Search

The study aimed to analyze the interaction effect teaching models and cognitive style field dependent (FD)-field independent (FI) to students’ mathematical problem-solving ability (MPSA), as well as students' MPSA differences based on teaching models and cognitive styles. Participants in this study were 145 junior high school students, with details of 50 students learning through the Connect, Organize, Reflect, and Extend Realistic Mathematics Education (CORE RME) model, 49 students use the CORE model, and 46 students use the Conventional model. Data collection tools used are the MPSA test, and the group embedded figure test (GEFT). The MPSA test finds out that there are interaction effect teaching models and cognitive styles on students' MPSA, as well as a significant difference in MPSA students who study through the CORE RME model, CORE model, and Conventional model. Based on cognitive style, between students who study through CORE RME model, CORE model, and Conventional model found that there was no significant difference in MPSA between FI students. Furthermore, there were significant differences in MPSA between FD students and also MPSA of FI students better than MPSA FD students. Therefore, teaching models and student cognitive styles are very important to be considered in the learning process, so students are able to solve mathematical problems.

The purpose of this study was to describe how to implement the REACT strategy to develop students’ mathematical representation, reasoning, and disposition ability. This research was a descriptive study with a qualitative approach. The subject of this study was grade 8 junior high school student in Bandung. Data collection techniques in this study with observations, interviews, and documentation. Based on data analysis results, it could be concluded that REACT strategies can be applied to develop a mathematical representation, reasoning, and disposition ability that engages students actively. Implementation of the REACT strategy runs smoothly and gets enthusiastic responses from students. The application of REACT strategies should be undertaken sustainably so that the learning objectives can be achieved by integrating various mathematical skills that were capable.

The study aimed at improving students’ algebraic thinking ability in the eighth-grade junior high school student through multiple representation strategies using realistic approach. The multiple representation strategies consist of orientation, exploration, internalization, and evaluation. This is a quasi-experimental study with nonrandomized pretest-posttest control group design. The population of this study was the student the eighth grade in Kudus city. Two classes were selected and classified as a class experiment that subject are given multiple representation strategies using realistic approach, and one other class as a control class that subjects are given scientific approach. Data obtained was analyzed by the independent t-test and proportions test. The result showed that there was an interaction between the multiple representation strategies using the realistic approach on the ability of algebraic thinking. The students with multiple representation strategies had better algebraic thinking ability than those with current scientific learning. In addition, more than seventy-five percent of the students with multiple representation strategies using realistic approach fulfill the learning completeness.

The purpose of this study was to investigate the errors experienced by students learning with REACT strategy and traditional learning in solving problems of mathematical representation ability. This study used quasi experimental pattern with static-group comparison design. The subjects of this study were 47 eighth grade students of junior high school in Bandung consisting of two samples. The instrument used was a test to measure students' mathematical representation ability. The reliability coefficient about the mathematical representation ability was 0.56. The most prominent errors of mathematical representation ability of students learning with REACT strategy and traditional learning, was on indicator that solving problem involving arithmetic symbols (symbolic representation). In addition, errors were also experienced by many students with traditional learning on the indicator of making the image of a real world situation to clarify the problem and facilitate its completion (visual representation). DOI: http://dx.doi.org/10.22342/jme.9.1.4301.121-128

The purpose of this study is to show the differences in problem-solving ability between first-year University students who received culture-based contextual learning and conventional learning. This research is a quantitative research using quasi-experimental research design. Samples were the First-year students of mathematics education department; Nusa Cendana University consists of 58 students who were divided into two groups each of 29 students. The results showed there are differences in the n-gain average of problem-solving ability significantly between students who receive culture-based contextual learning and conventional learning. The n-gain average of experiment group is 0.51 or medium category while the average n-gain of the control group is 0.29 or low category. Student categories of SNMPTN and Mandiri are significantly different whereas students’ category of SBMPTN between the two groups does not differ significantly. DOI: http://dx.doi.org/10.22342/jme.9.1.4125.81-94

The purpose of this study was to investigate the errors experienced by students learning with REACT strategy and traditional learning in solving problems of mathematical representation ability. This study used quasi experimental pattern with static-group comparison design. The subjects of this study were 47 eighth grade students of junior high school in Bandung consisting of two samples. The instrument used was a test to measure students' mathematical representation ability. The reliability coefficient about the mathematical representation ability was 0.56. The most prominent errors of mathematical representation ability of students learning with REACT strategy and traditional learning, was on indicator that solving problem involving arithmetic symbols (symbolic representation). In addition, errors were also experienced by many students with traditional learning on the indicator of making the image of a real world situation to clarify the problem and facilitate its completion (visual representation).

The intention of the present study was to see the improvement of students’ intuitive skills. This improvement was seen by comparing the Realistic Mathematics Education (RME)-based instruction with the conventional mathematics instruction. The subject of this study was 164 fifth graders of elementary school in Palembang. The design of this study was a Pretest-Posttest Control Group Experiment. Data was analyzed with the help of SPSS. The result of this study showed that there was different improvement of students’ skills. The improvement was higher in the class using the RME-based instruction that in conventional mathematics class.Keywords: Realistic Mathematics Education (RME), Intuition DOI: http://dx.doi.org/10.22342/jme.5.1.1446.27-34

The students’ difficulty which was found is in the problem of understanding, drawing diagrams, reading the charts correctly, conceptual formal mathematical understanding, and mathematical problem solving. The appropriate problem representation is the basic way in order to understand the problem itself and make a plan to solve it. This research was the experimental classroom design with a pretest-posttest control in order to increase the representation of visual thinking ability on mathematical problem solving approach with contextual learning. The research instrument was a test, observation and interviews. Contextual approach increases of mathematical representations ability increases in students with high initial category, medium, and low compared to conventional approaches. Keywords: Visual Thinking Representation, Mathematical Problem Solving, Contextual Teaching Learning Approach DOI: http://dx.doi.org/10.22342/jme.4.1.568.113-126