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Demonstrating mathematics learning as the emergence of eye–hand dynamic equilibrium

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Abstract

This paper combines recent developments in theories of knowledge (complex dynamic systems), technologies (embodied interactions), and research tools (multimodal data collection and analysis) to offer new insights into how conceptual mathematical understanding can emerge. A complex dynamic system view models mathematics learning in terms of a multimodal agent who encounters a set of task constraints. The learning process in this context includes destabilizing a systemic configuration (for example, coordination of eye and hand movements) and forming new dynamic stability adapted to the task constraints. To test this model empirically, we applied a method developed to study complex systems, recurrence quantification analysis (RQA), to investigate students’ eye–hand dynamics during a touchscreen mathematics activity for the concept of proportionality. We found that across participants (n = 32), fluently coordinated hand-movement solutions coincided with more stable and predictable gaze patterns. We present a case study of a prototypical participant’s hand–eye RQA and audio–video data to show how the student’s cognitive system transitioned out of prior coordination reflective of additive thinking into a new coordination that can ground multiplicative thinking. These findings constitute empirical substantiation in mathematics education research for cognition as a complex system transitioning among dynamic equilibria.

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Data availability

The data that support the findings of this study are available from the Freudenthal Institute at Utrecht University, but restrictions apply to the availability of these data, which were used under license for the current study and so are not publicly available. However, data are available from the authors upon reasonable request and with the permission of the Freudenthal Institute at Utrecht University.

References

  • Abdu, R., van Helden, G., Alberto, R., & Bakker, A. (2021). Multimodal dialogue in small-group mathematics learning. Learning, Culture and Social Interaction, 29, 100491. https://doi.org/10.1016/j.lcsi.2021.100491

    Article  Google Scholar 

  • Abdullah, A., Adil, M., Rosenbaum, L., Clemmons, M., Shah, M., Abrahamson, D., & Neff, M. (2017). Pedagogical agents to support embodied, discovery-based learning. In J. Beskow, C. Peters, G. Castellano, C. O’Sullivan, I. Leite, & S. Kopp (Eds.), Proceedings of 17th International Conference on Intelligent Virtual Agents (IVA, 2017) (pp. 1–14). Springer International Publishing. https://doi.org/10.1007/978-3-319-67401-8_1

  • Abrahamson, D. (2021). Grasp actually: An evolutionist argument for enactivist mathematics education. Human Development, 65(2), 77–93. https://doi.org/10.1159/000515680

    Article  Google Scholar 

  • Abrahamson, D., & Abdu, R. (2020). Towards an ecological-dynamics design framework for embodied-interaction conceptual learning: The case of dynamic mathematics environments. Educational Technology Research and Development, 69(4), 1889–1923. https://doi.org/10.1007/s11423-020-09805-1

    Article  Google Scholar 

  • Abrahamson, D., & Bakker, A. (2016). Making sense of movement in embodied design for mathematics learning. Cognitive Research: Principles and Implications, 1(1), 33. https://doi.org/10.1186/s41235-016-0034-3

    Article  Google Scholar 

  • Abrahamson, D., & Sánchez-García, R. (2016). Learning is moving in new ways: The ecological dynamics of mathematics education. Journal of the Learning Sciences, 25(2), 203–239. https://doi.org/10.1080/10508406.2016.1143370

    Article  Google Scholar 

  • Abrahamson, D., & Trninic, D. (2015). Bringing forth mathematical concepts: Signifying sensorimotor enactment in fields of promoted action. ZDM-Mathematics Education, 47(2), 295–306. https://doi.org/10.1007/s11858-014-0620-0

  • Abrahamson, D., Trninic, D., Gutiérrez, J. F., Huth, J., & Lee, R. G. (2011). Hooks and shifts: A dialectical study of mediated discovery. Technology, Knowledge, and Learning, 16(1), 55–85. https://doi.org/10.1007/s10758-011-9177-y

    Article  Google Scholar 

  • Abrahamson, D., Lee, R. G., Negrete, A. G., & Gutiérrez, J. F. (2014). Coordinating visualizations of polysemous action: Values added for grounding proportion. ZDM-Mathematics Education, 46(1), 79–93. https://doi.org/10.1007/s11858-013-0521-7

  • Abrahamson, D., Shayan, S., Bakker, A., & Van Der Schaaf, M. (2015). Eye-tracking Piaget: Capturing the emergence of attentional anchors in the coordination of proportional motor action. Human Development, 58(4–5), 218–244. https://doi.org/10.1159/000443153

    Article  Google Scholar 

  • Abrahamson, D., Flood, V. J., Miele, J. A., & Siu, Y.-T. (2019). Enactivism and ethnomethodological conversation analysis as tools for expanding Universal Design for Learning: The case of visually impaired mathematics students. ZDM-Mathematics Education, 51(2), 291–303. https://doi.org/10.1007/s11858-018-0998-1

  • Abrahamson, D., & Trninic, D. (2011). Toward an embodied-interaction design framework for mathematical concepts. In P. Blikstein & P. Marshall (Eds.), Proceedings of the 10th Annual Interaction Design and Children Conference (IDC 2011) (Vol. “Full papers,” pp. 1–10). IDC.

  • Abrahamson, D., Sánchez-García, R., & Smyth, C. (2016). Metaphors are projected constraints on action: An ecological dynamics view on learning across the disciplines. In C.-K. Looi, J. L. Polman, U. Cress, & P. Reimann (Eds.), “Transforming learning, empowering learners,” Proceedings of the International Conference of the Learning Sciences (ICLS 2016) (Vol. 1, pp. 314–321). International Society of the Learning Sciences.

  • Abrahamson, D. (2018). Moving forward: In search of synergy across diverse views on the role of physical movement in design for STEM education [symposium]. In J. Kay & R. Luckin (Eds.), “Rethinking learning in the digital age: Making the Learning Sciences count,” Proceedings of the 13th International Conference of the Learning Sciences (ICLS 2018) (Vol. 2, pp. 1243–1250). International Society of the Learning Sciences.

  • Adolph, K. E., Hoch, J. E., & Cole, W. G. (2018). Development (of walking): 15 suggestions. Trends in Cognitive Sciences, 22(8), 699–711. https://doi.org/10.1016/j.tics.2018.05.010

    Article  Google Scholar 

  • Alberto, R. A., Bakker, A., Walker–van Aalst, O., Boon, P. B. J., & Drijvers, P. H. M. (2019). Networking theories in design research: An embodied instrumentation case study in trigonometry. In U. T. Jankvist, v. d. Heuvel-Panhuizen, & M. Veldhuis (Eds.), Proceeding of the 11th Congress of the European Society for Research in Mathematics Education (CERME11) (pp. 3088–3095). Freudenthal Group & Freudenthal Institute, Utrecht University and ERME.

  • Alberto, R., Shvarts, A., Drijvers, P., & Bakker, A. (2021). Action-based embodied design for mathematics learning: A decade of variations on a theme. International Journal of Child-Computer Interaction, 100419. https://doi.org/10.1016/j.ijcci.2021.100419

  • Allen, J. W. P., & Bickhard, M. H. (2013). Stepping off the pendulum: Why only an action-based approach can transcend the nativist–empiricist debate. Cognitive Development, 28(2), 9–133. https://doi.org/10.1016/j.cogdev.2013.01.002

    Article  Google Scholar 

  • Anderson, M. L. (2003). Embodied cognition: A field guide. Artificial Intelligence, 149(1), 91–130. https://doi.org/10.1016/S0004-3702(03)00054-7

    Article  Google Scholar 

  • Anderson, M. L., Richardson, M. J., & Chemero, A. (2012). Eroding the boundaries of cognition: Implications of embodiment 1. Topics in Cognitive Science, 4(4), 717–730. https://doi.org/10.1111/j.1756-8765.2012.01211.x

    Article  Google Scholar 

  • Barsalou, L. W. (2010). Grounded cognition: Past, present, and future. Topics in Cognitive Science, 2(4), 716–724.

    Article  Google Scholar 

  • Bateson, G. (1972). Steps to an ecology of mind: A revolutionary approach to man’s understanding of himself. Ballantine Books.

    Google Scholar 

  • Blikstein, P., & Worsley, M. (2016). Multimodal learning analytics and education data mining: Using computational technologies to measure complex learning tasks. Journal of Learning Analytics, 3(2), 220–238. https://doi.org/10.18608/jla.2016.32.11

    Article  Google Scholar 

  • Bongers, T. J. D. (2020). Transfer of embodied experiences in a tablet environment towards a pen and paper task. Unpublished Masters thesis (Applied cognitive psychology). Utrecht University.

  • Chow, J. Y., Komar, J., Davids, K., & Tan, C. W. K. (2021). Nonlinear pedagogy and its implications for practice in the Singapore PE context. Physical Education and Sport Pedagogy, 26(3), 230–241. https://doi.org/10.1080/17408989.2021.1886270

    Article  Google Scholar 

  • Clancey, W. J. (2008). Scientific antecedents of situated cognition. In P. Robbins & M. Aydede (Eds.), Cambridge Handbook of situated cognition (pp. 11–34). Cambridge University Press.

  • Clemotte, A., Velasco, M. A., Torricelli, D., Raya, R., & Ceres Ruiz, R. (2014). Accuracy and precision of the Tobii X2–30 eye-tracking under non ideal conditions. In A. R. Londral (Ed.), Proceedings of the 2nd International Congress on Neurotechnology, Electronics and Informatics (pp. 111–116). Rome, Italy.

  • Coco, M. I., & Dale, R. (2014). Cross-recurrence quantification analysis of categorical and continuous time series: An R package. Frontiers in Psychology, 5, 510. https://doi.org/10.3389/fpsyg.2014.00510

    Article  Google Scholar 

  • Dackermann, T., Fischer, U., Nuerk, H.-C., Cress, U., & Moeller, K. (2017). Applying embodied cognition: From useful interventions and their theoretical underpinnings to practical applications. ZDM-Mathematics Education, 49(4), 545–557. https://doi.org/10.1007/s11858-017-0850-z

  • de Freitas, E., & Sinclair, N. (2013). New materialist ontologies in mathematics education: The body in/of mathematics. Educational Studies in Mathematics, 83(3), 453–470. https://doi.org/10.1007/s10649-012-9465-z

    Article  Google Scholar 

  • Dourish, P. (2001). Where the action is: The foundations of embodied interaction. MIT Press.

    Book  Google Scholar 

  • Duijzer, C. A., Shayan, S., Bakker, A., Van der Schaaf, M. F., & Abrahamson, D. (2017). Touchscreen tablets: Coordinating action and perception for mathematical cognition. Frontiers in Psychology, 8, 144. https://doi.org/10.3389/fpsyg.2017.00144

    Article  Google Scholar 

  • Fleuchaus, E., Kloos, H., Kiefer, A. W., & Silva, P. L. (2020). Complexity in science learning: Measuring the underlying dynamics of persistent mistakes. The Journal of Experimental Education, 88(3), 448–469. https://doi.org/10.1080/00220973.2019.1660603

    Article  Google Scholar 

  • Flood, V. J., Shvarts, A., & Abrahamson, D. (2020). Teaching with embodied learning technologies for mathematics: Responsive teaching for embodied learning. ZDM-Mathematics Education, 52(7), 1307–1331. https://doi.org/10.1007/s11858-020-01165-7

  • Galetzka, C. (2017). The story so far: How embodied cognition advances our understanding of meaning-making. Frontiers in Psychology, 8, 1315. https://doi.org/10.3389/fpsyg.2017.01315

    Article  Google Scholar 

  • Glenberg, A. M. (2010). Embodiment as a unifying perspective for psychology. Wiley Interdisciplinary Reviews: Cognitive Science, 1(4), 586–596. https://doi.org/10.1002/wcs.55

    Article  Google Scholar 

  • Goldenberg, E. P., Scher, D., & Feurzeig, N. (2008). What lies behind dynamic interactive geometry software. In G. W. Blume & M. K. Heid (Eds.), Research on technology and the teaching and learning of mathematics: Cases and perspectives (Vol. 2, pp. 53–87). Charlotte, NC: Information Age

  • Hutto, D. D. (2019). Re-doing the math: Making enactivism add up. Philosophical Studies, 176(3), 827–837. https://doi.org/10.1007/s11098-018-01233-5

    Article  Google Scholar 

  • Hutto, D. D., & Sánchez-García, R. (2015). Choking RECtified: Embodied expertise beyond Dreyfus. Phenomenology and the Cognitive Sciences, 14(2), 309–331. https://doi.org/10.1007/s11097-014-9380-0

    Article  Google Scholar 

  • Hutto, D. D., Kirchhoff, M. D., & Abrahamson, D. (2015). The enactive roots of STEM: Rethinking educational design in mathematics. In P. Chandler & A. Tricot (Eds.), Human movement, physical and mental health, and learning [Special issue]. Educational Psychology Review, 27(3), 371–389. https://doi.org/10.1007/s10648-015-9326-2

  • Kelso, J. A. S. (1984). Phase transitions and critical behavior in human bimanual coordination. American Journal of Physiology: Regulatory, Integrative and Comparative, 246(6), R1000–R1004.

    Google Scholar 

  • Kelso, J. S. (1995). Dynamic patterns: The self-organization of brain and behavior. MIT press.

    Google Scholar 

  • Kelso, J. A. S. (2010). Instabilities and phase transitions in human brain and behavior. Frontiers in Human Neuroscience, 4, 23. https://doi.org/10.3389/fnhum.2010.00023

    Article  Google Scholar 

  • Kelso, J. A. S. (2016). On the self-organizing origins of agency. Trends in Cognitive Sciences, 20(7), 490–499. https://doi.org/10.1016/j.tics.2016.04.004

    Article  Google Scholar 

  • Koopmans, M. (2020). Education is a complex dynamical system: Challenges for research. The Journal of Experimental Education, 88(3), 358–374. https://doi.org/10.1080/00220973.2019.1566199

    Article  Google Scholar 

  • Kostrubiec, V., Zanone, pier-G., Fuchs, A., & Kelso, J. A. S. (2012). Beyond the blank slate: Routes to learning new coordination patterns depend on the intrinsic dynamics of the learner—experimental evidence and theoretical model. Frontiers in Human Neuroscience, 6. https://doi.org/10.3389/fnhum.2012.00222

  • Lambert, S. G., Fiedler, B. L., Hershenow, C. S., Abrahamson, D., & Gorlewicz, J. L. (2022). A tangible manipulative for inclusive quadrilateral learning. Journal on Technology & Persons with Disabilities, 10, 66–81. http://hdl.handle.net/10211.3/223466. Accessed 21 Nov 2023

  • Lamon, S. J. (2007). Rational numbers and proportional reasoning: Toward a theoretical framework for research. Lester, F.K. (Ed.), Second Handbook of Research on Mathematics Teaching and Learning, 6(Vol. 1, pp. 629–667). Information Age.

  • Lee, M. C. Y., Chow, J. Y., Komar, J., Tan, C. W. K., & Button, C. (2014). Nonlinear pedagogy: An effective approach to cater for individual differences in learning a sports skill. PLoS ONE, 9(8), e104744. https://doi.org/10.1371/journal.pone.0104744

    Article  Google Scholar 

  • Liao, C., & Masters, R. S. (2001). Analogy learning: A means to implicit motor learning. Journal of Sports Sciences, 19, 307–319. https://doi.org/10.1080/02640410152006081

    Article  Google Scholar 

  • 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. https://doi.org/10.3102/0013189X1351166

    Article  Google Scholar 

  • Marwan, N., Romano, M. C., Thiel, M., & Kurths, J. (2007). Recurrence plots for the analysis of complex systems. Physics Reports, 438, 237–239. https://doi.org/10.1016/j.physrep.2006.11.001

    Article  Google Scholar 

  • Mechsner, F. (2003). Gestalt factors in human movement coordination. Gestalt Theory, 25(4), 225–245.

    Google Scholar 

  • Mechsner, F. (2004). A psychological approach to human voluntary movements. Journal of Motor Behavior, 36(4), 355–370. https://doi.org/10.1080/00222895.2004.11007993

    Article  Google Scholar 

  • Mechsner, F., Kerzel, D., Knoblich, G., & Prinz, W. (2001). Perceptual basis of bimanual coordination. Nature, 41(6859), 69–73. https://doi.org/10.1038/35102060

    Article  Google Scholar 

  • Muraoka, T., Nakagawa, K., Kato, K., Qi, W., & Kanosue, K. (2016). Interlimb coordination from a psychological perspective. The Journal of Physical Fitness and Sports Medicine, 5(5), 349–359. https://doi.org/10.7600/jpfsm.5.349

    Article  Google Scholar 

  • Nagataki, S., & Hirose, S. (2007). Phenomenology and the third generation of cognitive science: Towards a cognitive phenomenology of the body. Human Studies, 30(3), 219–232. https://doi.org/10.1007/s10746-007-9060-y

    Article  Google Scholar 

  • Nemirovsky, R., Kelton, M. L., & Rhodehamel, B. (2013). Playing mathematical instruments: Emerging perceptuomotor integration with an interactive mathematics exhibit. Journal for Research in Mathematics Education, 44(2), 372–415. https://doi.org/10.5951/jresematheduc.44.2.0372

    Article  Google Scholar 

  • Newell, K. M., & Ranganathan, R. (2010). Instructions as constraints in motor skill acquisition. In I. Renshaw, K. Davids, & G. J. P. Savelsbergh (Eds.), Motor learning in practice: A constraints-led approach (pp. 17–32). Routledge.

    Google Scholar 

  • Noroozi, O., Alikhani, I., Järvelä, S., Kirschner, P. A., Juuso, I., & Seppänen, T. (2019). 2019/11/01/). Multimodal data to design visual learning analytics for understanding regulation of learning. Computers in Human Behavior, 100, 298–304. https://doi.org/10.1016/j.chb.2018.12.019

    Article  Google Scholar 

  • Ott, E. (2006). Basin of Attraction. Scholarpedia, 1(8), 1701. https://doi.org/10.4249/scholarpedia.1701

    Article  Google Scholar 

  • Pardos, Z. A., Hu, C., Meng, P., Neff, M., & Abrahamson, D. (2018). Characterizing learner behavior from high frequency touchscreen data using recurrent neural networks. In D. Chin & L. Chen (Eds.), Adjunct proceedings of the 26th Conference on User Modeling, Adaptation and Personalization (UMAP ’18). ACM. 6 pages.

  • Petitmengin, C. (2007). Towards the source of thoughts: The gestural and transmodal dimension of lived experience. Journal of Consciousness Studies, 14(3), 54–82. https://doi.org/10.20314/als.8584e0642b

    Article  Google Scholar 

  • Pirie, S. E. B., & Kieren, T. E. (1989). A recursive theory of mathematical understanding. For the Learning of Mathematics, 9(3), 7–11.

    Google Scholar 

  • Radford, L. (2009). Why do gestures matter? Sensuous cognition and the palpability of mathematical meanings. Educational Studies in Mathematics, 70, 111–126. https://doi.org/10.1007/s10649-008-9127-3

    Article  Google Scholar 

  • Reed, E. S., & Bril, B. (1996). The primacy of action in development. In M. L. Latash & M. T. Turvey (Eds.), Dexterity and its Development (pp. 431–451). Lawrence Erlbaum Associates.

    Google Scholar 

  • Reid, D. A. (2014). The coherence of enactivism and mathematics education research: A case study. Avant, V(2), 137–172. https://doi.org/10.12849/50202014.0109.0007

    Article  Google Scholar 

  • Reinholz, D., Trninic, D., Howison, M., & Abrahamson, D. (2010). It’s not easy being green: Embodied artifacts and the guided emergence of mathematical meaning. In P. Brosnan, D. Erchick, & L. Flevares (Eds.), Proceedings of the Thirty-Second Annual Meeting of the North-American Chapter of the International Group for the Psychology of Mathematics Education (PME-NA 32) (Vol. VI, Ch. 18: Technology, pp. 1488–1496). PME-NA.

  • Savelsbergh, G. J. P., der Van, J., Oudejans, R. D., & Scott, M. A. (2004). Perceptual learning is mastering perceptual degrees of freedom. In A. M. Williams & N. Hodges (Eds.), Skill acquisition in sport (pp. 374–389). Routledge.

    Google Scholar 

  • Scheffer, M., Bascompte, J., Brock, W. A., Brovkin, V., Carpenter, S. R., Dakos, V., Held, H., van Nes, E. H., Rietkerk, M., & Sugihara, G. (2009). Early-warning signals for critical transitions. Nature, 461(7260), 53–59. https://doi.org/10.1038/nature08227

    Article  Google Scholar 

  • Schindler, M., & Lilienthal, A. J. (2019). Domain-specific interpretation of eye tracking data: Towards a refined use of the eye-mind hypothesis for the field of geometry. Educational Studies in Mathematics, 101(1), 123–139. https://doi.org/10.1007/s10649-019-9878-z

    Article  Google Scholar 

  • Schöner, G., Jiang, W. Y., & Kelso, J. A. S. (1990). A synergetic theory of quadrupedal gaits and gait transitions. Journal of Theoretical Biology, 142(3), 359–391. https://doi.org/10.1016/S0022-5193(05)80558-2

    Article  Google Scholar 

  • Shayan, S., Abrahamson, D., Bakker, A., Duijzer, A. C. G., & Van der Schaaf, M. F. (2015). The emergence of proportional reasoning from embodied interaction with a tablet application: An eye-tracking study. In L. Gómez Chova, A. López Martínez, & I. Candel Torres (Eds.), Proceedings of the 9th International Technology, Education, and Development Conference (INTED 2015) (pp. 5732–5741). International Academy of Technology, Education, and Development.

  • Shvarts, A., & Abrahamson, D. (2019). Dual-eye-tracking Vygotsky: A microgenetic account of a teaching/learning collaboration in an embodied-interaction technological tutorial for mathematics. Learning, Culture and Social Interaction, 22, 100316. https://doi.org/10.1016/j.lcsi.2019.05.003

    Article  Google Scholar 

  • Shvarts, A., & van Helden, G. (2021). Embodied learning at a distance: From sensory-motor experience to constructing and understanding a sine graph. Mathematical Thinking and Learning, 25(4), 1–28. https://doi.org/10.1080/10986065.2021.1983691

    Article  Google Scholar 

  • Spencer, J. P., Austin, A., & Schutte, A. R. (2012). Contributions of dynamic systems theory to cognitive development. Cognitive Development, 27(4), 401–418. https://doi.org/10.1016/j.cogdev.2012.07.006

    Article  Google Scholar 

  • Steffe, L. P., & Kieren, T. (1994). Radical constructivism and mathematics education. Journal for Research in Mathematics Education, 25(6), 711–733. https://doi.org/10.2307/749582

    Article  Google Scholar 

  • Stephen, D. G., & Dixon, J. A. (2009). The self-organization of insight: Entropy and power laws in problem solving. The Journal of Problem Solving, 2(1), 72–101.

    Article  Google Scholar 

  • Strohmaier, A. R. (2020). Eye-tracking methodology in mathematics education research: A systematic literature review. Educational Studies in Mathematics, 104, 147–200. https://doi.org/10.1007/s10649-020-09948-1

    Article  Google Scholar 

  • Tancredi, S., Abdu, R., Balasubramaniam, R., & Abrahamson, D. (2022). Intermodality in multimodal learning analytics for cognitive theory development: A case from embodied design for mathematics learning. In M. Giannakos, D. Spikol, D. D. Mitri, K. Sharma, X. Ochoa, & R. Hamma (Eds.), The multimodal learning analytics handbook (pp. 133–158). Springer.

    Chapter  Google Scholar 

  • Tancredi, S., Abdu, R., Abrahamson, D., & Balasubramaniam, R. (2021). Modeling nonlinear dynamics of fluency development in an embodied-design mathematics learning environment with recurrence quantification analysis. International Journal of Child-Computer Interaction, 100297. https://doi.org/10.1016/j.ijcci.2021.100297

  • Thelen, E., & Smith, L. B. (2006). Dynamic systems theories. In R. M. Lerner (Ed.), Handbook of child psychology Vol. 1: Theoretical models of human development (pp. 258–312). Wiley.

  • Thelen, E., & Smith, L. B. (1994). A dynamic systems approach to the development of cognition and action. MIT Press.

    Google Scholar 

  • Thulasiram, M. R., Langridge, R. W., Abbas, H. H., & Marotta, J. J. (2020). Eye–hand coordination in reaching and grasping vertically moving targets. Experimental Brain Research, 238(6), 1433–1440. https://doi.org/10.1007/s00221-020-05826-7

    Article  Google Scholar 

  • Turvey, M. T. (1990). Coordination. American Psychologist, 45(8), 938–953. https://doi.org/10.1037/0003-066X.45.8.938

    Article  Google Scholar 

  • Van Dooren, W., De Bock, D., & Verschaffel, L. (2010). From addition to multiplication … and back. The development of students’ additive and multiplicative reasoning skills. Cognition and Instruction, 28(3), 360–381. https://doi.org/10.1080/07370008.2010.488306

    Article  Google Scholar 

  • Varela, F. J., Thompson, E., & Rosch, E. (1991). The embodied mind: Cognitive science and human experience. M.I.T. Press.

  • Wilson, M. (2002). Six views of embodied cognition. Psychonomic Bulletin & Review, 9(4), 625–636.

    Article  Google Scholar 

  • Wilson, A. D., & Golonka, S. (2013). Embodied cognition is not what you think it is [Hypothesis & Theory]. Frontiers in Psychology, 4(58), 1–13. https://doi.org/10.3389/fpsyg.2013.00058

    Article  Google Scholar 

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Abdu, R., Tancredi, S., Abrahamson, D. et al. Demonstrating mathematics learning as the emergence of eye–hand dynamic equilibrium. Educ Stud Math (2023). https://doi.org/10.1007/s10649-023-10279-0

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