Skip to main content
SpringerLink
Log in

Concepts Maps as Versatile Learning, Teaching, and Assessment Tools

Learning, Design, and Technology

  • 410 Accesses

Abstract

Concept maps can serve as versatile tools for learning, teaching, and assessment to support integrating complex concepts. Research suggests that concept maps can be successfully implemented in a wide variety of settings, from K12 to higher and professional education. However, the effectiveness of concept maps depends on different factors, such as concept map training, choosing a suitable form of concept map to match the task and learner, and how to evaluate concept maps. This chapter presents two case studies that use a particular form of concept map, a Knowledge Integration Map, to illustrate different concept mapping tasks and evaluations. This chapter concludes that, if implemented thoughtfully, concept maps can be versatile tools to support knowledge integration processes toward a deeper understanding of the relations and structures of complex concepts.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Similar content being viewed by others

References

  • Acton, W. H., Johnson, P. J., & Goldsmith, T. E. (1994). Structural knowledge assessment – Comparison of referent structures. Journal of Education & Psychology, 86(2), 303–311.

    Article  Google Scholar 

  • Adamczyk, A., & Willson, M. (1996). Using concept maps with trainee physics teachers. Physics Education, 31(6), 374–381.

    Article  Google Scholar 

  • Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16(3), 183–198.

    Article  Google Scholar 

  • Ainsworth, S. E. (1999). A functional taxonomy of multiple representations. Computers & Education, 33(2/3), 131–152.

    Article  Google Scholar 

  • Alters, B. J., & Nelson, C. E. (2002). Perspective: Teaching evolution in higher education. Evolution, 56(10), 1891–1901.

    Article  Google Scholar 

  • Anderson, D., Lucas, K. B., & Ginns, I. S. (2000). Development of knowledge about electricity and magnetism during a visit to a science museum and related post-visit activities. Science Education, 84, 658–679.

    Article  Google Scholar 

  • Anderson, R. C. (1984). Some reflections on the acquisition of knowledge. Educational Researcher, 13(9), 5–10.

    Article  Google Scholar 

  • Ariew, A. (2003). Ernst Mayr’s ‘ultimate/proximate’ distinction reconsidered and reconstructed. Biology and Philosophy, 18(4), 553–565.

    Article  Google Scholar 

  • Atay, S., & Karabacak. (2012). Care plans using concept maps and their effects on the critical thinking dispositions of nursing students. International Journal of Nursing Practice, 18(3), 233–239.

    Article  Google Scholar 

  • Ault, C. R. (1985). Concept mapping as a study strategy in earth science. Journal of College Science Teaching, 15, 38–44.

    Google Scholar 

  • Austin, L. B., & Shore, B. M. (1995). Using concept mapping for assessment in physics. Physics Education, 30, 41.

    Article  Google Scholar 

  • Ausubel, D. P. (1963). The psychology of meaningful verbal learning: An introduction to school learning. New York, NY: Grune & Stratton.

    Google Scholar 

  • Ausubel, D. P., Novak, J. D., & Hanesian, H. (1978). Educational psychology – A cognitive view. London, UK: Holt, Rienhart and Winston.

    Google Scholar 

  • Ayala, C. C., Yin, Y., Shavelson, R. J., & Vanides, J. (2002). Investigating the cognitive validity of science performance assessment with think alouds: Technical aspects. New Orleans, LA: American Educational Researcher Association.

    Google Scholar 

  • Aydin, S., Aydemir, N., Boz, Y., Cetin-Dindar, A., & Bektas, O. (2009). The contribution of constructivist instruction accompanied by concept mapping in enhancing pre-service chemistry teachers’ conceptual understanding of chemistry in the laboratory course. Journal of Science Education and Technology, 18, 518–534.

    Article  Google Scholar 

  • Bakri, F., & Muliyati, D. (2018). Design of multiple representations e-learning resources based on a contextual approach for the basic physics course. Proceedings from Journal of Physics: Conference Series, 1013(1), 1–7.

    Google Scholar 

  • Banet, E., & Ayuso, G. E. (2003). Teaching of biological inheritance and evolution of living beings in secondary school. International Journal of Science Education, 25(3), 373–407.

    Article  Google Scholar 

  • Barnett, R. (2000). Realizing the university in an age of supercomplexity. Buckingham, UK/Philadelphia, PA: Society for Research into Higher Education & Open University Press.

    Google Scholar 

  • Bascones, J., & Novak, J. D. (1985). Alternative instructional systems and the development of problem-solving skills in physics. International Journal of Science Education, 7(3), 253–261.

    Google Scholar 

  • Baxter, G. P., & Glaser, R. (1998). Investigating the cognitive complexity of science assessments. Educational Measurement: Issues and Practice, 17(3), 37–45.

    Article  Google Scholar 

  • Berland, L. K., & Reiser, B. J. (2009). Making sense of argumentation and explanation. Science Education, 93(1), 26–55.

    Article  Google Scholar 

  • Birbili, M. (2006). Mapping knowledge: Concept maps in early childhood education. Early Childhood Research and Practice, 8(2).

    Google Scholar 

  • Bjork, R. A., & Linn, M. C. (2006). The science of learning and the learning of science – Introducing desirable difficulties. APS Observer, 19(3), 1–2.

    Google Scholar 

  • BouJaoude, S., & Attieh, M. (2008). The effect of using concept maps as study tools on achievement in chemistry. Eurasia Journal of Mathematics, Science and Technology Education, 4(3), 233–246.

    Article  Google Scholar 

  • Brandt, L., Elen, J., Hellemans, J., Heerman, L., Couwenberg, I., Volckaert, L., & Morisse, H. (2001). The impact of concept mapping and visualization on the learning of secondary school chemistry students. International Journal of Science Education, 23(12), 1303–1313.

    Article  Google Scholar 

  • Bransford, J., Brown, A. L., & Crocking, R. R. (2000). How people learn: Brain, mind, experience, and school (Expanded edition). Washington, DC: National Academy Press

    Google Scholar 

  • Bressington, D. T., Wong, W.-K., Lam, K. K. C., & Chien, W. T. (2018). Concept mapping to promote meaningful learning, help relate theory to practice and improve learning self-efficacy in Asian mental health nursing students: A mixed-methods pilot study. Nurse Education Today, 60, 47–55.

    Article  Google Scholar 

  • Brody, M. J. (1993). Student misconceptions of ecology: Identification, analysis and instructional design. In J. D. Novak (Ed.), Proceedings of the third international seminar on misconceptions and educational strategies in science and mathematics. Ithaca, NY: Cornell University.

    Google Scholar 

  • Brown, A. L., & Campione, J. C. (1996). Psychological learning theory and the design of innovative environments: On procedures, principles and systems. In L. Shauble & R. Glaser (Eds.), Contributions of instructional innovation to understanding learning. Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Brown, D. S. (2003). High school biology: A group approach to concept mapping. American Biology Teacher, 65(3), 192–197.

    Article  Google Scholar 

  • Bruechner, K., & Schanze, S. (2004). Using concept maps for individual knowledge externalization in medical education. In First international conference on concept mapping. Pamplona, Spain.

    Google Scholar 

  • Bruner, J. S. (1960). The process of education. New York, NY: Vantage.

    Google Scholar 

  • Bruner, J. S., Goodnow, J. J., & Austin, G. A. (1986). A study of thinking. New Brunswick, NJ: Transaction Publishers.

    Google Scholar 

  • Buntting, C., Coll, R. K., & Campell, A. (2006). Student views of concept mapping use in introductory tertiary biology classes. International Journal of Science and Mathematics Education, 4(4), 641–668.

    Article  Google Scholar 

  • Byrne, J., & Grace, M. (2010). Using a concept mapping tool with a photograph association technique (compat) to elicit children’s ideas about microbial activity. International Journal of Science Education, 32(4), 37–43.

    Google Scholar 

  • Cakir, M., & Crawford, B. (2001). Prospective biology teachers’ understanding of genetics concepts. Paper presented at the annual meeting of the Association for the education of Teachers in Science, Costa Mesa, CA.

    Google Scholar 

  • Cañas, A. J. (2003). A summary of literature pertaining to the use of concept mapping techniques and technologies for education and performance support. The Institute for Human and Machine Cognition 40 S. Alcaniz St. Pensacola FL 32502 http://www.ihmc.us/users/aCañas/Publications/ConceptMapLitReview/

  • Cañas, A. J. (2004). Cmap tools – Knowledge modeling kit [Computer Software]. Pensacola, FL: Institute for Human and Machine Cognition (IHMC).

    Google Scholar 

  • Canas, A. J. (2016). Cmap tools – Knowledge modeling kit [Computer Software]. Pensacola, FL: Institute for Human and Machine Cognition (IHMC).

    Google Scholar 

  • Cañas, A. J., Novak, J. D., & Reiska, P. (2012). Freedom vs. Restriction of content and structure during concept mapping – Possibilities and limitations for construction and assessment. In Proceedings of the fifth international conference on concept mapping, Proc. of the Fifth Int. Conference on Concept Mapping Valletta, Malta 2012 (pp. 247–257).

    Google Scholar 

  • Cañas, Suri, Sanchez, Gallo, & Brenes. (2003). Synchronous collaboration in cmap tools. IHMC.

    Google Scholar 

  • Carey, S., & Spelke, E. (1994). Domain-specific knowledge and conceptual change. In Mapping the mind: Domain specificity in cognition and culture (pp. 169–200). Cambridge, MA/New York, NY: Massachusetts Institute of Technology, Department of Brain & Cognitive Sciences/Cambridge University Press.

    Chapter  Google Scholar 

  • Cathcart, Laura, Stieff, Mike, Marbach-Ad, Gili, Smith, Ann, & Frauwirth, Kenneth. (2010). Using knowledge structure maps as a foundation for knowledge management. ICLS.

    Google Scholar 

  • Chand, L., Sowmya, K., & Silambanan, S. (2018). Meaningful learning in medical science by self-directed approach of concept mapping. Journal of Education Technology in Health Sciences, 5(1), 31–35.

    Article  Google Scholar 

  • Chang, K. E., Chiao, B. C., Chen, S. W., & Hsiao, R. S. (2000). A programming learning system for beginners-a completion strategy approach. IEEE Transactions on Education, 43(2), 211–220.

    Article  Google Scholar 

  • Chang, K. E., Sung, Y. T., & Chen, S. F. (2001). Learning through computer-based concept mapping with scaffolding aid. Journal of Computer Assisted Learning, 17(1), 21–33.

    Article  Google Scholar 

  • Chang, S.-N. (2007). Externalising students’ mental models through concept maps. Journal of Biological Education, 41(3), 107–112.

    Article  Google Scholar 

  • Chartrand, G., & Zhang, P. (2004). Introduction to graph theory. Boston, MA: McGraw-Hill Higher Education.

    Google Scholar 

  • Chen, S.-L., Liang, T., Lee, M.-L., & Liao, I.-C. (2011). Effects of concept map teaching on students’ critical thinking and approach to learning and studying. The Journal of Nursing Education, 50(8), 466–469.

    Article  Google Scholar 

  • Chi, M. T. H. (2000). Self-explaining: The dual processes of generating inference and repairing mental models. In Advances in instructional psychology: Educational design and cognitive science (Vol. 5, pp. 161–238). Mahwah, NJ: Lawrence Erlbaum Associates Publishers.

    Google Scholar 

  • Chi, M. T. H., Feltovich, P., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121–151.

    Article  Google Scholar 

  • Chi, M. T. H., Glaser, R., & Rees, E. (1982). Expertise in problem solving. In Advances in the psychology of human intelligence (pp. 7–75). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.

    Google Scholar 

  • Chinn, C. A., & Brewer, W. F. (2001). Models of data: A theory of how people evaluate data. Cognition and Instruction, 19(3), 323–393.

    Article  Google Scholar 

  • Chiu, J. (2008). Examining the role of self-monitoring and explanation prompts on students’ interactions with dynamic molecular visualizations. In Poster presented at the 8th international conference of the learning sciences, international perspectives in the learning sciences: Cre8ting a learning world, Utrecht, The Netherlands.

    Google Scholar 

  • Chiu, J. L. (2009). The impact of feedback on student learning and monitoring with dynamic visualizations. Annual meeting of the American Educational Research Association, San Diego, CA.

    Google Scholar 

  • Cicagnani. (2000). Concept mapping as a collaborative tool for enhancing online learning. Educational Technology & Society, 3(3).

    Google Scholar 

  • Clark, D. B., & Sampson, V. (2008). Assessing dialogic argumentation in online environments to relate structure, grounds, and conceptual quality. Journal of Research in Science Teaching, 45(3), 293–321.

    Article  Google Scholar 

  • Clark, D. B., & Slotta, J. (2000). Evaluating media-enhancement and source authority on the Internet: The knowledge integration environment. International Journal of Science Education, 22(8), 859–872.

    Article  Google Scholar 

  • Cliburn, J. W., Jr. (1990). Concept maps to promote meaningful learning. Journal of College Science Teaching, 19(4), 212–217.

    Google Scholar 

  • Cline, B. E., Brewster, C. C., & Fell, R. D. (2009). A rule-based system for automatically evaluating student concept maps. Expert Systems with Applications, 37, 2282.

    Article  Google Scholar 

  • Coleman, E. B. (1998). Using explanatory knowledge during collaborative problem solving in science. Journal of the Learning Sciences, 7(3), 387–427.

    Article  Google Scholar 

  • Collins, A., Brown, J. S., & Holum, A. (1991). Cognitive apprenticeship: Making thinking visible. American Educator, 15(3), 6–11.

    Google Scholar 

  • Crank, J. N., & Bulgren, J. A. (1993). Visual depictions as information organizers for enhancing achievement of students with learning disabilities. Learning Disabilities Research and Practice, 8(3), 140–147.

    Google Scholar 

  • Cuthbert, A., & Slotta, J. (2004). Fostering lifelong learning skills on the World Wide Web: Critiquing, questioning and searching for evidence. International Journal of Science Education, 27(7), 821–844.

    Article  Google Scholar 

  • Czerniak, C. M., & Haney, J. J. (1998). The effect of collaborative concept mapping on elementary preservice teachers’ anxiety, efficacy, and achievement in physical science. Journal of Science Teacher Education, 9(4), 303–320.

    Article  Google Scholar 

  • Daley, B. J., & Torre, D. M. (2010). Concept maps in medical education: An analytical literature review. Medical Education, 44(5), 440–448.

    Article  Google Scholar 

  • Davis, E. A. (2003). Prompting middle school science students for productive reflection: Generic and directed prompts. The Journal of the Learning Sciences, 12(1), 91–142.

    Article  Google Scholar 

  • Davis, E. A. (2004). Knowledge integration in science teaching: Analysing teachers’ knowledge development. Research in Science Education, 34(1), 21–54.

    Article  Google Scholar 

  • Davis, E. A., & Kirkpatrick, D. (2002). It’s all the news: Critiquing evidence and claims. Science Scope, 25(5), 32–37.

    Google Scholar 

  • Davis, E. A., & Linn, M. C. (2000). Scaffolding students’ knowledge integration: Prompts for reflection in KIE. International Journal of Science Education, 22(8), 819–837.

    Article  Google Scholar 

  • Demastes, S. S., Good, R. G., & Peebles, P. (1995). Students’ conceptual ecologies and the process of conceptual change in evolution. Science Education, 79(6), 637–666.

    Article  Google Scholar 

  • DeMeo, S. (2007). Constructing a graphic organizer in the classroom: Introductory students’ perception of achievement using a decision map to solve aqueous acid-base equilibria problems. Journal of Chemical Education, 84(3), 540–546.

    Article  Google Scholar 

  • Derbentseva, N., Safayeni, F., & Canas, A. J. (2007). Concept maps: Experiments on dynamic thinking. Journal of Research in Science Teaching, 44(3), 448–465.

    Article  Google Scholar 

  • diSessa, A. (2004). Metarepresentation: Native competence and targets for instruction. Cognition and Instruction, 22, 293–331.

    Article  Google Scholar 

  • diSessa, A. A. (1988). Knowledge in pieces. In G. Forman & P. Pufall (Eds.), Constructivism in the computer age. (pp. 49–70). Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • diSessa, A. A. (2002). Students’ criteria for representational adequacy. In K. Gravemeijer, R. Lehrer, B. Van Oers, & L. Verschaffel (Eds.), Synbolizing, modeling, and tool use in mathematics education (pp. 105–129). Boston, MA: Kluwer.

    Chapter  Google Scholar 

  • diSessa, A. A. (2006). A history of conceptual change research: Threads and fault lines. In K. Sawyer (Ed.), The cambridge handbook of the learning sciences (pp. 265–282). New York, NY: Cambridge University Press.

    Google Scholar 

  • diSessa, A. A. (2008). A bird’s eye view of the “pieces” vs. “Coherence” controversy. In S. Vosniadou (Ed.), International handbook of research on conceptual change. Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Duncan, R. G., & Reiser, B. J. (2005). Designing for complex system understanding in the high school biology classroom. Annual meeting of the National Association for Research in Science Teaching.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • Edmondson, K. M. (1993). Concept mapping for meaningful learning in veterinary education. In J. D. Novak (Ed.), Proceedings of the third international seminar on misconceptions and educational strategies in science and mathematics. Ithaca, NY: Cornell University.

    Google Scholar 

  • Edmondson, K. M. (1995). Concept mapping for the development of medical curricula. Journal of Research in Science Teaching, 32(7), 777–793.

    Article  Google Scholar 

  • Edmondson, K. M. (2000). Assessing science understanding through concept maps. In Assessing science understanding (pp. 15–40). Academic Press.

    Google Scholar 

  • El-Hay, S. A. A., El Mezayen, S. E., & Ahmed, R. E. (2018). Effect of concept mapping on problem solving skills, competence in clinical setting and knowledge among undergraduate nursing students. Journal of Nursing Education and Practice, 8, 34.

    Article  Google Scholar 

  • Englebrecht, A. C., Mintzes, J. J., Brown, L. M., & Kelso, P. R. (2005). Probing understanding in physical geology using concept maps and clinical interviews. Journal of Geoscience Education, 53(3), 263.

    Article  Google Scholar 

  • Enyedy, N. (2005). Inventing mapping: Creating cultural forms to solve collective problems. Cognition and Instruction, 427–466.

    Article  Google Scholar 

  • Ericsson, K. A., & Simon, H. A. (1985). Protocol analysis: Verbal reports as data. Cambridge, MA: MIT Press.

    Google Scholar 

  • Falchikov, N., & Goldfinch, J. (2000). Student peer assessment in higher education: A meta-analysis comparing peer and teacher marks. Review of Educational Research, 70(3), 287–322.

    Article  Google Scholar 

  • Fang, N. (2018). An analysis of student experiences with concept mapping in a foundational undergraduate engineering course. International Journal of Engineering Education, 34(2), 294.

    Google Scholar 

  • Farrokh, K., & Krause, G. (1996). The relationship of concept-mapping and course grade in cell biology. Meaningful Learning Forum, 1.

    Google Scholar 

  • Fisher, K. M. (2000). SemNet software as an assessment tool. In Assessing science understanding: A human constructivist view (pp. 197–221). San Diego, CA: Academic.

    Google Scholar 

  • Fisher, K. M., Wandersee, J. H. M., & Moody, D. E. (2000). Mapping biology knowledge. Dordrecht, The Netherlands: Kluwer Academic Publishers.

    Google Scholar 

  • Ford, M. J. (2008). Disciplinary authority and accountability in scientific practice and learning. Science Education, 92, 404.

    Article  Google Scholar 

  • Gaines, B. R., & Shaw, M. L. G. (1995). Collaboration through concept maps. In CSCL 1995 proceedings, 95, 135–138.

    Google Scholar 

  • Gallenstein, N. L. (2005). Never too young for a concept map. Science and Children, 43(1), 44–47.

    Google Scholar 

  • Garwood, J. K., Ahmed, A. H., & McComb, S. A. (2018). The effect of concept maps on undergraduate nursing students’ critical thinking. Nursing Education Perspectives, 39(4), 208–214.

    Article  Google Scholar 

  • Gentner, D. (1978). On relational meaning: The acquisition of verb meaning. Child Development, 49, 988.

    Article  Google Scholar 

  • Gerdeman, J. L., Lux, K., & Jacko, J. (2013). Using concept mapping to build clinical judgment skills. Nurse Education in Practice, 13(1), 11–17.

    Article  Google Scholar 

  • Gerstner, S., & Bogner, F. X. (2009). Concept map structure, gender and teaching methods: An investigation of students’ science learning. Educational Research, 51(4), 425–438.

    Article  Google Scholar 

  • Glaser, R., Chi, M. T. H., & Farr, M. J. (1985). The nature of expertise. Columbus, OH: National Center for Research in Vocational Education, The Ohio State University.

    Google Scholar 

  • Goel, A., & Chandrasekaran, B. (1989). Functional representation of designs and redesign problem solving. In Proceedings of the 11th international joint conference on artificial intelligence, 2, 1388–1394.

    Google Scholar 

  • Goel, A. K., Rugaber, S., & Vattam, S. (2008). Structure, behavior, and function of complex systems: The structure, behavior, and function modeling language. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 23, 23.

    Article  Google Scholar 

  • González, F. M. (1997). Diagnosis of spanish primary school students’ common alternative science conceptions. School Science and Mathematics, 97(2), 68–74.

    Article  Google Scholar 

  • Grosslight, L., Unger, C., Jay, E., & Smith, C. (1991). Understanding models and their use in science: Conceptions of middle and high school students and experts. Journal of Research in Science Teaching (Special Issue: Students’ Models and Epistemologies of Science), 28(9), 799–822.

    Article  Google Scholar 

  • Grossschedl, J., & Tröbst, S. (2018). Biologie lernen durch Concept Mapping: Bedeutung eines Lernstrategietrainings für kognitive Belastung, kognitive Prozesse und Lernleistung–Kurzdarstellung des DFG–Projekts. Zeitschrift für Didaktik der Biologie (ZDB)-Biologie Lehren und Lernen, 22(1), 20–30.

    Google Scholar 

  • Grundspenkis, J., & Strautmane, M. (2009). Usage of graph patterns for knowledge assessment based on concept maps. Scientific Journal of Riga Technical University. Computer Sciences, 38(38), 60–71.

    Article  Google Scholar 

  • Guastello, E. F., Beasley, T. M., & Sinatra, R. C. (2000). Concept mapping effects on science content comprehension of low-achieving inner-city seventh graders. Remedial and Special Education, 21(6), 356–364.

    Article  Google Scholar 

  • Guindon, R. (1990). Designing the design process: Exploiting opportunistic thoughts. Human Computer Interaction, 5(2), 305–344.

    Article  Google Scholar 

  • Halford, G. S. (1993). Children’s understanding: The development of mental models. Australia Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Hamdiyati, Y., Sudargo, F., Redjeki, S., & Fitriani, A. (2018). Using concept maps to describe undergraduate students’ mental model in microbiology course. Proceedings from Journal of Physics: Conference Series, 1013(1), 1–5.

    Google Scholar 

  • Hay, D. B. (2007). Using concept maps to measure deep, surface and non-learning outcomes. Studies in Higher Education, 32(1), 39–57.

    Article  Google Scholar 

  • Hay, D. B. (2008). Developing dialogical concept mapping as an e-learning technology. British Journal of Educational Technology, 39, 1057–1060.

    Article  Google Scholar 

  • Heinze-Fry, J. A. (1998). Concept mapping: Weaving conceptual connections. In Weaving connections: Cultures and environments – Selected papers from the 26th annual North American association of environmental education conference (NAAEE) (pp. 138–147), Troy, OH.

    Google Scholar 

  • Heinze-Fry, J. A., & Novak, J. D. (1990). Concept mapping brings long-term movement toward meaningful learning. Science Education, 74(4), 461–472.

    Article  Google Scholar 

  • Herl, H. E. (1999). Reliability and validity of a computer-based knowledge mapping system to measure content understanding. Computers in Human Behavior, 15(3-4), 315–333.

    Article  Google Scholar 

  • Herl, H. E., O’Neil, H. F. J., Chung, G. K., Dennis, R. A., & Lee, J. J. (1997, March). Feasibility of an on-line concept mapping construction and scoring system. Report: ED424233. 27pp.

    Google Scholar 

  • Hmelo, C. E., Holton, D. L., & Kolodner, J. L. (2000). Designing to learn about complex systems. The Journal of the Learning Sciences, 9(3), 247–298.

    Article  Google Scholar 

  • Hmelo-Silver, C. (2004). Comparing expert and novice understanding of a complex system from the perspective of structures, behaviors, and functions. Cognitive Science, 28, 127–138.

    Article  Google Scholar 

  • Hmelo-Silver, C. E., Marathe, S., & Liu, L. (2007). Fish swim, rocks sit, and lungs breathe: Expert–novice understanding of complex systems. Journal of the Learning Sciences, 16(3), 307–331.

    Article  Google Scholar 

  • Hoadley, C., & Kirby, J. (2004). Socially relevant representations in interfaces for learning. In Y. B. Kafai, W. A. Sandoval, N. Enyedy, A. S. Nixon, & F. Herrera (Eds.), Embracing diversity in the learning sciences: Proceedings of the sixth international conference of the learning sciences (pp. 262–269). Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Hoffman, R. R. (1998). How can expertise be defined? Implications of research from cognitive psychology. In R. Williams, W. Faulkner, & J. Fleck (Eds.), Exploring expertise (pp. 81–100). Edinburgh, Scotland: University of Edinburgh Press.

    Chapter  Google Scholar 

  • Holley, C. D., Dansereau, D. F., & Harold, F. O. N. (1984). Spatial learning strategies: Techniques, applications, and related issues. New York, NY: Academic.

    Book  Google Scholar 

  • Hook, P. A., & Boerner, K. (2005). Educational knowledge domain visualizations: Tools to navigate, understand, and internalize the structure of scholarly knowledge and expertise. In New directions in cognitive information retrieval (pp. 187–208). Springer, Dordrecht.

    Google Scholar 

  • Hoppe, H. U., Engler, J., & Weinbrenner, S. (2012). The impact of structural characteristics of concept maps on automatic quality measurement. In J. van Aalst, K. Thompson, M. J. Jacobson, & P. Reimann (Eds.), Proceedings of the 10th international conference of the learning sciences (ICLS). Sydney, NSW: ISLS.

    Google Scholar 

  • Horton, P. B., McConney, A. A., Gallo, M., Woods, A. L., Senn, G. J., & Hamelin, D. (1993). An investigation of the effectiveness of concept mapping as an instructional tool. Science Education, 77(1), 95–111.

    Article  Google Scholar 

  • Hoz, R., Tomer, Y., Bowman, D., & Chayoth, R. (1987). The use of concept mapping to diagnose misconceptions in biology and earth sciences. In J. D. Novak (Ed.), Proceedings of the second international seminar misconceptions and educational strategies in science and mathematics (Vol. I, pp. 245–256). Ithaca, NY: Cornell University.

    Google Scholar 

  • Hsu, Y. S. (2008). Learning about seasons in a technologically enhanced environment: The impact of teacher-guided and student-centered instructional approaches on the process of students’ conceptual change. Science Education, 92(2), 320–344.

    Article  Google Scholar 

  • Hsu, Y. S., Wu, H., & Hwang, F. (2008). Fostering high school students’ conceptual understandings about seasons: The design of a technology-enhanced learning environment. Research in Science Education, 38(2), 127–147.

    Article  Google Scholar 

  • Hyerle, D. (1996). Visual tools for constructing knowledge. Alexandria, VA: Association for Supervision and Curriculum Development.

    Google Scholar 

  • Ifenthaler, D. (2010). Relational, structural, and semantic analysis of graphical representations and concept maps. Educational Technology Research and Development, 58(1), 81–97. https://doi.org/10.1007/s11423-008-9087-4

    Article  Google Scholar 

  • Inspiration. (2016). Inspiration.

    Google Scholar 

  • Irvine, L. (1995). Can concept mapping be used to promote meaningful learning in nurse education? Journal of Advanced Nursing, 21(6), 1175–1179.

    Article  Google Scholar 

  • Karpicke, J. D., & Blunt, J. R. (2011). Retrieval practice produces more learning than elaborative studying with concept mapping. Science, 331, 772.

    Article  Google Scholar 

  • Kaya, O. N. (2008). A student-centred approach: Assessing the changes in prospective science teachers’ conceptual understanding by concept mapping in a general chemistry laboratory. Research in Science Education, 38(1), 91–110.

    Article  Google Scholar 

  • Keraro, F. N., Wachanga, S. W., & Orora, W. (2007). Effects of cooperative concept mapping teaching approach on secondary school students’ motivation in biology in Gucha district. International Journal of Science and Mathematics Education, 5(1), 111–124.

    Article  Google Scholar 

  • Kern, C., & Crippen, K. J. (2008). Mapping for conceptual change. The Science Teacher, 75(6), 32–38.

    Google Scholar 

  • Kinchin, I. M. (2000a). Concept mapping in biology. Journal of Biological Education, 34(2), 61–68.

    Article  Google Scholar 

  • Kinchin, I. M. (2000b). From ‘ecologist’ to ‘conceptual ecologist’: The utility of the conceptual ecology for teachers of biology. Journal of Biological Education, 34(4), 178–183.

    Article  Google Scholar 

  • Kinchin, I. M. (2001). If concept mapping is so helpful to learning biology, why aren’t we all doing it? International Journal of Science Education, 23(12), 1257–1269.

    Article  Google Scholar 

  • Kinchin, I. M. (2014). Concept mapping as a learning tool in higher education: A critical analysis of recent reviews. The Journal of Continuing Higher Education, 62(1), 39–49.

    Article  Google Scholar 

  • Kinchin, I. M., De-Leij, F. A. A. M., & Hay, D. B. (2005). The evolution of a collaborative concept mapping activity for undergraduate microbiology students. Journal of Further and Higher Education, 29(1), 1–14.

    Article  Google Scholar 

  • Kinchin, I. M., & Hay, D. B. (2007). The myth of the research-led teacher. Teachers and Teaching, 13(1), 43–61.

    Article  Google Scholar 

  • Klein, G., Moon, B. M., & Hoffman, R. R. (2006). Making sense of sensemaking 1: Alternative perspectives. IEEE Intelligent Systems, 21(4), 70–73.

    Article  Google Scholar 

  • Koc, M. (2012). Pedagogical knowledge representation through concept mapping as a study and collaboration tool in teacher education. Australasian Journal of Educational Technology, 28(4), 656–670.

    Article  Google Scholar 

  • Kommers, P., & Lanzing, J. (1997). Students’ concept mapping for hypermedia design: Navigation through world wide web (WWW) space and self-assessment. Journal of Interactive Learning Research, 8(3–4), 421–455.

    Google Scholar 

  • Koopman, M., Teune, P., & Beijaard, D. (2011). Development of student knowledge in competence-based pre-vocational secondary education. Learning Environments Research, 14(3), 205–227.

    Article  Google Scholar 

  • Koponen, I. T., & Nousiainen, M. (2018). Concept networks of students’ knowledge of relationships between physics concepts: Finding key concepts and their epistemic support. Applied Network Science, 3(1), 1–21.

    Google Scholar 

  • Koponen, I. T., & Pehkonen, M. (2010). Coherent knowledge structures of physics represented as concept networks in teacher education. Science & Education, 19(3), 259–282.

    Article  Google Scholar 

  • Kuhn, T. S. (1962). The structure of scientific revolutions (1st ed.). Chicago, IL: University of Chicago Press.

    Google Scholar 

  • Lambiotte, J. G., Dansereau, D. F., Cross, D. R., & Reynolds, S. B. (1989). Multirelational seminatic maps. Educational Psychology Review, 1(4), 331–367.

    Article  Google Scholar 

  • Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. In R. Pea & J. S. Brown (Eds.), Learning in doing: Social, cognitive, and computational perspectives (pp. 29–129). Cambridge, MA: Cambridge University Press.

    Google Scholar 

  • Lehrer, R., & Schauble, L. (2004). Modeling natural variation through distribution. American Educational Research Journal, 41(3), 635–679.

    Article  Google Scholar 

  • Lehrer, R., Schauble, L., Carpenter, S., & Penner, D. (2000). The interrelated development of inscriptions and conceptual understanding. In Symbolizing and communicating in mathematics classrooms: Perspectives on discourse, tools, and instructional design (pp. 325–360). Madison, WI/Mahwah, NJ: University of Wisconsin/Lawrence Erlbaum Associates Publishers.

    Google Scholar 

  • Leinhardt, G., Zaslavsky, O., & Stein, M. K. (1990). Functions, graphs, and graphing: Tasks, learning, and teaching. Review of Educational Research. Special Issue: Toward a Unified Approach to Learning as a Multisource Phenomenon, 60(1), 1–63.

    Google Scholar 

  • Levine, R. (1998). Cognitive lab report (report prepared for the national assessment governing board). Palo Alto, CA: American Institutes for Research.

    Google Scholar 

  • Linn, M. C. (2000). Designing the knowledge integation environment. International Journal of Science Education, 22(8), 781–796.

    Article  Google Scholar 

  • Linn, M. C. (2002). Science education: Preparing lifelong learners. In N. J. Smelser & P. B. Baltes (Eds.), International encyclopedia of the social and behavioral sciences. New York, NY: Pergamon.

    Google Scholar 

  • Linn, M. C. (2008). Teaching for conceptual change: Distinguish or extinguish ideas. In S. Vosniadou (Ed.), International handbook of research on conceptual change. New York, NY: Routledge.

    Google Scholar 

  • Linn, M. C., Chang, H.-Y., Chiu, J., Zhang, H., & McElhaney, K. (2010). Can desirable difficulties overcome deceptive clarity in scientific visualizations? In A. Benjamin (Ed.), Successful remembering and successful forgetting: A Festschrift in honor of Robert A. Bjork. London, UK: Psychology Press.

    Google Scholar 

  • Linn, M. C., Davis, E. A., & Eylon, B.-S. (2004). The scaffolded knowledge integration framework for instruction. In M. C. Linn, E. A. Davis, & P. Bell (Eds.), Internet environments for science education (pp. 47–72). Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Linn, M. C., & Eylon, B. S. (2006). Science education: Integrating views of learning and instruction. In P. A. Alexander & P. H. Winne (Eds.), Handbook of educational psychology (2nd ed., pp. 511–544). Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Linn, M. C., & Hsi, S. (2000). Computers, teachers, peers: Science learning partners. Mahwah, NJ: Lawrence Erlbaum Associates.

    Book  Google Scholar 

  • Linn, M. C., Lee, H.-S., Tinker, R., Husic, F., & Chiu, J. L. (2006). Teaching and assessing knowledge integration in science. Science, 313(5790), 1049–1050.

    Article  Google Scholar 

  • Liu, L., & Hmelo-Silver, C. E. (2009). Promoting complex systems learning through the use of conceptual representations in hypermedia. Journal of Research in Science Teaching, 46, 1023.

    Article  Google Scholar 

  • Liu, O. L., Lee, H. S., & Linn, M. C. (2010). Multifaceted assessment of inquiry-based science learning. Educational Assessment, 15(2), 69–86.

    Article  Google Scholar 

  • Liu, X. (2004). Using concept mapping for assessing and promoting relational conceptual change in science. Science Education, 88(3), 373–396.

    Article  Google Scholar 

  • Liu, X., & Hinchey, M. (1993). The validity and reliability of concept mapping as an alternative science assessment. In The proceedings of the third international seminar on misconceptions and educational strategies in science and mathematics. Ithaca, NY: Misconceptions Trust.

    Google Scholar 

  • Liu, X., & Hinchey, M. (1996). The internal consistency of a concept mapping scoring scheme and its effect on prediction validity. International Journal of Science Education, 18(8), 921–937.

    Article  Google Scholar 

  • Mahler, S., Hoz, R., Fischl, D., Tov-Ly, E., & Lernau, O. Z. (1991). Didactic use of concept mapping in higher education: Applications in medical education. Instructional Science, 20(1), 25–47.

    Article  Google Scholar 

  • Mancinelli, C., Gentili, M., Priori, G., & Valitutti, G. (2004). Concept maps in kindergarten. In Concept maps: Theory, methodology, technology. Proceedings of the first international conference on concept mapping. Pamplona, Spain: Universidad pública de navarra.

    Google Scholar 

  • Maneval, R. E., Filburn, M. J., Deringer, S. O., & Lum, G. D. (2011). Concept mapping: Does it improve critical thinking ability in practical nursing students? Nursing Education Perspectives, 32(4), 229–233.

    Article  Google Scholar 

  • Marcum, J. (2008). Instituting science: Discovery or construction of scientific knowledge? International Studies in the Philosophy of Science, 22, 185–210.

    Article  Google Scholar 

  • Markham, K. M., Mintzes, J. J., & Jones, M. G. (1993). The structure and use of biological knowledge about mammals in novice and experienced students. Paper presented at the third international seminar on misconceptions and educational strategies in science and mathematics, Cornell University, Ithaca, NY, August 1–4, 1993

    Google Scholar 

  • Markham, K. M., Mintzes, J. J., & Jones, M. G. (1994). The concept map as a research and evaluation tool: Further evidence of validity. Journal of Research in Science Teaching, 31(1), 91–101.

    Article  Google Scholar 

  • Markow, P. G., & Lonning, R. A. (1998). Usefulness of concept maps in college chemistry laboratories: Students’ perceptions and effects on achievement. Journal of Research in Science Teaching, 35(9), 1015–1029.

    Article  Google Scholar 

  • Martin, D. J. (1994). Concept mapping as an aid to lesson planning: A longitudinal study. Journal of Elementary Science Education, 6(2), 11–30.

    Article  Google Scholar 

  • Marzano, R. J., Pickering, D., & Pollock, J. E. (2001). Classroom instruction that works: Research-based strategies for increasing student achievement. Alexandria, VA: ASCD.

    Google Scholar 

  • Mason, C. L. (1992). Concept mapping: A tool to develop reflective science instruction. Science Education, 76(1), 51–63.

    Article  Google Scholar 

  • Maton, K., & Doran, Y.J. (n.d.in press, 2016) Semantic density: A translation device for revealing complexity of knowledge practices in discourse, part 1 – Wording, Onomázein, August.

    Google Scholar 

  • Mayr, E. (1988). Toward a new philosophy of biology. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • McClure, J. R., Sonak, B., & Suen, H. K. (1999). Concept map assessment of classroom learning: Reliability, validity, and logistical practicality. Journal of Research in Science Teaching, 36(4), 475–492.

    Article  Google Scholar 

  • McMillan, W. J. (2010). Teaching for clinical reasoning – Helping students make the conceptual links. Medical Teacher, 32, 436–442.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Michael, R. S. (1995). The validity of concept maps for assessing cognitive structure. Dissertation Abstracts International Section A: Humanities and Social Sciences, 55(10-A), 3141.

    Google Scholar 

  • Mintzes, J., & Quinn, H. J. (2007). Knowledge restructuring in biology: Testing a punctuated model of conceptual change. International Journal of Science and Mathematics Education, 5, 281–306.

    Article  Google Scholar 

  • Mintzes, J. J., Wanderersee, J. H., & Novak, J. D. (2001). Assessing understanding in biology. Journal of Biological Education, 35.

    Google Scholar 

  • Mintzes, J. J., Wandersee, J. H., & Novak, J. D. (1997). Meaningful learning in science: The human constructivist perspective. In Handbook of academic learning: Construction of knowledge. The educational psychology series (pp. 405–447). Wilmington, NC/San Diego, CA: University of North Carolina, Department of Biological Science/Academic.

    Chapter  Google Scholar 

  • Mintzes, J. J., Wandersee, J. H., & Novak, J. D. (2000). Assessing science understanding: A human constructivist view. San Diego, CA: Educational Psychology Press/Academic.

    Google Scholar 

  • Mistades, V. M. (2009). Concept mapping in introductory physics. Journal of Education and Human Development, 3(1), 177.

    Google Scholar 

  • Moreira, M. A. (1987). Concept mapping as a possible strategy to detect and to deal with misconceptions in physics. In J. D. Novak (Ed.), Proceedings of the second international seminar “misconceptions and educational strategies in science and mathematics” (Vol. III, pp. 352–360). Ithaca, NY: Cornell University.

    Google Scholar 

  • Morfidi, E., Mikropoulos, A., & Rogdaki, A. (2018). Using concept mapping to improve poor readers’ understanding of expository text. Education and Information Technologies, 23(1), 271–286.

    Article  Google Scholar 

  • Mun, K., Kim, J., Kim, S.-W., & Krajcik, J. (2014). Exploration of high school students concepts about climate change through the use of an issue concept map (ic-map). In International conference on science education 2012 proceedings (pp. 209–222). Springer, Berlin, Heidelberg

    Google Scholar 

  • Nehm, R. H., & Schonfeld, I. S. (2007). Does increasing biology teacher knowledge of evolution and the nature of science lead to greater preference for the teaching of evolution in schools? Journal of Science Teacher Education, 18(5), 699–723.

    Article  Google Scholar 

  • Nejat, N., Kouhestani, H. R., & Rezaei, K. (2011). Effect of concept mapping on approach to learning among nursing students. HAYAT, 17(2), 22–31.

    Google Scholar 

  • Nesbit, J. C., & Adesope, O. O. (2006). Learning with concept and knowledge maps: A meta-analysis. Review of Educational Research, 76(3), 413–448.

    Article  Google Scholar 

  • Nicoll, G., Francisco, J. S., & Nakhleh, M. (2001a). An investigation of the value of using concept maps in general chemistry. Journal of Chemical Education, 78(8), 1111.

    Article  Google Scholar 

  • Nicoll, G., Francisco, J.S., & Nakhleh, M.B. (2001b). A three-tier system for assessing concept map links: A methodological study.

    Google Scholar 

  • Nijman, J. L., Sixma, H., Triest, B. V., Keus, R. B., & Hendriks, M. (2012). The quality of radiation care: The results of focus group interviews and concept mapping to explore the patients perspective. Radiotherapy and Oncology, 102(1), 154–160.

    Article  Google Scholar 

  • Norton, P. B., McConney, A. A., Gallo, M., Woods, A. L., Senn, G. J., & Hamelin, D. (1993). An investigation of the effectiveness of concept mapping as an instructional tool. Science Education, 77(1), 95–111.

    Article  Google Scholar 

  • Novak, J. D. (1980). Meaningful reception learning as a basis for rational thinking. In The psychology of teaching for thinking and creativity. Columbus, Oh: ERIC Clearinghouse for Science, Mathematics and Environmental Education.

    Google Scholar 

  • Novak, J. D., Bob Gowin, D., & Johansen, G. T. (1983). The use of concept mapping and knowledge vee mapping with junior high school science students. Science Education, 67(5), 625–645.

    Article  Google Scholar 

  • Novak, J. D., & Cañas, A. J. (2006). The theory underlying concept maps and how to construct them. Pensacola, FL: IHMC.

    Google Scholar 

  • Novak, J. D., & Gowin, D. B. (1984). Learning how to learn. Cambridge, UK: Cambridge University Press.

    Book  Google Scholar 

  • Nugrahani, R., Prasetyo, A. P. B., & Iswari, R. S. (2018). Authentic assessment of fungi for vocational school student: concept map, self assessment and performance test. Journal of Innovative Science Education, 7(1), 11–24.

    Google Scholar 

  • O’Donnell, A. M., Dansereau, D. F., & Hall, R. H. (2002). Knowledge maps as scaffolds for cognitive processing. Educational Psychology Review, 14(1), 71–86.

    Article  Google Scholar 

  • Odom, A. L., & Kelly, P. V. (2001). Integrating concept mapping and the learning cycle to teach diffusion and osmosis concepts to high school biology students. Science Education, 85(6), 615–635.

    Article  Google Scholar 

  • Oezmen, H., Demircioglu, G., & Coll, R. K. (2007). A comparative study of the effects of a concept mapping enhanced laboratory experience on turkish high school students’ understanding of acid-based chemistry. International Journal of Science and Mathematics Education.

    Google Scholar 

  • Okebukola, P. A. (1992). Concept mapping with a cooperative learning flavor. The American Biology Teacher, 54(4), 218–221.

    Article  Google Scholar 

  • Okebukola, P. A., & Jegede, O. J. (1989). Students’ anxiety towards and perception of difficulty of some biological concepts under the concept-mapping heuristic. Research in Science & Technological Education, 7(1), 85–92.

    Article  Google Scholar 

  • Osborne, R. J., & Wittrock, M. C. (1983). Learning science: A generative process. Science Education, 67(4), 489–508.

    Article  Google Scholar 

  • Osmundson, E., Chung, G., Herl, H., & Klein, D. (1999). Knowledge mapping in the classroom: A tool for examining the development of students’ conceptual understandings. Los Angeles, CA: University of California Los Angeles.

    Google Scholar 

  • Pallant, A., & Tinker, R. F. (2004). Reasoning with atomic-scale molecular dynamic models. Journal of Science Education and Technology, 13(1), 51–66.

    Article  Google Scholar 

  • Pankratius, W. J. (1990). Building an organized knowledge base: Concept mapping and achievement in secondary school physics. Journal of Research in Science Teaching, 27(4), 315–333.

    Article  Google Scholar 

  • Park, H. J. (2007). Components of conceptual ecologies. Research in Science Education, 37(2), 217–237.

    Article  Google Scholar 

  • Parnafes, O., & diSessa, A. A. (2004). Relations between types of reasoning and computational representations. International Journal of Computers for Mathematical Learning, 9(3), 251–280.

    Article  Google Scholar 

  • Pearsall, N., Skipper, J., & Mintzes, J. J. (1997). Knowledge restructuring in the life sciences: A longitudinal study of conceptual change in biology. Science Education, 81(2), 193–215.

    Article  Google Scholar 

  • Pemmaraju, S. V., & Skiena, S. S. (2003). Computational discrete mathematics: Combinatorics and graph theory with mathematica. Cambridge, UK: Cambridge University Press.

    Book  Google Scholar 

  • Penner, D. E. (2000). Explaining systems: Investigating middle school students’ understanding of emergent phenomena. Journal of Research in Science Teaching, 37(8), 784–806.

    Article  Google Scholar 

  • Pirnay-Dummer, P., & Ifenthaler, D. (2010). Automated knowledge visualization and assessment. In D. Ifenthaler, P. Pirnay-Dummer, & N. M. Seel (Eds.), Computer-based diagnostics and systematic analysis of knowledge (pp. 77–115). New York, NY: Springer.

    Chapter  Google Scholar 

  • Plotnick, E. (1997). Concept mapping: A graphical system for understanding the relationship between concepts: An ERIC digest. Clearinghouse on Information & Technology.

    Google Scholar 

  • Popova-Gonci, V., & Lamb, M. C. (2012). Assessment of integrated learning: Suggested application of concept mapping to prior learning assessment practices. The Journal of Continuing Higher Education, 60, 186–191.

    Article  Google Scholar 

  • Preszler, R. (2004). Cooperative concept mapping: Improving performance in undergraduate biology. Journal of College Science Teaching, 33(6), 30–35.

    Google Scholar 

  • Puntambekar, S., Stylianou, A., & Huebscher, R. (2003). Improving navigation and learning in hypertext environments with navigable concept maps. Human Computer Interaction, 18(4), 395–428.

    Article  Google Scholar 

  • Pushkin, D. (1999). Concept mapping and students, physics equations and problem solving. In M. Komorek, H. Behrendt, H. Dahncke, R. Duit, W. Graeber, & A. Kross (Eds.), Research in science education – Past, present, and future (Vol. 1, pp. 260–262). Kiel, Germany: IPN Kiel.

    Google Scholar 

  • Rebich, S., & Gautier, C. (2005). Concept mapping to reveal prior knowledge and conceptual change in a mock summit course on global climate change. Journal of Geoscience Education, 53(4), 355.

    Article  Google Scholar 

  • Reiska, P., Dahncke, H., & Behrendt, H. (1999). Concept maps in a research project on “learning physics and taking action”. In M. Komorek, H. Behrendt, H. Dahncke, R. Duit, W. Graeber, & A. Kross (Eds.), Research in science education – Past, present, and future (Vol. 1, pp. 257–259). Kiel, Germany: IPN Kiel.

    Google Scholar 

  • Reiska, P., Soika, K., & Cañas, A. J. (2018). Using concept mapping to measure changes in interdisciplinary learning during high school. Knowledge Management & E-Learning: An International Journal (KM&EL), 10(1), 1–24.

    Google Scholar 

  • Rice, D. C., Ryan, J. M., & Samson, S. M. (1998). Using concept maps to assess student learning in the science classroom: Must different methods compete? Journal of Research in Science Teaching, 35(10), 1103–1127.

    Article  Google Scholar 

  • Ritchhart, R., Turner, T., & Hadar, L. (2009). Uncovering students’ thinking about thinking using concept maps. Metacognition and Learning, 4, 145–159.

    Article  Google Scholar 

  • Roessger, K. M., Daley, B. J., & Hafez, D. A. (2018). Effects of teaching concept mapping using practice, feedback, and relational framing. Learning and Instruction, 54, 11.

    Article  Google Scholar 

  • Romance, N. R., & Vitale, M. R. (1999). Concept mapping as a tool for learning: Broadening the framework for student-centered instruction. College Teaching, 47(2), 74–79.

    Article  Google Scholar 

  • Roth, W. M. (1993). Using Vee and concept maps in collaborative settings: Elementary education majors construct meaning in physical science courses. School Science and Mathematics, 93(5), 237–244.

    Article  Google Scholar 

  • Roth, W. M. (1994a). Student views of collaborative concept mapping: An emancipatory research project. Science Education, 78(1), 1–34.

    Article  Google Scholar 

  • Roth, W. M. (1994b). Science discourse through collaborative concept mapping – New perspectives for the teacher. International Journal of Science Education, 16(4), 437–455.

    Article  Google Scholar 

  • Roth, W. M., & McGinn, M. K. (1998). Inscriptions: Toward a theory of representing as social practice. Review of Educational Research, 68(1), 35–59.

    Article  Google Scholar 

  • Roth, W. M., & Roychoudhury, A. (1993). The concept map as a tool for the collaborative construction of knowledge: A microanalysis of high school physics students. Journal of Research in Science Teaching, 30(5), 503–534.

    Article  Google Scholar 

  • Royer, R., & Royer, J. (2004). Comparing hand drawn and computer generated concept mapping. Journal of Computers in Mathematics and Science Teaching, 23(1), 67–81.

    Google Scholar 

  • Ruiz-Primo, M. A. (2000). On the use of concept maps as an assessment tool in science: What we have learned so far. Revista Electrónica De Investigación Educativa, 2(1), 30.

    Google Scholar 

  • Ruiz-Primo, M. A., Iverson, H., & Yin, Y. (2009). Towards the use of concept maps in large-scale assessments: Exploring the efficiency of two scoring methods. NARST conference 2009, Garden Grove (CA).

    Google Scholar 

  • Ruiz-Primo, M. A., Schultz, S. E., Li, M., & Shavelson, R. J. (2001). Comparison of the reliability and validity of scores from two concept-mapping techniques. Journal of Research in Science Teaching, 38(2), 260–278.

    Article  Google Scholar 

  • Ruiz-Primo, M. A., Schultz, S. E., & Shavelson, R. J. (1997). Concept map-based assessment in science: Two exploratory studies (CSE report, 436).

    Google Scholar 

  • Ruiz-Primo, M. A., & Shavelson, R. J. (1996). Problems and issues in the use of concept maps in science assessment. Journal of Research in Science Teaching, 33(6), 569–600.

    Article  Google Scholar 

  • Rutledge, M. L., & Mitchell, M. A. (2002). High school biology teachers’ knowledge structure, acceptance and teaching of evolution. American Biology Teacher, 64(1), 21–28.

    Article  Google Scholar 

  • Rye, J. A., & Rubba, P. A. (2002). Scoring concept maps: An expert map-based scheme weighted for relationships. School Science and Mathematics, 102(1), 33–44.

    Article  Google Scholar 

  • Safayeni, F., Derbentseva, N., & Canas, A. J. (2005). A theoretical note on concepts and the need for cyclic concept maps. Journal of Research in Science Teaching, 42(7), 741–766. https://doi.org/10.1002/tea.20074

    Article  Google Scholar 

  • Santhanam, E., Leach, C., & Dawson, C. (1998). Concept mapping: How should it be introduced, and is there evidence for long term benefit? Higher Education, 35(3), 317–328.

    Article  Google Scholar 

  • Sarhangi, F., Masoumy, M., Ebadi, A., Seyyed Mazhari, M., Rahmani, A., & Raisifar, A. (2011). Effect of concept mapping teaching method on critical thinking skills of nursing students. Iranian Journal of Critical Care Nursing (IJCCN). 143–148.

    Google Scholar 

  • Scaife, M., & Rogers, Y. (1996). External cognition: How do graphical representations work? International Journal of Human Computer Studies, 45(2), 185–213.

    Article  Google Scholar 

  • Scardamalia, M., & Bereiter, C. (1991). Literate expertise. In Toward a general theory of expertise. Prospects and limits (pp. 172–194). Cambridge, UK: Cambridge University Press.

    Google Scholar 

  • Schaap, H., Van der Schaaf, M. F., & De Bruijn, E. (2011). Development of students’ personal professional theories in senior secondary vocational education. Evaluation & Research in Education, 24(2), 81–103.

    Article  Google Scholar 

  • Schau, C., & Mattern, N. (1997). Assessing students’ connected understanding of statistical relationships. From Gal, I. & Garfield, J. B. (editors). The Assessment Challenge in Statistics Education. IOS Press, 1997 (on behalf of the ISI). ISBN 90 5199 333 1, (pp. 91–104).

    Google Scholar 

  • Schau, C., Mattern, N., Weber, R., Minnick, K., & Witt, C. (1997). Use of fill-in concept maps to assess middle school students’ connected understanding of science. AERA annual meeting, Chicago, IL.

    Google Scholar 

  • Schauble, L., Glaser, R., Duschl, R. A., Schulze, S., & John, J. (1995). Students’ understanding of the objectives and procedures of experimentation in the science classroom. The Journal of the Learning Sciences, 4(2), 131–166.

    Article  Google Scholar 

  • Schmid, R. F., & Telaro, G. (1990). Concept mapping as an instructional strategy for high school biology. Journal of Educational Research, 84(2), 78–85.

    Article  Google Scholar 

  • Schuster, P. M. (2011). Concept mapping: A critical thinking approach to care planning. Philadelphia, PA: FA Davis.

    Google Scholar 

  • Schvaneveldt, R. W., Durso, F. T., Goldsmith, T. E., Breen, T. J., Cooke, N. M., Tucker, R. G., & DeMaio, J. C. (1985). Measuring the structure of expertise. International Journal of Man-Maschine Studies, 23, 699–728.

    Article  Google Scholar 

  • Schwarz, C. V., & White, B. Y. (2005). Metamodeling knowledge: Developing students’ understanding of scientific modeling. Cognition and Instruction, 23(2), 165–205.

    Article  Google Scholar 

  • Schwendimann, B. A. (2007). Integrating interactive genetics visualizations into high school biology. Annual meeting of the American Educational Research Association, Chicago, IL.

    Google Scholar 

  • Schwendimann, B. A. (2009). Scaffolding an integrated understanding of biology through dynamic visualizations and critique-focused concept mapping. Annual meeting of the American Education Research Association (AERA), San Diego, CA.

    Google Scholar 

  • Schwendimann, B. A. (2011a). Mapping biological ideas: Concept maps as knowledge integration tools for evolution education (Dissertation). Retrieved from http://search.proquest.com/docview/928947890?accountid=1475

  • Schwendimann, B. A. (2011b). Integrating genotypic and phenotypic ideas of evolution through critique-focused concept mapping. AERA annual meeting 2011, New Orleans, LA.

    Google Scholar 

  • Schwendimann, B. A. (2011c). Linking genotypic and phenotypic ideas of evolution through collaborative critique-focused concept mapping. In Proceedings of the 9th international conference on computer-supported collaborative learning (CSCL). Hong Kong, China: CSCL Conference.

    Google Scholar 

  • Schwendimann, B. A. (2014a). Making sense of knowledge integration maps. In D. Ifenthaler & R. Hanewald (Eds.), Digital knowledge maps in education: Technology enhanced support for teachers and learners. New York, NY: Springer.

    Google Scholar 

  • Schwendimann, B. A. (2014b). Comparing two forms of concept map critique activities to support knowledge integration in biology education. In Proceedings of the sixth international conference on concept mapping. Santos, Brazil: International Conference on Concept Mapping.

    Google Scholar 

  • Schwendimann, B. A., & Linn, M. C. (2015). Comparing two forms of concept map critique activities to facilitate knowledge integration processes in evolution education. Journal of Research in Science Teaching, 4, 70–94

    Google Scholar 

  • Shavelson, R. J., Ruiz-Primo, M. A., & Wiley, E. W. (2005). Windows into the mind. Higher Education, 49(4), 413–430.

    Article  Google Scholar 

  • Shawli, A. S. (2018). Concept mapping as an assessment of cognitive load and mental effort in complex problem solving in chemistry (Doctoral thesis). Montana State University.

    Google Scholar 

  • Shen, J. (2010). Nurturing students’ critical knowledge using technology-enhanced scaffolding strategies in science education. Journal of Science Education and Technology, 19(1), 1–12. https://doi.org/10.1007/s10956-009-9183-1

    Article  Google Scholar 

  • Shen, J., & Confrey, J. (2007). From conceptual change to transformative modeling: A case study of an elementary teacher in learning astronomy. Science Education, 91(6), 948–966.

    Article  Google Scholar 

  • Shen, J., & Confrey, J. (2010). Justifying alternative models in learning the solar system: A case study on K-8 science teachers’ understanding of frames of reference. International Journal of Science Education, 32(1), 1–29.

    Google Scholar 

  • Silva, J. H. D., Foureaux, G., Sá, M. A. D., Schetino, L. P. L., & Guerra, L. B. (2018). The teaching and learning of human anatomy: The assessment of student performance after the use of concept maps as a pedagogical strategy. Ciência & Educação (Bauru), 24(1), 95–110.

    Article  Google Scholar 

  • Sizmur, S., & Osborne, J. (1997). Learning processes and collaborative concept mapping. International Journal of Science Education, 19(10), 1117–1135.

    Article  Google Scholar 

  • Slotta, J. D., Chi, M. T. H., & Joram, E. (1995). Assessing students’ misclassifications of physics concepts: An ontological basis for conceptual change. Cognition and Instruction, 13(3), 373–400.

    Article  Google Scholar 

  • Slotta, J. D., & Linn, M. C. (2000). How do students make sense of Internet resources in the science classroom? In M. J. Jacobson & R. Kozma (Eds.), Learning the sciences of the 21st century (pp. 193–226). Hillsdale, NJ: Lawrence Erlbaum & Associates.

    Google Scholar 

  • Snead, D., & Snead, W. L. (2004). Concept mapping and science achievement of middle grade students. Journal of Research in Childhood Education, 18(4), 306–320.

    Article  Google Scholar 

  • Songer, N. B. (2006). Biokids: An animated conversation on the development of curricular activity structures for inquiry science. In R. K. Sawyer (Ed.), Cambridge handbook of the learning sciences (pp. 355–369). New York, NY: Cambridge University Press.

    Google Scholar 

  • Spaulding, D. T. (1989). Concept mapping and achievement in high school biology and chemistry. Dissertation. Florida. Institute of Technology.

    Google Scholar 

  • Starr, M. L., & Krajcik, J. S. (1990). Concept maps as a heuristic for science curriculum development: Toward improvement in process and product. Journal of Research in Science Teaching, 27(10), 987–1000.

    Article  Google Scholar 

  • Stensvold, M. S., & Wilson, J. T. (1990). The interaction of verbal ability with concept mapping in learning from a chemistry laboratory activity. Science Education, 74(4), 473–480.

    Article  Google Scholar 

  • Stewart, J. (1979). Concept maps: A tool for use in biology teaching. American Biology Teacher, 41(3), 171–175.

    Article  Google Scholar 

  • Stice, C. F., & Alvarez, M. C. (1987). Hierarchical concept mapping in the early grades. Childhood Education, 64(2), 86–96.

    Article  Google Scholar 

  • Stoddart, T., Abrams, R., Gasper, E., & Canaday, D. (2000). Concept maps as assessment in science inquiry learning-a report of methodology. International Journal of Science Education, 22(12), 1221–1246.

    Article  Google Scholar 

  • Strike, K. A., & Posner, G. J. (1992). A revisionist theory of conceptual change. In R. A. Duschl & R. J. Hamilton (Eds.), Philosophy of science, cognitive psychology, and educational theory and practice. Albany, NY: State University of New York Press.

    Google Scholar 

  • Sun, J. C.-Y., Hwang, G.-J., Lin, Y.-Y., Yu, S.-J., Pan, L.-C., & Chen, A. Y.-Z. (2018). A votable concept mapping approach to promoting students’ attentional behavior: An analysis of sequential behavioral patterns and brainwave data. Journal of Educational Technology & Society, 21(2), 177–191.

    Google Scholar 

  • Sundararajan, N., Adesope, O., & Cavagnetto, A. (2018). The process of collaborative concept mapping in Kindergarten and the effect on critical thinking skills. Journal of STEM Education, 19(1), 5–13.

    Google Scholar 

  • Suprapto, N., Prahani, B. K., Jauhariyah, M. N. R., & Admoko, S. (2018). Exploring physics concepts among novice teachers through CMAP tools. Proceedings from Journal of Physics: Conference Series, 997(1), 1–7.

    Google Scholar 

  • Sweller, J., Van Merrienboer, J. J. G., & Paas, F. G. W. C. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251–296.

    Article  Google Scholar 

  • Syarifuddin, H. (2018). The effect of using concept maps in elementary linear algebra course on students’ learning. Proceedings from IOP Conference Series: Materials Science and Engineering, 335(1), 1–4.

    Article  Google Scholar 

  • Tabak, I., Weinstock, M., & Zvilling-Beiser, H. (2009). Epistemology and learning in the disciplines: Cross-domain epistemological views of science versus humanities students. In J. Shen (Ed.), Critique to learn science. Symposium conducted at the meeting of the national association for research in science teaching, Garden Grove, CA.

    Google Scholar 

  • Taylor, L. A., & Littleton-Kearney, M. (2011). Concept mapping: A distinctive educational approach to foster critical thinking. Nurse Educator, 36(2), 84–88.

    Article  Google Scholar 

  • Trowbridge, J. E., & Wandersee, J. H. (1994). Identifying critical junctures in learning in a college course on evolution. Journal of Research in Science Teaching, 31(5), 459–473.

    Article  Google Scholar 

  • Trowbridge, J. E., & Wandersee, J. H. (1996). How do graphics presented during college biology lessons affect students’ learning? Journal of College Science Teaching, 26(1), 54–57.

    Google Scholar 

  • Tsai, C.-C., & Huang, C.-M. (2002). Exploring students’ cognitive structures in learning science: A review of relevant methods. Journal of Biological Education, 36(4), 163–169.

    Article  Google Scholar 

  • Tseng, H.-C., Chou, F.-H., Wang, H.-H., Ko, H.-K., Jian, S.-Y., & Weng, W.-C. (2011). The effectiveness of problem-based learning and concept mapping among Taiwanese registered nursing students. Nurse Education Today, 31(8), 41–46.

    Article  Google Scholar 

  • Tsui, C., & Treagust, D. (2010). Evaluating secondary students’ scientific reasoning in genetics using a two-tier diagnostic instrument. International Journal of Science Education, 32(8), 1073–1098.

    Article  Google Scholar 

  • Turan-Oluk, N., & Ekmekci, G. (2018). The effect of concept maps, as an individual learning tool, on the success of learning the concepts related to gravimetric analysis. Chemistry Education Research and Practice, 19, 819–833.

    Article  Google Scholar 

  • Uzuntiryaki, E., & Geban, O. (2005). Effect of conceptual change approach accompanied with concept mapping on understanding of solution concepts. Instructional Science, 33(4), 311–339.

    Article  Google Scholar 

  • van Amelsvoort, M., Andriessen, J., & Kanselaar, G. (2005). Using representational tools to support historical reasoning in computer-supported collaborative learning. Technology, Pedagogy and Education, 14(1), 25–41.

    Article  Google Scholar 

  • Van Bommel, M., Kwakman, K., & Boshuizen, H. P. (2012). Experiences of social work students with learning theoretical knowledge in constructivist higher vocational education: A qualitative exploration. Journal of Vocational Education & Training, 64(4), 529–542.

    Article  Google Scholar 

  • Van Merriënboer, J. J. G. (1990). Strategies for programming instruction in high school: Program completion vs. Program generation. Journal of Educational Computing Research, 6(3), 265–285.

    Article  Google Scholar 

  • Van Neste-Kenny, J., Cragg, C. E. B., & Foulds, B. (1998). Using concept maps and visual representations for collaborative curriculum development. Nurse Educator, 23(6), 21–25.

    Article  Google Scholar 

  • Van Zele, E., Lenaerts, J., & Wieme, W. (2004). Improving the usefulness of concept maps as a research tool for science education. International Journal of Science Education, 26(9), 1043–1064.

    Article  Google Scholar 

  • Veo, P. (2010). Concept mapping for applying theory to nursing practice. Journal for Nurses in Professional Development, 26(1), 17–22.

    Article  Google Scholar 

  • Vilela, R., Austrilino, L., & Costa, A. (2004). Using concept maps for collaborative curriculum development. In Proceedings of the first international conference on concept mapping, Pamplona, Spain.

    Google Scholar 

  • Walker, J. M. T., & King, P. H. (2003). Concept mapping as a form of student assessment and instruction in the domain of bioengineering. Journal of Engineering Education, 92(2), 167–178.

    Google Scholar 

  • Wallace, J. D., & Mintzes, J. J. (1990). The concept map as a research tool: Exploring conceptual change in biology. Journal of Research in Science Teaching, 27(10), 1033–1052.

    Article  Google Scholar 

  • Wandersee, J. H. (1996). Bioinstrumentation: Tools for understanding life. Reston, WA: National Association of Biology Teachers.

    Google Scholar 

  • Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications (p. 825). Cambridge, UK: Cambridge University Press.

    Book  Google Scholar 

  • Watson, C. E. (2005). Graphic organizers: Toward organization and complexity of student content knowledge (Dissertation).

    Google Scholar 

  • Weick, K. E. (1995). Sensemaking in organizations (Vol. 3). Thousand Oaks: Sage.

    Google Scholar 

  • Weinstein, C. E., & Mayer, R. E. (1983). The teaching of learning strategies. Innovation Abstracts, 5, 4.

    Google Scholar 

  • Wenger, E. (1998). Communities of practice: Learning, meaning and identity. Cambridge, UK: Cambridge University Press.

    Book  Google Scholar 

  • West, D. C., Pomeroy, J. R., Park, J. K., Gerstenberger, E. A., & Sandoval, J. (2000). Critical thinking in graduate medical education: A role for concept mapping assessment? JAMA, 284(9), 1105.

    Article  Google Scholar 

  • Wisdom Soft. (2016). Autoscreenrecorder 2.0. Autoscreenrecorder 2.0 [Computer Software].

    Google Scholar 

  • Wise, A. M. (2007). Map it: How concept mapping affects understanding of evolutionary processes (Thesis).

    Google Scholar 

  • Yin, Y., Vanides, J., Ruiz-Primo, M. A., Ayala, C. C., & Shavelson, R. J. (2005). Comparison of two concept-mapping techniques: Implications for scoring, interpretation, and use. Journal of Research in Science Teaching, 42(2), 166–184.

    Article  Google Scholar 

  • Zeilik, M., Schau, C., Mattern, N., Hall, S., Teague, K. W., & Bisard, W. (1997). Conceptual astronomy: A novel model for teaching postsecondary science courses. American Journal of Physics, 65, 987.

    Article  Google Scholar 

  • Ruiz-Primo, M. A., Iverson, H., & Yin, Y. (2009). Towards the use of concept maps in large-scale assessments: Exploring the efficiency of two scoring methods. NARST conference 2009, Garden Grove (CA).

    Google Scholar 

Download references

Acknowledgments

The research for this chapter was supported by the National Science Foundation grant DRL-0334199 (“The Educational Accelerator: Technology Enhanced Learning in Science”).

Disclaimer

Parts of this chapter have been previously published by the author in the form of a dissertation, journal articles, and book chapters.

Author information

Authors and Affiliations

  1. University of California, Berkeley, CA, USA

    Beat Adrian Schwendimann

Authors
  1. Beat Adrian Schwendimann
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Beat Adrian Schwendimann .

Editor information

Editors and Affiliations

  1. College of Info, Ste G150, Univ of North Texas, Denton, TX, USA

    Michael J Spector

  2. School of Education, Virginia Tech, Blacksburg, VA, USA

    Barbara B Lockee

  3. School of Education, Baker University, Overland Park, KS, USA

    Marcus D. Childress

Section Editor information

  1. Learning, Design and Technology, University of Mannheim, Mannheim, Germany

    Dirk Ifenthaler

  2. Curtin University, Perth, WA, Australia

    Dirk Ifenthaler

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Schwendimann, B.A. (2019). Concepts Maps as Versatile Learning, Teaching, and Assessment Tools. In: Spector, M., Lockee, B., Childress, M. (eds) Learning, Design, and Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-17727-4_86-1

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-17727-4_86-1

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17727-4

  • Online ISBN: 978-3-319-17727-4

  • eBook Packages: Springer Reference EducationReference Module Humanities and Social SciencesReference Module Education

Publish with us

Policies and ethics

Chapter history

  1. Latest

    Concepts Maps as Versatile Learning, Teaching, and Assessment Tools
    Published:
    04 July 2023

    DOI: https://doi.org/10.1007/978-3-319-17727-4_86-2

  2. Original

    Concepts Maps as Versatile Learning, Teaching, and Assessment Tools
    Published:
    06 December 2019

    DOI: https://doi.org/10.1007/978-3-319-17727-4_86-1

Search

Navigation