You are here:

The Application of Simulation-Assisted Learning Statistics (SALS) for Correcting Misconceptions and Improving Understanding of Correlation
ARTICLE

, ,

Journal of Computer Assisted Learning Volume 26, Number 2, ISSN 1365-2729 Publisher: Wiley

Abstract

Simulation-based computer assisted learning (CAL) is recommended to help students understand important statistical concepts, although the current systems are still far from ideal. Simulation-Assisted Learning Statistics (SALS) is a simulation-based CAL that is developed with a learning model that is based on cognitive conflict theory to correct misconceptions and enhance understanding of correlation. In this study, a mixed method (embedded experiment model) was utilized to examine the effects of SALS-based learning compared with lecture-based learning. The sample was composed of 72 grade-12 students, who were randomly assigned to either the experimental group or the comparison group. The findings reveal that the SALS-based learning approach is significantly more effective than lecture-based learning, in terms of correcting students' misconceptions and improving their understanding of correlation. The study also uses quantitative and qualitative data to examine how the learning model of the SALS-based learning approach contributes to the enhanced learning outcomes. Finally, practical suggestions were made with regard to directions for future studies.

Citation

Liu, T.C., Lin, Y.C. & , K. (2010). The Application of Simulation-Assisted Learning Statistics (SALS) for Correcting Misconceptions and Improving Understanding of Correlation. Journal of Computer Assisted Learning, 26(2), 143-158. Wiley. Retrieved September 22, 2019 from .

This record was imported from ERIC on April 19, 2013. [Original Record]

ERIC is sponsored by the Institute of Education Sciences (IES) of the U.S. Department of Education.

Copyright for this record is held by the content creator. For more details see ERIC's copyright policy.

Keywords