References
- Abraham, M., Varghese, V., & Tang, H. (2010). Using molecular representations to aid student understanding of stereochemical concepts. Journal of Chemical Education, 87(12), 1425–1429. https://doi.org/https://doi.org/10.1021/ed100497f
- Ametller, J., & Pintó, R. (2002). Students’ reading of innovative images of energy at secondary school level. International Journal of Science Education, 24(3), 285–312. https://doi.org/https://doi.org/10.1080/09500690110078914
- Barnea, N. (2000). Teaching and learning about chemistry and modelling with a computer-managed modelling system. In J. K. Gilbert & C. Boulter (Eds.), Developing models in Science education (pp. 307–324). Kluwer.
- Carvalho, G. S., Silva, R., & Clément, P. (2007). Historical analysis of Portuguese primary school textbooks (1920–2005) on the topic of digestion. International Journal of Science Education, 29(2), 173–193 https://doi.org/https://doi.org/10.1080/09500690600739340
- Chan, W. K., Fung, Y. C., Li, C. S. Y., Ng, K. K., & Sy, D. (2015). HKDSE biology: Concepts and applications 1B. Hong Kong: Aristo Educational Press Limited.
- Chang, H. Y. (2018). Students’ representational competence with drawing technology across two domains of science. Science Education, 102(5), 1129–1149. https://doi.org/https://doi.org/10.1002/sce.21457
- Chang, H. Y., Quintana, C., & Krajcik, J. S. (2010). The impact of designing and evaluating molecular animations on how well middle school students understand the particulate nature of matter. Science Education, 94 (1), 73–94. https://doi.org/10.1002/sce.20352
- Chang, H. Y., & Tzeng, S.-F. (2018). Investigating Taiwanese students’ visualization competence of matter at the particulate level. International Journal of Science and Mathematics Education, 16(7), 1207–1226. https://doi.org/https://doi.org/10.1007/s10763-017-9834-2
- Cheng, M. M. W., & Gilbert, J. K. (2014). Students’ visualization of metallic bonding and the malleability of metals. International Journal of Science Education, 36(8), 1373–1407. https://doi.org/https://doi.org/10.1080/09500693.2013.867089
- Cheng, M. M. W., & Gilbert, J. K. (2015). Students’ visualization of diagrams representing the human circulatory system: The use of spatial isomorphism and representational conventions. International Journal of Science Education, 37(1), 136–161. https://doi.org/https://doi.org/10.1080/09500693.2014.969359
- Cheung, K. K. C., & Winterbottom, M. (2021). Students’ integration of textbook representations into their understanding of photomicrographs: Epistemic network analysis. Research in Science & Technological Education, 1–20. https://doi.org/https://doi.org/10.1080/02635143.2021.1920382
- Chi, M. T. H., De Leeuwa, N., Chiu, M. H., & Lavancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18(3), 439–477. https://doi.org/10.1207/s15516709cog1803_3
- de Jager, T. (2017). Perceived advantages of 3D lessons in constructive learning for South African student teachers encountering learning barriers. International Journal of Inclusive Education, 21(1), 90–102. https://doi.org/https://doi.org/10.1080/13603116.2016.1184329
- Dinolfo, J., Heifferon, B., & Temesvari, L. A. (2007). Seeing cells: Teaching the visual/verbal rhetoric of biology. Journal of Technical Writing and Communication, 37(4), 395–417. https://doi.org/https://doi.org/10.2190/6261-4915-6LK8-11L8
- diSessa, A. A. (2004). Metarepresentation: Native competence and targets for instruction. Cognition and Instruction, 22(3), 293–331. https://doi.org/https://doi.org/10.1207/s1532690xci2203_2
- diSessa, A. A., & Sherin, B. L. (2000). Meta-representation: An introduction. Journal of Mathematical Behavior, 19(4), 385–398. https://doi.org/https://doi.org/10.1016/S0732-3123(01)00051-7
- Eilam, B. (2013). Possible constraints of visualization in biology: Challenges in learning with multiple representations. In D. Treagust. & C. Y. Tsui (Eds.), Multiple representations in biological education (Models and Modeling in Science Education Vol. 7, pp. 55–73). Springer.
- Etikan, I. (2016). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1–4. https://doi.org/https://doi.org/10.11648/j.ajtas.20160501.11
- Gilbert, J. K. (2004). Models and modelling: Routes to more authentic science education. International Journal of Science and Mathematics Education, 2(2), 115–130. https://doi.org/https://doi.org/10.1007/s10763-004-3186-4
- Gilbert, J. K. (2005). Visualization: A metacognitive skill in science and science education. In J. Gilbert (Ed.), Visualization in science education. Springer.
- Gilbert, J. K. (2008). Visualization: An emergent field of practice and enquiry in science education. In J. K. Gilbert, M. Reiner, & M. Nakhleh (Eds.), Visualization: Theory and practice in science education (pp. 3–24). Sringer.
- Goldstone, R. L., & Sakamoto, Y. (2003). The transfer of abstract princi-ples governing complex adaptive systems. Cognitive Psychology, 46(4), 414–466. https://doi.org/https://doi.org/10.1016/S0010-0285(02)00519-4
- Halverson, K. L., & Friedrichsen, P. (2013). Learning tree thinking: Developing a new framework of representational competence. In D. Treagust & C. Y. Tsui (Eds.), Multiple representations in biological education (pp. 185–201). Springer.
- Hegarty, M. (2011). The cognitive science of visual-spatial displays: Implications for design. Topics in Cognitive Science, 3(3), 446–474. https://doi.org/https://doi.org/10.1111/j.1756-8765.2011.01150.x
- Hirt, L., Leonard, C., & Lee, L. M. (2020). Are you copying me? Leveraging expert visual scan path to transmit visual literacy in novice histology students. The FASEB Journal, 34(S1), 1–1. https://doi.org/10.1096/fasebj.2020.34.s1.04665
- Howitt, D., & Cramer, D. (2008). Introduction to SPSS in psychology: For version 16 and earlier (4th ed.). Harlow: Pearson Education.
- Kiely, L. J. (1958). Student drawings vs. photomicrography. Science Education, 42(1), 66–73. https://doi.org/https://doi.org/10.1002/sce.3730420114
- Kozma, R., & Russell, J. (2005). Students becoming chemists: Developing representationl competence. In Visualization in science education. In J. K. Gilbert (Ed.), Visualization in science education (pp. 121–145). Springer.
- Krauss, D. A., Salame, I. I., & Goodwyn, L. N. (2010). Using photographs as case studies to promote active learning in biology. Journal of College Science Teaching, 40(1), 72–76.
- Linenberger, K. J., & Holme, T. A. (2015). Biochemistry instructors’ views toward developing and assessing visual literacy in their courses. Journal of Chemical Education, 92(1), 23–31. https://doi.org/https://doi.org/10.1021/ed500420r
- Merritt, J., & Krajcik, J. (2009). Developing a calibrated progress variable for the particle nature of matter. Paper presented at the Progressions in Science (LeaPS) Conference, Iowa City, IA.
- Mikula, A. R., & Lennox, J. E. (1979). Photomicrography as a variable in laboratory exercises. Journal of College Science Teaching, 8(4), 231–233.
- Moore, E. B., Chamberlain, J. M., Parson, R., & Perkins, K. K. (2014). PhET interactive simulations: Transformative tools for teaching chemistry. Journal of Chemical Education, 91(8), 1191–1197. https://doi.org/https://doi.org/10.1021/ed4005084
- Postigo, Y., & López-Manjón, A. (2012). Students’ conceptions of biological images as representational devices. Revista Colombiana de Psicología, 21(2), 265–284. https://repositorio.unal.edu.co/handle/unal/39339
- Postigo, Y., & López-Manjón, A. (2019). Images in biology: Are instructional criteria used in textbook image design? International Journal of Science Education, 41(2), 210–229. https://doi.org/https://doi.org/10.1080/09500693.2018.1548043
- Postigo, Y., & Pozo, J. I. (2004). On the road to graphicacy: The learning of graphical representation systems. Educational Psychology, 24(5), 623–644. https://doi.org/https://doi.org/10.1080/0144341042000262944
- Pozzer-Ardenghi, L., & Roth, W. M. (2005). Making sense of photographs. Science Education, 89(2), 219–241. https://doi.org/https://doi.org/10.1002/sce.20045
- Pun, J. K., & Cheung, K. K. C. (2021). Meaning making in collaborative practical work: A case study of multimodal challenges in a Year 10 chemistry classroom. Research in Science & Technological Education, 1–18. https://doi.org/https://doi.org/10.1080/02635143.2021.1895101
- Schnotz, W., & Bannert, M. (2003). Construction and interference in learning from multiple representation. Learning and Instruction, 13(2), 141–156. https://doi.org/https://doi.org/10.1016/S0959-4752(02)00017-8
- Schönborn, K. J., & Anderson, T. R. (2010). Bridging the educational research-teaching practice gap: Foundations for assessing and developing biochemistry students’ visual literacy. Biochemistry and Molecular Biology Education, 38(5), 347–354. https://doi.org/https://doi.org/10.1002/bmb.20436
- Sit, Y. L. (2020). Modelling students’ interpretation of diagrams of cell division. (Doctoral dissertation, The University of Hong Kong). https://hub.hku.hk/handle/10722/291142
- Slykhuis, D. A., Wiebe, E. N., & Annetta, L. A. (2005). Eye-tracking students’ attention to powerpoint photographs in a Science Education setting. Journal of Science Education and Technology, 14(5–6), 509–520. https://doi.org/https://doi.org/10.1007/s10956-005-0225-z
- Stieff, M., & DeSutter, D. (2021). Sketching, not representational competence, predicts improved science learning. Journal of Research in Science Teaching, 58(1), 128–156. https://doi.org/https://doi.org/10.1002/tea.21650
- Stylianidou, F. (2002). Analysis of science textbook pictures about energy and pupils’ readings of them. International Journal of Science Education, 24(3), 257–283. https://doi.org/https://doi.org/10.1080/09500690110078905
- Waldrip, B., Prain, V., & Carolan, J. (2010). Using multi-modal representations to improve learning in junior secondary science. Research in Science Education, 40(1), 65–80. https://doi.org/https://doi.org/10.1007/s11165-009-9157-6
- Wandersee, J. H., & Schussler, E. E. (1999). Preventing plant blindness. The American Biology Teacher, 61(2), 82–86. https://doi.org/https://doi.org/10.2307/4450624
- Warfa, A.-R. M., Roehrig, G. H., Schneider, J. L., & Nyachwaya, J. (2014). Role of teacher-initiated discourses in students’ development of representational fluency in chemistry: A case study. Journal of Chemical Education, 91(6), 784–792. https://doi.org/https://doi.org/10.1021/ed4005547
- Wilkinson, J. (1999). A quantitative analysis of physics textbooks for scientific literacy themes. Research in Science Education, 29(3), 385–399. https://doi.org/https://doi.org/10.1007/BF02461600