An Embedded and Embodied Cognition Review of Instructional Manipulatives

Educational Psychology Review

Volumn 26, Issue 1, 2014, Pages 51-72

  Pouw, Wim T J L ^a   van Gog, Tamara ^a   Paas, Fred ^a,b  

^a ERASMUS UNIVERSITY ROTTERDAM   (Netherlands)

^b UNIVERSITY OF WOLLONGONG   (Australia)

Author keywords

Embedded cognition; Embodied cognition; Instructional manipulatives

Indexed keywords

EID: 84894301646     PISSN: 1040726X     EISSN: 1573336X     Source Type: Journal    
DOI: 10.1007/s10648-014-9255-5     Document Type: Review

References (129)

1. Anderson, M. L. (2008). On the grounds of (X)-grounded cognition. In P. Calvo & T. Gomila (Eds.), Handbook of cognitive science: an embodied approach (pp. 423-435). New York: Elsevier.
2. Andres, M., Seron, X., & Oliver, E. (2007). Contribution of hand motor circuits to counting. Journal of Cognitive Neuroscience, 19, 563-576.
3. Antle, A. N. (2012). Exploring how children use their hands to think: an embodied interactional analysis. Behaviour & Information Technology, 32, 938-954.
4. Antle, A. N., Droumeva, M., & Ha, D. (2009). Hands on what?: Comparing children's mouse-based and tangible-based interaction. In Proceedings of the 8th International Conference on Interaction Design and Children (pp. 80-88).
5. Ball, D. L. (1992). Magical hopes: manipulatives and the reform of math education. American Educator, 16(2), 14-18.
6. Ballard, D. H., Hayhoe, M. M., & Pelz, J. B. (1995). Memory representations in natural tasks. Journal of Cognitive Neuroscience, 7(1), 66-80.
7. Ballard, D. H., Hayhoe, M. M., Pook, P. K., & Rao, R. P. N. (1997). Deiectic codes for the embodiment of cognition. Behavioral and Brain Sciences, 20, 723-767.
8. Barrós-Loscertales, A., González, J., Pulvermüller, F., VenturaCampos, N., Bustamante, J. C., Costumero, V., et al. (2011). Reading "salt" activates gustatory brain regions: fMRI evidence for semantic grounding in a novel sensory modality. Cerebral Cortex, 22, 2554-2563.
9. Barsalou, L. W. (1999). Perceptual symbol systems. Behavioral and Brain Sciences, 22(4), 577-660.
10. Barsalou, L. W. (2008). Grounded cognition. Annual Review of Psychology, 59, 617-645.
11. Black, J. B. (2011). Embodied cognition and learning environment design. Theoretical foundations of student-centered learning environments. New York: Routledge.
12. Borst, J. P., Buwalda, T. A., van Rijn, H., & Taatgen, N. A. (2013). Avoiding the problem state bottleneck by strategic use of the environment. Acta Psychologica, 144(2), 373-379.
13. Bredo, E. (1994). Reconstructing educational psychology: situated cognition and Deweyian pragmatism. Educational Psychologist, 29(1), 23-35.
14. Brown, M. C., McNeil, N. M., & Glenberg, A. M. (2009). Using concreteness in education: real problems, potential solutions. Child Development Perspectives, 3(3), 160-164.
15. Calvo, P., & Gomila, T. (2008). Handbook of cognitive science: an embodied approach. San Diego: Elsevier.
16. Chase, W. G., & Simon, H. A. (1973). Perception in chess. Cognitive Psychology, 4, 55-81.
17. Chu, M., & Kita, S. (2011). The nature of gestures' beneficial role in spatial problem solving. Journal of Experimental Psychology: General, 140, 102-116.
18. Chu, M., Meyer, A., Foulkes, L., & Kita, S. (2013). Individual differences in frequency and salience of speech-accompanying gestures: the role of cognitive abilities and empathy. Journal of Experimental Psychology: General. doi: 10. 1037/a0033861.
19. Clark, A. (2005). Beyond the flesh: some lessons from a mole cricket. Artificial Life, 11(1-2), 233-244.
20. Clark, A. (2008). Supersizing the mind: embodiment, action, and cognitive extension. New York: Oxford University Press.
21. Clark, A., & Chalmers, D. (1998). The extended mind. Analysis, 58(1), 7-19.
22. Clements, D. H. (2000). 'Concrete' manipulatives, concrete ideas. Contemporary Issues in Early Childhood, 1(1), 45-60.
23. De Bock, D., Deprez, J., van Dooren, W., Roelens, M., & Verschaffel, L. (2011). Abstract or concrete examples in learning mathematics? A replication and elaboration of Kaminski, Sloutsky, and Heckler's study. Journal for Research in Mathematics Education, 42(2), 109-126.
24. De Jong, T., Linn, M. C., & Zacharia, Z. C. (2013). Physical and virtual laboratories in science and engineering education. Science, 340(6130), 305-308.
25. De Koning, B. B., & van der Schoot, M. (2013). Becoming part of the story! Refueling the interest in visualization strategies for reading comprehension. Educational Psychology Review, 25, 261-287.
26. de Vega, M., Glenberg, A. M., & Graesser, A. C. (2008). Symbols, embodiment and meaning. Oxford: Oxford University Press.
27. DeLoache, J. S. (1987). Rapid change in the symbolic functioning of very young children. Science, 238(4833), 1556-1557.
28. DeLoache, J. S. (1991). Symbolic functioning in very young children: understanding of pictures and models. Child Development, 62(4), 736-752.
29. DeLoache, J. S. (2000). Dual representation and young children's use of scale models. Child Development, 71(2), 329-338.
30. DeLoache, J. S. (2004). Becoming symbol-minded. Trends in Cognitive Sciences, 8(2), 66-70.
31. Dienes, Z. P. (1973). The six stages in the process of learning mathematics. Slough: National Foundation for Education Research/Nelson.
32. Dourish, P. (2004). Where the action is: the foundations of embodied interaction. Massachusetts: MIT Press.
33. Droll, J. A., & Hayhoe, M. M. (2007). Trade-offs between gaze and working memory use. Journal of Experimental Psychology: Human Perception and Performance, 33(6), 1352.
34. Finkelstein, N. D., Adams, W. K., Keller, C. J., Kohl, P. B., Perkins, K. K., Podolefsky, N. S., et al. (2005). When learning about the real world is better done virtually: a study of substituting computer simulations for laboratory equipment. Physical Review Special Topics-Physics Education Research, 1(1), 1-8.
35. Flanagan, R. (2013). Effects of learning from interaction with physical or mediated devices. Cognitive Processing, 14, 213-215.
36. Flusberg, S. J., & Boroditsky, L. (2011). Are things that are hard to physically move also hard to imagine moving? Psychonomic Bulletin & Review, 18(1), 158-164.
37. Fodor, J. A. (1975). The language of thought. Cambridge: Harvard University Press.
38. Frank, M. C., & Barner, D. (2012). Representing exact number visually using mental abacus. Journal of Experimental Psychology: General, 141(1), 134-149.
39. Fu, W. T. (2011). A dynamic context model of interactive behavior. Cognitive Science, 35(5), 874-904.
40. Fyfe, E. McNeil, N., Son, J. & Goldstone, R. (2014/this issue). Concreteness fading offers the best of both concrete and abstract instruction. Educational Psychology Review.
41. Gaschler, R., Vaterrodt, B., Frensch, P. A., Eichler, A., & Haider, H. (2013). Spontaneous usage of different shortcuts based on the commutativity principle. PLoS ONE, 8(9), e74972.
42. Gibson, J. J. (1979). The ecological approach to visual perception. Boston: Houghton-Mifflin.
43. Glenberg, A. M. (2008). Embodiment for education. In P. Calvo & T. Gomila (Eds.), Handbook of cognitive science: an embodied approach (pp. 355-372). New York: Elsevier.
44. Glenberg, A. M., & Kaschak, M. P. (2002). Grounding language in action. Psychonomic Bulletin & Review, 9(3), 558-565.
45. Glenberg, A. M., Gutierrez, T., Levin, J. R., Japuntich, S., & Kaschak, M. P. (2004). Activity and imagined activity can enhance young children's reading comprehension. Journal of Educational Psychology, 96(3), 424-436.
46. Glenberg, A., Willford, J., Gibson, B., Goldberg, A., & Zhu, X. (2011a). Improving reading to improve math. Scientific Studies of Reading, 16, 316-340.
47. Glenberg, A. M., Goldberg, A. B., & Zhu, X. (2011b). Improving early reading comprehension using embodied CAI. Instructional Science, 39(1), 27-39.
48. Goldstone, R. L., & Sakamoto, Y. (2003). The transfer of abstract principles governing complex adaptive systems. Cognitive Psychology, 46(4), 414-466.
49. Goldstone, R. L., & Son, J. Y. (2005). The transfer of scientific principles using concrete and idealized simulations. The Journal of the Learning Sciences, 14(1), 69-110.
50. Gonzalez, J., Barros-Loscertales, A., Pulvermuller, F., Meseguer, V., & Sanjuán, A. (2006). Reading cinnamon activates olfactory brain regions. NeuroImage, 32, 906-912.
51. Gray, W. D., & Fu, W. (2004). Soft constraints in interactive behavior: the case of ignoring perfect knowledge in-the-world for imperfect knowledge in-the-head. Cognitive Science, 28(3), 359-382.
52. Gray, W. D., Sims, C. R., Fu, W.-T., & Schoelles, M. J. (2006). The soft constraints hypothesis: a rational analysis approach to resource allocation for interactive behavior. Psychological Review, 113, 461-482.
53. Han, I., & Black, J. B. (2011). Incorporating haptic feedback in simulation for learning physics. Computers & Education, 57(4), 2281-2290.
54. Haselen, G. L. V., van der Steen, J., & Frens, M. A. (2000). Copying strategies for patterns by children and adults. Perceptual and Motor Skills, 91(2), 603-615.
55. Hatano, G., & Osawa, K. (1983). Digit memory of grand experts in abacus-derived mental calculation. Cognition, 15(1), 95-110.
56. Hatano, G., Miyake, Y., & Binks, M. G. (1977). Performance of expert abacus operators. Cognition, 5(1), 47-55.
57. Hauk, O., Johnsrude, I., & Pulvermüller, F. (2004). Somatotopic representation of action words in human motor and premotor cortex. Neuron, 41, 301-307.
58. Hayhoe, M. M., Pook, P. K., & Rao, R. P. N. (1997). Deictic codes for the embodiment of cognition. Behavioral and Brain Sciences, 20, 723-767.
59. Hutchins, E. (1995). Cognition in the wild. Cambridge: MIT Press.
60. Hutchins, E. (2005). Material anchors for conceptual blends. Journal of Pragmatics, 37(10), 1555-1577.
61. Johnson, A. M., Reisslein, J., & Reisslein, M. (2014). Representation sequencing in computer-based engineering education. Computers & Education, 72, 249-261.
62. Kaminski, J. A., Sloutsky, V. M., & Heckler, A. F. (2008). Learning theory: the advantage of abstract examples in learning math. Science, 320(5875), 454-455.
63. Kaminski, J. A., Sloutsky, V. M., & Heckler, A. F. (2009a). Transfer of mathematical knowledge: the portability of generic instantiations. Child Development Perspectives, 3(3), 151-155.
64. Kaminski, J. A., Sloutsky, V. M., & Heckler, A. F. (2009a). The devil is in the superficial details: why generic instantiations promote portable mathematical knowledge. Child Development Perspectives, 3, 151-155.
65. Kaminski, J. A., Sloutsky, V. M., & Heckler, A. F. (2013). The cost of concreteness: the effect of nonessential information on analogical transfer. Journal of Experimental Psychology: Applied, 19(1), 14-29.
66. Kastens, K. A., Liben, L. S., & Agrawal, S. (2008). Epistemic actions in science education. In C. Freksa, N. S. Newcombe, P. Gardenfors, & S. W. Wölfl (Eds.), Proceedings of the International Conference on Spatial Cognition VI: learning, reasoning, and talking about space (pp. 205-215). Heidelberg: Springer.
67. Kiefer, M., & Trumpp, N. M. (2012). Embodiment theory and education: the foundations of cognition in perception and action. Trends in Neuroscience and Education, 1, 15-20.
68. Kirsh, D. (1995). The intelligent use of space. Artificial Intelligence, 73(1), 31-68.
69. Kirsh, D. (2009). Projection, problem space and anchoring. In Proceedings of the 31st annual conference of the cognitive science society (pp. 2310-2315). Hillsdale: Lawrence Erlbaum Associates.
70. Kirsh, D. (2010). Thinking with external representations. AI & Society, 25(4), 441-454.
71. Kirsh, D., & Maglio, P. (1994). On distinguishing epistemic from pragmatic action. Cognitive Science, 18, 513-549.
72. Klahr, D., Triona, L., Lara, M., & Williams, C. (2007). Hands on what? The relative effectiveness of physical versus virtual materials in an engineering design project by middle school children. Journal of Research in Science Teaching, 44(1), 183-203.
73. Lakoff, G., & Johnson, M. (1999). Philosophy in the flesh: the embodied mind and its challenge to Western thought. New York: Basic Books.
74. Lakoff, G., & Núñez, R. E. (2000). Where mathematics comes from: how the embodied mind brings mathematics into being. New York: Basic books.
75. Landy, D., & Goldstone, R. L. (2007). How abstract is symbolic thought? Journal of Experimental Psychology: Learning, Memory, and Cognition, 33, 720-733.
76. Lindgren, R., & Johnson-Glenberg, M. (2013). Emboldened by embodiment six precepts for research on embodied learning and mixed reality. Educational Researcher, 42(8), 445-452.
77. Manches, A. D., & O'Malley, C. (2012). Tangibles for learning: a representational analysis of physical manipulation. Personal and Ubiquitous Computing, 16(4), 405-419.
78. Manches, A., O'Malley, C., & Benford, S. (2010). The role of physical representations in solving number problems: a comparison of young children's use of physical and virtual materials. Computers & Education, 54(3), 622-640.
79. Markman, A., & Gentner, D. (1993). Structural alignment during similarity comparisons. Cognitive Psychology, 25, 431-467.
80. Marley, S. C., Levin, J. R., & Glenberg, A. M. (2007). Improving Native American children's listening comprehension through concrete representations. Contemporary Educational Psychology, 32(3), 537-550.
81. Marley, S. C., Szabo, Z., Leven, J. R., & Glenberg, A. M. (2011). Investigation of an activity-based text-processing strategy in mixed-age child dyads. The Journal of Experimental Education, 79(3), 340-360.
82. Martin, A. (2007). The representation of object concepts in the brain. Annual Review of Psychology, 58, 25-45.
83. Martin, T., & Schwartz, D. L. (2005). Physically distributed learning: adapting and reinterpreting physical environments in the development of fraction concepts. Cognitive Science, 29(4), 587-625.
84. Martin, T., Lukong, A., & Reaves, R. (2007). The role of manipulatives in arithmetic and geometry tasks [Electronic version]. Journal of Education and Human Development, 1, 1-10.
85. McNeil, N. M., & Fyfe, E. R. (2012). "Concreteness Fading" promotes transfer of mathematical knowledge. Learning and Instruction, 22, 440-448.
86. McNeil, N. M., & Jarvin, L. (2007). When theories don't add up: disentangling he manipulatives debate. Theory into Practice, 46(4), 309-316.
87. Morris, D., Tan, H., Barbagli, F., Chang, T., & Salisbury, K. (2007). Haptic feedback enhances force skill learning. In EuroHaptics Conference, 2007 and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems. World Haptics 2007. Second Joint (pp. 21-26).
88. Moyer, P. S., Bolyard, J. J., & Spikell, M. A. (2002). What are virtual manipulatives? Teaching Children Mathematics, 8, 372-377.
89. Nathan, M. J. (2008). An Embodied Cognition perspective on symbols, gesture, and grounding instruction. In M. De Vega, A. M. Glenberg, & A. C. Graesser (Eds.), Symbols and embodiment: debates on meaning and cognition (pp. 375-396). New York: Oxford University Press.
90. Nathan, M. J. (2012). Rethinking formalisms in formal education. Educational Psychologist, 47(2), 125-148.
91. Newell, A., & Simon, H. A. (1972). Human problem solving. Englewood Cliffs: Prentice-Hall.
92. Norman, D. A. (1988). The psychology of everyday things. New York: Basic books.
93. O'Malley, C., & Stanton-Fraser, D. (2004). Literature review in learning with tangible technologies (Report 12). Bristol: Nesta FutureLab Series.
94. Olympiou, G., & Zacharia, Z. C. (2012). Blending physical and virtual manipulatives: an effort to improve students' conceptual understanding through science laboratory experimentation. Science Education, 96(1), 21-47.
95. Olympiou, G., Zacharia, Z. C., de Jong, T. (2013). Making the invisible visible: Enhancing students' conceptual understanding by introducing representations of abstract objects in a simulation. Instructional Science, 41, 575-587.
96. Osman, M. (2010). Observation can be as effective as action in problem solving. Cognitive Science, 32(1), 162-183.
97. Page, M. (1990). Active learning: historical and contemporary perspectives. Unpublished manuscript, University of Massachusetts. Amherst: ERIC Document Reproduction Service, No. ED 338389.
98. Pecher, D., & Zwaan, R. A. (2005). Grounding cognition: the role of perception and action in memory, language, and thinking. Cambridge: Cambridge University Press.
99. Radman, Z. (2013). The hand, an organ of the mind. Massachusetts: MIT Press.
100. Resnick, L., & Omanson, S. (1987). Learning to understand arithmetic. Hillsdale: Advances in instructional psychology.
101. Risko, E. F., Medimorec, S., Chisholm, J. D., & Kingstone, A. (2013). Cognitive offloading in the identification of rotated objects: A natural behavior approach. Cognitive Science. doi: 10. 1111/cogs. 12087.
102. Roux, F.-E., Boetto, S., Sacko, O., Chollet, F., & Tremoulet, M. (2003). Writing, calculating, and finger recognition in the region of the angular gyrus: a cortical stimulation study of Gerstmann syndrome. Journal of Neurosurgery, 99, 716-727.
103. Sarama, J., & Clements, D. H. (2009). 'Concrete' computer manipulatives in mathematics education. Child Development Perspectives, 3(3), 145-150.
104. Scheiter, K., Gerjets, P., & Schuh, J. (2010). The acquisition of problem-solving skills in mathematics: how animations can aid understanding of structural problem features and solution procedures. Instructional Science, 38(5), 487-502.
105. Schwartz, D. L., & Martin, T. (2006). Distributed learning and mutual adaptation. Pragmatics & Cognition, 14(2), 313-332.
106. Shaer, O., & Hornecker, E. (2010). Tangible user interfaces: past, present, and future directions. Foundations and Trends in Human-Computer Interaction, 3(1-2), 1-137.
107. Shapiro, L. A. (2011). Embodied cognition. New York: Routledge.
108. Sherman, J., & Bisanz, M. (2009). Equivalence in symbolic and nonsymbolic contexts: benefits of solving problems with manipulatives. Journal of Educational Psychology, 101(1), 88-100.
109. Sigrist, R., Rauter, G., Riener, R., & Wolf, P. (2013). Augmented visual, auditory, haptic, and multimodal feedback in motor learning: a review. Psychonomic Bulletin & Review, 20, 21-53.
110. Sloutsky, V. M., Kaminski, J. A., & Heckler, A. F. (2005). The advantage of simple symbols for learning and transfer. Psychonomic Bulletin & Review, 12(3), 508-513.
111. Snow, J. C., Pettypiece, C. E., McAdam, T. D., Mclean, A. D., Stroman, P. W., Goodale, M. A., et al. (2011). Bringing the real world into the fMRI scanner: repetition effects for pictures versus real objects. Scientific Reports, 1(130), 1-10.
112. Son, J. Y., Smith, L. B., Goldstone, R. L., & Leslie, M. (2012). The importance of being interpreted: grounded words and children's relational reasoning. Frontiers in Psychology, 3(45), 1-12.
113. Stull, A. T., Hegarty, M., Dixon, B., & Stieff, M. (2012). Representational translation with concrete models in organic chemistry. Cognition & Instruction, 30(4), 404-434.
114. Stull, A. T., Barrett, T., & Hegarty, M. (2013). Usability of concrete and virtual models in chemistry instruction. Computers in Human Behavior, 29(6), 2546-2556.
115. Svensson, H. (2007). Embodied simulation as off-line representation. Licentiate thesis, University of Linköping/University of Skövde, Sweden.
116. Symes, E., Ellis, R., & Tucker, M. (2007). Visual object affordances: object orientation. Acta Psychologica, 124(2), 238-255.
117. Triona, L. M., & Klahr, D. (2003). Point and click or grab and heft: comparing the influence of physical and virtual instructional materials on elementary school students' ability to design experiments. Cognition and Instruction, 21(2), 149-173.
118. Triona, L. M., Klahr, D., & Williams, C. (2005). Point and click or build by hand: comparing the effects of physical vs. virtual materials on middle school students' ability to optimize an engineering Design. In Proceedings of the 30th Annual Conference of the Cognitive Science Society (pp. 2202-2205).
119. Uttal, D. H., Scudder, K. V., & DeLoache, J. S. (1997). Manipulatives as symbols: a new perspective on the use of concrete objects to teach mathematics. Journal of Applied Developmental Psychology, 18(1), 37-54.
120. Uttal, D. H., O'Doherty, K., Newland, R., Hand, L. L., & Deloache, J. S. (2009). Dual representation and the linking of concrete and symbolic representations. Child Development Perspectives, 3(3), 156-159.
121. van Elk, M., van Schie, H., & Bekkering, H. (2014). Action semantics: a unifying conceptual framework for the selective use of multimodal and modality-specific object knowledge. Physics of Life Reviews. doi: 10. 1016/j. plrev. 2013. 11. 005.
122. van Gog, T., & Rummel, N. (2010). Example-based learning: integrating cognitive and social-cognitive research perspectives. Educational Psychology Review, 22, 155-174.
123. Wheeler, M. (2007). Reconstructing the cognitive world: the next step. Cambridge: MIT Press.
124. Wilson, M. (2002). Six views of Embodied Cognition. Psychonomic Bulletin & Review, 9(4), 625-636.
125. Winn, W. (2003). Learning in artificial environments: embodiment, embeddedness and dynamic adaptation. Technology, Instruction, Cognition and Learning, 1(1), 87-114.
126. Zacharia, Z. C., & Constantinou, C. P. (2008). Comparing the influence of physical and virtual manipulatives in the context of the Physics by Inquiry curriculum: the case of undergraduate students' conceptual understanding of heat and temperature. American Journal of Physics, 76, 425-430.
127. Zacharia, Z. C., & Olympiou, G. (2011). Physical versus virtual manipulative experimentation in physics learning. Learning and Instruction, 21(3), 317-331.
128. Zacharia, Z. C., Loizou, E., & Papaevripidou, M. (2012). Is physicality an important aspect of learning through science experimentation among kindergarten students? Early Childhood Research Quarterly, 27(3), 447-457.
129. Zago, L., Pesenti, M., Mellet, E., Crivello, F., Mazoyer, B., & Tzourio-Mazoyer, N. (2001). Neural correlates of simple and complex mental calculation. NeuroImage, 13, 314-327.