Social learning Hoppitt, William; Laland, Kevin N
2013., 20130721, 2013, 2013-07-21
eBook
Many animals, including humans, acquire valuable skills and knowledge by copying others. Scientists refer to this as social learning. It is one of the most exciting and rapidly developing areas of ...behavioral research and sits at the interface of many academic disciplines, including biology, experimental psychology, economics, and cognitive neuroscience.Social Learningprovides a comprehensive, practical guide to the research methods of this important emerging field. William Hoppitt and Kevin Laland define the mechanisms thought to underlie social learning and demonstrate how to distinguish them experimentally in the laboratory. They present techniques for detecting and quantifying social learning in nature, including statistical modeling of the spatial distribution of behavior traits. They also describe the latest theory and empirical findings on social learning strategies, and introduce readers to mathematical methods and models used in the study of cultural evolution. This book is an indispensable tool for researchers and an essential primer for students.
Provides a comprehensive, practical guide to social learning researchCombines theoretical and empirical approachesDescribes techniques for the laboratory and the fieldCovers social learning mechanisms and strategies, statistical modeling techniques for field data, mathematical modeling of cultural evolution, and more
The dramatic increase in social media use has challenged traditional social structures and shifted a great deal of interpersonal communication from the physical world to cyberspace. Much of this ...social media communication has been positive: Anyone around the world who has access to the Internet has the potential to communicate with and attract a massive global audience. Unfortunately, such ubiquitous communication can be also used for negative purposes such as cyberbullying, which is the focus of this paper. Previous research on cyberbullying, consisting of 135 articles, has improved the understanding of why individuals—mostly adolescents—engage in cyberbullying. However, our study addresses two key gaps in this literature: (1) how the information technology (IT) artifact fosters/inhibits cyberbullying and (2) why people are socialized to engage in cyberbullying. To address these gaps, we propose the social media cyberbullying model (SMCBM), which modifies Akers’ Akers RL (2011)
Social Learning and Social Structure: A General Theory of Crime and Deviance
, 2nd ed. (Transaction Publishers, New Brunswick, NJ) social structure and social learning model. Because Akers developed his model for crimes in the physical world, we add a rich conceptualization of anonymity composed of five subconstructs as a key social media structural variable in the SMCBM to account for the IT artifact. We tested the SMCBM with 1,003 adults who have engaged in cyberbullying. The empirical findings support the SMCBM. Heavy social media use combined with anonymity facilitates the social learning process of cyberbullying in social media in a way that fosters cyberbullying. Our results indicate new directions for cyberbullying research and implications for anticyberbullying practices.
Penguins jumping off a cliff, economic forecasters and financial advisors speculating against a currency, and farmers using traditional methods in India are all practising social learning. Such ...learning from the behavior of others may and does lead to herds, crashes, and booms. These issues have become, over the last ten years, an exciting field of research in theoretical and applied economics, finance, and in other social sciences. This book provides both an informal introduction and in-depth insights into the subject. Each chapter is devoted to a separate issue: individuals learn from the observations of actions, the outcomes of these actions, and from what others say. They may delay or make an immediate decision; they may compete against others or gain from cooperation; they make decisions about investment, crop choices, and financial investments. The book highlights the similarities and the differences between the various cases.
Social learning via the observation of or interaction with other individuals can allow animals to obtain information about the local environment. Once social information is obtained, animals may or ...may not act on and use this information. Animals may learn from others selectively based on particular characteristics (e.g., familiarity, age, dominance) of the information provider, which is thought to maximize the benefits of social learning. Biases to copy certain individuals over others plays an important role in how information is transmitted and used among individuals, and can influence the emergence of group-level behaviors (i.e., traditions). Two underlying factors can affect from whom animals learn: the population social dynamics – with whom you associate (e.g., familiar), and status of the demonstrator (e.g., dominant). We systematically surveyed the literature and conducted a meta-analysis to test whether demonstrator characteristics consistently influence social learning, and if social dynamics strategies differ from status strategies in their influence on social learning. We extracted effect sizes from papers that used an observer-demonstrator paradigm to test if the characteristics of the individual providing social information (i.e., the demonstrator) influence social information use by observers. We obtained 139 effect sizes on 33 species from 54 experiments. First, we found an effect of experimental design on the influence of demonstrator characteristics on social learning: between-subject designs had stronger effects compared to within-subject designs. Second, we found that demonstrator characteristics do indeed influence social learning. Characteristics based on social dynamics and characteristics based on status had a significant effect on social learning, especially when copying familiar and kin demonstrators. These results highlight the role that demonstrator characteristics play on social learning, which can have implications for the formation and establishment of behavioural traditions in animals.
•Cultural evolution theory posits selective copying, but children over-imitate.•Here we show that 4- to 6-year-old children selectively copy a majority.•They only imitate their irrelevant actions ...when observers approved of them.•Children do not blindly follow the crowd: they are broadly optimal imitators.•This selective and flexible learning provides the basis for cumulative culture.
Cultural evolutionary theory posits that human cultural complexity rests on a set of adaptive learning biases that help to guide functionality and optimality in social learning, but this sits in contrast with the commonly held view that children are unselective “over-imitators.” Here, we tested whether 4- and 6-year-old children use social learning biases flexibly to fine-tune their copying of irrelevant actions. Children watched a video of a majority demonstrating causally irrelevant actions and a minority demonstrating only causally relevant actions. In one condition observers approved of the majority and disapproved of the minority, and in the other condition observers watched the majority and minority neutrally. Results showed that both 4- and 6-year-olds copied the inefficient majority more often than the efficient minority when the observers had approved of the majority’s actions, but they copied the efficient minority significantly more when the observers had watched neutrally. We discuss the implications of children’s optimal selectivity in copying and the importance of integrating social approval into majority-biased learning when acquiring norms and conventions and in broader processes of cultural evolution.
•Archaeological research provides important insights into climate change adaptation.•Norse and Proto-Inuit cultures developed in different learning environments.•Different learning environments ...produce different responses to environmental change.•Archaeology offers evidence of multi-century information transmission and learning.
Using archaeological, historical, and ethnographic analysis of Norse and Inuit toys and miniatures, this paper argues that legacies of childhood learning can create limits to climatic change adaptation and provide lessons from the past relevant today. In Medieval Greenland, Norse children played with objects that would have familiarised them with the expected norms and behaviours of farming, household activities, sailing and conflict, but not with hunting, which was a key omission given the fundamental importance of wild resources to successful climatic adaptation in Greenland after the climate shocks of the mid-13th century. The restricted range of toys combined with an instructional form of learning suggests a high degree of path dependence that limited adaptation to climatic change, and we know the Norse settlement ended with the conjunctures of the 15th century that included climatic change. Inuit children, by contrast, learnt highly adapted behaviours and technologies through objects that taught locally tuned hunting skills. Inuit approaches that prioritised unstructured learning time aided the development of creative skills and problem-solving capabilities, and the Inuit successfully navigated the climatic changes of the Little Ice Age in Greenland. This insight from the past has implications for our approaches to childhood learning in the 21st century and the unfolding climate crisis. Innovative approaches to childhood teaching and learning in the context of climate change adaptation could provide effective solutions, on a timescale commensurate with that of projected climate impacts.
Learning the value of stimuli and actions from others - social learning - adaptively contributes to individual survival and plays a key role in cultural evolution. We review research across species ...targeting the neural and computational systems of social learning in both the aversive and appetitive domains. Social learning generally follows the same principles as self-experienced value-based learning, including computations of prediction errors and is implemented in brain circuits activated across task domains together with regions processing social information. We integrate neural and computational perspectives of social learning with an understanding of behaviour of varying complexity, from basic threat avoidance to complex social learning strategies and cultural phenomena.
This paper builds on the model we have developed for creating quality online learning environments for higher education. In that model we argue that college-level online learning needs to reflect ...what we know about learning in general, what we understand about learning in higher-education contexts, and our emerging knowledge of learning in largely asynchronous online environments. Components of the model include a focus on learner roles, knowledge building, assessment, community, and various forms of “presence.” In this paper we focus on two components—teaching presence and community—and review the rationale and benefits for an emphasis on community in online learning environments. We argue that learning is social in nature and that online learning environments can be designed to reflect and leverage the social nature of learning. We suggest that previous research points to the critical role that community can play in building and sustaining productive learning and that teaching presence, defined as the core roles of the online instructor, is among the most promising mechanism for developing online learning community. We present a multi-institutional study of 2,036 students across thirty-two different colleges that supports this claim and provides insight into the relationship between online learning community and teaching presence. Factor and regression analysis indicate a significant link between students’ sense oflearning community and their recognition of effective instructional design and directed facilitation on the part of their course instructors—and that student gender plays a small role in sense of learning community. We conclude with recommendations for online course design, pedagogy, and future research.
We examine whether a friend or older sibling’s teen pregnancy impacts one’s own sexual behavior. Employing an event study design and rich retrospective data on sexual activity, we find that those who ...observe a peer’s teen pregnancy change sexual behavior after the pregnancy ends to put themselves at lower risk of their own teen pregnancy; specifically, they are less likely to have unprotected sex and have fewer sexual partners in the year following the end of the teen pregnancy. We find that females are more likely to change their sexual behavior compared to males, and the effects are primarily driven by peer live births, as opposed to other pregnancies. Ultimately, we find a slight decline in the likelihood of one’s own teen pregnancy, though estimates are noisy. Our work suggests that education campaigns that provide a realistic portrayal of teen parenthood may be an effective tool for impacting teen behavior.
PDF
