Classification and Analysis of Pre-Service Teachers' Errors in Solving Fermi Problems

Autor/inn/en	Segura, Carlos; Ferrando, Irene
Titel	Classification and Analysis of Pre-Service Teachers' Errors in Solving Fermi Problems
Quelle	In: Education Sciences, 11 (2021), Artikel 451 (19 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Zusatzinformation	ORCID (Segura, Carlos) ORCID (Ferrando, Irene)
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2227-7102
Schlagwörter	Error Patterns; Problem Solving; Preservice Teachers; Elementary School Teachers; Preservice Teacher Education; Mathematics Instruction; Mathematical Models; Elementary School Mathematics; Computation; Measurement; Foreign Countries; Spain (Valencia) + Suchen Sie Ihr Suchwort? Fehlertyp; Problemlösen; Elementary school; Teacher; Teachers; Grundschule; Volksschule; Lehrer; Lehrerin; Lehrende; Lehramtsstudiengang; Lehrerausbildung; Mathematics lessons; Mathematikunterricht; Mathematical model; Mathematisches Modell; Elementare Mathematik; Schulmathematik; Messverfahren; Ausland
Abstract	Fermi problems are useful for introducing modelling in primary school classrooms, although teachers' difficulties in problem solving may hinder their successful implementation. These difficulties are associated with the modelling process, but also with the estimation and measurement skills required by Fermi problems. In this work, a specific categorization of errors for Fermi problems was established, and it allowed us to analyse the errors of N = 224 pre-service primary school teachers. The results showed that prospective teachers make a large number of errors when solving this type of task, especially conceptual ones, which are associated with the process of simplifying/structuring the real situation and the mathematization process. They also showed that there is a significant relationship between the characteristics of the problem context and the error categories. Knowing the types of errors that prospective teachers make and designing task sequences that make them emerge so that prospective teachers learn from them could be an effective way to improve initial teacher education in modelling and estimation problem solving. (As Provided).
Anmerkungen	MDPI AG. Klybeckstrasse 64, 4057 Basel, Switzerland. Tel: e-mail: indexing@mdpi.com; Web site: http://www.mdpi.com
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01