Chemical Representations in the First-year Secondary School in the Light of the Next Generation Science Standards NGSS: An Evaluative Study of the Textbook, Inquiry Performances and Learning Outcomes.

Document Type : Original Article

Author

Curriculum and Methods of teaching, Faculty of Education, Alexandria University.

Abstract

The purpose of this study was to explore the reality of chemical representations in the first-year secondary school in the light of the next generation science standards NGSS; By analyzing the chemistry textbook, inquiry performances, and students’ chemical representations competency. A mixed methods was employed. The study sample included: three units (quantitative chemistry, solutions, acids and bases, and thermal chemistry) from the chemistry textbook, (321) students of the first-year secondary, and (13) chemistry teachers. The study tools included: the textbook’s chemical representations analysis sheet, the inquiry performances observation sheet, the chemical representations competency test, and interview forms. The results revealed deficiencies in the chemical representations standards in the textbook, also there was a decrease in the classrooms’ chemical representations inquiry performances, and a low level of chemical representations competency among the students. The study ended up with a proposed perspective for enhancing chemical representations learning. Several recommendations and proposals were also suggested with some related studies.

Keywords

Main Subjects


1.            Adams, K. & Luft, J. (2018). Beginning Chemistry Teachers’ Depictions of the Chemistry Content. International Journal of Environmental & Science Education, 13(1), 65-95. Article Number: ijese.2018.006.
2.            Ainsworth S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16(3), 183–198.  https://doi.org/10.1016/j.learninstruc.2006.03.001.
3.            Ainsworth S. (2008). The educational value of multiple representations when learning complex scientific concepts. In Gilbert J. K., Reiner M. and Nakhleh M. (eds.), Visualization: Theory and practice in science education, pp. 191–208. New York, NY: Springer.  https://doi.org/10.1007/978-1-4020-5267-5_9.
4.            Ainsworth, S. (2018). Multiple representations and multimedia learning. In Fischer F., Hmelo-Silver C. E., Goldman S. R. and Reimann P. (eds.), International handbook of the learning sciences, , pp. 96–105. New York: Routledge.
5.            Ainsworth S., & Newton L. (2014). Teaching and researching visual representations: shared vision or divided worlds? In Eilam B. and Gilbert J. K. (eds.), Science teachers’ use of visual representations, pp. 29–49. Dordrecht, The Netherlands: Springer International Publishing.
6.            Airey J., & Linder C., (2017). Social semiotics in university physics education. In Treagust D. F., Duit R. and Fischer H. E. (eds.), Multiple representations in physics education, pp. 95–122. Dordrecht, The Netherlands: Springer International Publishing.  https://doi.org/10.1007/978-3-319-58914-5_5.
7.            Akaygun, S., & Jones, L. L. (2013). Dynamic Visualizations: Tools for Understanding the Particulate Nature of Matter. In: Tsaparlis, G., Sevian, H. (eds) Concepts of Matter in Science Education. Innovations in Science Education and Technology, pp. 281–300, vol 19. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5914-5_13.
8.            Al-Balushi, S., & Al-Harthy, I. (2015). Students' mind wandering in macroscopic and submicroscopic textual narrations and its relationship with their reading comprehension. Chemistry Education Research and Practice,16(3), 680-688.  https://doi.org/10.1039/C5RP00052A.
9.            Ardac D., & Akaygun S., (2005), Using static and dynamic visuals to represent chemical change at molecular level. International Journal of Science Education, 27(11), 1269-1298.    https://doi.org/10.1080/09500690500102284.
10.         Aydin, S., Sinha, S., Izci, K., & Volkmann, M. (2014). Turkish, Indian, and American chemistry textbooks use of inscriptions to represent ‘Types of Chemical Reactions. Eurasia Journal of Mathematics, Science & Technology Education, 10 (5), 383-393.  https://doi.org/10.12973/eurasia.2014.1060a.
11.         Berg, A., Orraryd, D., Pettersson, A., J, & Hultén, M. (2019). Representational challenges in animated chemistry: self-generated animations as a means to encourage students’ reflections on submicro processes in laboratory exercises Chemistry Education Research and Practice, 20, 710–737. https://doi.org/10.1039/C8RP00288F.
12.         Bergqvist, A., & Rundgren, S. (2017). The influence of textbooks on teachers’ knowledge of chemical bonding representations relative to students’ difficulties understanding. Research in Science and Technological Education, 35(1):1-23. https://doi.org/10.1080/02635143.2017.1295934
13.         Bradley, J. (2014). The chemist’s triangle and a general systemic approach to teaching, learning and research in chemistry education. African Journal Chemical Education, 4(2), 64-79.
14.         Chandrasegaran, A., L., Treagust, D., F., & Mocerino, M. (2007). The development of a two-tier multiple-choice diagnostic instrument for evaluating secondary school students’ ability to describe and explain chemical reactions using multiple levels of representation. Chemistry Education Research and Practice, 8(3), 293–307. https://doi.org/10.1039/B7RP90006F.
15.         Chen, X., de Goes, L., Treagust, D. & Eilks, I. (2019). An Analysis of the Visual Representation of Redox Reactions in Secondary Chemistry Textbooks from Different Chinese Communities. Education Sciences, 9(1), 42.  https://doi.org/10.3390/educsci9010042. 
16.         Cheng, M., & Gilbert, J.K. (2009). Towards a Better Utilization of Diagrams in Research into the Use of Representative Levels in Chemical Education. In: Gilbert, J.K., Treagust, D. (eds) Multiple Representations in Chemical Education. Models and Modeling in Science Education, (pp. 55-73), vol 4. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-8872-8_4
17.         Chiappetta, E. L. (2008). Historical development of teaching science as inquiry. In J. Luft, R. Bell, & J. Gess- Newsome (Eds.), Science as inquiry in the secondary setting, (PP. 21-30). NSTA press.
18.         Chittleborough, G., & Treagust, D. (2008). Correct interpretation of chemical diagrams requires transforming from one level of representation to another. Research in Science Education, 38, 463–482. https://doi.org/10.1007/s11165-007-9059-4
19.         Cook, M. (2011). Teachers' Use of Visual Representations in the Science Classroom. Science Education International, 22(3), 175-184.
20.         Corradi D. M. J, Elen J., Schraepen B., & Clarebout G., (2014). Understanding Possibilities and Limitations of Abstract Chemical Representations for Achieving Conceptual Understanding. International Journal of Science Education, 36(5), 715–734, https://doi.org/10.1080/ 09500693.2013.824630.
21.         Dangur V., Avargil S., Peskin U., & Dori J. Y. (2014). Learning quantum chemistry via visual-conceptual approach: students’ bidirectional textual and visual understanding. Chemistry Education Research and Practice, 15, 297–310. https://doi.org/10.1039/C4RP00025K.
22.         Davidowitz B., & Chittleborough G. (2009). Linking the macroscopic and sub-microscopic levels: diagrams. In Gilbert J. K. and Treagust D. (ed.), Multiple representations in chemical education, pp. 169–191. Netherlands: Springer.
23.         De Moura, C., & Guerra, A. (2016). Cultural History of Science: A Possible Path for Discussing Scientific Practices in science Teaching? Revista Brasileira de Pesquisa em Educação em Ciências, 16(3), 749 – 771. Scribbr. https://periodicos.ufmg.br/index.php/rbpec/article/view/4587/2992
24.         Demirdogen B. (2017). Examination of chemical representations in Turkish high school chemistry textbooks. Journal of Baltic Science Education, 16(4), 472–499. https://doi.org/10.33225/jbse/17.16.472.
25.         Demirdöğen, B. (2017). Examination of chemical representations in Turkish high school chemistry textbooks. Journal of Baltic Science Education, 16(4), 472-499. https://doi.org/10.33225/jbse/17.16.472
26.         Devetak, I., & Glažar, S. A. (2010). The influence of 16-year-old students’ gender, mental abilities, and motivation on their reading and drawing sub-micro representations achievements. International Journal of Science Education, 32 (12), 1561-1593. https://doi.org/10.1080/09500690903150609.
27.         Devetak, I., Vogrinc, J., & Glažar, S. A. (2010). States of matter explanations in Slovenian textbooks for students aged 6 to 14. International Journal of Environmental & Science Education, 5 (2), 217-235.
28.         Dori, Y. J., & Hameiri M. (2003). Multidimensional analysis system for quantitative chemistry problems: Symbol, macro, micro, and process aspects. JRST, 40 (3), 278–302. https://doi.org/10.1002/tea.10077.
29.         Dori, Y.J., Dangur, V., Avargil, S., & Peskin, U. (2014). Assessing Advanced High School and Undergraduate Students' Thinking Skills: The Chemistry--From the Nanoscale to Microelectronics Module. Journal of Chemical Education, 91(9), 1306-1317.  https://doi.org/10.1021/ed500007s.
30.         Duis, J. (2011). Organic chemistry educators’ perspectives on fundamental concepts and misconceptions: An exploratory study. Journal of Chemical Education, 88(3), 346-350.  https://doi.org/10.1021/ed1007266.
31.         Dumon, A & Mzoughi-khadhraoui, I. (2014). Research and Practice Teaching chemical change modeling to Tunisian students: an “expanded chemistry triplet” for analyzing teachers’ discourse. Chemistry Education Research and Practice, 15(1),70–80. https://doi.org/10.1039/C3RP00126A.
32.         Duschl, R. A. (2019). Learning progressions: Framing and Designing Coherent Sequences for STEM Education. Disciplinary and Interdisciplinary Science Education Research, 1(4), 1-10. https://doi.org/10.1186/s43031-019- 0005-x.
33.         Eriksson U., Linder C., Airey J., & Redfors A., (2014). Who needs 3D when the universe is flat? Science Education, 98(3), 412–442. https://doi.org/10.1002/sce.21109.
34.         Evagorou, M., Erduran, S. & Mäntylä, T. (2015). The role of visual representations in scientific practices: from conceptual understanding and knowledge generation to ‘seeing’ how science works. International Journal of STEM Education, 2(11) . https://doi.org/10.1186/s40594-015-0024-x
35.         Furio-Mas C., Calatayud M. L., Guisasola J., & Furio-Gomez C., (2005), How are the concepts and theories of acid–base reactions presented? Chemistry in textbooks and as presented by teachers. International Journal of Science Education, 27(11), 1337–1358. https://doi.org/10.1080/09500690500102896.
36.         Gabel D. (1999). Improving teaching and learning through chemistry education research: a look to the future. Journal of Chemical Education, 76(4), 548–554.  https://doi.org/10.1021/ed076p548.
37.         Gilbert, J.K., & Treagust, D.F. (2009). Introduction: Macro, Submicro and Symbolic Representations and the Relationship Between Them: Key Models in Chemical Education. In: Gilbert, J.K., Treagust, D. (eds) Multiple Representations in Chemical Education. Models and Modeling in Science Education, vol 4. Springer, Dordrecht.  https://doi.org/10.1007/978-1-4020-8872-8_1.
38.         Gkitzia V., Salta K., & Tzougraki C. (2011). Development and application of suitable criteria for the evaluation of chemical representations in school textbooks. Chemistry Education Research and Practice, 12(1), 5–14. https://doi.org/10.1039/C1RP90003J.
39.         Gkitzia, L, Salta, K., & Tzougraki, C. (2019). Students’ competence in translating between different types of chemical representations. Chemistry Education Research and Practice, 21(1), 307-330. https://doi.org/10.1039/C8RP00301G.
40.         Gulacar, O., Eilk, I., & Bowman, C. (2014). Differences in General Cognitive Abilities and Domain-Specific Skills of Higher- and Lower-Achieving Students in Stoichiometry. Journal of Chemical Education, 91(7), 961-968. https://doi.org/ 10.1021/ed400894b
41.         Hand, B., Gunel, M., & Ulu, C. (2009). Sequencing embedded multimodal representations in a writing to learn approach to the teaching of electricity. Journal of Research in Science Teaching, 46, 225-247.  https://doi.org/10.1002/tea.20282.
42.         Harza, A, Wiji, W., & Mulyani, S. (2021). Potency to overcome misconceptions by using multiple representations on the concept of chemical equilibrium. Journal of Physics: Conference Series, 1806  012197. 
43.         Hein, S. M. (2012). Positive Impacts Using POGIL in Organic Chemistry. Journal of Chemical Education, 89 (7), 860-864. https://doi.org/10.1021/ed100217v.
44.         Herga, N., R., Čagran, B., & Dinevski, D. (2016). Virtual Laboratory in the Role of Dynamic Visualisation for Better Understanding of Chemistry in Primary School. Eurasia Journal of Mathematics, Science and Technology Education, 12(3), 593-608.  https://doi.org/10.12973/eurasia.2016.1224a.
45.         Herga, N., R., Glažar, S. & Dinevski, D. (2015). Dynamic visualization in the virtual laboratory enhances the fundamental understanding of chemical  concepts. Journal of Baltic Science Education, 14(3):351-365. https://doi.org/10.33225/jbse/15.14.351
46.         Hilton A., & Nichols K., (2011), Representational classroom practices that contribute to students’ conceptual and representational understanding of chemical bonding. International Journal of Science Education, 33(11), 2215–2246. https://doi.org/10.1080/09500693.2010.543438.
47.         Hrast, S., & Savec, V. (2017). The Integration of Submicroscopic Representations Used in Chemistry Textbook Sets into Curriculum Topics. Acta Chimica Slovenica, 64, 959-967. https://doi.org/10.17344/acsi.2017.3657.
48.         Hubber, P., Tytler, R., & Haslam, F. (2010). Teaching and Learning about Force with a Representational Focus: Pedagogy and Teacher Change. Research in Science Education, 40, 5-28. https://doi.org/10.1007/s11165-009-9154-9.
49.         Irez, S. (2009). Nature of science as depicted in Turkish biology textbooks. Science Education, 93(3), 422– 447.  https://doi.org/10.1002/sce.20305.
50.         Jaber, L. Z. & BouJaoude S. (2012). A macro–micro–symbolic teaching to promote relational understanding of chemical reactions. International Journal of Science education, 34(7), 973–998. https://doi.org/10.1080/09500693.2011.569959.
51.         Jensen, W. (1998). "Does chemistry have a logical structure? Journal of Chemical Education, 75(6), 679-687.  https://doi.org/10.1021/ed075p679.
52.         Jiménez-Aleixandre, M., & Crujeiras, B. (2017). Epistemic practices and scientific practices in science education. In K. Taber, & B. Akpan (Eds.), Science education: an international Course, PP. 69-80.  Companion Sense publishers. Scribbr. https://brill.com/view/book/edcoll/9789463007498/BP000006.xml
53.         Johnstone, A. H. (1991). Why is science difficult to learn? Things are seldom what they seem. Journal of Computer Assisted Learning, 7(2), 75–83.  https://doi.org/10.1111/j.1365-2729.1991.tb00230.x.
54.         Johnstone, A. H. (1993). The development of chemistry teaching: a changing response to changing demand, Journal of Chemical Education, 70(9), 701–705.  https://doi.org/10.1021/ed070p701.
55.         Johnstone, A. H. (2000). Teaching of chemistry: Logical or psychological? Chemistry Education Research and Practice, 1(1), 9–15.  https://doi.org/10.1039/A9RP90001B.
56.         Kapici H. & Acikalin-Savasci F. (2015). Examination of visuals about the particulate nature of matter in Turkish middle school science textbooks. Chemistry Education Research and Practice, 16, 518–536. https://doi.org/10.1039/C5RP00032G.
57.         Kelly, G. J. (2008). Inquiry, Activity, and Epistemic Practice. In R. Duschl & R. Grandy (Eds.) Teaching Scientific Inquiry: Recommendations for Research and Implementation (pp. 99-117; 288-291). Rotterdam: Sense Publishers.
58.         Kelly, R. M., Akaygun, S., Hansen, S. J. R., & Villalta-Cerdas, A. (2017). The effect that comparing molecular animations of varying accuracy has on students’ submicroscopic explanations. Chemistry Education Research and Practice, 18, 582-600. https://doi.org/10.1039/C6RP00240D.
59.         Kelly, R., Barrera, J., & Mohamed, S. (2010). An analysis of undergraduate general chemistry students’ misconceptions of the submicroscopic level of precipitation reactions. Journal of Chemical Education, 87(1), 113 – 118. https://doi.org/10.1021/ed800011a
60.         Kern, A. L., Wood, N. B., Roehrig, G. H., & Nyachwaya, J. (2010). A qualitative report of the ways high school chemistry students attempt to represent a chemical reaction at the atomic/molecular level. Chemistry Education Research and Practice, 11, 165-172.  https://doi.org/10.1039/C005465H.
61.         Khaddoor, R., Al-Amoush, S. & Eilks, I. (2017). A comparative analysis of the intended curriculum and its presentation in 10th grade chemistry textbooks from seven Arabic countries. Chemistry Education Research and Practice, 18, 375–385. https://doi.org/10.1039/C6RP00186F.
62.         Khine, M. S. (2013). Analysis of science textbooks for instructional effectiveness. In M. S. Khine (Ed.), Critical analysis of science textbooks (pp. 303-310). Netherlands: Springer.
63.         Kozma, R., & Russell, J. (2005). Students becoming chemists: Developing representational competence. In J. Gilbert (Ed.), Visualization in science education. Models and Modeling in Science Education (pp. 121–145), vol 1. Springer, Dordrecht. https://doi.org/10.1007/1-4020-3613-2_8.
64.         Lansangan, R, V., Orleans, A, V., & Camacho, V, M. (2018). Assessing Conceptual Understanding in Chemistry Using Representation. Journal of Computational and Theoretical Nanoscience, 24(11), 7930-7934. https://doi.org/10.1166/asl.2018.12459.
65.         Lee, V.R. (2010). Adaptations and continuities in the use and design of visual representations in US middle school science textbooks. International Journal of Science Education, 32, 1099–1126.  https://doi.org/10.1080/09500690903253916.
66.         Lewthwaite, B., & Wiebe, R. (2010). Fostering teacher development to a tetrahedral orientation in the teaching of chemistry. Research in Science Education, 41(5):667-689. https://doi.org/10.1007/s11165-010-9185-2.
67.         Li, W., & Arshad, M. (2014). Chemistry Teacher’s Questions at Multiple Representation Levels in Inquiry-Based Chemistry Lessons. Sains Humanika, 1(1), 31–36.  https://doi.org/10.11113/sh.v1n1.287
68.         Lin, Y., Son, J., & Rudd, J. (2016). Asymmetric translation between multiple representations in chemistry. International Journal of Science Education, 38(4), 644-662.  https://doi.org/10.1080/09500693.2016.1144945
69.         Liu, Y., & Taber, K. S. (2016). Analysing symbolic expressions in secondary school chemistry: their functions and implications for pedagogy. Chemistry Education Research and Practice, 17(3), 439-451. https://doi.org/10.1039/C6RP00013D
70.         Luviani, S, Mulyani, S & Widhiyanti, T. (2021). A review of three levels of chemical representation until 2020. Journal of Physics: Conference Series, 1806 012206. https://doi.org/10.1088/1742-6596/1806/1/012206.
71.         Mathewson, J. H., (2005), The visual core of science: definitions and applications to education, International Journal of Science Education, 27(5), 529-548.  https://doi.org/10.1080/09500690500060417.
72.         Mayer, R. (2002). Cognitive theory and the design of multimedia instruction: an example of the two‐way street between cognition and instruction. New Directions for Teaching and Learning, (89), 55-71.  https://doi.org/10.1002/tl.47.
73.         McDermott, M.A., & Hand, B. (2013). The impact of embedding multiple modes of representation within writing tasks on high school students’ chemistry understanding. Instructional Science, 41, 217–246. https://doi.org/10.1007/s11251-012-9225-6
74.         McTigue, E., & Flowers, A. (2011). Science visual literacy: Learners' perceptions and knowledge of diagrams. The Reading Teacher, 64(8), 578-589. https://doi.org/10.2307/41203457.
75.         Meijer, M. R., Bulte, A. M. W., & Pilot, A. (2008). Structure–property relations between macro and micro representations: Relevant meso-levels in authentic tasks. In J. K. Gilbert & D. Treagust (Eds.), Multiple representations in chemical education (pp. 195–213). the Netherlands: Springer.
76.         Melville, W., & A. Bartley. (2010). Mentoring and Community: Inquiry as Stance and Science as Inquiry. International Journal of Science Education, 32(6), 807– 828. https://doi.org/10.1080/09500690902914641.
77.         Milenkovic, D. D., Segedinac, M. D., & Hrin T. N. (2014). Increasing high school students’ chemistry performance and reducing cognitive load through an instructional strategy based on the interaction of multiple levels of knowledge representation. Journal of Chemical Education, 91(9), 1409–1416.  https://doi.org/10.1021/ed400805p.
78.         Miles, M., & Huberman, A. (1994). Qualitative data analysis: An expanded sourcebook. (2nd ed.). Thousand Oaks, CA: Sage Publications.
79.         Minner, D. D., Levy, A. J., & J. Century. (2010). Inquiry-based Science Instruction-What Is It and Does it Matter? Results from a Research Synthesis Years 1984 to 2002. Journal of Research Science Teaching, 47(4), 474–496.  https://doi.org/10.1002/tea.20347.
80.         Mocerino, M, Chandrasegaran, A., & Treagust, D. (2009). Emphasizing multiple levels of representation to enhance students' understandings of the changes occuring during chemical reactions. Journal of Chemical Education, 86(12), 1433-1436.  https://doi.org/10.1021/ed086p1433.
81.         Moje, B. (2008). Foregrounding the disciplines in secondary literacy teaching and learning: A call for change. Journal of Adolescent & Adult Literacy, 52(2), 96-107. https://doi.org/10.1598/JAAL.52.2.1
82.         Naah B. M. & Sanger M. J. (2012). Student misconceptions in writing balanced equations for dissolving ionic compounds in water. Chemistry Education Research and Practice, 13, 186–194. https://doi.org/10.1039/C2RP00015F.
83.         Nakiboğlu, C., & Yildirir, H. E. (2011). Analysis of Turkish high school chemistry textbooks and teacher-generated questions about gas laws. International Journal of Science and Mathematics Education, 9 (5), 1047-1071.  https://doi.org/10.1007/s10763-010-9231-6.
84.         National Research Council (NRC). (1996). National Science Education Standards. Washington, DC: The National Academies Press. https://doi.org/10.17226/4962.
85.         National Research Council (NRC). (2012). A framework for k-12 science education: Practices, Crosscutting Concepts, and Core Ideas. Washington, DC: The National Academies Press. https://doi.org/10.17226/13165.
86.         National Research Council (NRC). (2013). Next Generation Science Standards: For States, By States. Washington, DC: The National Academies Press. https://doi.org/10.17226/18290.
87.         National Science Teachers Association (NSTA). (2011). Quality science education and 21st - century skills. Scribbr. https://static.nsta.org/pdfs/PositionStatement_21stCentury.pdf.
88.         National Science Teachers Association (NSTA). 2016. NSTA Position Statement: The National Science Teachers Association. Scribbr. https://www.nsta.org/nstas-official-positions/next-generation-science-standards
89.         Nichols, K., Stevenson, M., Hedberg, J., & Gillies, R. (2015). Primary teachers’ representational practices: from competency to fluency. Cambridge Journal of Education, 46(4), 509-531. https://doi.org/10.1080/0305764X.2015.1068741.
90.         Nitz, S., Prechtl, H., & Nerdel, C. (2014). Survey of classroom use of representations: development, field test and multilevel analysis. Learning Environ Res, 17, 401–422. https://doi.org/10.1007/s10984-014-9166-x.
91.         Nyachwaya, J. M., & Wood N. B. (2014). Evaluation of chemical representations in physical chemistry textbooks. Chemistry Education Research and Practice. 15(4), 720–728. https://doi.org/10.1039/C4RP00113C.
92.         Nyachwaya J. M., Mohamed A., Roehrig G. H., Wood N. B., Kern A. L., & Schneider J. L., (2011). The development of an open-ended drawing tool: An alternative diagnostic tool for assessing students’ understanding of the particulate nature of matter. Chemistry Education Research and Practice,12, 121–132. https://doi.org/10.1039/C1RP90017J.
93.         Nyachwaya, J., & Gillaspie, M. (2016). Features of representations in general chemistry textbooks: a peek through the lens of the cognitive load theory. Chemistry Education Research and Practice, 17(1), 58-71. https://doi.org/10.1039/C5RP00140D.
94.         Opera, J. A., & Oguzor, N. (2011). Inquiry Instructional Method and the School Science Curriculum. Current Research Journal of Social Science, 3(3), 188–198.
95.         Osborne, J. (2014). Teaching scientific practices: Meeting the challenge of change. Journal of Science Teacher Education, 25(2), 177–196.  https://doi.org/10.1007/s10972-014-9384-1
96.         Papageorgiou G., Amariotakis V., & Spiliotopoulou V. (2017). Visual representations of microcosm in textbooks of chemistry: constructing a systemic network for their main conceptual framework. Chemistry Education Research and Practice,18(4), 559-571. https://doi.org/10.1039/ C6RP00253F.
97.         Patron E., Wikman S., Edfors I., Johansson-Cederblad B., & Linder C. (2017). Teachers’ reasoning: classroom visual representational practices in the context of introductory chemical bonding. Science Education, 101(6), 887–906. https://doi.org/10.1002/ sce.21298.
98.         Pavlin, J., Glažar, S. A., Slapničar, M., & Devetak, I. (2019). The impact of students’ educational background, interest in learning, formal reasoning and visualisation abilities on gas context-based exercises achievements with submicro-animations. Chemistry Education Research and Practice, 20(3), 633-649. https://doi.org/10.1039/C8RP00189H.
99.         Philipp, S., Johnson, D., & Yezierski, E. (2014). Development of a protocol to evaluate the use of representations in secondary chemistry instruction. Chemistry Education Research and Practice, 15, 777-786. https://doi.org/10.1039/c4rp00098f.
100.       Prain V., & Waldrip B., (2006), An Exploratory Study of Teachers’ and Students’ Use of Multi-modal Representations of Concepts in Primary Science, International Journal of Science Education, 28(15), 1843–1866. https://doi.org/10.1080/09500690600718294.
101.       Prain, V., & Tytler, R. (2012). Learning Through Constructing Representations in Science: A framework of representational construction affordances. International Journal of Science Education, 34(17), 2751-2773.  https://doi.org/10.1080/09500693.2011.626462.
102.       Prain, V., Tytler, R., & Peterson, S. (2009). Multiple representation in learning about evaporation. International Journal of Science Education, 31(6), 787–808. https://doi.org/10.1080/09500690701824249.
103.       Rakhmawan, A., Firman, H., Redjeki, S., & Mulyani, S. (2019). Achievement profile of high school students on chemical dynamics material at three levels of representation. Journal of Physics: Conference Series,1157 042027. https://doi.org/10.1088/1742-6596/1157/4/042027.
104.       Ramnarain U., & Joseph A., (2012). Learning difficulties experienced by grade 12 South African students in the chemical representation of phenomena. Chemistry Education Research and Practice, 13, 462–470.  https://doi.org/10.1039/C2RP20071F.
105.       Rau M. A., (2017), Conditions for the effectiveness of multiple visual representations in enhancing STEM learning. Educational Psychology Review, 29, 727–761. https://doi.org/10.1007/s10648-016-9365-3.
106.       Rees, S.W., Kind, V., & Newton, D. (2021). The development of chemical language usage by “non-traditional” students: the interlanguage analogy. Research in science education, 51 (2). pp. 419-438. https://doi.org/10.1007/s11165-018-9801-0.
107.       Rodić,D, Rončević, T., & Segedinac, M. (2018). The Accuracy of Macro–Submicro–Symbolic Language of Future Chemistry Teachers. Acta Chimica Slovenica, 65(2), 394–400. https://doi.org/10.17344/acsi.2017.4139. doi.org/10.17344/acsi.2017.4139.
108.       Roth, W. M., Bowen, G. M., & McGinn, M. K. (1999). Differences in graph‐related practices between high school biology textbooks and scientific ecology journals. Journal of research in science teaching, 36(9), 977-1019.  https://doi.org/10.1002/(SICI)1098-2736(199911)36:93.0.CO;2-V.
109.       Ruivenkamp, M, & Rip, A. (2010). Visualizing the invisible nanoscale study: visualization practices in nanotechnology community of practice. Science & Technology Studies, 23(1), 3–36.  https://doi.org/10.23987/sts.55255.
110.       Russ, R. S. (2014). Epistemology of science vs. epistemology for science. Science Education, 98(3), 388–396.  https://doi.org/10.1002/sce.21106
111.       Sana, S , Adhikary, C., & Chattopadhyay, K. (2018). Evolutionary Paradigm Shift in the Instructional Strategies of Chemical Concepts. Bhatter College Journal of Multidisciplinary Studies. 8(1). Scribbr. www.bcjms.bhattercollege.ac.in/v8/n1/v8n1sc06.pdf
112.       Sanchez, J. (2017). Integrated Macro-Micro-Symbolic Approach in Teaching Secondary Chemistry. KIMIKA, 28(2), 22-29. https://doi.org/10.26534/kimika.v28i2.22-29.
113.       Sande, M. E. (2010). Pedagogical content knowledge and the gas laws: A multiple case study. Doctor of Philosophy, University of Minnesota. Retrieved from the University of Minnesota Digital Conservancy. Scribbr. https://hdl.handle.net/11299/95498.
114.       Santos, V., & Arroio, A. (2016). The representational levels: Influences and contributions to research in chemical education. Journal of Turkish Science Education,13(1), 3-18. https://doi.org/10.12973/tused.10153a.
115.       Savec, V., Hrast, S., Devetak, I., & Torkar, G. (2016). Beyond the use of an Explanatory Key Accompanying Submicroscopic Representations. Acta Chimica Slovenica, 63, 864–873. https://doi.org/10.17344/acsi.2016.2835.
116.       Scalco, K., Talanquer, V., Kiill, K., & Cordeiro, M. (2018). Making Sense of Phenomena from Sequential Images versus Illustrated Text. Journal of Chemical Education, 95(3), 347-354.  https://doi.org/10.1021/acs.jchemed.7b00716.
117.       Schwonke, R., Berthold, K., & Renkl, A. (2009). How multiple external representations are used and how they can be made more useful. Applied Cognitive Psychology, 23 (9), 1227-1243. https://doi.org/10.1002/acp.1526.
118.       Seo, K. (2016). Representation as a language of scientific practice: exploring students’ views on the use of representation and the linkage to understanding of scientific models. (PhD dissertation), University of Iowa. ProQuest Number: 10188641. https://doi.org/10.17077/etd.38hclrvd.
119.       Seufert, T., & Brünken, R. (2006). Cognitive Load and the Format of Instructional Aids for Coherence Formation. Applied Cognitive Psychology, 20(3), 321–331.  https://doi.org/10.1002/acp.1248
120.       Shehab S. S., & BouJaoude S. (2017). Analysis of the chemical representations in secondary Lebanese chemistry textbooks. International Journal of Science and Mathematics Education, 15(5), 797–816. https://doi.org/10.1007/s10763-016-9720-3.
121.       Sim J. H., & Daniel, E. G. S. (2014). Representational competence in chemistry: a comparison between students with different levels of understanding of basic chemical concepts and chemical representations. Cogent Education, 1(1), 991180. https://doi.org/10.1080/2331186X.2014.991180.
122.       Slapničar, M, Tompa, V., Glažar, S., A., & Devetak, I. (2018). Fourteen-year-old students’ misconceptions regarding the sub-micro and symbolic levels of specific chemical concepts. Journal of Baltic Science Education, 17(4), 620-632. https://doi.org/10.33225/jbse/18.17.620.
123.       Slapničar, M., Devetak, I., Glažar, S. A., & Pavlin, J. (2017). Identification of the understanding of the states of matter of water and air among Slovenian students aged 12, 14 and 16 years through solving authentic tasks. Journal of Baltic Science Education, 16 (3), 308-323. https://doi.org/10.33225/jbse/17.16.308.
124.       Souza A. F. D. K., & Porto A. (2012). Chemistry and Chemical Education through Text and Image: Analysis of Twentieth Century Textbooks Used in Brazilian Context. Science and Education, 21(5), 705–727. https://doi.org/10.1007/s11191-012-9442-z
125.       Stains M., & Talanquer V. (2007). Classification of chemical substances using particulate representations of matter: An analysis of student thinking. International Journal of Science Education, 29(5), 643–661.  https://doi.org/10.1080/09500690600931129.
126.       Stanford, C. (2016). Using Discourse Analysis to Investigate the Influences of Instructor Facilitation and Course Materials on Student Argumentation and Conceptual Understanding in Pogil Physical Chemistry Classrooms. The University of Iowa. PhD dissertation. ProQuest Number: 10189603.
127.       Stieff M., Hegarty M., & Deslongchamps G. (2011). Identifying representational competence with multi-representational displays. Cognition and Instruction, 29(1), 123–145.  https://doi.org/10.1080/07370008.2010.507318.
128.       Stieff, M., & McCombs, M. (2006). Increasing representational fluency with visualization tools. In S. Barab, K. E. Hay & D. T. Hickey (Eds.), Proceedings of the Seventh International Conference of the Learning Sciences (ICLS) (Vol. 1, pp. 730–736). Mahwah, NJ: Erlbaum.
129.       Stieff, M., Ryu, M., & Yip, J. (2013). Speaking across levels – generating and addressing levels confusion in discourse. Chemistry Education Research and Practice, 14, 376-389. https://doi.org/10.1039/c3rp20158a.
130.       Stojanovska, M, Petruševski, V., & Šoptrajanov, B. (2017). STUDY OF THE USE OF THE THREE LEVELS OF THINKING AND REPRESENTATION. Contributions, Section of Natural, Mathematical and Biotechnical Sciences, 35(1).  https://doi.org/10.20903/csnmbs.masa.2014.35.1.52.
131.       Stroupe, D. (2015). Describing science practice in learning settings. Science Education, 99(6), 1033-1040. https://doi.org/10.1002/sce.21191.
132.       Sujak, K., & Daniel, E. (2017). Understanding of Macroscopic, Microscopic and Symbolic Representations among Form Four Students in Solving Stoichiometric Problems. Malaysian Online Journal of Educational Sciences, 5(3), 83-96.
133.       Sunyono, S., & Sudjarwo, S. (2018). Mental models of atomic structure concepts of 11th grade chemistry students. Asia-Pacific Forum on Science Learning and Teaching, 19(1), Article 9.
134.       Taber K. S. (2009). Learning at the symbolic level. in J.K. Gilbert and David F. Treagust (eds.), Multiple Representations in Chemical Education, pp. 75–108. Dordrecht: Springer.
135.       Taber, K. S. (2013). Revisiting the chemistry triplet: drawing upon the nature of chemical knowledge and the psychology of learning to inform chemistry education. Chemistry Education Research and Practice, 14 (2), 156-168. https://doi.org/10.1039/C3RP00012E
136.       Taber, K. S. (2018). Representations and visualisation in teaching and learning chemistry. Chemistry Education Research and Practice, 19, 405-409. https://doi.org/10.1039/C8RP90003E.
137.       Talanquer, V. (2011). Macro, submicro, and symbolic: The many faces of the chemistry triplet. International Journal of Science Education 33(2), 179-195. https://doi.org/10.1080/09500690903386435.
138.       Talanquer, V. (2021). Multifaceted Chemical Thinking: A Core Competence. Journal of Chemical Education, 98, 11, 3450–3456.  https://doi.org/10.1021/acs.jchemed.1c00785.
139.       Tasker, R. (2014). Research into Practice: Visualising the Molecular World for a Deep Understanding of Chemistry. Teaching Science, 60 (2(, 6-27. 
140.       Taskin, V., Bernholt, S., & Parchmann, I. (2017). Student teachers’ knowledge about chemical representations. International Journal of Science and Mathematics Education, 15(1), 39-55. https://doi.org/10.1007/s10763-015-9672-z.
141.       Tima, M.T., & Sutrisno, H. (2018). Effect of Using Problem-Solving Model Based on Multiple Representations on the Students' Cognitive Achievement: Representations of Chemical Equilibrium. Asia-Pacific Forum on Science Learning and Teaching, 19(1).
142.       Turkoguz, S. (2012). Learn to teach chemistry using visual media tools. Chemical Education Research and Practice, 13, 401-409. https://doi.org/10.1039/C2RP20046E.
143.       Tytler, R., Prain, V., & Peterson, S. (2007). Representational issues in students learning about evaporation. Research in Science Education, 37(3), 313-331. https://doi.org/10.1007/s11165-006-9028-3.
144.       Upahi J. E., & Jimoh M. A. (2016). Classification of end-of chapter questions in senior school chemistry textbooks used in Nigeria. European Journal of Science and Mathematics Education, 4(1), 90–102. https://doi.org/10.30935/scimath/9456.
145.       Upahi, J., & Ramnarain, U. (2019). Representations of chemical phenomena in secondary school chemistry textbooks. Chemistry Education Research and Practice, 20(1), 146-159. https://doi.org/10.1039/C8RP00191J.
146.       Wood L. (2013). Representing Chemistry: How instructional use of symbolic, microscopic and macroscopic modes influences student conceptual understanding in Chemistry. PhD dissertation. Arizona: Arizona State University. ERIC Number: ED559486.
147.       Wu H.-K., & Puntambekar S. (2012). Pedagogical Affordances of Multiple External Representations in Scientific Processes, Journal of Science Education and Technology, 21(6), 754–767. https://doi.org/10.1007/s10956- 011-9363-7.
148.       Yore, L. D., & Hand, B. (2010). Epilogue: Plotting a research agenda for multiple representations, multiple modality, and multimodal representational competency. Research in Science Education, 40(1), 93-101. https://doi.org/10.1007/s11165-009-9160-y.
149.       Yore, L., Pimm, D., & Tuan, H. (2007). The literacy component of mathematical and scientific literacy. American Educational Research Journal, 5 (4), pp. 559-589. https://doi.org/10.1007/s10763-007-9089-4.
150.       Yuanita, L., & Ibrahim, M. (2015). Mental Models Of Students On Stoichiometry Concept In Learning By Method Based On Multiple Representation. The Online Journal of New Horizons in Education, 5(2), 30-45.