Dissertations / Theses on the topic 'Social Learning'
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Sørensen, Peter Norman. "Rational Social learning." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/10833.
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Verrill, Stephen W. "Social Structure and Social Learning in Delinquency: A Test of Akers’ Social Structure-Social Learning Model." [Tampa, Fla] : University of South Florida, 2005. http://purl.fcla.edu/usf/dc/et/SFE0001305.
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Atton, Nicola. "Social learning in fish /." St Andrews, 2010. http://hdl.handle.net/10023/946.
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Ray, Elizabeth Deborah. "Social and associative learning." Thesis, University College London (University of London), 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266406.
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Ottaviani, Marco. "Social learning in markets." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/10863.
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Zhang, Min. "Essays in social learning." Thesis, London School of Economics and Political Science (University of London), 2015. http://etheses.lse.ac.uk/3116/.
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This thesis contains two theoretical essays built upon the canonical models of social learning, and one that applies social learning theory to durable goods markets. The first chapter, "Non-Monotone Observational Learning", revisits the canonical social-learning model that rationalizes herding in the long run, to investigate the possibility of non-imitative behavior in the short run generated by non-monotone learning: ceteris paribus, when some predecessor(s) switch to actions revealing greater confidence in one state of the world, agents become less confident in that state. I characterize conditions on the underlying information structures that lead to non-monotone learning. In particular, in a general setting with continuous private signals, I provide a necessary condition for non-monotone learning with an argument for its plausibility, as well as two non-restrictive suffient conditions that do not rely on parametrization. The second chapter, "Does Public Information Disclosure Help Social Learning?", studies the effect of releasing exogenous public information in the canonical social-learning model that predicts incomplete learning. To improve social learning, I show that it is weakly better to postpone the disclosure of a public signal irrespective of its precision. However, such weak monotonicity no longer holds if the objective is to maximize the discounted sum of people's expected payoffs or if the model goes beyond the canonical binary setting. On the other hand, it is suboptimal to ever release a public signal less precise than people's private signals even if sophisticated releasing strategies are allowed. The last chapter, "Learning and Price Dynamics in Durable Goods Markets", is joint work with Francesco Palazzo. We study how markets for durable goods with unobservable and time-varying aggregate market conditions determine price dynamics with market participants constantly learning from public observations. We set up a dynamic auction model with two key features: first, agents enjoy heterogeneous private use values and later resell the asset; second, prices do not incorporate all available information dispersed in the economy. Informational frictions slow down learning and affect price movements asymmetrically across high and low aggregate demand states. Learning and the resale motive are the predominant force for durable goods with short resale horizons, slow time varying aggregate demand, and similar use values across agents.
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Lant, Ginger M. "Social Learning and Alcohol." W&M ScholarWorks, 1999. https://scholarworks.wm.edu/etd/1539626233.
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Kiddle, Rebecca. "Learning outside the box : designing social learning space." Thesis, Oxford Brookes University, 2011. https://radar.brookes.ac.uk/radar/items/f7b36f17-cf4f-4590-8dd7-e6df3ecfc1d2/1/.
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Social learning theory asserts that learning involves constructing knowledge through dialogue with others. Traditional learning spaces designed with didactic pedagogies in mind are often not flexible enough to cater to the range of social learning activities promoted by educationalists in classrooms today. This thesis investigates the interaction between social constructivist theories of learning and urban design, developing a body of social learning space design theory as well as space design principles which foster social learning in a university setting. The research uses an 'Enquiry by Design' methodology to develop the principles, basing this enquiry on two case studies: (i) a pilot study analysing an existing social learning space; the Simon Williams Undergraduate Centre, and (ii) an ongoing masterplanning project at Oxford Brookes University's Gipsy Lane campus, Space to Think.
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Walker, Reginald John. "Social auditing as social learning : a theoretical reconstruction." Thesis, University of Hull, 2007. http://hydra.hull.ac.uk/resources/hull:7958.
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Finneran, Lisa. "Advertising, quality and social learning." Thesis, University of Oxford, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.342858.
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Ghali, Fawaz. "Social personalized e-learning framework." Thesis, University of Warwick, 2010. http://wrap.warwick.ac.uk/35247/.
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This thesis discusses the topic of how to improve adaptive and personalized e-learning in order to provide novel learning experiences. A recent literature review revealed that adaptive and personalized e-learning systems are not widely used. There is a lack of interoperability between adaptive systems and learning management systems, in addition to limited collaborative and social features. First of all, this thesis investigates the interoperability issue via two case studies. The first case study focuses on how to achieve interoperability between adaptive systems and learning management systems using e-learning standards and the second case study focuses on how to augment e-learning standards with adaptive features. Secondly, this thesis proposes a new social framework for personalized e-learning, in order to provide adaptive and personalized e-learning platforms with new social features. This is not just about creating learning content, but also about developing new ways of learning. For instance, in the presented vision, adaptive learning does not refer to individuals only, but also to groups. Furthermore, the boundaries between authors and learners become less distinct in the Web 2.0 context. Finally, a new social personalized prototype is introduced based on the new social framework for personalized e-learning in order to test and evaluate this framework. The implementation and evaluation of the new system were carried out through a number of case studies.
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Li, Hsien-Ta. "Learning in social work practice." Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/7939.
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The research question underpinning this study is ‘How is learning organised within the context of social work practice in the third sector?’ The research objective is to establish conceptual frameworks that theorise the organisation of learning in this context. Drawing upon literatures from Organisational Behaviour, Management, Social Work, Sociology and Psychology (e.g., Ballew and Mink 1996; Foucault 1995; Mayer and Salovey 1997; Ouchi 1979; Weihrich 1982) and undertaking an ethnographic inquiry in the Old-Five-Old Foundation in Taiwan, which collects documents as secondary data and gathers primary data through participant observations and interviews, this study establishes interdisciplinary frameworks to answer this research question. It argues that practitioners’ learning is organised by five kinds of structuring forces. At the macro level, practitioners’ direction of learning is organised by service purchasers’ demanding (an inter-organisational level structuring force) and the service provider’s planning (an organisational level structuring force). The evaluation of practitioners’ learning is organised by the service provider’s monitoring (an organisational level structuring force). At the micro level, practitioners’ methods of learning are organised by practitioners’ puzzle solving and instructors’ instructing (individual level structuring forces). By looking at the macro and micro structuring forces (cross level analysis) that organise practitioners’ learning, including their direction and methods of learning and the evaluation of their learning (process analysis), this study systematically analyses the organising of learning through both a cross-level analysis and a process analysis, deepening an understanding of the organising of learning and thus making an original contribution to previous studies of learning in the organisational setting (e.g., Argyris and ch n 1978; Nonaka and Takeuchi 1995; Senge 1990; Wenger 1998, 2000).
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Leonard, Julia Anne Ph D. Massachusetts Institute of Technology. "Social influences on children's learning." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/120622.
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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2018.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 129-170).
Adults greatly impact children's learning: they serve as models of how to behave, and as parents, provide the larger social context in which children grow up. This thesis explores how adults impact children's learning across two time scales. Chapters 2 and 3 ask how a brief exposure to an adult model impacts children's moment-to-moment approach towards learning, and Chapters 4 and 5 look at how children's long-term social context impacts their brain development and capacity to learn. In Chapter 2, I show that preschool-age children integrate information from adults' actions, outcomes, and testimony to decide how hard to try on novel tasks. Children persist the longest when adults practice what they preach: saying they value effort, or giving children a pep talk, in conjunction with demonstrating effortful success on their own task. Chapter 3 demonstrates that social learning about effort is present in the first year of life and generalizes across tasks. In Chapter 4, I find that adolescents' long-term social environments have a selective impact on neural structure and function: socioeconomic-status (SES) relates to hippocampal-prefrontal declarative memory, but not striatal-dependent procedural memory. Finally, in Chapter 5 I demonstrate that the neural correlates of fluid reasoning differ by SES, suggesting that positive brain development varies by early life environment. Collectively, this work elucidates both the malleable social factors that positively impact children's learning and the unique neural and cognitive adaptations that children develop in response to adverse environments.
by Julia Anne Leonard.
Ph. D.
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Atton, Nicola. "Investigations into stickleback social learning." Thesis, University of St Andrews, 2014. http://hdl.handle.net/10023/6610.
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The objective of the experiments contained within this thesis was to provide further insight into the social learning capabilities of threespined sticklebacks and the factors affecting the transmission of information through populations. There are a number of previous studies which provide evidence that both threespined and ninespined sticklebacks possess the ability to learn socially under a range of contexts, such as foraging, anti-predator behaviour, mate choice, and cooperation. The studies presented in this thesis aim to extend this knowledge and shed light on the social learning processes used. Evidence was found to support previous opinion that threespined sticklebacks are capable of using a number of social learning processes, including local enhancement, stimulus enhancement, and the social enhancement of food preferences. However, therewas no evidence to suggest that either threespined or ninespined sticklebacks are capable of using the social learning process of delayed local enhancement under a shelter choice context, a process which both species have previously been shown to use under a foraging context. This thesis also explores the effect of the social network within shoals of threespined sticklebacks upon the transmission of novel foraging information. It was discovered that both prior association preferences and prior diet have an effect on the order in which individuals discover a novel foraging task.
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Jaques, Natasha(Natasha M. ). "Social and affective machine learning." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/129901.
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Thesis: Ph. D., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, February, 2020Cataloged from student-submitted PDF of thesis. "February 2020."
Includes bibliographical references (pages 309-342).
Social learning is a crucial component of human intelligence, allowing us to rapidly adapt to new scenarios, learn new tasks, and communicate knowledge that can be built on by others. This dissertation argues that the ability of artificial intelligence to learn, adapt, and generalize to new environments can be enhanced by mechanisms that allow for social learning. I propose several novel deep- and reinforcement-learning methods that improve the social and affective capabilities of artificial intelligence (AI), through social learning both from humans and from other AI agents. First, I show how AI agents can learn from the causal influence of their actions on other agents, leading to enhanced coordination and communication in multi-agent reinforcement learning. Second, I investigate learning socially from humans, using non-verbal and implicit affective signals such as facial expressions and sentiment.
This ability to optimize for human satisfaction through sensing implicit social cues can enhance human-AI interaction, and guide AI systems to take actions aligned with human preferences. Learning from human interaction with reinforcement learning, however, may require dealing with sparse, off-policy data, without the ability to explore online in the environment - a situation that is inherent to safety-critical, real-world systems that must be tested before being deployed. I present several techniques that enable learning effectively in this challenging setting. Experiments deploying these models to interact with humans reveal that learning from implicit, affective signals is more effective than relying on humans to provide manual labels of their preferences, a task that is cumbersome and time-consuming. However, learning from humans' affective cues requires recognizing them first.
In the third part of this thesis, I present several machine learning methods for automatically interpreting human data and recognizing affective and social signals such as stress, happiness, and conversational rapport. I show that personalizing such models using multi-task learning achieves large performance gains in predicting highly individualistic outcomes like human happiness. Together, these techniques create a framework for building socially and emotionally intelligent AI agents that can flexibly learn from each other and from humans.
by Natasha Jaques.
Ph. D.
Ph.D. Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences
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Bossan, Benjamin. "The evolution of social learning." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2013. http://dx.doi.org/10.18452/16860.
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Menschen unterscheiden sich von anderen Tieren insbesondere dadurch, dass ihr Alltag durch vielfältige kulturelle Praktiken bestimmt wird. Diese erlaubten es dem Menschen, fast alle terrestrischen Habitate auf der Erde in hoher Dichte zu besiedeln. Kulturelle Merkmale werden nicht genetisch vererbt, sondern durch soziales Lernen zwischen Menschen übertragen -- niemand könnte ohne den vorhandenen Wissensbeitrag anderer ein funktionstüchtiges Kanu bauen. Daraus zu schließen, kulturelle und genetische Evolution seien komplett getrennt zu behandeln, wäre allerdings falsch. Genetische Evolution hat es überhaupt erst erlaubt, von anderen in adaptiver Weise zu lernen. Kulturelle und genetische Evolution müssen zusammen betrachtet werden, um die Einzigartigkeit des Menschen zu verstehen. Der offensichtlich vorhandene adaptive Nutzen sozialen Lernens konnte in theoretischen Arbeiten allerdings nicht repliziert werden. Das deutet darauf hin, dass das Verständnis über die Funktionsweise sozialen Lernens noch unvollständig ist. Zwar haben einige Wissenschaftler mögliche Lösungen für dieses Paradox vorgeschlagen, aber unser Modell zeigt, dass diese unzureichend sind. Stattdessen hält sich der Widerspruch hartnäckiger als geglaubt. Wir analysieren zwar neue soziale Lernstrategien, die den Widerspruch lösen könnten, doch das erfolgt nur unter sehr beschränkten Bedingungen. Außerdem treten wir für eine neue Sicht auf soziales Lernen ein und damit einhergehend für einen Modellierungsansatz, der Lernformen in realistischerer Weise berücksichtigt. Die Untersuchung des evolutionären Ursprungs sozialen Lernens sollte den gleichen Stellenwert haben wie jene des evolutionären Ursprungs kooperativen Verhaltens. Dass dies sinnvoll wäre, belegen wir, indem wir zeigen, welchen Einfluss soziales Lernen sogar auf moderne Gesellschaften und Volkswirtschaften hat und wie es beispielsweise hilft, Finanzkrisen besser zu verstehen.Humans differ most from other animals in that their lives are shaped by many cultural practices. Having cultural traits allowed human populations to grow considerably in a short time and to conquer almost all terrestrial habitats on Earth. Cultural traits are not inborn but are instead transmitted between humans through social learning -- no individual could build a fully functional kayak without learning from others. Concluding that cultural evolution is thus a separate process from genetic evolution would, however, be rash. The latter has endowed humans with the possibility to learn from others in the first place, and prepared learning to make it especially adaptive. To find out what makes humans unique, cultural and genetic evolution, therefore, have to be studied in concert. Although nobody doubts that evolution gave rise to social learning and that the resulting cultural practices serve an adaptive purpose, theoretical works have shown that simple forms of social learning do not improve human adaptedness. This finding contradicts the observations and thus implies that our understanding of social learning is incomplete. Several authors have proposed solutions to this paradox but, as our model results will show, the solutions are unsatisfying. Instead, we find the paradox to be more resilient than is believed and propose forms of social learning that could solve it, albeit only under very narrow circumstances. Furthermore, we argue for a new perspective on social learning and, consequently, for a different framework that allows for more realistic learning models. We suggest that the study of the evolutionary origin of social learning should be given equal weight as the study of the evolutionary origin of cooperation, and illustrate this by elaborating on the impact of social learning on modern societies and market behaviors in general, and on financial crises specifically.
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Barkoczi, Daniel. "Ecological rationality of social learning." Doctoral thesis, Humboldt-Universität zu Berlin, Lebenswissenschaftliche Fakultät, 2016. http://dx.doi.org/10.18452/17468.
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Wie Menschen von anderen lernen und wann es adaptiv-rational ist sich auf soziales Lernen zu verlassen sind wichtige Fragen in vielen Disziplinen einschließlich der Psychologie, der Biologie, der Anthropologie und den Wirtschaftswissenschaften. Trotz der geteilten Interessen dieser Disziplinen sind viele der vorhandenen Resultate voneinander isoliert und oft nicht vergleichbar, teilweise weil es der Forschung zum sozialen Lernen immer noch eines theoretischen Rahmens fehlt, welcher die gewonnen Erkenntnisse vergleichbar machen würde sowie erklären würde warum unterschiedliche Strategien in Abhängigkeit vom sozialen Kontext erfolgreich sind oder nicht. In meiner Arbeit schlage ich einen solchen theoretischen Rahmen vor, welcher sich auf der Forschung zur ökologischen Rationalität gründet. Ich benutze den theoretischen Rahmen der ökologischen Rationalität sozialen Lernens, um drei Fragen zu beantworten: i) Wie können soziale Lernstrategien als kognitiv plausible Strategien modelliert werden, die auf drei einfachen Building Blocks beruhen (Such-, Stopp- und Entscheidungsregeln), ii) was sind die wichtigsten Faktoren von sozialen Umwelten und Problemumwelten, in denen soziales Lernen stattfindet und iii) wie interagieren soziale Lernstrategien, die auf unterschiedlichen Building Blocks beruhen, mit der Struktur von Umwelten, um unterschiedliche Erfolgsniveaus zu erreichen. Indem ich diese drei Fragen adressiere, erarbeite ich die Bedingungen unter denen unterschiedlichen Strategien adaptiv-rational sind und erkläre wie unterschiedlichen Strategien in bestimmten Umwelten erfolgreich sind. Jedes der Kapitel behandelt eine wichtige alltägliche soziale Lernsituation, identifiziert die Schlüsselcharakteristiken der Situation und demonstriert wie die Building Blocks des sozialen Lernens mit diesen Umweltstrukturen interagieren, um unterschiedliche Erfolgsniveaus zu erreichen.How people learn from others and when it is adaptive to rely on social learning have been major questions in several disciplines including psychology, biology, anthropology and economics. Despite the shared interest of these diverse fields, many of the results remain isolated and are often incomparable, in part because the study of social learning still lacks a general theoretical framework that would make results comparable or explain why different strategies perform well in different contexts. In this thesis I propose such a framework that is grounded in the study of ecological rationality. I use this frame- work to explore three primary questions: i) how can social learning strategies be modeled as cognitively plausible strategies composed of simple building blocks (search, stopping and decision rules), ii) what are key characteristics of social and task environments in which social learning takes place, and iii) how do social learning strategies composed of different building blocks interact with the structure of the environment to produce different levels of success. Through addressing these three questions I map out the conditions under which different strategies are adaptive and explain how the building blocks of different strategies contribute to their performance in certain environments. The thesis focuses on three representative classes of social learning strategies, namely, frequency-dependent, payoff-biased, and unbiased copying. Different chapters focus on important everyday social learning settings, identify key environmental characteristics defining the setting and demonstrate how the building blocks of social learning strategies interact with these environmental structures to produce different outcomes.
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Curtis, George E. "Social self-evaluation and social problem-solving skills in learning and non-learning disabled males." Virtual Press, 1990. http://liblink.bsu.edu/uhtbin/catkey/762976.
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The questions investigated concerned the social problem solving skills of 41 learning disabled (LD) students compared to 41 typical students in grades 10, 11, and 12. Since (a) LD students are generally described as impulsive, lacking in social judgment, and unaware of consequences; since (b) these social problems have been described as some of the most devastating for LD students as they interfere with their everyday adaptation to living; since (c) social decision making has been found to be somewhat correlated with mental and emotional health and the self-concept; since (d) studies have indicated a range of from 26% to 73% of the criminal population have a Learning Disability - indicating a difficulty in adapting to society; it appears very important that we find ways to improve the social adaptation of LD persons. This study was a beginning of research with this goal in mind.The questions investigated were: 1) are LD students as good as Non-LD in social problem solving, as measured by the number of solutions they can spontaneously generate to presented social situations; 2) do LD students tend to select the same categories of response to social conflicts as non-LD students, as measured by their choices from a group of predetermined solutions to the same presented social conflict situations; are LD student's self evaluations of their problem solving ability as accurate as the self evaluations of non-LD student's as measured by their responses on a revised version of the Problem Solving Inventory and their ability to generate solutions to problem situations. First, the social situations, revisions of situations from the MeansEnds Problem Solving test, were read by the tester while the student followed along with a printed copy of the text. The student was informed as to what he preferred to do and what he was expected to do. After hearing the social conflict, he was then instructed, "In one minute, tell me as many ways as you can that you would deal with this this situation." Thus, no inappropriate behaviors were suggested. Second, the student was presented the same social situations in the same manner. He was then presented eight choices. He was told, "From the following choices, circle the letters next to the four choices you would most likely use to deal with this situation". The goal of the experiment was to determine if the LD person would choose the same types of strategies for adapting as the typical student. As there were no pre and post tests, the names of the individuals were not required, only whether or not they were LD and possibly their grade level. This would guarantee confidentiality. Tests were administered individually for generating solutions and in small groups where answers could be written.Next, the experiment attempted to determine if there is a relationship between one's ability to generate solutions and their self-rating as problem solvers. A modified version of Heppner's Problem Solving Inventory was prepared. It was believed that a statistical analysis of the two factors using LD and Non-LD students would give an indication of this relationship.The documents used in the test were: 1. the revision of the Means-Ends Problem Solving Test and 2. the revision of the Problem Solving Inventory. These are attached to this document in the appendices.The results of the study indicated that there is no statistically significant difference between the LD and the Non-LD students ability to generate solutions to the problem solving situations. There was no statistically significant difference in the self-evaluated problem solving ability of the two groups. There was a statistically very significant difference in the type of response category selected by the LD students when compared with non-LD students.Department of Special Education
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Dawson, Erika H. "Social information use in social insects." Thesis, Queen Mary, University of London, 2014. http://qmro.qmul.ac.uk/xmlui/handle/123456789/7980.
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Social learning plays a valuable role in the lives of many animal taxa, sometimes allowing individuals to bypass the costs of personal exploration. The ubiquity of this behaviour may arise from the fact that learning from others is often underpinned by simple learning processes that also enable individuals to learn asocially. Insects have proven to be particularly valuable models for investigating parsimonious hypotheses with regards to social learning processes, due to their small brain sizes and the prevalence of social information use in their life histories. In this thesis, I use social insects to further investigate the mechanisms underlying more complex social learning behaviours and explore the circumstances under which social information use manifests. In the first chapter, I investigate the proximate mechanisms underlying social learning and demonstrate that even seemingly complex social learning behaviours can arise through simple associative learning processes. In Chapter two, I investigate whether bees are more predisposed to learning from conspecific cues and discover that social information is learnt to a greater extent than information originating from non-social sources. In Chapter four, I demonstrate that classical conditioning also underpins learning from evolved social signals in honeybees. Finally, I investigate whether social information is used adaptively by bumblebees: Chapter three demonstrates that joining behaviour in free-flying bees is contingent upon whether flowers are familiar or not, and in Chapter six, I show that when social information is costly to acquire, bees are more likely to rely on social information to make foraging decisions. Taken as a whole, my findings suggest that bees may be specially adapted for receiving social information, but the ability to learn from others arises through general associative learning mechanisms.
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Brasser, Angela L. "Social learning strategies| A qualitative study of self-regulated learning." Thesis, Capella University, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3702736.
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This qualitative study examined low achieving online learners' uses of social self-regulated learning strategies. Research has shown that low achieving online learners lack strategies for self-regulated learning, which directly relates to their lack of achievement. Social self-regulated learning strategies examined in this study included help seeking, social comparison and social interactions. As learners constructed meaning and struggled with content, interactions between learners and peers, the instructor/instructor's assistant, technical support, and materials facilitated the process. Low achieving online learners resisted utilizing social self-regulated learning strategies. However, according to the research, little data was collected from low achieving online learners directly. This study asked low achieving online learners to describe their experiences, through semi-structured interviews. Barriers to social self-regulated learning strategies included poor attitudes, internet addiction, and exterior blame, according to the research. Self-regulated learning, in general, is linked to higher achievement. This study found that low achieving online learners lacked the use of social self-regulated learning strategies. Additionally, participants lacked help seeking behaviors, experienced social isolation, and held negative views of their classmates and instructor. The findings in this study may assist instructional designers to increase opportunities for social self-regulated learning in online courses, which may, in turn, increase achievement.
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Hardy, Sarah J. "The Role of Leadership in Social-emotional Learning Implementation: Making Sense of Social-emotional Learning Initiatives." Thesis, Boston College, 2018. http://hdl.handle.net/2345/bc-ir:107979.
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Thesis advisor: Vincent ChoThe Role of Leadership in Social-Emotional Learning Implementation: Making Sense of Social-Emotional Learning Initiatives by Sarah J. Hardy Dr. Vincent Cho, Chair, Dr. Elida Laski, Reader, Dr. Ingrid Allardi, Reader Social-emotional learning (SEL) is an essential component of every student’s education. District leaders play an important role in the development and implementation of SEL programs in schools. This qualitative case study explored the strategies used by district leaders in supporting sensemaking of SEL initiatives as they were implemented. Data were collected through semi-structured interviews with district and school leaders, focus group interviews with teachers, and a document review. Findings revealed district leaders employed strategies in the broad areas of setting direction, developing people, and redesigning the organization (Leithwood et al., 2004). However, there was no district-wide, unified vision for SEL programming, and the majority of SEL reform was advanced by principals. SEL interactions mostly occurred between principals and teachers, and between members of the teaching staff. SEL interactions were focused on essential principles of SEL initiatives, procedural information about SEL implementation, and crisis-driven support for individual students. Some interactions supported sensemaking. One recommendation of this study is to set a district-wide vision for SEL learning to align practices and provide a framework for principal autonomy. This study also recommends establishing structures that support collaboration in order to promote sensemaking through SEL interactions
Thesis (EdD) — Boston College, 2018
Submitted to: Boston College. Lynch School of Education
Discipline: Educational Leadership and Higher Education
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Malerba, Candilio Maria Luisa. "Social Networking in Second Language Learning." Doctoral thesis, Universitat Oberta de Catalunya, 2015. http://hdl.handle.net/10803/565551.
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Aquesta tesi se centra en l'aprenentatge informal d'una segona llengua en comunitats en línia com Livemocha i Busuu. Els objectius són: (1) analitzar el potencial de les comunitats en línia per a aconseguir resultats d'aprenentatge a llarg termini; (2) examinar les accions dels estudiants mentre construeixen oportunitats d'ús de la segona llengua en aquests entorns, i (3) explorar les potencialitats i les limitacions de les eines de les comunitats en línia. Amb la finalitat d'assolir aquests objectius, l'estudi, que s'inscriu en el marc teòric de la perspectiva sociocultural i de la teoria de l'activitat, ha utilitzat una metodologia de recerca principalment qualitativa i centrada en el mètode etnogràfic. La recerca conclou amb una reflexió crítica sobre la importància de l'autonomia de l'estudiant. S'ha destacat que l'autonomia de l'estudiant és un requisit important perquè l'experiència d'aprenentatge informal en aquests entorns sigui eficaç. A més, aquest estudi tradueix els resultats obtinguts en un conjunt de recomanacions pedagògiques dirigides a experts d'entorns d'aprenentatge, a estudiants i a professors d'idiomes, per tal de fomentar una experiència d'aprenentatge en les comunitats en línia més positiva tenint en compte, també, la seva possible aplicació en un context d'aprenentatge formal.Esta tesis está centrada en el aprendizaje informal de una segunda lengua en comunidades en línea como Livemocha y Busuu. Los objetivos son: (1) analizar el potencial de las comunidades en línea para lograr resultados de aprendizaje a largo plazo; (2) examinar las acciones de los estudiantes mientras construyen oportunidades de uso de la segunda lengua en estos entornos, y (3) explorar las potencialidades y las limitaciones de las herramientas de las comunidades en línea. Con la finalidad de alcanzar estos objetivos, el estudio, que se inscribe en el marco teórico de la perspectiva sociocultural y de la teoría de la actividad, ha utilizado una metodología de investigación principalmente cualitativa y centrada en el método etnográfico. La investigación concluye con una reflexión crítica sobre la importancia de la autonomía del estudiante. Se ha destacado que la autonomía del estudiante es un requisito importante para que la experiencia de aprendizaje informal en estos entornos sea eficaz. Además, este estudio traduce los resultados obtenidos en una serie de recomendaciones pedagógicas dirigidas a expertos de entornos de aprendizaje, a estudiantes y a profesores de idiomas, con el fin de fomentar una mejor experiencia de aprendizaje en las comunidades en línea tomando en consideración también su posible aplicación en un contexto de aprendizaje formal.
This thesis deals with informal second language learning in online communities such as Livemocha and Busuu. The thesis' objectives are: (1) analyse the potential effectiveness of these communities for long-term learning outcomes; (2) examine learners' construction of opportunities for L2 use in these environments; (3) explore affordances and constraints of online communities. To this end, a longitudinal multiple ethnographic case study approach was used under the theoretical framework of Socio-Cultural Theory and Activity Theory (AT). The research concludes with a critical reflection on the role of learner autonomy as a prerequisite for the creation of effective learning experiences in these environments, as this study clearly demonstrates. Moreover, the study translates its findings into a set of pedagogical recommendations for platform developers, learners and teachers to maximize the advantages of L2 learning in online communities as well as establish possible applications in formal learning settings.
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Bordianu, Gheorghita. "Learning influence probabilities in social networks." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=114597.
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Social network analysis is an important cross-disciplinary area of research, with applications in fields such as biology, epidemiology, marketing and even politics. Influence maximization is the problem of finding the set of seed nodes in an information diffusion process that guarantees maximum spread of influence in a social network, given its structure. Most approaches to this problem make two assumptions. First, the global structure of the network is known. Second, influence probabilities between any two nodes are known beforehand, which is rarely the case in practical settings. In this thesis we propose a different approach to the problem of learning those influence probabilities from past data, using only the local structure of the social network. The method is grounded in unsupervised machine learning techniques and is based on a form of hierarchical clustering, allowing us to distinguish between influential and the influenceable nodes. Finally, we provide empirical results using real data extracted from Facebook.L'analyse des réseaux sociaux est un domaine d'études interdisciplinaires qui comprend des applications en biologie, épidémiologie, marketing et même politique. La maximisation de l'influence représente un problème où l'on doit trouver l'ensemble des noeuds de semence dans un processus de diffusion de l'information qui en même temps garantit le maximum de propagation de son influence dans un réseau social avec une structure connue. La plupart des approches à ce genre de problème font appel à deux hypothèses. Premièrement, la structure générale du réseau social est connue. Deuxièmement, les probabilités des influences entre deux noeuds sont connues à l'avance, fait qui n'est d'ailleurs pas valide dans des circonstances pratiques. Dans cette thèse, on propose un procédé différent visant la problème de l'apprentissage de ces probabilités d'influence à partir des données passées, en utilisant seulement la structure locale du réseau social. Le procédé se base sur l'apprentissage automatique sans surveillance et il est relié à une forme de regroupement hiérarchique, ce qui nous permet de faire la distinction entre les noeuds influenceurs et les noeuds influencés. Finalement, on fournit des résultats empiriques en utilisant des données réelles extraites du réseau social Facebook.
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Patnam, Manasa. "Essays in social interactions and learning." Thesis, University of Cambridge, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.607718.
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Jindani, Sam. "Social norms and learning in games." Thesis, University of Oxford, 2017. https://ora.ox.ac.uk/objects/uuid:90268309-1920-4f1d-a769-f50783f435be.
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Duelling The norm of duelling endured for hundreds of years in Europe. In the United Kingdom it disappeared abruptly in the mid-nineteenth century, whereas in France it declined slowly. I present a simple model of social norms that explains these phenomena. The model predicts that the evolution of norms is characterised by tipping, whereby norms can shift suddenly due to shocks, and by a ratchet effect, whereby changes in parameters can cause norms to decline gradually. I show that the model can be supported by an equilibrium of a repeated game, with no special assumptions about preferences. Community enforcement using modal actions I prove two folk theorems for repeated games with random matching. A large group of players is rematched at random each period, so that players who deviate must be sanctioned by third parties. Previous analyses have either relied on strong assumptions about information transmission, or have been limited to equilibria that are not robust to noise or in which players are indifferent. I use a simple construction based on modal actions to obtain results for strict and robust equilibria. Learning repeated-game strategies The literature on boundedly rational learning has tended to focus on stagegame actions. I present a stochastic learning rule for repeated-game strategies. Players form beliefs about their opponentâs strategy based on past actions and best-respond. Occasionally, they make mistakes and experiment, and I show that the equilibrium selected depends on exactly how players make mistakes. Simple specifications of the learning rule yield intuitive selection results: the maxmin, or Rawlsian, outcome; the Nash bargaining solution; the maximum of the sum of payoffs; and a generalisation of risk dominance.
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Watson, Stuart Kyle. "Factors shaping social learning in chimpanzees." Thesis, University of St Andrews, 2018. http://hdl.handle.net/10023/12781.
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Culture is an important means by which both human and non-human animals transmit useful behaviours between individuals and generations. Amongst animals, chimpanzees live particularly varied cultural lives. However, the processes and factors that influence whether chimpanzees will be motivated to copy an observed behaviour are poorly understood. In this thesis, I explore various factors and their influence on social learning decisions in chimpanzees. In turn, the chapters examine the influence of (i) rank-bias towards copying dominant individuals, (ii) majority and contextual influences and finally (iii) individual differences in proclivity for social learning. In my first experiment, I found evidence that chimpanzees are highly motivated to copy the behaviour of subordinate demonstrators and innovators in an open-diffusion puzzle-box paradigm. In contrast, behaviours seeded by dominant individuals were not transmitted as faithfully. This finding has important implications for our understanding of the emergence of novel traditions. In my second experiment, I found that some chimpanzees are highly motivated to relinquish an existing behaviour to adopt an equally rewarding alternative if it is consistently demonstrated by just one or two individuals within a group context, but not in a dyadic context. This contrasts with prior studies which argue that chimpanzees are highly conservative and may hint at a hitherto unrecognised process by which conformity-like behaviour might occur. Finally, I performed a novel type of ‘meta' analysis on 16 social learning studies carried out at our research site to determine whether individuals demonstrated consistency in their social learning behaviour across experimental contexts. Strong evidence for individual differences in social information use was found, with females more likely to use social information than males. No effect of age, research experience or rearing history was found. This presents a promising new method of studying individual differences in behaviour using the accumulated findings of previous work at a study site.
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Sharad, Kumar. "Learning to de-anonymize social networks." Thesis, University of Cambridge, 2016. https://www.repository.cam.ac.uk/handle/1810/262750.
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Releasing anonymized social network data for analysis has been a popular idea among data providers. Despite evidence to the contrary the belief that anonymization will solve the privacy problem in practice refuses to die. This dissertation contributes to the field of social graph de-anonymization by demonstrating that even automated models can be quite successful in breaching the privacy of such datasets. We propose novel machine-learning based techniques to learn the identities of nodes in social graphs, thereby automating manual, heuristic-based attacks. Our work extends the vast literature of social graph de-anonymization attacks by systematizing them. We present a random-forests based classifier which uses structural node features based on neighborhood degree distribution to predict their similarity. Using these simple and efficient features we design versatile and expressive learning models which can learn the de-anonymization task just from a few examples. Our evaluation establishes their efficacy in transforming de-anonymization to a learning problem. The learning is transferable in that the model can be trained to attack one graph when trained on another. Moving on, we demonstrate the versatility and greater applicability of the proposed model by using it to solve the long-standing problem of benchmarking social graph anonymization schemes. Our framework bridges a fundamental research gap by making cheap, quick and automated analysis of anonymization schemes possible, without even requiring their full description. The benchmark is based on comparison of structural information leakage vs. utility preservation. We study the trade-off of anonymity vs. utility for six popular anonymization schemes including those promising k-anonymity. Our analysis shows that none of the schemes are fit for the purpose. Finally, we present an end-to-end social graph de-anonymization attack which uses the proposed machine learning techniques to recover node mappings across intersecting graphs. Our attack enhances the state of art in graph de-anonymization by demonstrating better performance than all the other attacks including those that use seed knowledge. The attack is seedless and heuristic free, which demonstrates the superiority of machine learning techniques as compared to hand-selected parametric attacks.
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Adjodah, Dhaval D. K. (Adjodlah Dhaval Dhamnidhi Kumar). "Social inductive biases for reinforcement learning." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/128415.
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Thesis: Ph. D., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, September, 2019Cataloged from the official PDF of thesis. "The Table of Contents does not accurately represent the page numbering"--Disclaimer page.
Includes bibliographical references (pages 117-126).
How can we build machines that collaborate and learn more seamlessly with humans, and with each other? How do we create fairer societies? How do we minimize the impact of information manipulation campaigns, and fight back? How do we build machine learning algorithms that are more sample efficient when learning from each other's sparse data, and under time constraints? At the root of these questions is a simple one: how do agents, human or machines, learn from each other, and can we improve it and apply it to new domains? The cognitive and social sciences have provided innumerable insights into how people learn from data using both passive observation and experimental intervention. Similarly, the statistics and machine learning communities have formalized learning as a rigorous and testable computational process.
There is a growing movement to apply insights from the cognitive and social sciences to improving machine learning, as well as opportunities to use machine learning as a sandbox to test, simulate and expand ideas from the cognitive and social sciences. A less researched and fertile part of this intersection is the modeling of social learning: past work has been more focused on how agents can learn from the 'environment', and there is less work that borrows from both communities to look into how agents learn from each other. This thesis presents novel contributions into the nature and usefulness of social learning as an inductive bias for reinforced learning.
I start by presenting the results from two large-scale online human experiments: first, I observe Dunbar cognitive limits that shape and limit social learning in two different social trading platforms, with the additional contribution that synthetic financial bots that transcend human limitations can obtain higher profits even when using naive trading strategies. Second, I devise a novel online experiment to observe how people, at the individual level, update their belief of future financial asset prices (e.g. S&P 500 and Oil prices) from social information. I model such social learning using Bayesian models of cognition, and observe that people make strong distributional assumptions on the social data they observe (e.g. assuming that the likelihood data is unimodal).
I were fortunate to collect one round of predictions during the Brexit market instability, and find that social learning leads to higher performance than when learning from the underlying price history (the environment) during such volatile times. Having observed the cognitive limits and biases people exhibit when learning from other agents, I present an motivational example of the strength of inductive biases in reinforcement learning: I implement a learning model with a relational inductive bias that pre-processes the environment state into a set of relationships between entities in the world. I observe strong improvements in performance and sample efficiency, and even observe the learned relationships to be strongly interpretable.
Finally, given that most modern deep reinforcement learning algorithms are distributed (in that they have separate learning agents), I investigate the hypothesis that viewing deep reinforcement learning as a social learning distributed search problem could lead to strong improvements. I do so by creating a fully decentralized, sparsely-communicating and scalable learning algorithm, and observe strong learning improvements with lower communication bandwidth usage (between learning agents) when using communication topologies that naturally evolved due to social learning in humans. Additionally, I provide a theoretical upper bound (that agrees with our empirical results) regarding which communication topologies lead to the largest learning performance improvement.
Given a future increasingly filled with decentralized autonomous machine learning systems that interact with humans, there is an increasing need to understand social learning to build resilient, scalable and effective learning systems, and this thesis provides insights into how to build such systems.
by Dhaval D.K. Adjodah.
Ph. D.
Ph.D. Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences
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Rogers, Brian W. Palfrey Thomas R. "Learning and status in social networks /." Diss., Pasadena, Calif. : Caltech, 2006. http://resolver.caltech.edu/CaltechETD:etd-05262006-004112.
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Over, Harriet. "Social influence and social learning in young children and infants." Thesis, Cardiff University, 2009. http://orca.cf.ac.uk/54866/.
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This thesis examines the motivations underlying social influence and behaviour matching in young children. In my General Introduction, I argue that, in adults, behaviour matching is often motivated by goals to learn from and affiliate with other group members (or by a combination of these two factors). In addition to explicit forms of behaviour matching, however, adults also subconsciously assimilate their behaviour to those around them. I argue that imitation in young children may be similarly motivated by goals to learn from and affiliate with others. In other words, that imitation performs an instrumental and a social function in development. Further, I argue that young children may also subconsciously assimilate their behaviour to those around them. The following experimental chapters test aspects of these claims. Chapter 2 investigates verbal imitation. Focusing on the instrumental aspects of this ability, I test whether young children copy the perceived intentions behind speech. Results show that children correct the ungrammatical utterances of an intentional model, but copy the utterances of a non-intentional model exactly. Chapter 3 investigates social imitation. In that chapter, I test whether children increase their imitation when they have a goal to affiliate. Results show that children who have been given a goal to affiliate (through priming with social exclusion) copy the actions of a model significantly more closely than children who have been given a neutral prime. Chapter 4 investigates unintentional, or subconscious, behaviour matching and tests whether even infants assimilate their behaviour to social primes. Results show that infants primed with affiliation are significantly more likely to help an experimenter than infants primed with individuality. Taken together, these experiments demonstrate that behaviour matching is a diverse and important phenomenon in development. It occurs both intentionally and unintentionally, and enables children to learn from and affiliate with those around them.
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Asano, Takahiro. "Professional learning as a way of being a social worker : post-qualifying learning among Japanese social workers." Thesis, University of York, 2015. http://etheses.whiterose.ac.uk/11499/.
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This study examined how the experienced social workers continued to learn as professionals in the context of Japanese social work. The findings have suggested that the challenges and struggles they confronted were closely related to their professional ways of being. We cannot understand their learning unless we set each person’s learning experiences in the context of their way of being a social worker. They saw their learning as something about changes in their understanding in varying ways. Though those perspective changes in learning varied widely depending on their learning situation, three components of professional learning have been identified: Experience; Opportunity; and Reflection. Experience describes how professional learning involves the interconnection of cumulative background experiences they had, which can include both within their professional work and outside. What counts as a learning Opportunity can vary considerably according to them. It makes good sense to treat learning opportunities not as a distinct one but as a unified entity. Reflection involves them seeing practice from different perspectives, in that their taken-for-granted assumption is challenged, which may lead to new possibilities that can make their practice different in their working context. These three components are not entirely distinct from each other, but inextricably interwoven. The findings reveal that there is the significant gap between what the social workers value in learning and what is expected from their organizations, professional associations, and universities in today’s uncertain working environments, in which they are required to ensure increased professional accountability for their performance with measurable standards. In the gap, voices of social workers have been underrepresented in the discourse of professional development. To share awareness of diverse and complex learning as experienced by social workers can be a first step in making a difference to professional learning in the context of Japanese social work.
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Rhamachan, Molly. "Social movement learning: Collective,participatory learning within the jyoti jivanam movement of south Africa." University of the Western Cape, 2014. http://hdl.handle.net/11394/4401.
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Magister Educationis (Adult Learning and Global Change) - MEd(AL)The purpose of this research paper is to explore and examine the nature of learning within the context of and situated within a social movement. Based on an exploratory qualitative study of learning within the Jyoti Jivanam Movement of South Africa, this research explores the nature and purpose/s of learning within a social movement. Accordingly, this study is guided by the research questions: How and why do adults learn as they collectively participate in social movements; and what factors facilitate, contribute, hinder and influence learning within social movement? This study confirms that social movements are important sites for. Collective learning and knowledge construction. For this reason, social movements need to be acknowledged as pedagogical sites that afford adults worthwhile learning opportunities. Furthermore, social movements, as pedagogical sites, not only contribute to conceptions of what constitute legitimate knowledge(s), social movements also contribute to the creation of transformative knowledge(s).
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Frisk, Martin. "Social robot learning with deep reinforcement learning and realistic reward shaping." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-395918.
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Deep reinforcement learning has been applied successfully to numerous robotic control tasks, but its applicability to social robot tasks has been comparatively limited. This work combines a spatial autoencoder and state-of-the-art deep reinforcement learning to train a simulated autonomous robot to perform group joining behavior. The resulting control policy uses only first-person camera images and the robot's speed as input. The behavior of the control policy was evaluated in a perceptual study, and was shown to be less rude, more polite, and more sociable when compared to the reference model. We believe this methodology is generalizable to other social robot tasks.
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McGarrigle, Donna M. "The Role of Leadership in Social-Emotional Learning Implementation: Principal and Counselor Practices to Support Social-Emotional Learning." Thesis, Boston College, 2018. http://hdl.handle.net/2345/bc-ir:107977.
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Thesis advisor: Vincent ChoThis case study of a public school district in the Northeast United States explores the leadership practices of elementary and middle school counseling staff and principals in supporting SEL, using a distributed leadership framework (Spillane, 2006). Data sources included 24 interviews with administrators, guidance counselors and social workers and document review. Findings indicate counseling staff support students and staff in a variety of ways through both formal and informal leadership practices. Principals support SEL by establishing SEL programs or strategies to match the needs of their student population. Two different models were found for how guidance counselor and social worker responsibilities are structured. The most common model, in six of the nine schools, is a tiered model where guidance counselors work with the majority of students on academic support/monitoring and delivering SEL lessons. Social workers focus on smaller numbers of students with more intensive needs. The second but less common model, in three of the nine schools, does not differentiate the roles of social workers and guidance counselors and instead assigns responsibilities by grade level. Concerns with this second model were raised by some administrators and several counselors. The quality of peer and administrator relationships was reported to be supportive and collaborative in the schools with differentiated roles. In the non-differentiated schools, it varied, and was related to shifting staff, a misunderstanding of the role differences, and challenges in developing collaborative relationships. Recommendations include assessing support structures to ensure the model adequately supports the SEL needs of the school
Thesis (EdD) — Boston College, 2018
Submitted to: Boston College. Lynch School of Education
Discipline: Educational Leadership and Higher Education
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Isaacs, Lorraine Ann. "Social constructivism and collaborative learning in social networks: the case of an online masters programme in adult learning." Thesis, University of the Western Cape, 2013. http://hdl.handle.net/11394/5130.
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Magister Educationis (Adult Learning and Global Change) - MEd(AL)This study investigates how students in an online Masters Programme in Adult Learning, although geographically dispersed used SNs to develop a supportive environment that enables collaborative learning to support and deepen their learning. Web 2.0 social software provided the tools for various forms of communication and information sharing amongst student within the social networks. This study shows how the use of Web 2.0 tools such as wikis, podcasts, blogs, chat rooms, social networking sites and email have the potential to expand the learning environment, increase participation and enrich the learning experience. Rapid technological developments transform our world into a global society which is ever changing and interconnected. The SNs as a learning environment in this technological driven global society is complex and not clearly defined; therefore it was not easy for me to understand the nature of the SNs as learning environment. The social nature of this study has therefore urged me to use social constructivism as a conceptual framework to gain insights into how students have used the social networks to develop a supportive environment that enables collaborative learning to support and deepen their learning. The utilisation of social constructivism as theoretical lens has helped to broaden my perceptions of the SNs as learning environment, to deepen my understanding of how learning occurs in the SNs and to comprehend learner behaviour within this pedagogical space. Social constructivists view learning as a social process in which people make sense of their world by interacting with other people (Doolittle & Camp, 1999). Social constructivists belief in the social nature of knowledge, and the belief that knowledge is the result of social interaction and language usage, and, thus, is a shared, rather than an individual, experience (Prawat & Floden, 1994). Furthermore, they believe that this social interaction always occurs within a socio-cultural context, resulting in knowledge that is bound to a specific time and place (Vygotsky, 1978).
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Li, Xudong. "The Impact of Social Learning and Social Norms on Auditor Choice." Thesis, University of North Texas, 2014. https://digital.library.unt.edu/ark:/67531/metadc700085/.
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The purpose of this dissertation is to explore the influences of industry dynamic factors (e.g., peer selections) on a client’s subsequent decision to select the type of auditor (e.g., Big N versus non-Big N), following auditor turnover. More specifically, drawing on social norms and social learning theories, I develop testable implications and investigate whether and how industry dynamics have an incremental power in explaining auditor choice beyond traditional firm-specific variables documented in prior research. Using a large sample from years 1988 – 2012, I find that clients are more likely to imitate their industry peers’ prior selections to select the type of their succeeding auditors, consistent with the implications of social learning theory. I also find that clients in industries with stronger industry norms, as measured by a greater proportion of clients audited by Big N auditors in an industry, are more likely to select Big N auditors as their succeeding auditors, consistent with the implications of social norms theory. To my best knowledge, this is the first study to explore the impact of social dynamics measured at the industry level on auditor selection and provide large-sample evidence on the relations between industry dynamics and auditor selection at the firm level. Findings of this study provide insights into the dynamic process of auditor selection in which companies do not make auditor-selection decisions in isolation of one another as often posited in existing literature, contribute to the research on the determinants of auditor choice by incorporating industry dynamics into an agent-principal model, and provide a more comprehensive view of the phenomenon of auditor selection.
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Leadbeater, Ellouise Anderson. "Social information use and social learning in the Bumblebee (Bombus terrestris)." Thesis, Queen Mary, University of London, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.499999.
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The "explosion of interest" in animal social learning which has taken place over the last two decades has rarely touched upon invertebrate models. Yet, often social learning does not reflect complex cognitive processing, but instead derives from simple learning processes which also occur when animals learn asocially, shaped or directed by social behaviour mechanisms. In this thesis, I investigate how information provided inadvertently by conspecifics can influence foraging decisions in an animal with a small brain, and yet highly developed learning abilities, the bumblebee. In the first two chapters, I show that foraging bumblebees, when visiting unfamiliar flower species, prefer to probe those individual inflorescences where others are foraging. By comparing individual learning curves when foraging in the absence or presence of experienced conspecifics, I find that this can lead to faster learning about the relative rewards that different flower species offer. I investigate the proximate mechanistic causes of joining behaviour in Chapter four, showing that social information use is a flexible trait which can be modified by learning. In Chapter five, I explore the influence of social cues in learning about "nectar robbing" - a process by which bees remove nectar from 1 flowers without pollination, by biting through the corolla. Finally, in Chapter six, I extend the context of the thesis to address the whether bees might use social information about danger. Taken together, my findings provide a model of how social learning can arise through a combination of simple social behaviour and individual learning, suggesting that social influences on learning in invertebrates may be more common than the current literature would suggest.
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Smith, Elizabeth R. "Social media and social learning| A critical intersection for journalism education." Thesis, Pepperdine University, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10251916.
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For the past decade, the profession of journalism has been under intense pressure to adapt to changing business models, technology, and forms of communication. Likewise, journalism education has been under intense scrutiny for failing to keep pace with the industry and inadequately preparing students for a rapidly changing professional environment. Social media has become a nexus for the pressures being experienced by both the profession and academia. This study uses Wenger’s (1998) model of Communities of Practice to consider how a student newsroom functions and how student journalists adapt within a newsroom and on social media. This study used a quantitative self-reported survey (N=334) design to understand the relationship of students’ social media use and newsroom participation, social media use and digital skills, and the differences relationships between demographic variables and the use of social media. Items in the survey were in one of four categories: newsroom participation, social media use, digital skills, and demographics. Results demonstrated that as students take on more responsibilities in a newsroom, the more likely they are to have relationships in the newsroom, to have a voice (in both editorial content and newsroom policy), to share their experiences with newer staff members, and to see the importance of social media use in their newsroom experience. Findings also related to meaning, identity, and practice within Wenger’s (1998) notions of Communities of Practice. Significant correlations among items measuring digital skills are related to length of time on staff, use of social media (e.g. watch breaking news and find story ideas), holding a digital position, frequency of use of social media, and critical knowledge of digital skills (including high-level relationships among libel, audience analytics, and multi-media content). Analysis showed that participants who held primarily digital positions demonstrated patterns of the more sophisticated digital skills.
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Houff, J. Keith. "The effects of social learning intervention procedures on occupational social adjustment." Diss., Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/54446.
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There are a great number of people whose suggestions and encouragement have contributed to the preparation and completion of this study. Special recognition is due to the committee of faculty evaluating this study through the various stages from inception. I appreciate the patience plus clear arid precise guidance of Tom Hohenshil, and Dennis Hinkle's counsel and completion of the computer analyses of the results of this study, I am grateful for the inspiration Dean Hummel provided especially during the early stages of this project. I wish also to express my thanks to Cherry Houck who’s door was always open and was also instrumental in the inception of this study, I also appreciate Harriett Cobb's perceptiveness and special efforts in dissipating my committee meeting jitters. Finally, I consider myself fortunate to have had exposure to these individual's expertise and vast experiences.
I wish also to acknowledge the assistance and financial support, I received from Charlotte McNulty, SYEP Project Director, and from the Board of Directors of People Places Inc. in Staunton, Virginia. I am indebted to the patience and trust Ms. McNulty repeatedly afforded me throughout the various stages of carrying out this project. The generous offer of the use of equipment .and office space of People Places Inc. is also greatly appreciated.
And finally, I consider myself fortunate to have a wife supportive of my efforts in achieving an advanced degree in education. Her genuine interest in the topic of this study and willingness to listen, proofread, type, and many other supportive actions deserve a special "thank you".Ed. D.
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Cortese, Juliann. "A social cognitivist view of hypermedia learning." Connect to resource, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1117124538.
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Thesis (Ph.D.)--Ohio State University, 2005.Title from first page of PDF file. Document formatted into pages; contains xv, 201 p.; also includes graphics. Includes bibliographical references (p. 191-201). Available online via OhioLINK's ETD Center
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Hällsten, Martin. "Essays on social reproduction and lifelong learning /." Stockholm : The Swedish Institute for Social Research (SOFI), Stockholm University, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-37315.
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Milán, Pau. "The Social economics of networks and learning." Doctoral thesis, Universitat Pompeu Fabra, 2016. http://hdl.handle.net/10803/393733.
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This thesis explores various economic environments where the structure of social interactions across individuals determines outcomes. In the first chapter, I study mutual insurance arrangements restricted on a social network. I test the network-based sharing rules on data from Bolivian communities, and I argue that this framework provides a reinterpretation of the standard risk sharing results, predicting household heterogeneity in response to income shocks. In the second paper, I study individual and collective behavior in coordination games where information is dispersed through a network. I show how changes in the distribution of connectivities in the population affect the types of coordination in equilibrium as well as the probability of success. In the third chapter, I explore a framework of learning and turnover in the labor market. I show that positive assortative matching (PAM) extends beyond the stable environment of Eeckhout & Weng (2010) to a situation of residual uncertainty that exhibits periods of unlearning. I also extend this setting to allow for career concerns and I show that PAM can only be sustained under strong assumptions.Esta tesis explora diversos entornos económicos en los que la estructura de las interacciones sociales entre los individuos determina los distintos resultados. En el primer capítulo, se estudia acuerdos de seguro mutuo restringidos en una red social. Utilizo datos de comunidades bolivianas para medir las predicciones teóricas y encuentro que los intercambios observados entre los hogares coinciden con la regla de reparto basada en la red obtenida por la teoría. Sostengo que este marco ofrece una reinterpretación de los resultados estándar de distribución de riesgos, prediciendo heterogeneidad entre los hogares en respuesta a los shocks de ingresos. En el segundo artículo, estudio el comportamiento individual y colectivo en juegos de coordinación, donde la información se dispersa a través de una red. Demuestro cómo los cambios en la distribución de las conectividades de la población afectan a los tipos de coordinación en equilibrio, así como la probabilidad de éxito. En el tercer capítulo, analizo un marco de aprendizaje y cambio de personal en el mercado de trabajo. Muestro que emparejamiento selectivo positivo (PAM) se extiende más allá del entorno estable de Eeckhout y Weng (2010) a una situación de incertidumbre residual que exhibe períodos de des-aprendizaje. También extiendo esta configuración para permitir elementos de career concerns y muestro que el equilibrio de PAM sólo puede sostenerse bajo fuertes supuestos.
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Bas, Jesús 1990. "Influence of social hierarchies on infants' learning." Doctoral thesis, Universitat Pompeu Fabra, 2018. http://hdl.handle.net/10803/664967.
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Humans are social animals living in groups and tending to organize themselves hierarchically. This social stratification influences individuals’ social interactions, as well as their cognitive processes such as learning. Because learning is essential during infancy, in this dissertation we aim to explore infants’ representation of social hierarchies and their influence on learning. A first set of studies showed that infants understand and can link from a third-party perspective two types of social hierarchies: those regulating conflicts (dominant-subordinate relationships) and those regulating collective actions (leader-follower relationships). A final study showed that infants are biased to learn from high-rank (dominant) individuals. We propose that infants' learning is influenced by high-rank agents because they are represented as leaders. We discuss the possible reasons behind human tendency to imitate high-rank agents (leaders) and we formulate a proposal of future studies addressing infants' representation of leadership.Los humanos son animales sociales que viven en grupos y que tienden a organizarse jerárquicamente. Esta estratificación social influye en las interacciones entre individuos, así como en sus procesos cognitivos, como por ejemplo el aprendizaje. Debido a que el aprendizaje es esencial durante la infancia, en esta tesis queremos explorar la representación infantil de las jerarquías sociales y su influencia en el aprendizaje. Un primer conjunto de estudios mostró que los bebés entienden y vinculan desde la perspectiva de un tercero dos tipos de jerarquías sociales: las que regulan conflictos (relaciones dominante-subordinado) y las que regulan acciones colectivas (relaciones líder-seguidor). Un último estudio demostró que los bebés están predispuestos a aprender de los individuos de alto rango (dominantes). Proponemos que el aprendizaje de los bebés está influenciado por los agentes de alto rango porque son representados como líderes. Planteamos las posibles razones detrás de la tendencia a imitar a los agentes de alto rango (líderes) y formulamos una propuesta de estudios futuros que aborden la representación infantil del liderazgo.
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McKee, Sherry A. "Social learning determinants of alcohol outcome expectancies." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0008/NQ40275.pdf.
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D'Souza, Lorraine. "Social learning in primates : patterns and processes." Thesis, Goldsmiths College (University of London), 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.429419.
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Larsson, Stephan. "Can Social Learning help facilitate Stormwater Management?" Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-254133.
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This thesis shows the effect social learning has on various stakeholders involved in a project aimed at tackling a stormwater challenge in the city of Uppsala in Sweden and if social learning is a useful tool to address such an issue. Due to the onset of climate change societies are having to deal with increasingly complex issues. Finding sustainable answers to these challenges is proving difficult so alternative methods such innovation competitions much like the one studied in this paper are becoming attractive alternatives to conventional climate change mitigations approaches. By using an active participation method, this thesis attempts to study whether or not social learning is taking place in the innovation competition and if it is having an impact on the innovation competition. The study found that social learning is in fact taking place during the meetings which were attended but whether or not the resulting knowledge created as a result of the social learning was being used to the advantage of the stakeholders was compounded by communication issues outside of the project meetings.
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Bilakhia, Sanjay. "Machine learning for high-level social behaviour." Thesis, Imperial College London, 2016. http://hdl.handle.net/10044/1/59041.
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The ability to recognize and interpret the complex displays of nonverbal behavioral cues that arise in social interaction comes naturally to humans. Indeed, the survival and flourishing of early groups of homo sapiens may have depended on this ability to share implicit social information. It is a process so innate that complex social behaviours can occur without conscious awareness, even in young babies. Though we would benefit from artificial devices having the ability to understand these nonverbal cues, it has proven an elusive goal. In this thesis we are primarily motivated by the problem of recognizing and exploiting displays of high–level social behavior, focusing on behavioural mimicry. Mimicry describes the tendency of individuals to adopt the postures, gestures and expressions of social interaction partners. We first provide a background to the phenomenon of behavioural mimicry, disambiguate it from other related phenomena in social interaction, and survey its surprisingly complex dependencies on the broader social context. We then discuss a number of methods that could be used to recognize mimicry behaviour in naturalistic interaction. We list some publicly available databases these tools could be trained on for the analysis of spontaneous instances of mimicry. We also examine the scarce prior work on recognition of naturalistic mimicry behaviour, and we discuss the challenges in automatically recognizing mimicry in spontaneous data. Subsequently we present a database of naturalistic social interactions, designed for analysis of spontaneous mimicry behaviour. This has been annotated for mimicry episodes, low-level non-verbal behavioural cues, and continuous affect. We also present a new software package for web-based annotation, AstAn, which has been extensively deployed for temporal event segmentation and continuous annotation. Collecting annotation data for high-level social affect is a difficult problem. This is due to inter-annotator variance, dependent on a variety of factors including i) the content of the data to annotate ii) the complexity of the variables to annotate, and iii) the annotators' cultures and personality traits. AstAn is the first software package to enable large-scale collection of annotations relevant to affective computing, without the costly manual distribution and management of (perhaps sensitive) data. Large-scale and cost-effective data collection can significantly help to overcome the aforementioned difficulties. We present experiments showing that prevailing methods for mimicry recognition on posed data, generalize suboptimally to spontaneous data. These include methods based on cross-correlation and dynamic time warping, which are prevalent in current work on recognition of interpersonal co-ordination, including mimicry and synchrony. We also show that popular temporal models such as recurrent neural networks, when applied in a straightforward classification approach, also find it challenging to discriminate between mimicry and non-mimicry. We expand upon these baseline results using methods adapted from work on multimodal classification. Nonlinear regression models are used to learn the relationships between the non-verbal cues from each subject. Namely, for mimicry and non-mimicry classes, we learn a set of neural networks to forecast the behaviour of each subject, given the behaviour of their counterpart. The set of networks that produces the best behavioural forecast corresponds to the predicted class. Subsequently, we investigate whether high-level social affect like mimicry, conflict, valence and arousal are uniquely displayed between individuals. Specifically, we show that for episodes of a given behavioural display such as mimicry or high-conflict, the spatiotemporal movement characteristics are unique enough to construct a "kinematic template" for that behaviour. Given an unseen episode of the same behavioural display, we can compare it against the template in order to verify identity. This is useful in verification contexts where facial appearance and geometry can change due to lighting, facial hair, facial decoration, or weight loss. We present a new method, Multi-Sequence Robust Canonical Time Warping (M-RCTW), in order to construct this subject- and behaviour-specific template. Unlike prior methods, M-RCTW can warp together multiple multivariate sequences in the presence of large non-Gaussian errors, which can occur due to e.g. tracking artefacts in naturalistic behaviour, such as those resulting from occlusions. We show on two databases of natural interaction that identity verification is possible from a number of high- and low-level behaviours, and that M-RCTW outperforms existing methods for multiple sequence warping on the task of subject verification.
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Lobel, Ilan. "Social networks : rational learning and information aggregation." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/54232.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (p. 137-140).
This thesis studies the learning problem of a set of agents connected via a general social network. We address the question of how dispersed information spreads in social networks and whether the information is efficiently aggregated in large societies. The models developed in this thesis allow us to study the learning behavior of rational agents embedded in complex networks. We analyze the perfect Bayesian equilibrium of a dynamic game where each agent sequentially receives a signal about an underlying state of the world, observes the past actions of a stochastically-generated neighborhood of individuals, and chooses one of two possible actions. The stochastic process generating the neighborhoods defines the network topology (social network). We characterize equilibria for arbitrary stochastic and deterministic social networks and characterize the conditions under which there will be asymptotic learning -- that is, the conditions under which, as the social network becomes large, the decisions of the individuals converge (in probability) to the right action. We show that when private beliefs are unbounded (meaning that the implied likelihood ratios are unbounded), there will be asymptotic learning as long as there is some minimal amount of expansion in observations. This result therefore establishes that, with unbounded private beliefs, there will be asymptotic learning in almost all reasonable social networks. Furthermore, we provide bounds on the speed of learning for some common network topologies. We also analyze when learning occurs when the private beliefs are bounded.
(cont.) We show that asymptotic learning does not occur in many classes of network topologies, but, surprisingly, it happens in a family of stochastic networks that has infinitely many agents observing the actions of neighbors that are not sufficiently persuasive. Finally, we characterize equilibria in a generalized environment with heterogeneity of preferences and show that, contrary to a nave intuition, greater diversity (heterogeneity) 3 facilitates asymptotic learning when agents observe the full history of past actions. In contrast, we show that heterogeneity of preferences hinders information aggregation when each agent observes only the action of a single neighbor.
by Ilan Lobel.
Ph.D.
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Buchsbaum, Daphna 1979. "Imitation and social learning for synthetic characters." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/28775.
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Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2004.Includes bibliographical references (p. 137-149).
We want to build animated characters and robots capable of rich social interactions with humans and each other, and who are able to learn by observing those around them. An increasing amount of evidence suggests that, in human infants, the ability to learn by watching others, and in particular, the ability to imitate, could be crucial precursors to the development of appropriate social behavior, and ultimately the ability to reason about the thoughts, intents, beliefs, and desires of others. We have created a number of imitative characters and robots, the latest of which is Max T. Mouse, an anthropomorphic animated mouse character who is able to observe the actions he sees his friend Morris Mouse performing, and compare them to the actions he knows how to perform himself. This matching process allows Max to accurately imitate Morris's gestures and actions, even when provided with limited synthetic visual input. Furthermore, by using his own perception, motor, and action systems as models for the behavioral and perceptual capabilities of others (a process known as Simulation Theory in the cognitive literature), Max can begin to identify simple goals and motivations for Morris's behavior, an important step towards developing characters with a full theory of mind. Finally, Max can learn about unfamiliar objects in his environment, such as food and toys, by observing and correctly interpreting Morris's interactions with these objects, demonstrating his ability to take advantage of socially acquired information.
by Daphna Buchsbaum.
S.M.
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Shi, Lei. "Scaffolding for social personalised adaptive e-learning." Thesis, University of Warwick, 2014. http://wrap.warwick.ac.uk/67201/.
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This work aims to alleviate the weaknesses and pitfalls of the strong modern trend of e-learning by capitalising on and taking advantage of theoretical and implementation advances that have been made in the fields of adaptive hypermedia, social computing, games research and motivation theories. Whilst both demand for and supply of e-learning are growing, especially with the rise of MOOCs, the problems that it faces remain to be addressed, notably isolation, depersonalisation and lack of individual navigation. This often leads to poor learning experience. This work explores an innovative method of combining, threading and balancing the amount of adaptation, social interaction, gamification and open learner modelling for e-learning techniques and technologies. As a starting point, a novel combination of classical adaptation based on user modelling, fine-grained social interaction features and a Facebook-like appearance is explored. This has been shown to be able to ensure a high level of effectiveness, efficiency and satisfaction amongst learners when using the e-learning system. Contextual gamification strategies rooted in Self-Determination Theory (SDT) are then proposed, which have been shown to be able to ensure learners of the system adopt desirable learning behaviours and achieve pre-specified learning goals, thus providing a high level of motivation. Finally, a multifaceted open social learner modelling is proposed. This allows visualising both learners’ performance and their contributions to a learning community, provides various modes of comparison, and is integrated and adapted to learning content. Evidence has shown that this can provide a high level of effectiveness, efficiency and satisfaction amongst learners. Two innovative social personalised adaptive e-learning systems including Topolor and Topolor 2 are devised to enable the proposed approach to be tested in the real world. They have been used as online learning environments for undergraduate and postgraduate students in Western and Eastern Europe as well as Middle Eastern universities, including the University of Warwick, UK, Jordan University, Jordan, and Sarajevo School of Science and Technology, Bosnia and Herzegovina. Students’ feedback has shown this approach to be very promising, suggesting further implementation of the systems and follow-up research. The worldwide use of Topolor has also promoted international collaborations.