Evaluating the Application of the Mental Model Mapping Tool (M-Tool)
Mental models influence how individuals think and act in relation to their external environment and have been identified as leverage points to address sustainability challenges. Given the importance of mental models, a new tool to assess mental models has been developed: the Mental Model Mapping Too...
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Published in | Frontiers in psychology Vol. 12; p. 761882 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
Frontiers Media S.A
14.12.2021
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Subjects | |
Online Access | Get full text |
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Summary: | Mental models influence how individuals think and act in relation to their external environment and have been identified as leverage points to address sustainability challenges. Given the importance of mental models, a new tool to assess mental models has been developed: the Mental Model Mapping Tool (M-Tool). M-Tool was designed to have a standardized format and to be user-friendly for low literacy populations, using pictograms and audio instructions. In this paper, we evaluate M-Tool's application in two studies with Tanzanian fishers. In Study 1, we investigated M-tool's convergent validity compared to standard interviewing methods (
= 30). Study 2 investigated M-Tool's construct validity by relating mental model complexity to participants' education level (
= 185), a relationship that has been well established. The findings show that (1) mental models produced with M-Tool are more complex than mental models obtained through interviewing techniques; (2) model composition is similar across the two methods; and (3) participants with higher levels of education tend to produce more complex mental models with M-Tool than participants with lower levels of education, in line with previous research. These findings suggest that M-Tool can successfully capture mental models among diverse participants. This tool offers researchers and practitioners an instrument to map and compare perceptions of (conservation) challenges across groups. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Edited by: Mariona Portell, Universitat Autònoma de Barcelona, Spain This article was submitted to Quantitative Psychology and Measurement, a section of the journal Frontiers in Psychology Reviewed by: Eugenio Cavallo, CNR – Istituto di Scienze e Tecnologie per l’Energia e la Mobilità Sostenibili (STEMS), Italy; C. Dominik Güss, University of North Florida, United States |
ISSN: | 1664-1078 1664-1078 |
DOI: | 10.3389/fpsyg.2021.761882 |