THE TAXONOMY OF MULTIPLE REPRESENTATIONS FUNCTIONS Representations have advantages in supporting learning science (Ainsworth, 2006).

Research on the benefits of providing learners with combinations of more than one representation has discovered a number of functions in supporting learning. According to de Jong, et al. (1998) there are many reasons for using more than one representation in learning. First, specific information can best be conveyed in a specific representation, while a combination of several representations is likely to display learning material that contains a variety of information; second, problem solving depends on having a large repertoire of representations or mental models, being able to switch between them and selecting the appropriate ones.

2.6.2.1 Multiple Representations in Complementary Roles

The complementary functions of MERs in Ainsworth’s (1999) functional taxonomy are to use representations that provide complementary information or support complementary cognitive processes so that learners could benefit from the advantages of combined representations such as teaching with both diagrams and written-textual representations.

Multiple External Representations support learning by providing complementary

information. On one hand, the multi-representational environments allow learners to

concentrate on different aspects of a task so that they can likely achieve their goals in the learning task (Oliver & O'Shea, 1996). On the other hand, how multiple representations can support new inferences by providing partially redundant representations such as a functional diagram of a heating system and a physical map to show the position of its components (Ainsworth, 1999).

Multiple External Representations also can provide complementary cognitive

processes. According to Ainsworth (1999), firstly, the different representations

containing equivalent information can still support inferences. For example, diagrams could demonstrate learners’ perceptual processes by classifying the relevant information that then makes conceptual learning easier (Larkin & Simon, 1987). Textual representations could help learners perform spatial judgement more accurately (Tapiero, 2001). Secondly, multi-representational learning environments

present a choice of different representations to cater for the varying degree of experience and expertise of students who have different representational preferences. Thirdly, learners’ performance in problem solving was found to be effectively improved when they have been employed in multiple representational learning environment (Moreno et al., 2011).

2.6.2.2 Multiple Representations in Constraining Information

In the functional taxonomy of Multiple External Representations (Ainsworth, 1999), constraining functions refer to introducing a familiar representation to constrain the learner’s interpretation/ misinterpretation of a less familiar representation so as to help learners achieve a better understanding of the domain. In addition, the constraints also can be achieved by taking advantage of inherent properties of representations. For example, photographs are always employed in secondary biology textbooks alongside complex and unfamiliar representations such as diagrams or written text: when explaining the term ATP, two modes of representations were employed in Figure 2.3.

Written text: ‘ATP consists of an adenine linked to a ribose sugar and three phosphate groups’.

Diagram:

Figure 2.3 Structure of Adenosine Triphosphate (ATP) Shown by Diagram (adopted from teacher’s handout).

Though the two representations contain the same information, students may have difficulty in understanding the detailed information solely by reading the text, such as, the exact locations of the three chemical components, and how they are connected. However, Stenning et al (1995) argued that graphical representations contains more specific information than textual representations. Therefore, when both representations are employed, interpretation of the ambiguous (textual)

representation may be constrained by the specific (diagram) representation. As a result, the inherent ambiguity contained within the text could be eliminated by the information provided by the diagram. The literature also confirmed the similar mutual explaining effects between diagram and text.

2.6.2.3 Multiple External Representations in Constructing Understanding

The third function of Multiple External Representations is to encourage learners to construct deeper understanding of a phenomenon through abstraction of, extension from and developing a relational understanding between the representations (see figure 2). The differences between these functions of Multiple External Representations are subtle and all may exist in certain processes.

Abstraction refers to the process by which learners create mental entities that could

serve the basis for further conceptual formation at a higher level (Ainsworth, 2006, p. 8). Abstraction also can be conceptualized as the process of detecting the extract features and removing the redundant details through interacting with representations (Giunchiglia & Walsh, 1992). Students construct references across different modes of representations that have the underlying structure of the domain knowledge. This meaning is compatible with ontological conceptual change (Chi et al., 1994). The abstraction function may support learners to switch their understanding between different types of representations and apply their learning in other specific contexts.

Extension is a way of extending knowledge to new situations without fundamentally

changing the nature of that knowledge at a higher level (Ainsworth, 2006). Accordingly, within the same domain, the extension involves a learner exploiting an understanding of one representation in order to understand a second representation for the same knowledge. For example, a learner may know how to interpret a photograph in order to determine that cell division for growth is taking place during the mitosis process; subsequently they can extend their knowledge of mitosis to more abstract representations like schematic diagrams and text.

Relational understanding is the process by which two representations are associated

without reorganization of knowledge (Ainsworth, 2006). The goal of teaching for relational understanding emphasizes that students’ consideration should be placed on

creating the relationship between the two representations that they may already be familiar with. On this occasion, Dugdale (1992) gave an example in constructing understanding between graph and equation.

Though students’ interpretation of the information in visualizations is critical to learning, Ainsworth, Prain, and Tytler (2011) argued that learners need to develop representational skills. They further concluded the importance of teachers’ and learners’ use of drawings - to enhance students’ engagement, to acquire visual literacies of representing science, to organize their knowledge more effectively, and to communicate and clarify ideas with peers. Therefore, research may need to establish explicit connections between drawings and the methods that they are engaged in during the teaching and learning process.

2. 7 CONCLUSION

This chapter has drawn together constructs that are pertinent to teaching and learning with diagrams under the theory of multiple representations, the discussion of a number of significant constructs have been reviewed in attempting to answer the research questions.

In section 1 of the chapter, the researcher has portrayed how scientists reasoned and developed theories and strategies on metacognitive learning. Gilbert (2007) suggested that metacognitive teaching and learning can be best discussed in respect of a person with metavisual capability that includes a range of knowledge and skills in dealing with various modes/levels of representations.

Section 2 discussed the explanatory strengths of instructional representations in conveying meaning between the concrete referent and its sign. The intellectual demand of interpreting representation, have been classified by theorists differently as external and internal (e.g., Zhang, 1997) or as descriptive and depictive (e.g., Schnotz & Bannert, 2003). Even to make sense of one single scientific concept, learners need to move fluently between different levels of representation such as macroscopic, sub-microscopic and symbolic levels (Johnstone, 2000; Treagust & Chittleborough, 2001). No matter in which way representations aid the formation of meaningful learning of a certain science concept, analogical transfer Gilbert (2008)

emphasizes the bridging effects of representations in helping learners build connections between different modes of visualizations.

Section 3 examined specific difficulties and challenges for teaching and learning secondary biology. In this section, students’ misconceptions have been categorized based on the representational levels to which particular biological content have been assigned. The difficulties lie not only in interpreting different types of illustrations, but also in switching and integrating learners’ understanding across various levels of mental models.

Section 4 aimed at specifying the instructional functions of diagrams in teaching biology. Among all the static visual displays used in instruction, diagrams have an important role to play in demonstrating a wide range of information either abstract or concrete (Pozzer & Roth, 2003). Though a variety of definitions of the term diagram have been suggested, Hegarty et al. first categorized the diagrams used in science education into three types: ionic, schematic, and charts and graphs. Novick further supported this categorization and traced its usage in learning to a number of biological topics such as meiosis and evolution. Furthermore, research on learning with visualization has shown that the use of multiple representations in various modalities and combinations provides unique benefits in learning complex scientific concepts. The review has also brought together the discussions on the connectedness of text and visual medium, because both of them constitute a key component in the multimedia-based instruction.

Section 5 described the theoretical framework for analysing and interpreting data to investigate how the biology learning process implies how and why constraining, constructing and complementary functions occur between diagrams and texts.

CHAPTER 3