Ainsworth, S. (2006). DeFT: a conceptual framework for considering learning with multiple representations. Learning and Instruction, 16(3), 183–198.
Barak, M., & Dori, Y. J. (2011). Science education in primary schools: is an animation worth a thousand pictures? Journal of Science Education and Technology, 20(5), 608–620.
Barak, M., & Hussein-Farraj, R. (2012). Integrating model-based learning and animations for enhancing students’ understanding of proteins structure and function. Research in Science Education, 43(2), 619–636.
Berney, S., & Bétrancourt, M. (2016). Does animation enhance learning? A meta-analysis. Computers & Education, 101(2016), 150–167.
Bravo, M., Cervetti, G., Hiebert, E., & Pearson, P. (2008). From passive to active control of science vocabulary. Yearbook of the National Reading Conference, 56, 122–135.
Cheon, J., Chung, S., Crooks, S. M., Song, J., & Kim, J. (2014). An investigation of the effects of different types of activities during pauses in a segmented instructional animation. Journal of Educational Technology & Society, 17(2), 296–306.
Chu, Y.-C., & Reid, N. (2012). Genetics at school level: addressing the difficulties. Research in Science & Technological Education, 30(3), 285–309.
Clark, R. C., & Mayer, R. E. (2011). E-learning and the science of instruction: proven guidelines for consumers and designers of multimedia learning. New York: John Wiley & Sons.
Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159.
Duncan, R. G., & Reiser, B. J. (2007). Reasoning across ontologically distinct levels: students’ understandings of molecular genetics. Journal of Research in Science Teaching, 44(7), 938–959.
Elmesky, R. (2013). Building capacity in understanding foundational biology concepts: a K-12 learning progression in genetics informed by research on children’s thinking and learning. Research in Science Education, 43(3), 1155–1175. https://doi.org/10.1007/s11165-012-9286-1.
Furberg, A. (2009). Sociocultural aspects of prompting student reflection in web-based inquiry learning environments. Journal of Computer Assisted Learning, 25, 397–409.
Furberg, A., Kluge, A., & Ludvigsen, S. (2013). Student sense-making with science diagrams in a computer-based setting. International Journal of Computer-Supported Collaborative Learning, 8, 41–64.
Gericke, N. M., Hagberg, M., dos Santos, V. C., Joaquim, L. M., & El-Hani, C. N. (2014). Conceptual variation or incoherence? Textbook discourse on genes in six countries. Science & Education, 23(2), 381–416.
Haug, B. S., & Ødegaard, M. (2014). From words to concepts: focusing on word knowledge when teaching for conceptual understanding within an inquiry-based science setting. Research in Science Education, 44(5), 777–800.
Höffler, T. N., & Leutner, D. (2007). Instructional animation versus static pictures: a meta-analysis. Learning and Instruction, 17, 722–738.
Jordan, B., & Henderson, A. (1995). Interaction analysis: foundations and practice. The Journal of the Learning Sciences, 4(1), 39–103.
Jorde, D., Strømme, A., Sørborg, Ø., Erlien, W., & Mork, S. M. (2003). Virtual environments in science. Viten.no. Oslo: ITU.
Karlsson, G. (2010). Animation and grammar in science education: learners’ construal of animated educational software. International Journal of Computer-Supported Collaborative Learning, 5(2), 167–189.
Kress, G. (2013). What is mode? In C. Jewitt (Ed.), The Routledge handbook of multimodal analysis (pp. 60–75). London: Routledge.
Kühl, T., Scheiter, K., Gerjets, P., & Gemballa, S. (2011). Can differences in learning strategies explain the benefits of learning from static and dynamic visualizations? Computers & Education, 56(1), 176–187.
Lemke, J. L. (1990). Talking science. Language, learning, and values. Norwood: Ablex.
Lemke, J. (2000). Across the scales of time: artifacts, activities, and meanings in ecosocial systems. Mind, Culture, and Activity, 7(4), 273–290.
Lewis, J., & Kattman, U. (2004). Traits, genes particles and information: re-visiting students’ understanding of genetics. Internal Journal of Science Education, 26, 195–206.
Lewis, A., Peat, M., & Franklin, S. (2005). Understanding protein synthesis: an interactive card game discussion. Journal of Biological Education, 39(3), 125–130.
Linell, P. (1998). Approaching dialogue: talk, interaction and contexts in dialogical perspectives. Amsterdam: John Benjamins Publishing Company.
Lowe, R. K., & Boucheix, J.-M. (2008). Learning from animated diagrams: how are mental models built? In J. H. G. Stapleton & J. Lee (Eds.), Diagrammatic representation and inference (pp. 266–281). Berlin: Springer.
Marbach-Ad, G. (2001). Attempting to break the code in student comprehension of genetic concepts. Journal of Biological Education, 35(4), 183–189.
Marbach-Ad, G., Rotbain, Y., & Stavy, R. (2008). Using computer animation and illustration activities to improve high school students’ achievement in molecular genetics. Journal of Research in Science Teaching, 45(3), 273–292.
Maria, F., Santos, T. d., & Mortimer, E. F. (2003). How emotions shape the relationship between a chemistry teacher and her high school students. International Journal of Science Education, 25(9), 1095–1110.
Mayer, R. E. (2001). Multimedia learning. Cambridge: Cambridge University Press.
Mayer, R. E., Hegarty, M., Mayer, S., & Campbell, J. (2005). When static media promote active learning: annotated illustrations versus narrated animations in multimedia instruction. Journal of Experimental Psychology: Applied, 11(4), 256–265.
McElhaney, K. W., Chang, H.-Y., Chiu, J. L., & Linn, M. C. (2015). Evidence for effective uses of dynamic visualisations in science curriculum materials. Studies in Science Education, 51(1), 49–85.
Mercer, N. (2004). Sociocultural discourse analysis: analysing classroom talk as a social mode of thinking. Journal of Applied Linguistics, 1(2), 137–168.
Moreno, R. (2007). Optimising learning from animations by minimising cognitive load: cognitive and affective consequences of signaling and segmentation methods. Applied Cognitive Psychology, 21(6), 765–781.
Mork, S. M. (2006). ICT in science education. Exploring the digital learning materials at viten.no. Oslo: University of Oslo.
Mork, S. M. (2011). An interactive learning environment designed to increase the possibilities for learning and communicating about radioactivity. Interactive Learning Environments, 19(2), 163–177.
Mortimer, E. F., & Scott, P. H. (2003). Meaning making in secondary science classrooms. Philadelphia: Open University Press.
O'day, D. H. (2006). Animated cell biology: a quick and easy method for making effective, high-quality teaching animations. CBE-Life Sciences Education, 5(3), 255–263.
Ploetzner, R., & Lowe, R. (2012). A systematic characterisation of expository animations. Computers in Human Behavior, 28(3), 781–794.
Pozzer-Ardenghi, L., & Roth, W. M. (2005). Making sense of photographs. Science Education, 89(2), 219–241.
Rebetez, C., Bétrancourt, M., Sangin, M., & Dillenbourg, P. (2010). Learning from animation enabled by collaboration. Instructional Science, 38(5), 471–485.
Rotbain, Y., Marbach-Ad, G., & Stavy, R. (2006). Effect of bead and illustrations models on high school students’ achievement in molecular genetics. Journal of Research in Science Teaching, 43(5), 500–529.
Rundgren, C.-J., Hirsch, R., Chang Rundgren, S.-N., & Tibell, L. A. E. (2012). Students’ communicative resources in relation to their conceptual understanding – the role of non-conventionalized expressions in making sense of visualizations of protein function. Research in Science Education, 42, 891–913.
Ryoo, K., & Linn, M. C. (2012). Can dynamic visualizations improve middle school students’ understanding of energy in photosynthesis? Journal of Research in Science Teaching, 49(2), 218–243.
Sangin, M., Molinari, G., Dillenbourg, P., Rebetez, C., & Bétrancourt, M. (2006). Collaborative learning with animated pictures: the role of verbalizations. ICLS ‘06 Proceedings of the 7th International Conference on Learning Sciences (pp. 667-673).
Schnotz, W. (2005). An integrated model of text and picture comprehension. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 49–69). Cambridge: Cambridge University Press.
Scott, P., Mortimer, E., & Ametller, J. (2011). Pedagogical link-making: a fundamental aspect of teaching and learning scientific conceptual knowledge. Studies in Science Education, 47(1), 3–36.
Shea, N. A., & Duncan, R. G. (2013). From theory to data: the process of refining learning progressions. Journal of the Learning Sciences, 22(1), 7–32.
Spanjers, I. A., van Gog, T., & van Merriënboer, J. J. (2010). A theoretical analysis of how segmentation of dynamic visualizations optimizes students’ learning. Educational Psychology Review, 22(4), 411–423.
Spanjers, I. A., Wouters, P., van Gog, T., & van Merrienboer, J. J. (2011). An expertise reversal effect of segmentation in learning from animated worked-out examples. Computers in Human Behavior, 27(1), 46–52.
Strømme, T. A., & Furberg, A. (2015). Exploring teacher intervention in the intersection of digital resources, peer collaboration, and instructional design. Science Education. https://doi.org/10.1002/sce.21181.
Thörne, K., & Gericke, N. (2014). Teaching genetics in secondary classrooms: a linguistic analysis of teachers’ talk about proteins. Research in Science Education, 44(1), 81–108.
Treagust, D. F., & Tsui, C.-Y. (Eds.). (2013). Multiple representations in biological education (Vol. 7). New York: Springer.
Tytler, R., Prain, V., Hubber, P., & Waldrip, B. E. (2013). Constructing representations to learn in science. Rotterdam: Sense Publishers.
Vygotsky, L. S. (1978). Mind in society: the development of higher psychological processes. Cambridge: Harvard University Press.
Vygotsky, L. S. (1986). Thought and language. Cambridge: Harvard University Press.
Wertsch, J. V. (1991). Voices of the mind: a sociocultural approach to medicated action. Cambridge: Harvard University Press.
Wouters, P., Paas, F., & van Merriënboer, J. J. (2008). How to optimize learning from animated models: a review of guidelines based on cognitive load. Review of Educational Research, 78(3), 645–675.
Yarden, H., & Yarden, A. (2010). Learning using dynamic and static visualizations: students’ comprehension, prior knowledge and conceptual status of a biotechnological method. Research in Science Education, 40(3), 375–402.