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Journal of Science Education and Technology

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09.08.2022

Building an NGSS-aligned Middle School Summer Camp for an Observational Investigation with a Virtual Field Environment

verfasst von: Nancy A. Price, Jennifer G. Wells, Frank D. Granshaw

Erschienen in: Journal of Science Education and Technology | Ausgabe 6/2022

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Abstract

A learning experience designed for the Next Generation Science Standards (NGSS) should integrate the Science & Engineering Practices and Crosscutting Concepts (CCCs) with science content. Such three-dimensional learning engages students in the epistemic components of the scientific process. Whether the Practices and CCCs are used in epistemically meaningful ways to build more expert-like understanding and behaviors is context dependent. The NGSS defines learning progressions for the Practices and CCCs, but they do not provide the detail needed to build activities within the grade bands. It is also up to curriculum developers to decide how to incorporate the Practices and CCCs using technology in domain-specific inquiry contexts. We document the development and evaluation of the week-long middle school summer Camp NANO, where campers participated in an observational investigation of a stream habitat from the macro-to-nano scale using the scanning electron microscope (SEM) as well as produced an interactive Virtual Field Environment (VFE) communication of the stream environment. This pilot is an example of a domain-specific authentic scientific inquiry experience built around three-dimensional learning as guided by the novice-to-expert literature to meet the NGSS middle school learning targets of the selected Practices and CCCs. We found that it was possible to build an activity plan that authentically incorporated and integrated the Practices and CCCs with the SEM and VFE, and that the involvement with the SEM and VFE in association with the observational investigation facilitated expert-like thinking and behaviors towards the selected Practices and CCCs.

Vorheriger Artikel Thinking Thru Making: Mapping Computational Thinking Practices onto Scientific Reasoning

Nächster Artikel Effects of a BCI-Based AR Inquiring Tool on Primary Students’ Science Learning: A Quasi-Experimental Field Study

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Alonzo, A. C., & Gotwals, A. W. (2012). Learning progressions in science: Current challenges and future directions. SensePublishers.CrossRef

Assaraf, O. B. Z., & Orion, N. (2005). Development of system thinking skills in the context of earth system education. Journal of Research in Science Teaching, 42, 518–560. https://doi.org/10.1002/tea.20061CrossRef

Bazeley, P. (2009). Analysing qualitative data: More than ‘identifying themes.’ Malaysian Journal of Qualitative Research, 2, 6–22.

Berland, L. K., Schwarz, C. V., Krist, C., Kenyon, L., Lo, A. S., & Reiser, B. J. (2015). Epistemologies in practice: Making scientific practices meaningful for students. Journal of Research in Science Teaching., 53, 1082–1112. https://doi.org/10.1002/tea.21257CrossRef

Bernstein, J., & Kemp, K. (2020). The role of spatial science in environmental case studies: A special collection from the University of Southern California. Case Studies in the Environment, 4(1), 1–5. https://doi.org/10.1525/cse.2019.sc.948362CrossRef

Cady, S. L., Blok, M., Grosse, K., & Wells, J. (2015). The Evolution of Project NANO: A Program that Enables Students to Explore in Real Time Several Crosscutting Concepts of the Next Generation Science Standards. Microscopy and Microanalysis, 21, 479–480. https://doi.org/10.1017/S1431927615003190CrossRef

Coffey, T., Zsuppan, G., & Corbin, R. (2015). Exploring nanoscience and scanning electron microscopy in K–12 classrooms. Microscopy Today, 23(1), 44–47. https://doi.org/10.1017/S1551929514001321CrossRef

Corcoran, T., Mosher, F. A., & Rogat, A. (2009). Learning progressions in science: An evidence-based approach to reform. CPRE Research Reports. https://doi.org/10.12698/cpre.2009.rr63CrossRef

Crujeiras-Pérez, B., & Jiménez-Aleixandre, M. P. (2017). High school students’ engagement in planning investigations: Findings from a longitudinal study in Spain. Chemistry Education Research and Practice, 18, 99–112. https://doi.org/10.1039/C6RP00185HCrossRef

Dalgarno, B., & Lee, M. J. (2010). What are the learning affordances of 3-D virtual environments? British Journal of Educational Technology, 41(1), 10–32. https://doi.org/10.1111/j.1467-8535.2009.01038.xCrossRef

Dickes, A. C., Kamarainen, A., Metcalf, S. J., Gün-Yildiz, S., Brennan, K., Grotzer, T., & Dede, C. (2019). Scaffolding ecosystems science practice by blending immersive environments and computational modeling. British Journal of Educational Technology, 50(5), 2181–2202. https://doi.org/10.1111/bjet.12806CrossRef

diSessa, A. A. (2004). Metarepresentation: Native competence and targets for instruction. Cognition and Instruction, 22, 293–331. https://doi.org/10.1207/s1532690xci2203_2CrossRef

Duin, R. P., & Pękalska, E. (2007). The science of pattern recognition. Achievements and perspectives. In Duch W. & Mańdziuk J. (Eds.) Challenges for Computational Intelligence, Vol 63. (pp. 221–259). Berlin Heidelberg:Springer. https://doi.org/10.1007/978-3-540-71984-7_10

Duncan, R. G., & Rivet, A. E. (2013). Science learning progressions. Science, 339(6118), 396–397. https://doi.org/10.1126/science.1228692CrossRef

Duschl, R. (2008). Science education in three-part harmony: Balancing conceptual, epistemic, and social learning goals. Review of Research in Education, 32, 268–291. https://doi.org/10.3102/0091732X07309371CrossRef

Duschl, R. A. (2019). Learning progressions: Framing and designing coherent sequences for STEM education. Disciplinary and Interdisciplinary Science Education Research, 1(1), 1–10. https://doi.org/10.1186/s43031-019-0005-xCrossRef

Duschl, R. A., & Bybee, R. W. (2014). Planning and carrying out investigations: An entry to learning and to teacher professional development around NGSS science and engineering practices. International Journal of STEM Education, 1, 1–9. https://doi.org/10.1186/s40594-014-0012-6CrossRef

Duschl, R., Maeng, S., & Sezen, A. (2011). Learning progressions and teaching sequences: A review and analysis. Studies in Science Education, 47(2), 123–182. https://doi.org/10.1080/03057267.2011.604476CrossRef

Erduran, S., & Dagher, Z. (2014). Reconceptualizing the nature of science for science education. Springer, Netherlands.CrossRef

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(1), 1–13. https://doi.org/10.1186/s40594-015-0024-xCrossRef

Farris, A. V., Dickes, A. C., & Sengupta, P. (2019). Learning to interpret measurement and motion in fourth grade computational modeling. Science & Education, 28(8), 927–956. https://doi.org/10.1007/s11191-019-00069-7CrossRef

Ford, M. (2008). Disciplinary authority and accountability in scientific practice and learning. Science Education, 92(3), 404–423. https://doi.org/10.1002/sce.20263CrossRef

Granshaw, F., & Duggan-Haas, D. (2012). Virtual fieldwork in geoscience teacher education: Issues, techniques and Models. In Whitmeyer, S.J. (Eds.) Google Earth and Virtual Visualizations in Geoscience Education and Research. (pp. 285–304). Geological Society of America Special Papers, 492. https://doi.org/10.1130/2012.2492(21)

Harrower, M., MacEachren, A., & Griffin, A. L. (2000). Developing a geographic visualization tool to support earth science learning. Cartography and Geographic Information Science, 27, 279–293. https://doi.org/10.1559/152304000783547759CrossRef

Harwood, W. S. (2004). A new model for inquiry: Is the scientific method dead? Journal of College Science Teaching, 33(7), 29–33. https://doi.org/10.1177/155335060501200218CrossRef

Harwood, D., & Usher, M. (1999). Assessing progression in primary children’s map drawing skills. International Research in Geographical and Environmental Education, 8, 222–238. https://doi.org/10.1080/10382049908667613CrossRef

Hegerl, G. C., Zwiers, F. W., Braconnot, P., Gillett, N. P., Luo. Y., Marengo Orsini, J. A., Nicholls, N., Penner, J. E., & Stott, P. A. (2007). Understanding and attributing climate change. In Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K.B., Tignor, M., & Miller, H.L. (Eds.) Climate change 2007: The physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. (pp. 663–745). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. hal-03375749f.

Hofstein, A., Shore, R., & Kipnis, M. (2004). Providing high school chemistry students with opportunities to develop learning skills in an inquiry-type laboratory: A case study. International Journal of Science Education, 26, 47–62. https://doi.org/10.1080/0950069032000070342CrossRef

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/s11165-009-9154-9CrossRef

Iedema, R. (2001). Resemiotization. Semiotica, 137, 23–29. https://doi.org/10.1515/semi.2001.106CrossRef

Jiménez-Aleixandre, M. P., & Crujeiras, B. (2016), Epistemic practices and Scientific practices in science education. In Taber K. S. & Akpan B. (Eds.). Science education: An international course companion (pp. 69–80). The Netherlands: Sense Publishers. https://doi.org/10.1007/978-94-6300-749-8_5

Jones, M. G., Andre, T., Superfine, R., & Taylor, R. (2003). Learning at the nanoscale: The impact of students’ use of remote microscopy on concepts of viruses, scale, and microscopy. Journal of Research in Science Teaching, 40, 303–322. https://doi.org/10.1002/tea.10078CrossRef

Jones, M. G., & Taylor, A. R. (2009). Developing a sense of scale: Looking backward. Journal of Research in Science Teaching, 46, 460–475. https://doi.org/10.1002/tea.20288CrossRef

Jones, M. G., Taylor, A., Minogue, J., Broadwell, B., Wiebe, E., & Carter, G. (2007). Understanding scale: Powers of ten. Journal of Science Education and Technology, 16, 191–202. https://doi.org/10.1007/s10956-006-9034-2CrossRef

Jones, M. G., Tretter, T., Taylor, A., & Oppewal, T. (2008). Experienced and novice teachers’ concepts of spatial scale. International Journal of Science Education, 30, 409–429. https://doi.org/10.1080/09500690701416624CrossRef

Kamarainen, A. M., Metcalf, S., Grotzer, T., & Dede, C. (2015). Exploring ecosystems from the inside: How immersive multi-user virtual environments can support development of epistemologically grounded modeling practices in ecosystem science instruction. Journal of Science Education and Technology, 24(2), 148–167. https://doi.org/10.1007/s10956-014-9531-7CrossRef

Kastens, K. A., & Ishikawa, T. (2006). Spatial thinking in the geosciences and cognitive sciences: A cross-disciplinary look at the intersection of the two fields. In Meduca, C.A. & Mogk, D.W. (Eds.) Earth and mind: How geologists think and learn about the Earth, (pp. 53–76). Geological Society of America Special Papers, 413. https://doi.org/10.1130/2006.2413(05)

Kelly, G. J., & Licona, P. (2018). Epistemic practices and science education. In Matthews, M.R. (Ed.). History, philosophy and science teaching (pp. 139–165). Springer, Cham. https://doi.org/10.1007/978-3-319-62616-1_5

Ketelhut, D. J., Nelson, B. C., Clarke, J., & Dede, C. (2010). A multi-user virtual environment for building and assessing higher order inquiry skills in science. British Journal of Educational Technology, 41(1), 56–68. https://doi.org/10.1111/j.1467-8535.2009.01036.xCrossRef

Klein, P. D., & Kirkpatrick, L. C. (2010). Multimodal literacies in science: Currency, coherence and focus. Research in Science Education, 40, 87–92. https://doi.org/10.1007/s11165-009-9159-4CrossRef

Klippel, A., Zhao, J., Oprean, D., Wallgrün, J. O., Stubbs, C., La Femina, P., & Jackson, K. L. (2020). The value of being there: Toward a science of immersive virtual field trips. Virtual Reality, 24(4), 753–770. https://doi.org/10.1007/s10055-019-00418-5CrossRef

Kozma, R. (2003). The material features of multiple representations and their cognitive and social affordances for science understanding. Learning and Instruction, 13, 205–226. https://doi.org/10.1016/S0959-4752(02)00021-XCrossRef

Kozma, R. B., & Russell, J. (1997). Multimedia and understanding: Expert and novice responses to different representations of chemical phenomena. Journal of Research in Science Teaching, 34, 949–968. https://doi.org/10.1002/(SICI)1098-2736(199711)34:9%3c949::AID-TEA7%3e3.0.CO;2-UCrossRef

Krajcik, J., Blumenfeld, P. C., Marx, R. W., Bass, K. M., Fredricks, J., & Soloway, E. (1998). Inquiry in project-based science classrooms: Initial attempts by middle school students. Journal of the Learning Sciences, 7, 313–350. https://doi.org/10.1080/10508406.1998.9672057CrossRef

Krajcik, J., Codere, S., Dahsah, C., Bayer, R., & Mun, K. (2014). Planning instruction to meet the intent of the Next Generation Science Standards. Journal of Science Teacher Education, 25, 157–175. https://doi.org/10.1007/s10972-014-9383-2CrossRef

Kress, G. (2009). Multimodality: A social semiotic approach to contemporary communication. Routledge.CrossRef

Kress, G. R., Jewitt, C., Ogborn, J., & Tsatsarelis, C. (2001). Multimodal teaching and learning: The rhetorics of the science classroom. Continuum.

Landauer, M., Juhola, S., & Klein, J. (2019). The role of scale in integrating climate change adaptation and mitigation in cities. Journal of Environmental Planning and Management, 62(5), 741–765. https://doi.org/10.1080/09640568.2018.1430022CrossRef

Lemke, J. (1998). Multiplying meaning: Visual and verbal semiotics in scientific text. In J. R. Martin & R. Veel (Eds.), Reading science: Critical and functional perspectives on discourses of science (pp. 87–113). Routledge.

Lewandowsky, S., Herrmann, D. J., Behrens, J. T., Li, S. C., Pickle, L., & Jobe, J. B. (1993). Perception of clusters in statistical maps. Applied Cognitive Psychology, 7, 533–551. https://doi.org/10.1002/acp.2350070606CrossRef

Liben, L. S., & Yekel, C. A. (1996). Preschoolers’ understanding of plan and oblique maps: The role of geometric and representational correspondence. Child Development, 67, 2780–2796. https://doi.org/10.1111/j.1467-8624.1996.tb01888.xCrossRef

Liu, L., & Jackson, T. (2019). A recent review of learning progressions in science: Gaps and shifts. The Educational Review, USA, 3(9), 113–126. https://doi.org/10.26855/er.2019.09.001CrossRef

MacDonald, S. P. (2019). Visualization and analysis of environmental data. In Lansiquot, R. D., & MacDonald, S. P. (Eds.). Interdisciplinary perspectives on virtual place-based learning. (pp. 69–81). Palgrave Pivot Cham. https://doi.org/10.1007/978-3-030-32471-1_5

MacEachren, A. M. (1991). The role of maps in spatial knowledge acquisition. The Cartographic Journal, 28, 152–162. https://doi.org/10.1179/000870491787859223CrossRef

MacLeod, M. (2018). What makes interdisciplinarity difficult? Some consequences of domain specificity in interdisciplinary practice. Synthese, 195(2), 697–720. https://doi.org/10.1007/s11229-016-1236-4CrossRef

Mead, C., Buxner, S., Bruce, G., Taylor, W., Semken, S., & Anbar, A. D. (2019). Immersive, interactive virtual field trips promote science learning. Journal of Geoscience Education, 67(2), 131–142. https://doi.org/10.1080/10899995.2019.1565285CrossRef

Metcalf, S. J., Reilly, J. M., Kamarainen, A. M., King, J., Grotzer, T. A., & Dede, C. (2018). Supports for deeper learning of inquiry-based ecosystem science in virtual environments-comparing virtual and physical concept mapping. Computers in Human Behavior, 87, 459–469. https://doi.org/10.1016/j.chb.2018.03.018CrossRef

Miller, E., Manz, E., Russ, R., Stroupe, D., & Berland, L. (2018). Addressing the epistemic elephant in the room: Epistemic agency and the next generation science standards. Journal of Research in Science Teaching, 55(7), 1053–1075. https://doi.org/10.1002/tea.21459CrossRef

Minner, D. D., Levy, A. J., & Century, J. (2010). Inquiry-based science instruction-what is it and does it matter? Results from a research synthesis years 1984 to 2002. Journal of Research in Science Teaching, 47, 474–496. https://doi.org/10.1002/tea.20347CrossRef

Mohan, L., Chen, J., & Anderson, C. W. (2009). Developing a multi-year learning progression for carbon cycling in socio-ecological systems. Journal of Research in Science Teaching, 46, 675–698. https://doi.org/10.1002/tea.20314CrossRef

Moysey, S. M., & Lazar, K. B. (2019). Using virtual reality as a tool for field-based learning in the earth sciences. In Lansiquot, R. D., & MacDonald, S. P. (Eds.). Interdisciplinary perspectives on virtual place-based learning. (pp. 99–126). Palgrave Pivot Cham. https://doi.org/10.1007/978-3-030-32471-1_7

National Research Council (NRC). (2000). How people learn: Brain, mind, experience, and school. National Academies Press.

National Research Council. (2002). Inquiry and the national science education standards: A guide for teaching and learning. The National Academies Press.

National Research Council. (2007). Taking science to school: Learning and teaching science in grades K-8. The National Academies Press.

National Research Council. (2012). A framework for K-12 science education: Practices, crosscutting themes, and core ideas. The National Academies Press.

Next Generation Science Standards (NGSS) Lead States. (2013). Next generation science standards: For states, by states. The National Academies Press.

Nyman, M., & Clair, T. S. (2016). A geometric model to teach nature of science, science practices, and metacognition. Journal of College Science Teaching, 45(5), 44–50. https://doi.org/10.2505/4/jcst16_045_05_44CrossRef

Oliveira, A., Feyzi Behnagh, R., Ni, L., Mohsinah, A. A., Burgess, K. J., & Guo, L. (2019). Emerging technologies as pedagogical tools for teaching and learning science: A literature review. Human Behavior and Emerging Technologies, 1(2), 149–160. https://doi.org/10.1002/hbe2.141CrossRef

Osborne, J. F., Henderson, J. B., MacPherson, A., Szu, E., Wild, A., & Yao, S. Y. (2016). The development and validation of a learning progression for argumentation in science. Journal of Research in Science Teaching, 53(6), 821–846. https://doi.org/10.1002/tea.21316CrossRef

Petcovic, H. L., & Libarkin, J. C. (2007). Research in science education: The expert-novice continuum. Journal of Geoscience Education, 55(4), 333–339. https://doi.org/10.1080/10899995.2007.12028060CrossRef

Peterson, M. P. (1985). Evaluating a map’s image. The American Cartographer, 12, 41–56. https://doi.org/10.1559/152304085783914659CrossRef

Piatek, J. L., Beatty, C. L. K., Beatty, W. L., Wizevich, M. C., & Steullet, A. (2012). Developing virtual field experiences for undergraduates with high-resolution panoramas (GigaPans) at multiple scales. In Whitmeyer, S.J. (Eds.) Google Earth and virtual visualizations in geoscience education and research, (pp. 305–313). Geological Society of America Special Papers, 492. https://doi.org/10.1130/2012.2492(21)

Pierson, A. E., & Clark, D. B. (2019). Sedimentation of modeling practices. Science & Education, 28(8), 897–925. https://doi.org/10.1007/s11191-019-00050-4CrossRef

Pierson, A. E., Clark, D. B., & Kelly, G. J. (2019). Learning progressions and science practices. Science & Education, 28(8), 833–841. https://doi.org/10.1007/s11191-019-00070-0CrossRef

Sandoval, W. A. (2005). Understanding students’ practical epistemologies and their influence on learning through inquiry. Science Education, 89, 634–656. https://doi.org/10.1002/sce.20065CrossRef

Schwarz, C., Reiser, B. J., Acher, A., Kenyon, L., & Fortus, D. (2012). MoDeLS: Challenges in defining a learning progression for scientific modeling. In Alonzo A. & W. Gotwals (Eds.), Learning progressions in science: Current challenges and future directions. (pp. 101–137). SensePublishers, Rotterdam https://doi.org/10.1007/978-94-6091-824-7_6

Schwarz, C. V., Reiser, B. J., Davis, E. A., Kenyon, L., Achér, A., Fortus, D., Shwartz, Y., Hug, B., & Krajcik, J. (2009). Developing a learning progression for scientific modeling: Making scientific modeling accessible and meaningful for learners. Journal of Research in Science Teaching, 46(6), 632–654. https://doi.org/10.1002/tea.20311CrossRef

Shah, P., & Hoeffner, J. (2002). Review of graph comprehension research: Implications for instruction. Educational Psychology Review, 14, 47–69. https://doi.org/10.1023/A:1013180410169CrossRef

Shekhar, S., Evans, M. R., Kang, J. M., & Mohan, P. (2011). Identifying patterns in spatial information: A survey of methods. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 1, 193–214. https://doi.org/10.1002/widm.25CrossRef

Sikorski, T. R. (2019). Context-dependent “upper anchors” for learning progressions. Science & Education, 28(8), 957–981. https://doi.org/10.1007/s11191-019-00074-wCrossRef

Smith, T. K. (2014). Elementary science instruction: Examining a virtual environment for evidence of learning, engagement, and 21st century competencies. Education Sciences, 4(1), 122–138. https://doi.org/10.3390/educsci4010122CrossRef

Stevens, S. Y., Sutherland, L. M., & Krajcik, J. S. (2009). The big ideas of nanoscale science and engineering. NSTA Press.

Stroupe, D. (2015). Describing “science practice” in learning settings. Science Education, 99(6), 1033–1040. https://doi.org/10.1002/sce.21191CrossRef

Thorndyke, P. W., & Stasz, C. (1980). Individual differences in procedures for knowledge acquisition from maps. Cognitive Psychology, 12, 137–175. https://doi.org/10.1016/0010-0285(80)90006-7CrossRef

Tretter, T. R., Jones, M. G., Andre, T., Negishi, A., & Minogue, J. (2006a). Conceptual boundaries and distances: Students’ and experts’ concepts of the scale of scientific phenomena. Journal of Research in Science Teaching, 43, 282–319. https://doi.org/10.1002/tea.20123CrossRef

Tretter, T. R., Jones, M. G., & Minogue, J. (2006b). Accuracy of scale conceptions in science: Mental maneuverings across many orders of spatial magnitude. Journal of Research in Science Teaching, 43, 1061–1085. https://doi.org/10.1002/tea.20155CrossRef

Tsai, C. C. (2004). Beyond cognitive and metacognitive tools: The use of the internet as an ‘epistemological’ tool for instruction. British Journal of Educational Technology, 35(5), 525–536. https://doi.org/10.1111/j.0007-1013.2004.00411.xCrossRef

Tversky, B., & Schiano, D. J. (1989). Perceptual and conceptual factors in distortions in memory for graphs and maps. Journal of Experimental Psychology: General, 118, 387–398. https://doi.org/10.1037/0096-3445.118.4.387CrossRef

Waldrip, B., Prain, V., & Carolan, J. (2010). Using multi-modal representations to improve learning in junior secondary science. Research in Science Education, 40, 65–80. https://doi.org/10.1007/s11165-009-9157-6CrossRef

Wang, N., Stern, R. J., Urquhart, M. L., & Seals, K. M. (2022). Google earth geoscience video library (GEGVL): Organizing geoscience videos in a google earth environment to support fieldwork teaching methodology in earth science. Geosciences, 12(6), 250. https://doi.org/10.3390/geosciences12060250CrossRef

Wiegand, P. (2006). Learning and teaching with maps. Routledge.CrossRef

Wilbanks, T. J., & Kates, R. W. (1999). Global change in local places: how scale matters. Climatic Change, 43(3), 601–628. https://doi.org/10.1023/A:1005418924748CrossRef

Winch, C. (2013). Curriculum design and epistemic ascent. Journal of Philosophy of Education, 47(1), 128–146. https://doi.org/10.1111/1467-9752.12006CrossRef

Winn, W. (1991). Learning from maps and diagrams. Educational Psychology Review, 3, 211–247. https://doi.org/10.1007/BF01320077CrossRef

Yoon, S. A., Goh, S. E., & Yang, Z. (2019). Toward a learning progression of complex systems understanding. Complicity: An International Journal of Complexity and Education, 16(1), 1–19. https://doi.org/10.29173/cmplct29340CrossRef

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, 93–101. https://doi.org/10.1007/s11165-009-9160-yCrossRef

Zhang, J., Tian, Y., Yuan, G., & Tao, D. (2022). Epistemic agency for costructuring expansive knowledge-building practices. Science Education, 106(4), 890–923. https://doi.org/10.1002/sce.21717CrossRef

Zimmerman, H. T., & Weible, J. L. (2018). Epistemic agency in an environmental sciences watershed investigation fostered by digital photography. International Journal of Science Education, 40(8), 894–918. https://doi.org/10.1080/09500693.2018.1455115CrossRef

Titel: Building an NGSS-aligned Middle School Summer Camp for an Observational Investigation with a Virtual Field Environment
verfasst von: Nancy A. Price
Jennifer G. Wells
Frank D. Granshaw
Publikationsdatum: 09.08.2022
Verlag: Springer Netherlands
Erschienen in: Journal of Science Education and Technology / Ausgabe 6/2022
Print ISSN: 1059-0145
Elektronische ISSN: 1573-1839
DOI: https://doi.org/10.1007/s10956-022-09990-z

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