Mental models: an interdisciplinary synthesis of theory and methods
By Natalie A. Jones, H. Ross, Tim Lynam, P. Perez, A. Leitch. 2011
913 citations recorded by the source corpus.
Mental models are personal, internal representations of external reality that people use to interact with the world around them. They are constructed by individuals based on their unique life experiences, perceptions, and understandings of the world. Mental models are used to reason and make decisions and can be the basis of individual behaviors. They provide the mechanism through which new information is filtered and stored. Recognizing and dealing with the plurality of stakeholder's perceptions, values, and goals is currently considered a key aspect of effective natural resource management (NRM) practice. Therefore, gaining a better understanding of how mental models internally represent complex, dynamic systems and how these representations change over time will allow us to develop mechanisms to enhance effective management and use of natural resources. Realizing this potential, however, relies on developing and testing adequate tools and techniques to elicit these internal representations of the world effectively. This paper provides an interdisciplinary synthesis of the literature that has contributed to the theoretical development and practical application of the mental model construct. It explores the utility and applicability of the construct in the context of NRM and includes a review of elicitation techniques used within the field. The major theoretical and practical challenges that arise in drawing on the construct to provide a cognitive dimension to NRM are also addressed.
Subfields: Artificial Intelligence, Environmental Engineering, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/c65d53bbe1b165f63d55290e7fdd95c6fd20973c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Michel E. Etienne
- Tim Lynam
- Raphael Mathevet
- Coralie Calvet
- Deborah Blackman
- Helen Ross
- A. Guerrero
- Darren Gergle
In Environmental Engineering
In Management Science and Operations Research
- Michel E. Etienne
- C. Pahl‐Wostl
- Art Dewulf
- Geeske Scholz
- Tim Lynam
- Raphael Mathevet
- Coralie Calvet
- Emilee J. Rader
Citations in the corpus
- ARDI: a co-construction method for participatory modelling in natural resources management (2011, background): “The approach focuses on encouraging participants to describe, explain, and predict the purpose, form, function, and state of a given system (Rouse and Morris 1986), so as to elicit causal knowledge as defined by Jones et al. (2011).”
- Water Management in the Camargue Biosphere Reserve: Insights from Comparative Mental Models Analysis (2011, background): “We can find several synonyms or closely related concepts in the social science literature (see Jones et al. 2011), including social representations (Moscovici 1961, Jodelet 2003), social construction of reality (Gumuchian 1991), world view, social thought, and thinking system (Daré 1985).”
- An Analytical Framework of Social Learning Facilitated by Participatory Methods (2014, background): “A primary challenge that remains in relation to the consideration of mental models in the context of resource management research relates to the appropriate elicitation techniques (Jones et al. 2011).”
- "Algorithms ruin everything": #RIPTwitter, Folk Theories, and Resistance to Algorithmic Change in Social Media (2017, background): “” This suggests that future research should take into account (and, potentially, directly compare) the potential differences between directly elicited and indirectly identified theories noted by [16] as the two methods may be revealing different sides of a user’s folk theory: a causal theory stemmin”
- Understanding User Beliefs About Algorithmic Curation in the Facebook News Feed (2015, background): “These intuitive theories are generated out of each person’s unique experiences, and as such are contextual and usually inaccurate in some way [19].”
- Censored, suspended, shadowbanned: User interpretations of content moderation on social media platforms (2018, neutral): “These theories are often incomplete, are generated out of each user’s personal experiences, and serve to help them both to filter information and to make decisions about how they interact with the world (Gelman and Legare, 2011; Jones et al., 2011; Rader and Gray, 2015).”
- Mental models for conservation research and practice (2019, background): ““A shared mental model is the mental model constructed and shared when individuals interact together in a team setting, it represents the shared cognition among groups of individuals” (Jones et al., 2011, p. 4; Langan-Fox et al. 2001).”
- The Future in Mind: Aspirations and Forward-Looking Behaviour in Rural Ethiopia (2014, background): “Mental models help people in interpreting information and making decisions (Jones et al., 2011).”