Improving Students’ Performance in Stoichiometry through the Implementation of Collaborative Learning
Mary Felicia Opara
Journal of Education and Vocational Research, 2014, vol. 5, issue 3, 85-93
Abstract:
The study was designed to foster the implementation of collaborative learning in stoichiometry among secondary school students. It was hypothesized that students who were exposed to collaborative learning will not perform significantly better than those exposed to lecture method. The design of the study was a pretest – posttest non-equivalent control group design. Two hundred and eighty seven Senior Secondary class 2 students from Special Science Schools in Anambra State, Nigeria participated in the study. The reliability of the instrument, Stoichiometry Achievement Test (SAT) was established using split-half reliability coefficient. Analysis of covariance (ANCOVA) was used to test the null hypothesis after obtaining the mean of the pretest and posttest scores. The results revealed that collaborative learning significantly enhanced students’ performance in stoichiometry, as students who were exposed to collaborative learning outperformed those exposed to lecture method. Based on the findings of the study educational practices in Nigeria were urged to promote and implement collaborative learning and decrease on the structure of transmission model.
Date: 2014
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
https://ojs.amhinternational.com/index.php/jevr/article/view/156/156 (application/pdf)
https://ojs.amhinternational.com/index.php/jevr/article/view/156 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:rnd:arjevr:v:5:y:2014:i:3:p:85-93
DOI: 10.22610/jevr.v5i3.156
Access Statistics for this article
More articles in Journal of Education and Vocational Research from AMH International
Bibliographic data for series maintained by Muhammad Tayyab ().