You are here:

Effects of Online Math Applets on Students’ Mathematical Thinking
PROCEEDINGS

, University of Detroit Mercy, United States

Society for Information Technology & Teacher Education International Conference, in Jacksonville, Florida, United States ISBN 978-1-939797-07-0 Publisher: Association for the Advancement of Computing in Education (AACE), Chesapeake, VA

Full Text

Abstract

This study examined the effects of using online math applets (OMAs) on students’ performance on the problems requiring various levels of mathematical thinking. Through using Webb’s (2002) Depth of Knowledge (DOK) framework, the problems are assigned into three levels of mathematical thinking: “recall,” “skill/concept” and “strategic thinking.” Participants were forty-eight college students taking a remedial mathematics course, randomly assigned into two groups, and used the same set of OMAs with open-ended exploratory versus structured mathematics questions. The pre-and posttest assessing students’ performance on the three types of items mentioned above were administered and students’ interactions with the OMAs were analyzed. The findings revealed that OMAs enabled students working with open-ended exploratory activities to improve their solutions to the “strategic thinking” type of items.

Citation

Demir, M. (2014). Effects of Online Math Applets on Students’ Mathematical Thinking. In M. Searson & M. Ochoa (Eds.), Proceedings of SITE 2014--Society for Information Technology & Teacher Education International Conference (pp. 1405-1410). Jacksonville, Florida, United States: Association for the Advancement of Computing in Education (AACE). Retrieved December 12, 2019 from .

© 2014 Association for the Advancement of Computing in Education (AACE)

References

View References & Citations Map
  1. Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16(3), 183-198.
  2. Crawford, C., & Brown, E. (2003). Integrating Internet-based mathematical manipulatives within a learning environment. Journal of Computers in Mathematics and Science Teaching, 22(2), 169-180.
  3. Decker, R. (2011). The Mathlet Toolkit: Creating Dynamic Applets for Differential Equations and Dynamical Systems. International Journal for Technology in Mathematics Education, 18(4), 189-194.
  4. Gadanidis, G., Gadanidis, J. & Schindler, K. (2003). Factors Mediating the Use of Online Applets in the Lesson Planning of Preservice Mathematics Teachers. Journal of Computers in Mathematics and Science Teaching, 22(4), 323-344. Norfolk, VA: AACE. Retrieved January 16, 2014 from http://www.editlib.org/p/11933. Hutchins, E.L., Hollan, J.D., & Norman, D.A. (1986). Direct manipulation interfaces. In D.A. Norman& S.W. Draper (Eds), User centered system design: New perspectives in human–computer interaction.
  5. Kaput, J.J. (1998). Representations, inscriptions, descriptions and learning: A kaleidoscope of windows. Journal of Mathematical Behavior, 17(2), 265–281.
  6. Manches, A., & O’Malley, C. (2011). Tangibles for learning: a representational analysis of physical manipulation. Personal and Ubiquitous Computing, 16(4), 405–419. .
  7. Moyer-Packenham, P.S., & Suh, J.M. (2012). Learning mathematics with technology: The influence of virtual manipulatives on different achievement groups. Journal of Computers in Mathematics and Science Teaching, 31(1), 39-59.
  8. Parnafes, O., & Disessa, A. (2004). Relations between types of reasoning and computational representations. International Journal of Computers for Mathematical Learning, 9(3), 251-280.
  9. Scaife, M., & Rogers, Y. (1996). External cognition: How do graphical representations work? International Journal of Humane-Computer Studies, 45(2), 185-213.
  10. Suh, J., & Moyer, P.S. (2007). Developing students’ representational fluency using virtual and physical algebra balances. Journal of Computers in Mathematics and Science Teaching, 26(2), 155-173.
  11. Thompson, P.W. (1994). Images of rate and operational understanding of the fundamental theorem of calculus. Educational Studies in Mathematics, 26(2-3), 229-274.
  12. Tobias, S. (1982). When do instructional methods. Educational Researcher, 11(4), 4–9. .
  13. Webb, N.L. (2002). An Analysis of the alignment between mathematics standards and assessments for three states. American Educational Research Association Annual Meeting, New Orleans, LA.
  14. White, T., & Pea, R. (2011). Distributed by design: On the promises and pitfalls of collaborative learning with multiple representations. Journal of the Learning Sciences, 20(3), 489-547.
  15. Zbiek, R.M., Heid, M.K., Blume, G.W., & Dick, T.P. (2007). Research on technology in mathematics education: The perspective of constructs. In F. Lester (Ed.), Handbook of research on mathematics teaching and learning (Vol. 2, pp. 1169-1207). Charlotte, NC: Information Age Publishing.

These references have been extracted automatically and may have some errors. Signed in users can suggest corrections to these mistakes.

Suggest Corrections to References

Also Read

Related Collections