Robotics in School Chemistry Laboratories

  • Igor M. Verner
  • Leonid B. Revzin
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 457)


This paper proposes an approach to integrated learning of robotics and chemistry implemented in a laboratory course, in which high school students majoring in mechanical engineering are involved in the development of laboratory robotic devices and use them for chemical experiments. We consider learning activities at different stages of the course and characterize students’ engagement along the stages.


Educational robotics Chemistry Experiential learning Laboratory automation High school 


  1. 1.
    Sterling, J.D.: Laboratory automation curriculum at Keck Graduate Institute. J. Assoc. Lab. Autom. 9(5), 331–335 (2004)CrossRefGoogle Scholar
  2. 2.
    Wang, F., Hannafin, M.J.: Design-based research and technology-enhanced learning environments. Educ. Technol. Res. Dev. 53(4), 5–23 (2005)CrossRefGoogle Scholar
  3. 3.
    Wu, H.K., Huang, Y.L.: Ninth-grade student engagement in teacher-centered and student-centered technology-enhanced learning environments. Sci. Educ. 91(5), 727–749 (2007)CrossRefGoogle Scholar
  4. 4.
    Kim, M.C., Hannafin, M.J., Bryan, L.A.: Technology-enhanced inquiry tools in science education: An emerging pedagogical framework for classroom practice. Sci. Educ. 91, 1010–1030 (2007)CrossRefGoogle Scholar
  5. 5.
    Barnea, N., Dori, Y.J., Hofstein, A.: Development and implementation of inquiry-based and computerized-based laboratories: reforming high school chemistry in Israel. Chem. Educ. Res. Pract. 11, 218–228 (2010)CrossRefGoogle Scholar
  6. 6.
    Ainley, M., Hidi, S., Berndorff, D.: Interest, learning, and the psychological processes that mediate their relationship. J. Educ. Psychol. 94, 545–561 (2002)CrossRefGoogle Scholar
  7. 7.
    Mistler-Jackson, M., Songer, N.B.: Student motivation and Internet technology: Are students empowered to learn science? J. Res. Sci. Teach. 37(5), 459–479 (2000)CrossRefGoogle Scholar
  8. 8.
    Linn, M.: Technology and science education: starting points, research programs, and trends. Int. J. Sci. Educ. 25(6), 727–758 (2003)CrossRefGoogle Scholar
  9. 9.
    Dori, Y.J., Kaberman, Z.: Assessing high school chemistry students’ modeling sub-skills in a computerized molecular modeling learning environment. Instr. Sci. Int. J. Learn. Sci. 40(1), 69–91 (2012)Google Scholar
  10. 10.
    Girasoli, A.J., Hannafin, R.D.: Using asynchronous AV communication tools to increase academic self-efficacy. Comput. Educ. 51(4), 1676–1682 (2008)CrossRefGoogle Scholar
  11. 11.
    Corcoran, T., Silander, M.: Instruction in high schools: the evidence and the challenge. Future Child. 19(1), 157–183 (2009)CrossRefGoogle Scholar
  12. 12.
    Verner, I., Ushin, I., Korchnoy, E.: Learning physical fields through operating robot movements: a case study. In: Jamshidi et al. (eds.) Robotics, Manufacturing, Automation and Control, vol. 14. TSI Press, Albuquerque, NM, pp. 383–388 (2002)Google Scholar
  13. 13.
    Korchnoy, E., Verner, I.: Characteristics of learning computer-controlled mechanisms by teachers and students in a common laboratory environment. Int. J. Technol. Des. Educ. 20(2), 217–237 (2008)CrossRefGoogle Scholar
  14. 14.
    Cuperman, D., Verner, I.: Learning through creating robotic models of biological systems. Int. J. Technol. Des. Educ. 23(4), 849–866 (2013)CrossRefGoogle Scholar
  15. 15.
    Verner, I., Hershko, E.: School graduation project in robot design: a case study of team learning experiences and outcomes. J. Technol. Educ. 14(2), 40–55 (2003)CrossRefGoogle Scholar
  16. 16.
    Verner, I.M., Revzin, L.B.: Characteristics and educational advantages of laboratory automation in high school chemistry. Special focus paper. Int. J. Online Eng. 7(S1), 44−49 (2011)Google Scholar
  17. 17.
    Verner, I.M., Revzin, L.B.: Automation of manual operation in a high school chemistry laboratory: characteristics and students’ perceptions. The Chem. Educ. 15, 141–145 (2010)Google Scholar
  18. 18.
    Goldin, G.A., Epstein, Y.M., Schorr, R.Y., Warner, L.B.: Beliefs and engagement structures: Behind the affective dimension of mathematical learning. ZDM Math. Educ. 43, 547–560 (2011)CrossRefGoogle Scholar
  19. 19.
    Verner, I.: Characteristics of student engagement in robotics. In: Omar, K., et al. (eds.) FIRA 2013, CCIS 376, pp. 181–194. Springer, Heidelberg (2013)Google Scholar
  20. 20.
    Tortosa, M.: The use of microcomputer based laboratories in chemistry secondary education: present state of the art and ideas for research-based practice. Chem. Educ. Res. Pract. 13, 161–171 (2012)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Faculty of Education in Science and TechnologyTechnion – Israel Institute of TechnologyHaifaIsrael

Personalised recommendations