Statistical Reasoning Ability Research Articles

PENGARUH MODEL PEMBELAJARAN BERBASIS MASALAH PADA MATERI STATISTIKA TERHADAP KEMAMPUAN PENALARAN STATISTIK DAN HABITS OF MIND SISWA SMPN 1 WANASABA

This research aims to determine the effect of problem-based learning models on statistics material on the statistical reasoning abilities and habits of mind of students at SMPN 1 Wanasaba. The study utilized a quasi-experimental design with a Non-Equivalent Control Group Design. The population consisted of all seventh-grade students at SMPN 1 Wanasaba, totaling 225 students. The sample included class VII B as the control group with 30 students and class VII C as the experimental group with 30 students. Data collection instruments included a test of statistical reasoning abilities and a habits of mind questionnaire. The data on students' statistical reasoning abilities and habits of mind were normally distributed, and their variances were homogeneous. The t-test results indicated that there was a difference in the average statistical reasoning abilities and habits of mind between the experimental and control groups, with the experimental group showing superior average statistical reasoning abilities and habits of mind compared to the control group. In conclusion, the problem-based learning model on statistics material has a partial effect on the statistical reasoning abilities and habits of mind of students at SMPN 1 Wanasaba.

Development of Electronic Test Instruments Through Vinesa to Improve Statistical Reasoning Ability on Tendency Central Materials

This study aims to assess the feasibility of developing an e-test instrument for statistics courses on central tendency material so that student learning outcomes can increase. The analysis used in this research is quantitative and descriptive. This research method uses 20 students. Methods of data collection using tests, observations, interviews, and questionnaires The procedures carried out in developing the test instrument are: 1) compiling test specifications; 2) writing test questions; 3) reviewing the item items; 4) conducting test trials; 5) analyzing the item items; 6) revising the test; 7) compiling the test; 8) carrying out the test; and 9) interpreting the test results. The ADDIE model is used in this development research. The results of the feasibility of developing electronic test instruments were stated to be valid with: a) the results of validating the material were very feasible (96%); b) the results of validating learning media were very feasible (94%). If c) the results of validating learning designs were very feasible (94%), d) the results of individual trials were very feasible (81%), and e) the results of small group trials were very feasible (82%), then the development of electronic test instruments is very feasible for use in statistical learning.

Implementation of R Software in Improving Student Statistical Reasoning, is it Effectivities?

In the current era of digitalization, statistical skills are needed to interpret and understand and make good decisions about statistical data. However, many students still have the view that statistics is a difficult subject to understand. This is based on the fact that in working on the problem sufficient statistical skills are needed, starting from basic skills to application abilities. Students who have low statistical abilities become less interested in statistics lectures. One of these statistical abilities is statistical reasoning. Statistical reasoning is the student's ability to make logical conclusions from a problem by using statistical concepts in a comprehensive manner, and making decisions as well as evaluating and interpreting the information processed. Efforts to improve statistical reasoning skills require a learning innovation using an application. The role of technology in learning statistics includes using modules assisted by the R program. The research method used is quasi-experimental with a research design, namely pretest-posttest control group design. The results showed that the statistical reasoning abilities of students whose lectures used the R program assisted module were higher than regular lectures for both the low, medium and overall groups. However, the high group had the same increase in statistical reasoning abilities between the experimental and control classes. The effect of statistics lectures using the R program assisted module was high in the medium, low and overall groups. Thus, the use of the R program assisted module is effective in increasing statistical reasoning.

Student-Teacher Level of Statistical Reasoning Ability Reviewed by Apos Theory (Action, Process, Object, Schema)

In learning statistics, there is the term statistical reasoning. Statistical reasoning arises because of the opinion that learning statistics using a traditional approach does not lead students to have statistical reasoning abilities or to think statistically. There are four statistical reasoning levels: idiosyncratic, transitional, quantitative, and analytical. Student-teachers must understand fundamental statistical concepts more deeply to develop statistical reasoning abilities. The mental construction of a statistical concept can be analyzed using APOS (Action, Process, Object, Schema) theory. Through the APOS theory, researchers can determine individual understanding of statistical concepts that cause individuals to reason or draw reasonable conclusions based on the statistical information obtained. This study aims to analyze the interrelationships and make conjectures regarding the level of statistical reasoning ability based on the APOS theory. The research subjects are. 19 informants. The research results obtained four conjectures, namely. Students at the idiosyncratic level are in the action stage; students at the transitional stage are in the action, process, or object stage; students at the quantitative stage are in the process or object stage; lastly, students at the analytical are in the schema stage.

Differences in the Improvement of Statistical Reasoning Ability Based on Students' Self-Regulated Learning Level in Online Learning Using LMS

In the literature, studies on technology-supported learning, especially using LMS, have been widely carried out during a pandemic. However, little is known about LMS, which is interesting and helps to develop students' statistical reasoning abilities for online learning by considering the students' Self-Regulated Learning (SRL) levels (High, medium and low). This study aims to examine and analyze the differences in statistical reasoning abilities of students who study using LMS in terms of SRL levels (high, medium and low). This study uses a quantitative method with the type of One-group pre-test post-test design. What took sampled randomly at the University of Pasundan Bandung, totalling 54 third-level students of Pasundan University Bandung, Indonesia. Research data related to statistical reasoning abilities were collected through a test consisting of six questions. In contrast, SRL level data were collected using a questionnaire consisting of 46 question items. Paired t-test and One-way ANOVA analysis were applied to answer the research hypothesis. The results of the study concluded that students studying with LMS with High SRL obtained a higher increase in statistical reasoning ability than students studying with LMS with Medium and low SRL categories, with the criteria for improvement in the three categories being in the high and medium improvement categories. Research findings related to learning using LMS can be used as an alternative learning model in online learning situations.

Making sense of students’ errors in solving problems related to measures of dispersion

The importance of statistical learning has been widely discussed. However, little effort has been made to understand the difficulties of students in learning measure of dispersion, which is the key component to statistical learning. The present study sought to identify the reasons behind the errors committed in solving problems related to measures of dispersion, by examining students’ errors in the diagnostics tests, followed by in depth interviews to elicit their thinking and understanding. There were 85 grade-11 high school students involved in the first phase of the quantitative research and 10 students with weak performance were subsequently selected for the second phase qualitative research. The interviews were conducted using the contingent teaching model. The findings indicated that students’ committing errors in solving problems related to measure of dispersion due to lacking statistical vocabulary knowledge, weak symbol sense, rote learning, low statistical reasoning and statistical thinking ability. The results of the study and proper remedials are discussed.

Sport Student Statistical Reasoning Ability as the Outcomes of Statistical Reasoning Learning Environment

This research aimed to describe the quality of sports student Statistical Reasoning Ability (SRA) through the Statistical Reasoning Learning Environment (SRLE). This research employed a qualitative analysis. The qualitative analysis was carried out using the grounded theory method. The research subjects were 29 Sports Coaching Education Study Program students receiving SRLE learning. The research finding shows that there are five categories to describe the quality of sports student Statistical Reasoning Ability: problem understanding, concept mastery, argument validity, well-ordered thinking process, and interpretation accuracy.

Measuring Changes of Students’ Statistical Reasoning Taught by Ethnomathematics Approach Assisted TinkerPlots: A Stacking Analysis Study

This study aims to use the Rasch model stacking analysis technique to assess students' statistical reasoning abilities in descriptive statistics learning utilizing a TinkerPlots-assisted ethnomathematics approach in Nias cultural environment. This research is a quasi-experimental study that uses pre-and post-test control group designs. The stacking technique is used to examine how students' statistical reasoning abilities change in the presence of the intervention. The sample for this study is students in the 12th year at Gunungsitoli High School in the Nias Islands, Sumatera Utara region. Students are administered an exam that consists of five essay questions. Their responses are evaluated using a rubric that incorporates diagnostic criteria and a response certainty index. The data is analyzed using the Rasch Partial Credit Model with WINTSTEPS 4.5.5. The results indicate that students in the experimental group improved their statistical reasoning abilities more than students in the control group when they used TinkerPlots-assisted ethnomathematics in Nias cultural environment (the group with an ordinary learning approach). Along with the intervention, it is discovered that changes in student learning capacities are achievable in some situations due to pupils receiving the correct response or cheating. In other circumstances, pupils who undergo negative changes may respond inappropriately due to carelessness, boredom, or misconceptions. Additionally, these findings demonstrate that some children provide correct responses following intervention on certain items. According to the findings of this study, stacking analysis approaches are critical for describing each change in student abilities as a result of each person and each item.

Pre-service Teachers’ Statistical Reasoning based on Cognitive Style

The use of statistical concepts in real-life problems has become a challenge for students. This challenge is related to statistical reasoning (SR) ability which is influenced by several factors including cognitive style. Therefore, this research aims to understand the process of statistical reasoning from the perspective of cognitive style. A qualitative method was used and the subjects were students who are pre-service mathematics teachers. The instrument used were Group Embedded Figures Test (GEFT), statistical reasoning tests, as well as interview guidelines, and the data were analyzed using the qualitative descriptive method. The results showed statistical reasoning of the field independent pre-service mathematics teacher is better than the field dependent. Also, those with the same cognitive style, which is field independent, but different genders showed different reasoning processes. It was concluded that males have better Statistical Reasoning processes than females, and cognitive style as well as gender affect the reasoning abilities.

Profile of Students’ Statistical Reasoning Capabilities in Introductory Social Statistics Courses

Statistical Reasoning is the ability to understand information in daily life based on statistical data. This study aims to determine the ability of student statistical reasoning based on 5 levels of statistical reasoning models. The research subjects are two classes of first semester students majoring in Communication Sciences. The data collected is in the form of statistical reasoning test result. The data are categorized into five namely Level 1 (Idiosyncratic reasoning), level 2 (Verbal reasoning), level 3 (Transitional reasoning), level 4 (Procedural reasoning) and level 5 (Integrated process reasoning). Next, look at the percentage of student statistical reasoning included in the level 1, level 2, level 3, level 4 and level 5 categories. The results of data analysis showed that students level 3 with statistical reasoning were far more numerous than students’ statistical reasoning abilities categorized as than on the other.

Statistical reasoning through metacognitive brain-based learning

The low ability of students' statistical reasoning needs a promising learning innovation. The aim of this paper is to evaluate students' learning abilities through brain-based learning with metacognitive strategy. The Quasi Experiment Method, Nonequivalent Pretest-Posttest Control Group design, involved a sample of two classes of third semester students from Gunung Djati Swadaya University Cirebon. Instruments of this paper are statistical reasoning test and statistical preliminary knowledge tests. The result shows an increase in the ability of statistical reasoning among students who conducted brain-based learning with metacognitive strategy in the smart category, higher than students who applied expository learning strategy that only classified as the moderate category. Based on initial statistical knowledge (low, middle, and high) students who applied brain-based learning with metacognitive strategy, got a higher level than students who applied expository learning strategy. It shows interaction between the type of learning as well as initial statistical knowledge with the escalation of the ability of statistical reasoning. Brain-based learning with metacognitive strategy facilitates the process of conflict, discovery, social interaction, and reflective processes of students. Therefore, students abilities of statistical reasoning are better than expository learning strategy.

PENINGKATAN KEMAMPUAN PENALARAN STATISTIS MAHASISWA MELALUI PEMBELAJARAN BERBASIS PROYEK BERBANTUAN ICT

The problem with this research is the students’ low ability of statistical reasoning. This study aims to determine the students’ achievement and improvement of statical reasoning through project-based learning with ICT assistance. This research was in the form of a quasi-experimental design of the pretest-posttest control group. The numbers of samples of this study were 51 students taken by purposive sampling from 102 students who took statistics introductory lectures. This study has two variables, namely: the application of project-based learning with ICT assisted as an independent variable, and the students' statistical reasoning ability as an independent variable. The instrument used for data collection was six items of an essay the statistical reasoning test. The data obtained were analyzed descriptively and inferentially. Descriptive analysis, including a description of student statistical reasoning achievement and improvement. The inferential analysis is using the Mann-Whitney U test statistic. The results showed that the students’statistical reasoning achievement and improvement who received project-based learning with ICT assisted was better than those who obtained conventional learning. Students’ statistical reasoning Achievement who received project-based learning with ICT assisted in the good category while those who received conventional learning in the sufficient category. The increased student's statistical reasoning who received project-based learning with ICT assisted was relatively high and those who received conventional learning where classified as moderate. There is a significant difference in the achievement and improvement of students' statistical reasoning abilities between those who obtain project-based learning with ICT assisted and those who obtain conventional learning. The significance of these differences can be concluded that the implementation of project-based learning with ICT assisted can improve students' statistical reasoning abilities.

Students’ statistical reasoning reviewed from academic internal factors in two learning classes

This paper presents the research results about the profile of students’ statistical reasoning ability (SRA) based on their academic internal factors, namely statistical prior knowledge (SPK), the intensity of study, and length of time to study. Data was collected from the seventy students of mathematics educations in a year of 2018/2019 that divided into two learning classes. One class was determined randomly as an experimental group and another class as a control group. The SRA and SPK achievements were measured by a written test. The aged of students ranged from 19 to 22 years. Based on gender, there were about 71% of females and 29% of males. The result of the study showed that the most answered about the intensity to study was “seldom”. They used the length of time to study for reviewing the statistics topic for about one to two hours. Both of the intensity to study and the length of time to study was not a significant effect on the difference of students’ SRA achievement between experimental and control groups. The difference in learning model was not the only one factor that significantly influenced the difference of students’ SRA achievement. The difference of the SPK factor produced the difference of the SRA achievement between experimental and control groups. Nevertheless, there was no interaction effect between the learning model and the level of SPK to the difference of the students’ SRA achievement.

Statistical reasoning of prospective teachers through blended learning

Blended learning is a learning model that combines face-to-face learning in classroom with on line learning. This research is a descriptive study that aims to describe the ability of statistical reasoning of prospective teachers through the Blended Learning models. The subjects in this study were 40 students of second year of Mathematics Education Department at Universitas PGRI Palembang in Academic Year 2018/2019. Data collected through written tests and interviews. The test aims to reveal the statistical reasoning of prospective teacher students. The interview aims to explore further about students’ statistical reasoning through Blended learning. The results showed that the statistical reasoning of prospective teachers after applying Blended Learning was included in the good category.

Penalaran Statistik pada Peserta Didik Kelas IX

This study aims to explore the ability to reason students in statistical material. This is motivated by the ability to reason statistics class IX students have not yet reached the highest level at the level of reasoning ability. This research is a qualitative research. The instrument used consisted of statistical question sheets and interview guidelines compiled based on indicators of statistical reasoning ability. The results of the study indicate that students are still unsure of the answers to the problems because basically students still have a level of informal quantitative reasoning ability.

STUDENTS’ STATISTICAL REASONING IN STATISTICS METHOD COURSE

The role of statistics is wide and crucial in daily life, making statistics important. Many students have difficulty understanding statistics. This study aims to determine students' statistical reasoning about inference statistics, which is limited to the subject matter of the testing hypotheses about two-sample hypotheses testing. This study used descriptive research method. The subjects were 25 students of third-year Mathematics Education Departement at Universitas PGRI Palembang in the academic year 2018/2019. Data were collected through tests and interviews. Data were analyzed through descriptive quantitative. The results of data analysis showed that 32% of students had level 1 statistical reasoning (the lowest level), 20% were at level 2, 28% at level 3, 12% at level 4 and 8% at level 5 (highest level). Based on the result, it can conclude that students' statistical reasoning ability in learning statistical method is not satisfactory, students are still very lacking in reasoning.

The Statistical Reasoning Learning Environment: A Comparison of Students’ Statistical Reasoning Ability

The purpose of this study was to study the impact of conformity to statistical reasoning learning environment (SRLE) principles on students’ statistical reasoning in advanced placement statistics courses. A quasi-experimental design was used to compare teachers’ levels of conformity to SRLE principles through a matching process used to mitigate the effects of nonrandom assignment. This matching process resulted in five pairs of similar teachers and schools who differed in self-reported beliefs in the effectiveness and application of SRLE principles. Increases in students’ statistical reasoning were found at varying levels in both high and low conformity classrooms. Improvements among teachers with low conformity to SRLE principles were less varied and consistent with national averages for improvement by college students. Improvements in classes with high conformity to SRLE principles were more varied. Students of two teachers with high levels of conformity to SRLE principles showed large levels of improvement in statistical reasoning in comparison to national results. While the comparison between classrooms conformity to SRLE principles revealed no statistically significant differences in students’ statistical reasoning ability, deeper analysis suggests that beliefs and practices aligned with SRLE principles have potential to increase students’ statistical reasoning at rates above national averages.

The Influence of Statistical Anxiety on Statistic Reasoning of Pre-service Mathematics Teachers

Abstract The large number of statistical data present in everyday life makes statistical reasoning an absolute ability possessed by students. Meanwhile, the statistical reasoning is influenced by various cognitive and non-cognitive factors. This study emphasizes the influence of non-cognitive factors, which are the statistical anxiety. The purpose of this study is to describe the statistical anxiety of pre-service mathematics teacher and the influence of statistical anxiety on statistical reasoning. This research method is a mixed-method with sample of 33 pre-service teachers who are taking basic statistics courses. The instrument used in this study is a statistical anxiety questionnaire developed by Earp (2007)and a statistical reasoning test developed by Chan et al (2016). The result showed that the statistical anxiety of pre-service mathematics teachers was in the moderate level on the aspects of taking the courses, studying and practicing; and was in the higher level on the aspect of the examination. Statistical anxiety levels on every aspect are equally good for both men and women. Statistical anxiety does not directly affect the ability of statistical reasoning and it can only impair 0.1% of the statistical reasoning ability. On reasoning indicators and statistical anxiety indicators, there are relevant results between the statistical anxiety experienced by the pre-service teachers on the indicator for developing conclusions based on mathematical solutions, explaining statistical findings, and interpreting statistics with indicators on statistical reasoning; they areanalyzing and interpreting data.

Developing Statistics Learning Equipment Based on the PMRI Approach Oriented to Students’ Statistical Reasoning Ability

This development research aims to produce valid, practical, and effectivelearning equipment. The developed learning equipmentincludesemester learning plans (RPS), student worksheets (LKM), and test questions in basic statistics courses using the PMRI approach oriented to statistical reasoning ability. This study employs the ADDIE development model. The quality of the product was assessed based on the validity, practicality, and effectiveness aspects. The result shows that the validity quality of the learning equipment has fulfilledthe valid criteria indicated by the average score of semester learning plans of 3.75 and the average score of the student worksheet of 3.70. The practicality of learning equipmenthas met the practical criteria indicated by the students’ questionnaire responsesscore of 3.125 and the results of learning implementation observation of 90.17. The effectiveness shows a score of 15% with low effective criteria, although based on the results of students’ answers as a whole,the students' statistical reasoning is at level 3 (Procedural Reasoning).

Developing Statistical Reasoning Ability of Industrial Engineering Students Through Experiential Learning

Education is one way to develop thinking skills. The aim of implementing education is to produce quality human resources. So that the development of science and technology can develop in a better direction as technology advances. Quality learning will encourage students to have better cognitive abilities. Experiential learning implementation is a learning process that prioritizes experience during the learning process. The purpose of this study was to determine the effects of experiential learning on students’ statistical reasoning abilities. The design of this study was one sample group with purposive sampling technique. The subjects of this study were students who contracted industrial statistics courses. Statistical test results prove that experiential learning provides a positive contribution to students’ statistical reasoning abilities.