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Reinert_Moeller_Review_unbounded_NLE_ActaPsy.pdf (750.28 kB)

The new unbounded number line estimation task: A systematic literature review

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posted on 2021-09-07, 14:15 authored by Regina Miriam Reinert, Korbinian MoellerKorbinian Moeller
In 2011, Cohen and Blanc-Goldhammer introduced a new unbounded version of the number line estimation task which they argued to overcome limitations of its ‘traditional’ bounded counterpart. In line with this proposition, there is increasing evidence that the unbounded number line estimation task may indeed reflect a purer measure of the underlying representation of number magnitude. However, only few studies used this task version yet. In the present literature review, we aimed at evaluating all studies employing the unbounded task version so far to provide an overview of the current state of research. To identify all relevant articles and to evaluate the validity of the task, we conducted a systematic literature search in different databases following the PRISMA guidelines in May 2021. Methodological differences and commonalities of the 16 studies that met the inclusion criteria are discussed here. Our evaluation indicated considerable differences between studies with respect to the number range covered or methodological features such as display size. Additionally, five studies observed evidence for estimation biases in the unbounded task as well. Nevertheless, this review also substantiated the claim that the unbounded task version might indeed be a more valid and purer measure of the mental representation of number magnitude as the results of 14 studies confirmed this hypothesis.

History

School

  • Science

Department

  • Mathematics Education Centre

Published in

Acta Psychologica

Volume

219

Publisher

Elsevier

Version

  • VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (CC BY-NC-ND 4.0). Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

2021-07-06

Publication date

2021-07-30

Copyright date

2021

ISSN

0001-6918

eISSN

1873-6297

Language

  • en

Depositor

Prof Korbinian Moeller. Deposit date: 2 September 2021

Article number

103366

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