Literaturnachweis - Detailanzeige
Autor/inn/en | Setyani, Geovani Debby; Kristanto, Yosep Dwi |
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Titel | A Case Study of Promoting Informal Inferential Reasoning in Learning Sampling Distribution for High School Students |
Quelle | 4 (2020) 1, S.64-77 (14 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
Zusatzinformation | ORCID (Kristanto, Yosep Dwi) |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
ISSN | 2549-3639 |
Schlagwörter | High School Students; Grade 11; Private Schools; Foreign Countries; Statistical Inference; Problem Based Learning; Data Use; Evidence; Probability; Student Attitudes; Sampling; Mathematics Instruction; Statistical Distributions; Indonesia High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; School year 11; 11. Schuljahr; Schuljahr 11; Private school; Privatschule; Ausland; Inferential statistics; Schließende Statistik; Problem-based learning; Problemorientiertes Lernen; Evidenz; Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie; Schülerverhalten; Mathematics lessons; Mathematikunterricht; Wahrscheinlichkeitsverteilung; Indonesien |
Abstract | Drawing inference from data is an important skill for students to understand their everyday life, so that the sampling distribution as a central topic in statistical inference is necessary to be learned by the students. However, little is known about how to teach the topic for high school students, especially in Indonesian context. Therefore, the present study provides a teaching experiment to support the students' informal inferential reasoning in understanding the sampling distribution, as well as the students' perceptions toward the teaching experiment. The subjects in the present study were three 11th-grader of one private school in Yogyakarta majoring in mathematics and natural science. The method of data collection was direct observation of sampling distribution learning process, interviews, and documentation. The present study found that that informal inferential reasoning with problem-based learning using contextual problems and real data could support the students to understand the sampling distribution, and they also gave positive responses about their learning experience. (As Provided). |
Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2022/1/01 |