid water. (drawing after Chan et al. 2018: 183). Figure 4.13 The addition reaction of ethene with bromine (Chan et al. 2019: 313). 78 Zhigang Yu et al. Figure 4.14 The formation of the hydronium ion. (drawing after Chan et al. 2019: 148) The key point for our analysis here is that composites offer a way of bringing together a range of complexities in one eyeful. Significantly for our conjecture of a growing range of epistemic–semantic density through secondary schooling, composite images in textbooks occur mainly in Stage 6 (though remain relatively infrequent compared to non-composite images). In addition to composites that combine everyday and technical images, composites can also bring together technical images of different levels of complexity. For example, Figure 4.14 (from Year 12) brings together: a technical-compact representation of a model diagram on the bottom showing a water molecule (the diagrammatic model consisting of one red ball and two smaller white balls) adopting a proton (the white ball labelled ‘+’) to become a hydronium ion (the diagrammatic model on the right of the arrow) and a technical-conglomerate representation on the top that represents the reaction through a diagrammatic equation. Arranging these images together relates Chemistry meanings that are themselves complex to even more complex meanings. The composites in Figures 4.12 and 4.14 offer a way of ‘bridging’ between meanings with different degrees of complexity. They embody a range of epistemic–semantic density. This may help compound meanings from simpler into complex forms. In terms of Johnstone’s (1991) chemical triplet, composite images present a transition between macroscopic and microscopic knowledges in Figure 4.12 and between microscopic and symbolic knowledges in Figure 4.14. The change in the complexity of the images suggests that students are expected to be able to understand the shift between the different levels of epistemic–semantic density of the images embodied by the composites. Conclusion Along with language and chemical formalisms, images are one of the key means of expressing Chemistry knowledge in textbooks and beyond. Images may exhibit different degrees of complexity in different learning stages. However, to date, there has been little exploration of how images embody the complexity of Chemistry knowledge. This chapter has explored the complexity of images using the concept of epistemic–semantic density from LCT and developed a Building complexity in Chemistry through images 79 model for complexity of images as used in secondary school Chemistry textbooks in NSW, Australia. Enacting the device, we suggested that to build Chemistry knowledge, images develop from the everyday category with relatively weak epistemic–semantic density to the technical category with increasingly stronger epistemic–semantic density. The former tends to play the role of presenting common-sense physical and experiential phenomena, thereby offering students a common-sense ‘way into’ understanding, whereas the latter usually offers theoretical understandings of the phenomena. Our analysis of the range of epistemic–semantic density of images across curriculum stages suggests that knowledge expressed by the images in each stage maintains connections with the ‘everyday’ world but shows an increasing complexity as the curriculum progresses. This widening range of epistemic–semantic density indicates that in each stage students are expected to engage with both everyday and technical images. In Stage 6, the textbooks additionally involve composite images that bring together images embodying different levels of complexity, either between everyday images and technical images or between technical images with different degrees of complexity. This suggests that students are expected to be able to move between the different levels of complexity to connect meanings together. The translation device for epistemic–semantic density presented in this chapter was developed through analysis of textbooks. However, it is likely it will be of use to images in Chemistry more broadly, such as images used in classroom teaching or assessments. Although in LCT terms, they are specific translation devices for the problem-situation of a specific study (see Maton and Howard 2018), they offer a pathway to developing a generic translation device that works for all images in Chemistry. Our chapter is also limited to offering a way of seeing the complexity of knowledge expressed by images in Chemistry education. How this can be enacted to support teaching with images is, as yet, unexplored. Nonetheless, the model offered here represents, we believe, a valuable first step towards seeing the complexity of images in Chemistry. Notes 1 On constellations in LCT, see Maton (2014) and Maton and Doran (2021). Here we are only concerned the complexity of network of relations among meanings within which a meaning is situated. 2 We have as far as possibly echoed the names of categories in the generic translation device for English discourse as a whole set out by Maton and Doran (2017) in order to facilitate inter-modal comparison and multimodal analysis in future. However, English discourse and images are different objects of study whose different attributes often required different labels. We should emphasize that the current paper offers a specific translation device for images in secondary school chemistry textbooks, rather than a generic translation device for all images in Chemistry, let alone all images. 3 Kress and van Leeuwen (2020) call these boundaries ‘framing,’ a term which is easily confused with a different meaning of ‘framing’ by Bernstein (1973). We shall not use the term here. 80 Zhigang Yu et al. References Bernstein, B. 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