Concepts maps is a graphical means to organize and represent knowledge (see Novak, 1991, 1998). The maps include the following features:
The concept map usually pertains to a specific issue, called the focus question, such as "How do managers decide which employees to recruit?" Three characteristics of these maps generate insight and creativity. First, most concept maps are hierarchical, with the broadest concepts at the top. Second, specific examples of events or objects are often included to exemplify a concept. These features are summarized in the concept map below, a hierarchical map presented by Novak and Cañas (2008).
Lord, Desforges, Fein, Pugh, and Lepper (1994) demonstrate the construction of a concept map, associated with a common cold. The author began with a blank paper, with the concept "the common cold" written at the top. First, the author thought of symptoms, such as chest congestion and runny nose. A line was drawn from a circle labelled common cold to a circle labelled symptoms. Lines were also drawn from this circle labelled symptoms to smaller circles, each specifying a particular symptom. During this process, thoughts of other symptoms were entertained, and hence additional smaller circles were added accordingly.
Next, the author thought of treatments, such as bed rest, cold pills, doctor, and so forth--and again a circle was created to represent treatments and smallers circles created to represent each treatment, and so forth. Other sets of concepts were later added, such as types of individuals who are most likely to experience colds, and so forth. In addition, a +, 0, or - was added to each node, to represent whether the concept was positive or negative.
The format of concept maps can be divided into several principal types, such as hierarchy, systems, spider, and landscape maps. Examples, derived from http://classes.aces.uiuc.edu/ACES100/Mind/c-m4.html, are presented below. Other maps include flowcharts and multidimensional maps.
Concept maps were derived from the learning psychology of Ausubel (1963;; 1968). According to this perspective, learning involves the assimilation of novel concepts and propositions-that is, statements that relate to or more concepts together-into the extant concepts and propositions of individuals. In this context, concepts are sometimes equated to atoms, whereas propositions are equated to molecules. Concept maps were then developed by Novak (1972) to represent these cognitive structures.
According to this underpinning, children begin to recognize regularities in their environment from birth, called the discovery learning process. After age 3, this awareness of regularities becomes mediated by language, in which the begin to ask questions that integrate new concepts and propositions and their extant concepts and propositions. This phase, called the reception learning process, entails an interchange between themselves and other individuals.
Concept maps were designed to facilitate this learning process. For example, learning is more meaningful if the material to be acquired is related to the prior knowledge of learners. Concept maps can thus be utilized to clarify this knowledge base. Second, concept maps can highlight that relationship between new and old concepts or propositions, which fosters meaningful rather than rote learning (see Chularut & DeBacker, 2004), even if teachers are reasonably prescriptive. In contrast, rote learning does not extend knowledge appreciably. Third, concept maps can uncover misconceptions and are occasionally used to assess student learning (see Rafferty & Fleschner, 1993).
In addition, concept maps can facilitate memory, by forming larger units of information and organizing knowledge coherently, hierarchically, visually, and spatially-characteristic that facilitate memory processes (Einstein, McDaniel, Bowers, & Stevens, 1984;; Novak & Wandersee, 1991;; see also www.mlrg.org). Fifth, concept maps facilitate collaboration in the learning domain, which expedites the acquisition of knowledge (see Boxtel, Linden, Roelofs, & Erkens, 2002;; Preszler, 2004).
Novak (1977, 1993, 1998) argues that two factors facilitate the creation of new knowledge. First, the individuals must have formed an organized, comprehensive knowledge structure in some domain. Second, they must experience the emotional motivation to pursue new meaning. In other words, progress is a function of both knowledge and emotion or drive.
Other forms of concept maps present other benefits. Trochim and Kane (2005) discussed a form of concept maps that combine the perceptions of multiple participants. This procedure can be used to analyze qualitative data, overcoming limitations with other approaches.
Concept maps can be derived from personal reflections or empirical studies. To derive concept maps from personal reflections, several phases need to be implemented (for examples, see Lord, Desforges, Fein, Pugh, & Lepper, 1994).
First, choose a domain with which you are familiar-a topic you know well, such as an issue that you often need to solve. Second, specify a focus question, which is a question that specifies the topic or issue that you would like to resolve, such as "What is wellbeing?" Third, list a series of concepts, between 15 and 25 words for example, that you feel are related to this question. The questions what, where, when, who, why, and how are generate some responses. Fourth, rank these concepts from the most general and inclusive to the most specific or concrete, at least roughly. Fifth, construct a preliminary map, placing the more general concepts towards the top-either using Post-it notes or a software package. Sixth, specify links or draw lines between concepts;; use words to describe these relationships, such as "in part of", "is near", "will prevent", and so forth. Seventh, change the position of concepts to improve clarity and appearance. Finally, continue refining the map.
Trochim and Kane (2005) enumerate six phases that can be implemented to create a concept map, representing the knowledge structures of groups rather than individuals, from the responses of participants to open questions (see also Jackson & Trochim, 2002;; Trochim, 1989). Usually, the participants are individuals who have been exposed to the topic of interest. For example, to improve a health care system, participant might include health care workers or patients.
First, participants are asked to generate a series of answers to a focus question, such as "What factors affect wellbeing at work?", called brainstorming. They might generate between 10 and 100 answers, such as mood of supervisor, physical space, excessive workload, and so forth. Similarly, they might generate 20 benefits and drawbacks to answer the question "Should the organization introduce affirmative action?", such as "Reduces credibility of females" or "Improves culture".
Second, each of the answers is presented on separate cards. The role of participants is to sort these cards into groups, according to any classification system. They can sort the cards into as many categories as they feel are appropriate. For example, one participant might sort mood of supervisor, morale, and motivation in the same category. Another participant might sort these answers into separate categories.
Third, this classification of cards is subjected to statistical analysis, often using Concept Mapping Software for multivariate statistical analysis, to create a concept map. All the answers appear on a map. Answers that tend to be placed in separate categories appear farther away from each other. Answers that tend to be placed in the same category appear close to one another. Indeed, if very close to each other, these answers are assumed to reflect the same concept, called a cluster. Usually, multidimensional scaling is used to place the answers on the map and cluster analysis is used to uncover the clusters (Jackson & Trochim, 2002).
Fourth, after this concept map is created, participants are then granted an opportunity to name each cluster. A cluster that includes mood of supervisor, morale, and motivation might be labeled "Emotional factors" for example.
Fifth, participants consider whether any of the answers perhaps should do not align to the cluster in which they appear. These answers could be shifted to another cluster.
Sixth, participants might rate the various answers. They might, for example, rate the extent to which each answer is important. For example, they could evaluate the degree to which these factors affect wellbeing. Second, they might rate the effect of each answer-in this instance, whether the factors enhance or compromise wellbeing. Later, researchers can then calculate, for example, the mean importance and effect of each answer or each cluster.
This software, which can be downloaded from http://cmap.ihmc.us, presents many benefits. For example, when individuals create links, the software can reposition the concepts to promote clarity and organization. Second, even individuals located in different places can collaborate to create the concept map. Third, individuals can then link resources, such as images, videos, web pages, and tables, to the maps, which other internet uses can access and utilize. Thus, concept maps provide a form of indexing.
The software also includes many other features. For example, the process of constructing a concept map can be retraced. Second, the maps can be presented in a piecemeal fashion, to organize oral presentations.
Other packages
For other packages, see:
All, A., Huycke, L., & Fisher, M. (2003). Instructional tools for nursing education: Concept maps. Nursing Education Perspectives, 24(6), 311-317.
Ausubel, D. P. (1963). The psychology of meaningful verbal learning. New York: Grune and Stratton.
Ausubel, D. P. (1968). Educational psychology: A cognitive view. New York: Holt, Rinehart and Winston.
Ausubel, D. P., Novak, J. D., & Hanesian, H. (1978). Educational psychology: A cognitive view (2nd ed.). New York: Holt, Rinehart and Winston.
Baugh, N., & Mellott, K. (1998). Clinical concept mapping as preparation for student nurses' experiences. Journal of Nursing Education, 37(6), 253-257.
Boxtel, C. V., Linden, J. V., Roelofs, E., & Erkens, G. (2002). Collaborative concept mapping: Provoking and supporting meaningful discourse. Theory and Practice, 41, 40-46.
Bransford, J., Brown, A. L., & Cocking, R. R. (Eds.). (1999). How people learn: Brain, mind, experience, and school. Washington, D.C.: National Academy Press.
Cañas, A. J., Ford, K. M., Novak, J. D., Hayes, P., Reichherzer, T., & Suri, N. (2001). Online concept maps: Enhancing collaborative learning by using technology with concept maps. The Science Teacher, 68, 49-51.
Carley, K., & Kaufer, D. (1993). Semantic connectivity: An approach for analyzing symbols in semantic networks. Communication Theory, 3, 183-213.
Carley, K., & Palmquist, M. (1992). Extracting, representing, and analyzing mental models. Social Forces, 70, 601-636.
Chang, K., Sung, Y., & Chen, I. (2002). The effect of concept mapping to enhance text comprehension and summarization. Journal of Experimental Education, 71, 5-23.
Chularut, P., & DeBacker, T. K. (2004). The influence of concept mapping on achievement, self-regulation, and self-efficacy in students of English as a second language. Contemporary Educational Psychology, 29, 248-263.
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, 303-320
Daley, B., Shaw, C., Balistrieri, T., Glasenapp, K., & Piacentine, L. (1999). Concept maps: A strategy to teach and evaluate critical thinking. Journal of Nursing Education, 38, 42-47.
Edwards, J., & Fraser, K. (1983). Concept maps as reflections of conceptual understanding. Research in Science Education, 13, 19-26.
Einstein, G. O., McDaniel, M. A., Bowers, C. A., & Stevens, D. T. (1984). Memory for prose: The influence of relational and proposition-specific processing. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10, 133-143.
Esiobu, G. O., & Soyibo, K. (1995). Effects of concept and vee mappings under three learning modes on students, cognitive achievement in ecology and genetics. Journal of Research in Science Teaching, 32, 971-995.
Ford, K. M., Cañas, A. J., Jones, J., Stahl, H., Novak, J. D., & Adams-Webber, J. (1991). Iconkat: An integrated constructivist knowledge acquisition tool. Knowledge Acquisition, 3, 215-236.
Guastello, E. F., Beasley, M., & Sinatra, R. C. (2000). Concept mapping effects on science content comprehension of low-achieving inner-city seventh graders. Remedial and Special Education, 21, 356-365.
Hoffman, R. R., Shadbolt, N. R., Buton, A. M., & Klein, G. (1995). Eliciting knowledge from experts: A methodological analysis. Organizational Behavior and Human Design Processes, 62, 129-158.
Horton, P. B., McConney, A. A., Gallo, M., & Woods, A. L. (1993). An investigation of the effectiveness of concept mapping as an instructional tool. Science Education, 77, 95-111.
Jackson, K., and Trochim, W. (2002). Concept mapping as an alternative approach for the analysis of open-ended survey responses. Organizational Research Methods, 5, 307-336.
Jegede, O. J., Alaiyemola, F. F., & Okebukola, P. A. (1990). The effect of concept mapping on students' anxiety and achievement in biology. Journal of Research in Science Teaching, 27, 951-960.
Lehman, J. D., Carter, C., & Kahle, J. B. (1985). Concept mapping, vee mapping, and achievement: Results of a field study with black high school students. Journal of Research in Science Teaching, 22, 663-673.
Lord, C. G., Desforges, D. M., Fein, S., Pugh, M. A., & Lepper, M. R. (1994). Typicality effects in attitudes toward social policies: A concept-mapping approach. Journal of Personality and Social Psychology, 66, 658-673.
Minagawa, J. (1999). Effect of making linking labels in concept mapping. Japanese Journal of Educational Psychology, 47, 328-334.
Mintzes, J. J., Wandersee, J. H., & Novak, J. D. (1998). Teaching science for understanding: A human constructivist view. San Diego: Academic Press.
Mintzes, J. J., Wandersee, J. H., & Novak, J. D. (2000). Assessing science understanding: A human constructivist view. San Diego: Academic Press.
Nicoll, G., Francisco, J., & Nakhleh, M. (2001). An investigation of the value of using concept maps in general chemistry. Journal of Chemical Education, 78, 1111-1117
Novak, J. D. (1977). A theory of education. Ithaca, NY: Cornell University Press.
Novak, J. D. (1990). Concept maps and vee diagrams: Two metacognitive tools for science and mathematics education. Instructional Science, 19, 29-52.
Novak, J. D. (1991). Clarify with concept maps: A tool for students and teachers alike. The Science Teacher, 58, 45-49.
Novak, J. D. (1993). Human constructivism: A unification of psychological and epistemological phenomena in meaning making. International Journal of Personal Construct Psychology, 6, 167-193.
Novak, J. D. (1995). Concept maps to facilitate teaching and learning. Prospects, 25, 95-111.
Novak, J. D. (1998). Learning, creating, and using knowledge: Concept maps as facilitative tools in schools and corporations. Mahwah, NJ: Lawrence Erlbaum Associates.
Novak, J. D. (2002). Meaningful learning: The essential factor for conceptual change in limited or appropriate propositional hierarchies leading to empowerment of learners. Science Education, 86, 548-571.
Novak, J. D. & A. J. Cañas (2008). The theory underlying concept maps and how to construct them. Technical Report IHMC CmapTools, 2006-01 Rev 01-2008, Florida Institute for Human and Machine Cognition, 2008", available at: http://cmap.ihmc.us/Publications/ResearchPapers/TheoryUnderlyingConceptMaps.pdf.
Novak, J. D., & Gowin, D. B. (1984). Learning how to learn. New York, NY: Cambridge University Press.
Novak, J. D., & Musonda, D. (1991). A twelve-year longitudinal study of science concept learning. American Educational Research Journal, 28, 117-153.
O'Donnell, A., Dansereau, D., & Hall, R. H. (2002). Knowledge maps as scaffolds for cognitive processing. Educational Psychology Review, 14, 71-86.
Okebukola, P. A. (1990). Attaining meaningful learning of concepts in genetics and ecology: An examination of the potency of the concept-mapping technique. Journal of Research in Science Teaching, 27, 493-504.
Okebukola, P. A. (1992). Concept mapping with a cooperative learning flavor. American Biology Teacher, 54, 218-221.
Okebukola, P. A., & Jegede, O. J. (1988). Cognitive preference and learning-mode as determinants of meaningful learning through concept mapping. Science Education, 72, 489-500.
Preszler, R. W. (2004). Cooperative concept mapping improves performance in biology. Journal of College Science Teaching, 33, 30-35.
Quinn, H., Mintzes, J., & Laws, R. (2004). Successive concept mapping: Assessing understanding in college science classes. Journal of College Science Teaching, 33, 12-16.
Rafferty, C. D., & Fleschner, L. K. (1993). Concept mapping: A viable alternative to objective and essay exams. Reading, Research, and Instruction, 32, 25-33.
Reader, W., & Hammond, N. (1994). Computer-based tools to support learning from hypertext: Concept mapping tools and beyond. Computers Education, 22, 99-106.
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, 503-534.
Schmid, R. F., & Telaro, G. (1990). Concept mapping as an instructional strategy for high school biology. Journal of Educational Research, 84, 78-85.
Schuster, P. (2002). Concept mapping: A critical-thinking approach to care planning. Philadelphia: FA Davis.
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, 473-480.
Stoyanova, N., & Kommers, P. (2002). Concept mapping as a medium of shared cognition in computer-supported collaborative problem solving. Journal of Interactive Learning Research, 13, 111-133.
Takumi, I. (2001). Hierarchical concept maps: Effect on writing. Japanese Journal of Educational Psychology, 49, 11-20.
Trochim, W. (1989). An introduction to concept mapping for planning and evaluation. Evaluation and Program Planning, 12, 1-16.
Trochim W, & Kane, M. (2005). Concept mapping: An introduction to conceptualization in health care. International Journal for quality in health care, 17, 187-191.
Tsien, J. Z. (2007). The memory, Scientific American, July, 52-59.
Vitale, M. R., & Romance, N. R. (2000). Portfolios in science assessment: A knowledge-based model for classroom practice. In J. J. Mintzes, J. H. Wandersee & J. D. Novak (Eds.), Assessing science understanding: A human constructivist view. San Diego, CA: Academic Press.
West, D., Pomeroy, J., Park, J., Gerstenberger, E., & Jonathan, S. (2000). Critical thinking in graduate medical education: A role for concept mapping assessment? Journal of the American Medical Association, 284, 1105-1111.
Willerman, M., & Mac Harg, R. A. (1991). The concept map as an advance organizer. Journal of Research in Science Teaching, 28, 705-712.
Winn, W. (1991). Learning from maps and diagrams. Educational Psychology Review, 3, 211-247.
Last Update: 6/2/2016