Full-text resources of CEJSH and other databases are now available in the new Library of Science.
Visit https://bibliotekanauki.pl

PL EN


2016 | 44 | 153-164

Article title

Effectiveness of geogebra on academic and conceptual knowledge: role of students’ procedural knowledge as a mediator

Content

Title variants

Languages of publication

Abstracts

EN
Quasi-experimental research was conducted to identify the effectiveness of GeoGebra in achieving students’ conceptual and procedural knowledge. The research was performed to identify the effects of a mediator in students’ conceptual knowledge in relation to procedural knowledge with student achievement. A total of 284 students were involved in this study. The students in the experimental group learned using GeoGebra, whereas the students in the control group used the conventional method. The collected data were analyzed using SPSS 22.0, AMoS 18, and Anates V4. Findings of the study demonstrate that GeoGebra is used as a mediator of students’ procedural knowledge in relation to conceptual knowledge for academic achievement. This study also shows that conceptual knowledge affected the students’ mathematics procedures. The result of the study supports the related theory of the role and contribution of conceptual and procedural knowledge to student achievement. This study provides suggestions as intervention to increase students’ conceptual and procedural knowledge.

Year

Volume

44

Pages

153-164

Physical description

Dates

published
2016

Contributors

References

  • Ahmad Fauzi Mohd Ayub, Tengku Mohd Tengku Sembok and Wong Su Luan. (2009). The use of computers in teaching and learning calculus students in the diploma: rat- ings on packages TeMACCC (ed.), Ahmad Fauzi Mohd Ayub and Aida Suraya Md. yunus. Mathematic education and Technology Applied, Putra University of Malaysia. pp. 274-300.
  • Aizikovitsh, U.e and radakovic, N. (2011). Using GeoGebra for Understanding and Sup- porting Students’ Learning of Probability. Proceedings Of The Second North American GeoGebra Conference: Where Mathematics, Education and Technology Meet. University of Toronto. June 17-18, 2011. ISBN 978-0-920233-65-8 (Cd).
  • Best, J.W and Kahn, J.V. (2003). Research in education (ed.), Boston: A Pearson education Company.
  • Carpenter, T.P. (1986). Conceptual knowledge as a foundation for procedural knowledge. In: J Hibert (ed.), Conceptual and procedural knowledge: The case of mathematics. Hills- dale, NJ, Lawrence erlbaum Assosiates. pp. 113-131.
  • Engelbrecht, J., Harding, A., and Potgieter, M. (2005). Undergraduate students’ performance and confidence in procedural and conceptual mathematics. http://ridcully.upac.za/multi/conceptualmath.pdf.
  • Hair, J., Black, W., Babin, B., Anderson, r., Tatham, r. (2006). Multivariate data analysis (6th ed.), Uppersaddle river, NJ, Pearson Prentice Hall.
  • Harper, J.L. (2007). The use of computer algebra systems in a procedural Algebra course to facilitate a framework for Procedural understanding. Dissertation Doctor of Philosophy. Montana State University. ProQuest.
  • Hashim, r.A., and Sani, A.M. (2008). A Confirmatory Factor Analysis of Newly Integrated Multidimensional School engagement Scale. MJLI, 5: 21-40.
  • Hiebert, J. 1986. Conceptual and Procedural Knowledge: The case of mathematics. Hillsdale, Lawrence erlbaum Associates.
  • Hibert, J., and Lefevre, P. (1986). Coceptual and procedural knowledge in mathematics: An introductory analyis. In: J. Hibert (ed.), Conceptual and procedural knowledge; the case of mathematics, Hillsdale, NJ, Lawrence erlbaum Associates. pp. 1-23.
  • Hope Marchionda. (2006). Preservice teacher procedural and conceptual understanding of fractions and the effects of inquiry based learning on this understanding. Unpublished Doctoral Dissertation. Clemson University.
  • Juter, K. (2006). Limits of functions: University students’ concept development. Ph.d thesis, Lulea University of Technology.
  • Karno To. (1996). Identification Test Analysis (Introduction to Computer Program ANATES). Bandung: educational Psychology and Guidance FIP IKIP.
  • Kiuru, N., Pakarinen, e., Vasalampi, K., Silinskas, G., Aunola, K., Poikkeus, A.M., Leena, R., Metsäpelto, Lerkkanen, M.K., and Nurmi, J.e. (2014). Task-Focused Behavior Mediates the Associations Between Supportive Interpersonal environments and Students’ Academic Performance. Psychological Science published, 1: 1-7. doI: 10.1177/0956797613519111.
  • Kline, r.B. (2005). Principles and Practice of Structural Equation Modeling (2nd Edition). New york: The Guilford Press.
  • Lim, C.H. (2007). Educational Research: Quantitative and Qualitative Approaches. Kuala Lumpur: McGraw Hilll education.
  • Nesher, P. (1986). Are mathematical understanding and algorithmic performance related? For the Learning of Mathematics, 6(3): 2-9.
  • Oldknow, A., and Taylor, r. (2000). Teaching Mathematics with ICT. London: Continuum.
  • Pesek, d.d., and Kirshner, d. (2000). Interference of instrumental instruction in the sub- sequent relational learning. Journal for Research in Mathematics Education, 31:524-540. doi: 10.2307/749885.
  • Pettersson, K., and Scheja, M. (2008). Algorithmic contexts and learning potentiality: A case study of students’ understanding of calculus. International Journal of Mathematical Education in Science and Technology, 39(6): 767-784. doi: 10.1080/00207390801986908. rico, L. 2006. Marco teôrico de evaluaciôn en PISA sobre matemâticas y resoluciôn de problemas. revista de educaciôn, extraordinario, 1: 275-294.
  • Rincon, L.F. (2009). Designing Dynamic and Interactive Applications Using GeoGebra Software. Kean University. erIC Full text and Thesis.
  • Rittle-Johnson, B., and Koedinger, K.r. (2005). designing knowledge scaffolds to sup- port mathematical problem solving. Cognition and Instruction, 23(3):313-349. doi: 10.1207/s!532690xci230.
  • Robiah Sidin. (1994). Education in Malaysia. Challenges of the Future. Kuala Lumpur: Fajar Bakti. rohani Ahmad Tarmizi, Che Wan rosida Wan Hasan, Ahamd Fauzi Mohd Ayub, Kamariah Abu Bakar, and Aida Suraya Md yunus (2009). Use of graphing calculators in the teaching and learning of mathematics. In: Ahmad Fauzi Mohd Ayub and Aida Suraya Md yunus. Mathematics Education and Technology Application. Putra University of Malaysia.
  • Selden, A., and Selden, J. (1992). research perspective on conceptions of functions: sum- mary and overview. In: Harel, G. and dubinsky e (ed.), the concept of function: aspects of epistemology and pedagogy. Washington, dC, Mathematical Association of America. pp. 1-16.
  • Setu Budiardjo (2011). Adoption Jigsaw cooperative learning methods to improve the learning outcomes of students class XII-2 light transport techniques SMK Negeri 5 Semarang in resolving the derivative function. Journal AKSIOMA. (2).
  • Sivin-Kachala, J., and Bialo, e.r. (2000). Research Report on the Effectiveness of Technology in Schools 7 Edition. Washington, dC, software Information Industry Association.
  • Slameto (2003). Learning and Factors Affecting. Jakarta: rhineka Cipta.
  • Star, J. (2005). reconceptualizing procedural knowledge. Journal for Research in Mathemat- ics Education, (36): 404-411.
  • Tall, d.o., and Vinner, S. (1981). Concept image and concept definition in mathematics, with special reference to limits and continuity. Educational Studies in Mathematics, (12): 151-169. doi: 10.1007/BF00305619.
  • Williams, S. (1991). Models of limits held by college calculus students. Journal for Research in Mathematics Education, 22(3): 219-236. doi: 10.2307/749075.
  • Zainuddin Awang (2012). Structural Equation Modeling Using Amos Graphic: UiTM Press.

Document Type

Publication order reference

Identifiers

Biblioteka Nauki
2004969

YADDA identifier

bwmeta1.element.ojs-doi-10_15804_tner_2016_44_2_12
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.