Effect of Model-Eliciting Activities using Cloud Technology on the Mathematical Problem-Solving Ability of Undergraduate Students

Abstract

Problem-solving is considered as an important skill for learning Mathematics. Integration of cloud technology into Model-Eliciting Activities (MEAs) has been considered as an instructional approach to study students’ mathematical problem-solving abilities. The purposes of this study were to evaluate the suitability of the MEAs using cloud technology, and assess the mathematical problem-solving ability of undergraduate students learning the proposed model compared with the criteria of 50%. The participants were 50 undergraduate students who were enrolled on Numerical Analysis courses, selected by using a purposive sampling technique. We conducted quasi-experiments using a one-group design to determine the impact of the model on students and assessed whether the students had exceeded the criterion for mathematical problem-solving ability. The research instruments were instructional plans of the MEAs using cloud technology, a suitability assessment form, and a mathematical problem-solving test. The data were analysed quantitatively using descriptive statistics such as mean and standard deviation, and a t-test. The findings revealed that 5 experts evaluated the model as being “most suitable”, and that the mathematical problem-solving ability of the undergraduate students exceeded the criterion of 50% at a .05 level of statistical significance. The students displayed satisfactory competence in implementing key mathematical concepts to solve problems.