Journal of Science Education and Technology

, Volume 28, Issue 3, pp 209–221 | Cite as

Understanding the Notion of Friction Through Gestural Interaction with a Remotely Controlled Robot

  • Alexandros MerkourisEmail author
  • Betty Chorianopoulou
  • Konstantinos Chorianopoulos
  • Vassilios Chrissikopoulos


Embodied interaction with tangible interactive objects can be beneficial for introducing abstract scientific concepts, especially for young learners. Nevertheless, there is limited comparative evaluation of alternative interaction modalities with contemporary educational technology, such as tablets and robots. In this study, we explore the effects of touch and gestural interaction with a tablet and a robot, in the context of a primary education physics course about the notion of friction. For this purpose, 56 students participated in a between-groups study that involved four computationally enhanced interventions which correspond to different input and output modalities, respectively: (1) touch-virtual, (2) touch-physical, (3) hand gesture-virtual, and (4) hand gesture-physical. We measured students’ friction knowledge and examined their views. We found that the physical conditions had greater learning impact concerning friction knowledge compared to the virtual way. Additionally, physical manipulation benefited those learners who had misconceptions or limited initial knowledge about friction. We also found that students who used the more familiar touchscreen interface demonstrated similar learning gains and reported higher usability compared to those using the hand-tilt interface. These findings suggest that user interface familiarity should be carefully balanced with user interface congruency, in order to establish accessibility to a scientific concept in a primary education context.


Embodied learning Educational robotics Human-robot interaction Science education Gestural congruency Surrogate embodiment Physicality 


Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed Consent

Informed consent was obtained from all individual participants included in the study.


  1. Abrahamson, D. (2014). Building educational activities for understanding: an elaboration on the embodied-design framework and its epistemic grounds. International Journal of Child-Computer Interaction, 2(1), 1–16.Google Scholar
  2. Alibali, M. W., & Nathan, M. J. (2012). Embodiment in mathematics teaching and learning: Evidence from learners’ and teachers’ gestures. Journal of the Learning Sciences, 21(2), 247–286.Google Scholar
  3. Barsalou, L. W. (1999). Perceptions of perceptual symbols. Behavioral and Brain Sciences, 22(4), 637–660.Google Scholar
  4. Barsalou, L. W. (2008). Grounded cognition. Annual Review of Psychology, 59(1), 617–645.Google Scholar
  5. Black, J. B. (2010). An embodied/grounded cognition perspective on educational technology. In New science of learning (pp. 45–52). Springer New York.Google Scholar
  6. Black, J. B., Segal, A., Vitale, J., & Fadjo, C. L. (2012). Embodied cognition and learning environment design. Theoretical Foundations of Learning Environments, 198–223.Google Scholar
  7. Card, S. K., English, W. K., & Burr, B. J. (1978). Evaluation of mouse, rate-controlled isometric joystick, step keys, and text keys for text selection on a CRT. Ergonomics, 21(8), 601–613.Google Scholar
  8. Chan, M. S., & Black, J. B. (2006, June). Direct-manipulation animation: Incorporating the haptic channel in the learning process to support middle school students in science learning and mental model acquisition. In Proceedings of the 7th international conference on Learning sciences (pp. 64–70). International Society of the Learning Sciences.Google Scholar
  9. De Jong, T., Linn, M. C., & Zacharia, Z. C. (2013). Physical and virtual laboratories in science and engineering education. Science, 340(6130), 305–308.Google Scholar
  10. Dourish, P. (2004). Where the action is: the foundations of embodied interaction. Cambridge: MIT press.Google Scholar
  11. Enyedy, N., Danish, J. A., Delacruz, G., & Kumar, M. (2012). Learning physics through play in an augmented reality environment. International Journal of Computer-Supported Collaborative Learning, 7(3), 347–378.Google Scholar
  12. Fadjo, C. L. (2012). Developing computational thinking through grounded embodied cognition. New York: Columbia University.Google Scholar
  13. Fadjo, C. L., Hallman Jr, G., Harris, R., & Black, J. B. (2009). Surrogate embodiment, mathematics instruction and video game programming. In EdMedia: World Conference on Educational Media and Technology (pp. 2787–2792). Association for the Advancement of Computing in Education (AACE).Google Scholar
  14. Frei, P., Su, V., Mikhak, B., & Ishii, H. (2000, April). Curlybot: designing a new class of computational toys. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 129–136). ACM.Google Scholar
  15. Gallagher, S., & Lindgren, R. (2015). Enactive metaphors: learning through full-body engagement. Educational Psychology Review, 27(3), 391–404.Google Scholar
  16. Gallese, V., & Lakoff, G. (2005). The brain’s concepts: the role of the sensory-motor system in conceptual knowledge. Cognitive Neuropsychology, 22(3–4), 455–479.Google Scholar
  17. 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. Scholar
  18. Han, I. (2013). Embodiment: a new perspective for evaluating physicality in learning. Journal of Educational Computing Research, 49(1), 41–59.Google Scholar
  19. Han, I., & Black, J. B. (2011). Incorporating haptic feedback in simulation for learning physics. Computers & Education, 57(4), 2281–2290.Google Scholar
  20. Jaakkola, T., Nurmi, S., & Veermans, K. (2011). A comparison of students’ conceptual understanding of electric circuits in simulation only and simulation-laboratory contexts. Journal of Research in Science Teaching, 48(1), 71–93.Google Scholar
  21. Jacob, R. J., Girouard, A., Hirshfield, L. M., Horn, M. S., Shaer, O., Solovey, E. T., & Zigelbaum, J. (2008, April). Reality-based interaction: a framework for post-WIMP interfaces. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 201–210). ACM.Google Scholar
  22. Johnson-Glenberg, M. C., & Megowan-Romanowicz, C. (2017). Embodied science and mixed reality: how gesture and motion capture affect physics education. Cognitive Research: Principles and Implications, 2(1), 24.Google Scholar
  23. Johnson-Glenberg, M. C., Megowan-Romanowicz, C., Birchfield, D. A., & Savio-Ramos, C. (2016). Effects of embodied learning and digital platform on the retention of physics content: centripetal force. Frontiers in Psychology, 7, 1819.Google Scholar
  24. Khan, S. A., & Black, J. B. (2014). Reactivation of multimodal representations and perceptual simulations for meaningful learning: a comparison of direct embodiment, surrogate embodiment, and imagined embodiment. Boulder, CO: International Society of the Learning Sciences.Google Scholar
  25. Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: an analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75–86.Google Scholar
  26. Kolb, D. A. (1975). Towards an applied theory of experiential learning. Theory s of Group Processes, 33–58.Google Scholar
  27. de Koning, B. B., & Tabbers, H. K. (2011). Facilitating understanding of movements in dynamic visualizations: an embodied perspective. Educational Psychology Review, 23(4), 501–521.Google Scholar
  28. Kontra, C., Lyons, D. J., Fischer, S. M., & Beilock, S. L. (2015). Physical experience enhances science learning. Psychological Science, 26(6), 737–749. Scholar
  29. Lakoff, G., & Johnson, M. (2008). Metaphors we live by. Chicago: University of Chicago press.Google Scholar
  30. Lakoff, G., & Núñez, R. E. (2000). Where mathematics comes from: how the embodied mind brings mathematics into being. AMC, 10, 12.Google Scholar
  31. Li, D., Kang, S., Lu, C., Han, I., & Black, J. (2009, June). Case studies of developing programming skills via embodied experiences in an after-school LEGO Robotics Program for elementary school students. In EdMedia: World Conference on Educational Media and Technology (pp. 2209–2216). Association for the Advancement of Computing in Education (AACE).Google Scholar
  32. 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.Google Scholar
  33. Lindgren, R., Tscholl, M., Wang, S., & Johnson, E. (2016). Enhancing learning and engagement through embodied interaction within a mixed reality simulation. Computers & Education, 95, 174–187.Google Scholar
  34. Lu, C. M., Kang, S., Huang, S. C., & Black, J. B. (2011, June). Building student understanding and interest in science through embodied experiences with LEGO Robotics. In EdMedia: World Conference on Educational Media and Technology (pp. 2225–2232). Association for the Advancement of Computing in Education (AACE).Google Scholar
  35. Malinverni, L., & Pares, N. (2014). Learning of abstract concepts through full-body interaction: a systematic review. Journal of Educational Technology & Society, 17(4), 100.Google Scholar
  36. Melcer, E. F., & Isbister, K. (2016, May). Bridging the physical divide: a design framework for embodied learning games and simulations. In Proceedings of the 2016 CHI Conference Extended Abstracts on in Computing Systems (pp. 2225–2233). ACM.Google Scholar
  37. Merkouris, A., Chorianopoulos, K., & Kameas, A. (2017). Teaching programming in secondary education through embodied computing platforms: robotics and wearables. ACM Transactions on Computing Education (TOCE), 17(2), 9.Google Scholar
  38. Millar, S. (1999). Memory in touch. Psicothema, 11(4).Google Scholar
  39. Minogue, J., & Borland, D. (2016). Investigating students’ ideas about buoyancy and the influence of haptic feedback. Journal of Science Education and Technology, 25(2), 187–202.Google Scholar
  40. Montessori, M. (1966). The secret of childhood, trans. MJ Costello (Notre Dame, IN: Fides, 1966), 20.Google Scholar
  41. Nemirovsky, R., Rasmussen, C., Sweeney, G., & Wawro, M. (2012). When the classroom floor becomes the complex plane: addition and multiplication as ways of bodily navigation. Journal of the Learning Sciences, 21(2), 287–323.Google Scholar
  42. Oviatt, S., Cohen, A., Miller, A., Hodge, K., & Mann, A. (2012). The impact of interface affordances on human ideation, problem solving, and inferential reasoning. ACM Transactions on Computer-Human Interaction (TOCHI), 19(3), 22.Google Scholar
  43. Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. New York: Basic Books, Inc.Google Scholar
  44. Parmar, D., Isaac, J., Babu, S. V., D’Souza, N., Leonard, A. E., Jörg, S., ... & Daily, S. B. (2016). Programming moves: design and evaluation of applying embodied interaction in virtual environments to enhance computational thinking in middle school students. In Virtual Reality (VR), 2016 IEEE (pp. 131–140). IEEE.Google Scholar
  45. Phamduy, P., DeBellis, M., & Porfiri, M. (2015). Controlling a robotic fish via a natural user interface for informal science education. IEEE Transactions on Multimedia, 17(12), 2328–2337.Google Scholar
  46. Piaget, J. (2013). The construction of reality in the child (Vol. 82). Routledge.Google Scholar
  47. Pouw, W. T., Van Gog, T., & Paas, F. (2014). An embedded and embodied cognition review of instructional manipulatives. Educational Psychology Review, 26(1), 51–72.Google Scholar
  48. Raffle, H. S., Parkes, A. J., & Ishii, H. (2004). Topobo: a constructive assembly system with kinetic memory. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 647–654). ACM.Google Scholar
  49. Ramani, G. B., & Siegler, R. S. (2008). Promoting broad and stable improvements in low-income children’s numerical knowledge through playing number board games. Child Development, 79(2), 375–394.Google Scholar
  50. Resnick, M. (2001). Closing the fluency gap. Communications of the ACM, 44(3), 144–145.Google Scholar
  51. Resnick, M., Martin, F., Sargent, R., & Silverman, B. (1996). Programmable bricks: Toys to think with. IBM Systems Journal, 35(3.4), 443–452.Google Scholar
  52. Resnick, M., Martin, F., Berg, R., Borovoy, R., Colella, V., Kramer, K., & Silverman, B. (1998). Digital manipulatives: new toys to think with. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 281–287). ACM Press/Addison-Wesley Publishing Co.Google Scholar
  53. Segal, A. (2011). Do gestural interfaces promote thinking? Embodied interaction: congruent gestures and direct touch promote performance in math. New York: Columbia University.Google Scholar
  54. Skulmowski, A., & Rey, G. D. (2018). Embodied learning: introducing a taxonomy based on bodily engagement and task integration. Cognitive Research: Principles and Implications, 3(1), 6.Google Scholar
  55. Skulmowski, A., Pradel, S., Kühnert, T., Brunnett, G., & Rey, G. D. (2016). Embodied learning using a tangible user interface: the effects of haptic perception and selective pointing on a spatial learning task. Computers & Education, 92, 64–75.Google Scholar
  56. Song, H. S., Pusic, M., Nick, M. W., Sarpel, U., Plass, J. L., & Kalet, A. L. (2014). The cognitive impact of interactive design features for learning complex materials in medical education. Computers & Education, 71, 198–205.Google Scholar
  57. Tran, C., Smith, B., & Buschkuehl, M. (2017). Support of mathematical thinking through embodied cognition: nondigital and digital approaches. Cognitive Research: Principles and Implications, 2(1), 16.Google Scholar
  58. 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.Google Scholar
  59. Vygotsky, L. S. (1980). Mind in society: the development of higher psychological processes. Cambridge: Harvard university press.Google Scholar
  60. Wilson, M. (2002). Six views of embodied cognition. Psychonomic Bulletin & Review, 9(4), 625–636.Google Scholar
  61. 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(4), 425–430.Google Scholar
  62. Zacharia, Z. C., & De Jong, T. (2014). The effects on students’ conceptual understanding of electric circuits of introducing virtual manipulatives within a physical manipulatives-oriented curriculum. Cognition and Instruction, 32(2), 101–158.Google Scholar
  63. Zacharia, Z. C., & Olympiou, G. (2011). Physical versus virtual manipulative experimentation in physics learning. Learning and Instruction, 21(3), 317–331.Google Scholar
  64. 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.Google Scholar
  65. Zhai, S., Milgram, P., & Buxton, W. (1996). The influence of muscle groups on performance of multiple degree-of-freedom input. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 308–315). ACM.Google Scholar
  66. Zhu, K., Ma, X., Wong, G. K. W., & Huen, J. M. H. (2016). How different input and output modalities support coding as a problem-solving process for children. In Proceedings of the The 15th International Conference on Interaction Design and Children (pp. 238–245). ACM.Google Scholar
  67. Zuckerman, O., & Gal-Oz, A. (2013). To TUI or not to TUI: Evaluating performance and preference in tangible vs. graphical user interfaces. International Journal of Human-Computer Studies, 71(7), 803–820.Google Scholar
  68. Zuckerman, O., Arida, S., & Resnick, M. (2005). Extending tangible interfaces for education: digital montessori-inspired manipulatives. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 859–868). ACM.Google Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Department of InformaticsIonian UniversityCorfuGreece
  2. 2.School of Science and TechnologyHellenic Open UniversityPatrasGreece

Personalised recommendations