| Published: February 28, 2017
Problem Solving In Mathematics-Role of Worked Examples in Reducing Cognitive Load and Improving Scholastic Performance
Mathematics is a compulsory subject at school level across the globe. It is also considered as a difficult subject. Reducing the cognitive load and improving the scholastic performance are the main concerns in the teaching learning process of mathematics. The present study is an attempt in this direction by using cognitive load theory. The study is intended to analyze the role of worked examples in learning mathematics and to design and conduct an intervention to reduce the cognitive load and improve the performance of students in mathematics. Sample comprised of 76 students of 6th grade. The sample was divided in to two groups of control and treatment conditions. There were two phases in the intervention namely learning phase and test phase. At Learning phase students were taught according to either a traditional procedure or according to worked examples effect of cognitive load theory. At test phase all students (control condition and treatment condition) were presented a common test (Scholastic Achievement Test). During the learning phase student’s performance in the form of errors committed and cognitive load experienced were recorded. During the test phase student’s performance and cognitive load experienced were recorded. The study revealed that students who studied worked examples committed fewer errors and experienced low cognitive load. Students who studied worked examples performed better and experienced less cognitive load than students who solved the same number of problems. It is recommended to give more emphasis on worked examples to improve the performance of children in mathematics and to reduce the cognitive load experienced by students in mathematics.
This is an Open Access Research distributed under the terms of the Creative Commons Attribution License (www.creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any Medium, provided the original work is properly cited.
© 2017 Rao V
Received: February 11, 2017; Revision Received: February 24, 2017; Accepted: February 28, 2017
Published in Volume 04, Issue 2, January-March, 2017