Bayes nets and babies: infants? developing statistical reasoning abilities and their representation of causal knowledge

Abstrak: Artikel ini membahas tentang pembelajaran yang dapat digunakan untuk mengembangkan kemampuan penalaran inferensial statistis. Tujuan kognitif pembelajaran Statistika adalah untuk mengembangkan kemampuan literasi, penalaran, dan berpikir statistis. Salah satu tujuan dalam penalaran statistis adalah mengembangkan kemampuan penalaran inferensial. Model pembelajaran yang dapat digunakan untuk mengembangkan kemampuan penalaran inferensial statistis adalah model Statistical Reasoning Learning Environment (SRLE) yang didasarkan pada teori belajar konstruktivisme. Analisis didasarkan pada: 1) definisi inferensi statistis; 2) definisi penalaran inferensial informal dan formal; 3) kerangka kerja penalaran inferensial informal; 5) model pembelajaran SRLE; dan 6) penelitian terkait penalaran inferensial statistis.Abstract: This article deals with learning that can be used to develop inferential reasoning abilities statistically. The cognitive goal of statistical learning is to develop literacy, reasoning, and statistical thinking skills. One of the goals in statistical reasoning is to develop inferential reasoning abilities. The learning model that can be used to develop static inferential reasoning abilities is Statistical Reasoning Learning Environment (SRLE) model based on constructivism learning theory. The analysis is based on: 1) the definition of statistical inference; 2) the definition of informal and formal inferential reasoning; 3) informal inferential reasoning framework; 5) the learning model of SRLE; and 6) research related to inferential statistical reasoning.

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The roles of self-efficacy and perceived teacher support in the acquisition of statistical reasoning abilities: a path analysis

Educational Research and Evaluation ◽

10.1080/13803611.2011.554742 ◽

2010 ◽

Vol 16 (6) ◽

pp. 517-528 ◽

Cited By ~ 1

Author(s):

Aboma Olani ◽

Egbert Harskamp ◽

Rink Hoekstra ◽

Greetje van der Werf

Keyword(s):

Path Analysis ◽

Self Efficacy ◽

Teacher Support ◽

Statistical Reasoning ◽

Reasoning Abilities ◽

Perceived Teacher Support

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Penalaran Statistis Siswa dalam Menyelesaikan Masalah Case Study

Mosharafa: Jurnal Pendidikan Matematika ◽

10.31980/mosharafa.v8i2.449 ◽

2019 ◽

Vol 8 (2) ◽

pp. 179-190

Author(s):

Baiq Rika Ayu Febrilia

Keyword(s):

Mathematics Education ◽

Process Integration ◽

Statistical Reasoning ◽

Education Department ◽

Intended Meaning ◽

Data Presentation ◽

Reasoning Abilities ◽

The World ◽

Basic Concepts

AbstrakPenalaran siswa secara statistika belum begitu baik, kebanyakan siswa menggunakan terminologi yang tidak sesuai dengan maksud dari terminologi yang seharusnya. Penelitian ini bertujuan untuk mendapatkan gambaran mengenai penalaran statistis melalui permasalahan case study. Jenis penelitian ini adalah deskriptif kualitatif dan melibatkan 9 orang mahasiswa Program Studi Pendidikan Matematika, di mana 3 diantaranya berjenis kelamin laki-laki dan yang lainnya adalah perempuan. Instrumen yang digunakan berupa permasalahan case study yang relevan dengan permasalahan nyata di dunia dengan fokus materi pada hal-hal yang berhubungan dengan konsep dasar statistika dan bentuk penyajian data. Hasil penelitian menunjukkan bahwa hampir sebagian besar subjek memiliki kemampuan penalaran statistis pada level penalaran idiosinkratik dan penalaran verbal berkaitan dengan konsep tertentu sedangkan level prosedural dan pengintegrasian proses muncul pada permasalahan terkait bentuk penyajian data. Agar level penalaran statistis siswa dapat meningkat, maka diperlukan adanya rancangan permasalahan yang tepat. Students’ Statistical Reasoning in Solving Case Study Problem AbstractStudent reasoning is statistically not so good; most students use terminology that is not by following the intended meaning of the terminology. This study aims to get an overview of statistical reasoning through a case study problem. This type of research is descriptive qualitative and involves 9 students of the Mathematics Education Department, which 3 are male and the others are female. The instrument used is a case study problem that is relevant to real problems in the world with a focus on material on the basic concepts of statistics and forms of data presentation. The results showed that most subjects had statistical reasoning abilities at the level of idiosyncratic reasoning and verbal reasoning was related to certain concepts, while procedural levels and process integration appeared on problems related to the form of data presentation. So that the level of students' statistical reasoning can increase, it is necessary to design appropriate problems.

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KONSTRUKSI PENALARAN STATISTIS PADA STATISTIKA PENELITIAN

Scholaria Jurnal Pendidikan dan Kebudayaan ◽

10.24246/j.scholaria.2017.v7.i1.p60-69 ◽

2017 ◽

Vol 7 (1) ◽

pp. 60 ◽

Cited By ~ 1

Author(s):

Yusfita Yusuf

Keyword(s):

Mathematics Education ◽

Everyday Life ◽

Test Scores ◽

Statistical Reasoning ◽

Statistical Research ◽

Reasoning Abilities ◽

Research Material ◽

Reasoning Skills

Statistics can be viewed as a tool to solve problems that always occur in everyday life,workplace, and science. Based on the observation on the students, it was found that the there was statistical reasoning abilities of different students. This could be demonstrated by the acquisition of the different test scores, in which there were students who just copy the questions until finishing the work on the problems given. This study discussesed the development deduction level / degree of statistical reasoning skills based on understanding and opinion of several experts, which were constructed based on the results of a case study of mathematics education on STKIP students of Sebelas April Sumedang with statistical research material.

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Causality

The Oxford Handbook of Developmental Psychology, Vol. 1 ◽

10.1093/oxfordhb/9780199958450.013.0022 ◽

2013 ◽

pp. 627-650

Author(s):

Alison Gopnik

Keyword(s):

Probabilistic Model ◽

Bayesian Learning ◽

Probabilistic Models ◽

Developmental Research ◽

Causal Knowledge ◽

Bayes Nets ◽

The World ◽

Causal Bayes Nets

Causal knowledge is central to children’s understanding of the world, but there have been many different conceptions of how causal knowledge is represented and how it is learned. I outline four different approaches to causality that have influenced developmental research, stressing agency, mechanism, association, and probabilistic models, and give examples of theory and research in each area. I focus in more detail on the most recent probabilistic model accounts that stress the role of causation in inferences about possibilities. These include potential interventions to change the world and counterfactuals about alternate ways the world might be. These accounts also employ computational ideas about causal Bayes nets and Bayesian learning, and these ideas are outlined.

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