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Engineering education research has long been rich in behavioral observations and inquiries. These investigations span a range of levels, from individual behaviors to group dynamics to organizational influences. Such behavioral research delves into the complex interplay of behaviors and actions, exploring their origins and impacts on educational environments and structures. Topics encompass learning, identity development, engagement, and professional practices, among others, that benefit from understanding behavioral choices and their underlying motivations. Ultimately, behavioral research in engineering education aids in comprehending and predicting how individuals operate, form habits, and transform themselves and their surroundings through their chosen actions. Regrettably, behavioral research in engineering education has traditionally relied on a limited set of frameworks, like EVT, SDT, and self-efficacy, thereby restricting the analytic depth of behavioral choice. These frameworks primarily focus on whether individuals feel they can perform a certain behavior or which behaviors are most salient in given situations while overlooking the justifications, or the why, that drive behavioral choices – a critical aspect of the complete picture. Justifications are important; behaviors are context-specific and dynamic, closely tied to an individual's interpretations of their surroundings, expectations, self-concept, and goals, among other factors. Therefore, understanding why behaviors are performed yields a more nuanced image that combines these influences with their eventual outcomes. In an effort to explore behavioral choices and investigate why they are, or are not, performed, this paper presents the Reasoned Action Approach (RAA) framework. This approach emphasizes the pivotal role of intention in individuals' behavioral choices. It proposes that personal beliefs, norms, and abilities are the key determinants of intentionality. Whether or not an individual performs a behavior is therefore contingent upon their beliefs about performing the behavior, specifically their behavioral, normative, and control beliefs. These beliefs reveal their feelings toward a behavior, their expectations of social acceptability, and their perceived capability to execute the behavior. As a result, the RAA transcends contextual constraints and can be applied to a wide spectrum of behaviors, environments, and systems, shedding light on how individuals perceive actions and decide whether to act upon them. We introduce the RAA to offer engineering education research a substantive theory for extracting and investigating the determinants behind individuals' preferential behaviors. Further, the RAA broadens existing behavioral analysis by emphasizing the factors behind behavioral choices, specifically focusing on the intricate interplay between beliefs and social norms in the decision-making process. In this context, the RAA represents a distinctive and novel approach to conceptualizing behavior, which will benefit fellow researchers. This paper begins with a review of pertinent engineering and higher education literature to situate the RAA within similar behavioral choice studies. It then explores the components of the RAA, delving into their significance and implications. The paper concludes with select research both within and beyond the engineering education domain to underscore the applicability, utility, and relevance of the RAA and provide examples for future inquiries.
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Wild animals suppress the spread of socially transmitted misinformation
Understanding the mechanisms by which information and misinformation spread through groups of individual actors is essential to the prediction of phenomena ranging from coordinated group behaviors to misinformation epidemics. Transmission of information through groups depends on the rules that individuals use to transform the perceived actions of others into their own behaviors. Because it is often not possible to directly infer decision-making strategies in situ, most studies of behavioral spread assume that individuals make decisions by pooling or averaging the actions or behavioral states of neighbors. However, whether individuals may instead adopt more sophisticated strategies that exploit socially transmitted information, while remaining robust to misinformation, is unknown. Here, we study the relationship between individual decision-making and misinformation spread in groups of wild coral reef fish, where misinformation occurs in the form of false alarms that can spread contagiously through groups. Using automated visual field reconstruction of wild animals, we infer the precise sequences of socially transmitted visual stimuli perceived by individuals during decision-making. Our analysis reveals a feature of decision-making essential for controlling misinformation spread: dynamic adjustments in sensitivity to socially transmitted cues. This form of dynamic gain control can be achieved by a simple and biologically widespread decision-making circuit, and it renders individual behavior robust to natural fluctuations in misinformation exposure.
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- PAR ID:
- 10426909
- Date Published:
- Journal Name:
- Proceedings of the National Academy of Sciences
- Volume:
- 120
- Issue:
- 14
- ISSN:
- 0027-8424
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1073/pnas.2215428120
