The Effect of Mathematical Disposition on Mathematical Power Formation: Review of Dispositional Mental Functions

Kusmaryono, Imam; Suyitno, Hardi; Dwijanto, Dwijanto; Dwidayati, Nur Karomah

doi:10.29333/iji.2019.12123a

Cited by 41 publications

(36 citation statements)

References 9 publications

(9 reference statements)

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“…Based on the results of data analysis it was concluded that mathematical disposition and student learning motivation had a significant influence on problem solving abilities, it could see from the double regression equation: ̂ . This is in line with the research of Darmawati (2017), Fadila, Septiana, Amelia, & Wahyuni (2019), Kusmaryono, Suyitno, Dwijanto, & Dwidayati (2019) and Taiyeb & Mukhlisa (2015), that there were a relationship between mathematical disposition, learning motivation and learning outcomes. Likewise, it is also in line with the research of Huda (2016) and Ningsih & Rohana (2016) that mathematical dispositions and student learning motivation are mainly students' activeness in aspects: working together to solve problems, giving opinions when there are group friends who have not understood, resolved dissent, and communicated with friends and teachers during the learning process in the classroom has increased.…”

Section: Enoughsupporting

confidence: 91%

The Effect of Mathematical Disposition and Learning Motivation on Problem Solving: An Analysis

Hutajulu

Wijaya

Hidayat

2019

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This research was motivated by the low problem-solving abilities, mathematical disposition, and learning motivation of junior students. This study aims to find and analyze the influence of mathematical dispositions empirically and learning motivation on problem-solving abilities. Samples were obtained in class VII-2 at SMPN 2 Cimahi as many as 34 students. The study uses quantitative correlational methods. The analysis was done by a regression method. The data collection was given two pieces of study instruments, namely problem-solving test instruments and non-test questionnaires in a set of mathematical dispositions and learning motivation. The data were tested for regression and correlation. The results of data analysis that was a mathematical disposition and learning motivation were significantly influenced by the problem-solving ability of junior students, with the regression equation Y = 1.95 + 0.121X1 + 0.015X2 indicating a positive influence, and the degree of closeness is the Pearson correlation coefficient of 0.827 classified in a robust positive interpretation. Together, mathematical disposition variables and learning motivation variables can determine the problem-solving variable by 68.3%. Recommendations from this study, teachers should design learning processes that can improve mathematical disposition and student motivation so that students' problem-solving abilities increase.

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Section: Enoughsupporting

confidence: 91%

The Effect of Mathematical Disposition and Learning Motivation on Problem Solving: An Analysis

Hutajulu

Wijaya

Hidayat

2019

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“…According to Kemendikbud (2016) the affective domain determines a person's learning success. This is in line with Kusmaryono, Suyitno, Dwijanto, & Dwidayati, 2019;Lin & ChunTai (2016) teacher need to focus not just on the development of math knowledge and skills, but on the development of the mathematics disposition and also should optimize the dispositional mental functions of the students by selecting a learning model, affective and conative. Mathematical disposition is, therefore, strong willingness, awareness, dedication, and tendency of a student to think and act mathematically in a positive manner (Akbar, Hamid, Bernard, & Sugandi, 2017).…”

Section: Introductionmentioning

confidence: 65%

The Effectiveness of Geogebra-Based Van Hiele Model on Mathematical Disposition Assessed From Early Mathematics Ability

Noviana

Hadi

Handayani

2020

KJPM

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The aim of this research was to observe the effectiveness of geogebra based van hiele model on mathematical disposition assessed from early mathematics ability. The accessible population of the present study was students of Prof. DR. HAMKA Muhammadiyah University. Samples of this research is semester two students from mathematics education program. Due to the happening Covid-19 pandemic, the present study was conducted online. The method employed was quasi-experiment using factorial treatment by level 2 × 2 design. The data were collected with mathematical disposition questionnaire and early mathematics ability instrument. After the data were collected, they were then analyzed with two-way ANAVA analysis. The result showed that there was no significant difference in the increase mathematical disposition of students who are given the learning model and early mathematics ability. The conclusion obtained is that the geogebra based Van Hiele Model is ineffective on students’ mathematical disposition in terms of their early mathematics abilitiy. This is due to several factors, namely internal factors and external factors. The internal factors are decreas in the score of mathematical disposition from pretest to posttest, lack of understanding applying geogebra software with online learning. External factors are quotas and poor internet network.

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“…However, after the scaffolding implementation, all factors of mathematics anxiety decreased significantly. The scaffolding gave to students to reflect their work and led them to initial knowledge to solve problems they had [10] and also improved positive disposition toward mathematics [16], [23].…”

Section: Figure 3 Student (S3) Answer After Scaffoldingmentioning

confidence: 99%

Effectiveness of Scaffolding Strategies in Learning Against Decrease in Mathematics Anxiety Level

Kusmaryono

Gufron

Rusdiantoro³

2020

Numerical: J.Mat and Pend.Mat

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This study is a mixture of quantitative and qualitative with sequential explanatory designs. The study aims to (1) analyze the improvement of student achievement in learning after scaffolding, (2) evaluate the level of students 'mathematics anxiety, and (3) describe the role of scaffolding in changing students' perceptions of mathematics anxiety in classroom learning. Sampling through random sampling techniques obtained by students of class X-IPA-1 and X-IPA-2 in SMA Negeri 6 Semarang. Quantitative data analysis uses statistical test techniques: normality test, paired sample t-test, and N-gain test. Qualitative data analysis through interactive methods namely data collection, data reduction, data presentation, and drawing conclusions. Data validation techniques through the source and method triangulation. The results showed that (1) there was an increase in student learning achievement after the application of the scaffolding strategy by 33.0% to 34.5%; (2) there was a decrease in the level of mathematics anxiety in students by 90.4%; (3) through scaffolding, students succeed in reflecting and correcting mistakes in solving previous problems. This means scaffolding can be an effective strategy to help students move across different Zones of Proximal Development (ZPD). The scaffolding strategy has also created a positive classroom environment that encourages students to learn mathematics without fear.

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The Effect of Mathematical Disposition on Mathematical Power Formation: Review of Dispositional Mental Functions

Cited by 41 publications

References 9 publications

The Effect of Mathematical Disposition and Learning Motivation on Problem Solving: An Analysis

The Effect of Mathematical Disposition and Learning Motivation on Problem Solving: An Analysis

The Effectiveness of Geogebra-Based Van Hiele Model on Mathematical Disposition Assessed From Early Mathematics Ability

Effectiveness of Scaffolding Strategies in Learning Against Decrease in Mathematics Anxiety Level

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