Social Learners Research Articles

Symmetric conformity functions make decision-making processes independent of the distribution of learning strategies

Two main procedures characterize the way in which social actors evaluate the qualities of the options in decision-making processes: they either seek to evaluate their intrinsic qualities (individual learners), or they rely on the opinion of the others (social learners). For the latter, social experiments have suggested that the mathematical form of the probability of adopting an option, called the , is symmetric in the adoption rate. However, the literature on decision-making includes models where social learners employ either symmetric or nonsymmetric conformity functions. We generalize a particular case studied in a previous work, and we show analytically that if the conformity function is symmetric, the details of the probability distribution of the propensity of the agents to behave as a social or an individual learner do not matter, only its expected value influences the determination of the steady state. We also show that in this case, the same steady state is reached for two extreme dynamical processes: one that considers propensities as idiosyncratic properties of the agents (each agent being an individual learner always with the same probability), and the opposite one, which allows them to change their propensity during the dynamics. This is not the case if the conformity function is nonsymmetric. This fact can inspire experiments that could shed light on the debate about mathematical properties of conformity functions. Published by the American Physical Society 2024

Learning styles, approaches and academic performance of second and third-year medical students of a medical college of Kathmandu: a descriptive cross-sectional study.

The research is based on a questionnaire to study the different learning styles among medical students, and their approach to intellectual development. This is an observational, cross-sectional study conducted on 140 participants. Initially after the informed consent process, the second-year and third-year medical students were requested to respond to the questionnaire without consulting friends. Data were analyzed descriptively and comparison was made. In this study, the students were mostly visual learners, followed by solo learners, audio learners, verbal learners, and social learners. The majority of the students in our study (84.56%) studied less than 4 h per day beyond normal lecture hours. Similarly, 45.71% of students studied continuously for 30-60 min. During break, 63.57% of students used social media, watched television, and videos, and listened to music. Most students (75%) preferred to study in a hostel room and only 12.85% used the library as their study place. The majority of the students (65.71%) of students slept between six to eight hours. The University's suggested medical textbooks and reference materials were consulted by 94.3% of the students. The 47.85% of students favored self-directed learning with 56.42% preferring to read and write to retain the learned materials. Self-prepared notes were commonly used by the majority of students (60.7%). This research evaluates the preferred learning preferences of medical students and their relationship to academic performance, which will improve the effectiveness of teaching and learning between teachers and medical students.

Facilitating social learning through learning design

In the field of technology-enhanced learning design, the rise of Web 2.0 has been the filip needed to accelerate the emergence of socially-connected global learners. These highly social learners now use the web to engage with knowledge and skill development and as such, online education has moved irrevocably beyond simply the finding and sharing of information among learners. The higher education sector is responding to this learning landscape. This is particularly relevant to the massive open online courses (MOOCs) environment where there is the potential for thousands of participants to learn through multiple open source tools with minimum intervention from educators. This social learning perspective can present a challenge for some educators. In this paper we present a work-in-progress collaborative project designed to respond to the professional development of teaching academics newly engaged in designing and teaching from a social learning perspective. We, in a central learning and teaching unit, designed and developed a professional development (PD) course that sought to build the capacity of academics going through this change: they were about to teach on a MOOC platform. Our purpose was to model the social learning framework as a method of capacity-building, but we also aimed to distil authentic social learning for the academics themselves. This resulted in creating a community of practice among educators. Further research is required to measure the impact of this capacity-building course in order to further enhance the learning experiences of academics preparing to teach on a MOOC platform.

Social demonstration of colour preference improves the learning of associated demonstrated actions.

We studied how different types of social demonstration improve house sparrows' (Passer domesticus) success in solving a foraging task that requires both operant learning (opening covers) and discrimination learning (preferring covers of the rewarding colour). We provided learners with either paired demonstration (of both cover opening and colour preference), action-only demonstration (of opening white covers only), or no demonstration (a companion bird eating without covers). We found that sparrows failed to learn the two tasks with no demonstration, and learned them best with a paired demonstration. Interestingly, the action of cover opening was learned faster with paired rather than action-only demonstration despite being equally demonstrated in both. We also found that only with paired demonstration, the speed of operant (action) learning was related to the demonstrator's level of activity. Colour preference (i.e. discrimination learning) was eventually acquired by all sparrows that learned to open covers, even without social demonstration of colour preference. Thus, adding a demonstration of colour preference was actually more important for operant learning, possibly as a result of increasing the similarity between the demonstrated and the learned tasks, thereby increasing the learner's attention to the actions of the demonstrator. Giving more attention to individuals in similar settings may be an adaptive strategy directing social learners to focus on ecologically relevant behaviours and on tasks that are likely to be learned successfully.

Counseling Group With self-management techniques for Lower Prejudice Social Learners

Service Counseling Group with self-management techniques for Lower Prejudice Social Students at SMAN 2 Palangka Raya. The aim of this study For know service counseling group with deep self-management techniques lower participants ' social prejudices educate. Type of research used is quantitative with Pre- Experiment technique dangn form of One-Group Pretest-Posttest Design. Population in this research is participant educate class X MIPA-7 at SMAN2 Palangka Raya, totaling 40 people, with sample of 9 participants identified students own level high social prejudice. Data is analyzed with the T Test Using SPSS software application version 20.00. technique Data collection uses observation and scale prejudice social. Based on Pre-test results before providing subject treatment get mark average scores were 86-114 in in category high, and after giving treatment based on Subject average Post-test results get mark score 57-85 and in in category currently. On observation beginning before giving treatment mark score 9-13 in in category low and after providing treatment during observation end of subject average get mark score 4-8 in in category low. Research result showing ninth participant students who are given treatment experience decline behavior prejudice social after providing known treatment from results Pretest-Posttest comparison

Modelling the emergence of social-bird biological controls to mitigate invasions of the spotted lanternfly and similar invasive pests.

The spotted lanternfly is an emerging global invasive insect pest. Due to a lack of natural enemies where it is invasive, human intervention is required. Extensive management has been applied but the spread continues. Recently, the idea of bird-based biological controls has re-emerged and shown effective in studies. However, it is questionable, if birds are able to effectively control unfamiliar and occasionally toxic invasive pests in short timeframes. Unless, perhaps, the birds are effective social learners and toxicity of the invaders is rare. Here, we introduce a mathematical model for social learning in a great tit-like bird to investigate conditions for the emergence of a collective biological control of a pest that is occasionally toxic, like the lanternfly. We find that the social observation rate relative to the proportion of toxic lanternfly dictate when collective biological controls will emerge. We also implement the social learning model into a model of collective motion in bird-like animals, and find that it produces results consistent with the mathematical model. Our work suggests that social birds may be useful in managing the spotted lanternfly, and that removing the toxicity-inducing preferred host of the lanternfly should be a priority to facilitate this.

As strong as the weakest node: The impact of misinformation in social networks

We study the impact of misinformation in a model of boundedly rational opinion formation in a social network. We capture misinformation via misspecified prior beliefs and consider networks that contain agents with differing social learning sophistication: identity social learners and quasi-Bayesian social learners. An attractive feature of the underlying heuristics is that in the baseline case absent misinformation both coincide with DeGroot updating, the arguably canonical boundedly rational heuristic. We find that the impact of misinformation depends upon the sophistication of the agents exposed to misinformation. If at least one misinformed agent engages in the simpler heuristic, identity social learning, then the long run opinions of all agents are extremely fragile to misinformation. Even if the perceived precision of the misinformation is infinitesimally small, the opinions of all agents in the network, identity and quasi-Bayesian social learners alike, converge to the misinformation state. Instead, if only the more sophisticated quasi-Bayesian social learners are exposed to misinformation, then the opinion process is robust to infinitessimal misinformation. Finally, we consider a general class of updating functions and show that there is a type of infinitessimal perturbation to the updating function of any agent such that the asymptotic consensus opinion is extremely fragile.

Naïve information aggregation in human social learning

To glean accurate information from social networks, people should distinguish evidence from hearsay. For example, when testimony depends on others’ beliefs as much as on first-hand information, there is a danger of evidence becoming inflated or ignored as it passes from person to person. We compare human inferences with an idealized rational account that anticipates and adjusts for these dependencies by evaluating peers’ communications with respect to the underlying communication pathways. We report on three multi-player experiments examining the dynamics of both mixed human–artificial and all-human social networks. Our analyses suggest that most human inferences are best described by a naïve learning account that is insensitive to known or inferred dependencies between network peers. Consequently, we find that simulated social learners that assume their peers behave rationally make systematic judgment errors when reasoning on the basis of actual human communications. We suggest human groups learn collectively through naïve signaling and aggregation that is computationally efficient and surprisingly robust. Overall, our results challenge the idea that everyday social inference is well captured by idealized rational accounts and provide insight into the conditions under which collective wisdom can emerge from social interactions.

Does fishing dismantle fish culture and ecosystem structure? Questions about the implications of social learning among fish and fishers

AbstractScientific awareness of social learning, especially among vertebrates, has expanded rapidly in recent decades. That literature suggests that social learning may be a second adaptive mechanism that interacts with and refines genetic adaptation. For an individual fish, learning from others reduces the costs of acquiring experience‐based behaviours and minimizes the hazards that arise from imperfect knowledge of local regularities. For a group of fish, social learning facilitates the evolution of time and place behaviours that work in its locality. It spreads those behaviours within the group and to subsequent generations. Thus, social learning enables persistent adaptation at a finer scale than might be possible through genetic processes alone. Strong evidence of genetic differentiation at less than a panmictic scale and persistent local depletions suggests regular, fine‐scale system structure. Social learning may play an important role in creating and maintaining this finer‐scale structure. Fishers' learned adaptations to the market and natural system usually lead them to target larger/older fish and fish aggregations at familiar times and places. However, older fish are likely to be the principal repository of the time‐and‐place experience required for local growth, survival, and reproduction, while social aggregations are important schools in which younger fish acquire the experience of older fish. Consequently, if adaptation through social learning is important among fish, there is reason to be concerned that heavy fishing of social learners reduces their abundance, as usually assumed, and impairs the inheritance of the socially learned experience required for persistent local adaptation.

Cultural evolution with uncertain provision of learning resources.

An essential feature of human progress is the use of different modes of learning so agents acquire the appropriate behaviour to survive in a changing environment. Learning may result from agents who discover new knowledge on their own (individual learning), or imitate the behaviour of others (social learning). Social learning is less costly than discovery, but imitation might yield no benefit. Early theoretical models of a population consisting of purely individual and purely social learners found that both types are present in an evolutionary equilibrium. However, the presence of social learners did not provide any improvement to the average population fitness. Subsequent research showed that the presence of social learners could improve the average population fitness, provided that the pure characterisation of the agents' learning is relaxed. We return to the pure conceptualisation of agents to challenge an assumption in the early work: agents were guaranteed enough resources to perform their desired learning. We show that, if the resources an agent receives are uncertain, this turns social learning into a source of fitness improvement at the population level. Perhaps counter-intuitively, uncertain provision of resources prompts an increase in the proportion of the population that pursues the costlier individual learning activity in equilibrium.

Exploring Iraqi Kurd EFL Students’ Learning Styles at University Level

Learning styles have gained the attention of educators specially curriculum designers due to its relation with how learners transfer information into knowledge. The present study tries to explore the learning styles of Kurd students at university level. In an attempt to find answers to the following research questions : "What are the common learning styles of Iraqi Kurd EFL learners?" and "Do Iraqi Kurd learners are able to define their styles of learning?". The study hypothesizes that English department students are visual, auditory, reading/writing and kinesthetic (hereafter VARK). It is also hypothesized that they are not able to regulate their learning styles. The results of the study have been collected by applying a questionnaire given to the sample. Furthermore, the results showed that most Iraqi Kurd EFL learners are visual and social learners that they agree with the items that are related to the above mentioned styles.

Social Thinking Metacognitive Strategies to Support Self-Determined Social Goals in Autistic Youth.

On any given day, the social mind is taxed with attending to and making sense of a myriad of social events. The social mind is at work when trying to imagine the experiences of others and their inner mental worlds, and is equally active when people seek to approach, connect with, and sometimes avoid one another. Ultimately, the social mind is responsible for thinking about (social) thinking, or social metacognition. Social metacognitive teaching strategies can be helpful for supporting social learners as they observe social landscapes, interpret what is observed to problem solve, or decide whether and how to produce social responses. This article describes how social metacognitive strategies from the Social Thinking Methodology have been used to support the self-determined social goals of two autistic students. Visual frameworks and their underlying theories are provided as evidence-aligned tools for supporting clinical journeys.

Success-biased social learning in a one-consumer, two-resource model

Previous analyses have predicted that social learning should not evolve in a predator–prey system. Here we examine whether success-biased social learning, by which social learners copy successful demonstrators, allows social learning by foragers to evolve. We construct a one-predator, two-prey system in which foragers must learn how to feed on depletable prey populations in an environment where foraging information can be difficult to obtain individually. We analyze two models in which social learning is success-biased: in the first, individual learning does not depend on the resource dynamics, and in the second model it depends on the relative frequency of the resource. Unlike previous results, we find that social learning does not cause predators to over-harvest one type of prey over the other. Furthermore, increasing the probability of social learning increases the probability of learning a successful foraging behavior, especially when individually learned information tends to be inaccurate. Whereas social learning does not evolve among individual learners in the first model, the assumption of resource-dependent learning in the second model allows a mutant with an increased probability of social learning to spread through the forager population.

Social cognitive career theory and rural high school learners’ intentions to pursue an accounting career

ABSTRACT The extended social cognitive career theory (SCCT) suggests that career intentions are influenced by person inputs, background contextual affordances, learning experiences, self-efficacy expectations and outcome expectations, as well as satisfaction and well-being in academic and work settings. The main purpose of the current study was to examine the career intentions of South African high school learners towards a career in the accounting field. Using proportionate stratified random sampling, 305 learners from eight high schools in a rural community were surveyed. Respondents’ intentions to pursue a career in accounting were significantly positively correlated with self-efficacy expectations and outcome expectations. Work satisfaction, earning potential, self-efficacy expectations, personal interest, Accounting being offered as a subject and having a family member in the accounting field are factors influencing participants’ career choice. Recommendations are made that could assist in better-informed career decision-making, guidance and support for learners who wish to pursue a career in the accounting field.

Hybrid social learning in human-algorithm cultural transmission.

Humans are impressive social learners. Researchers of cultural evolution have studied the many biases shaping cultural transmission by selecting who we copy from and what we copy. One hypothesis is that with the advent of superhuman algorithms a hybrid type of cultural transmission, namely from algorithms to humans, may have long-lasting effects on human culture. We suggest that algorithms might show (either by learning or by design) different behaviours, biases and problem-solving abilities than their human counterparts. In turn, algorithmic-human hybrid problem solving could foster better decisions in environments where diversity in problem-solving strategies is beneficial. This study asks whether algorithms with complementary biases to humans can boost performance in a carefully controlled planning task, and whether humans further transmit algorithmic behaviours to other humans. We conducted a large behavioural study and an agent-based simulation to test the performance of transmission chains with human and algorithmic players. We show that the algorithm boosts the performance of immediately following participants but this gain is quickly lost for participants further down the chain. Our findings suggest that algorithms can improve performance, but human bias may hinder algorithmic solutions from being preserved.This article is part of the theme issue ‘Emergent phenomena in complex physical and socio-technical systems: from cells to societies’.

Lifelong and multirelational community detection to support social and collaborative e‐learning

AbstractLearners' community choice has a crucial role in e‐learning effectiveness. Indeed, individual and structural factors (i.e., learners pre‐existing profiles and networks of interactions) significantly affect how learners develop a collaborative e‐learning environment. In this context, social network analysis, singularly community detection has been a good approach to improve collaborative environment through discovering pertinent learners' communities and new effective relations. However, with social media emergence, many real‐world networks, such as learners' networks, evolve the connections in multiple layers, where each layer represents a different type of relationship. This, combined with their continuous evolution over time, has brought new challenges to the field of community detection. Thus, this paper proposes a new configurable algorithm for detecting collaborative and lifelong communities within dynamic multirelational social learners' networks. To do so, this algorithm is based on a graph model to represent these different interactions as well as different learners' profiles and characteristics. Moreover, by using particle swarm optimization, it aims to optimize a configurable combined metric to detect the most relevant community appropriate to a given situation. Finally, it considers the temporal dimension to find the final lifelong community. By the end of this paper, experimental results using synthetic networks prove that the proposed algorithm achieves better results compared with other community detection algorithms. Therewith, experiments on a real e‐learning network show this algorithm's role in improving collaboration within learners' network.

What is the extent of a frequency-dependent social learning strategy space?

Models of frequency-dependent social learning posit that individuals respond to the commonality of behaviours without additional variables modifying this. Such strategies bring important trade-offs, e.g. conformity is beneficial when observing people facing the same task but harmful when observing those facing a different task. Instead of rigidly responding to frequencies, however, social learners might modulate their response given additional information. To see, we ran an incentivised experiment where participants played either a game against nature or a coordination game. There were three types of information: (a) choice frequencies in a group of demonstrators; (b) an indication of whether these demonstrators learned in a similar or different environment; and (c) an indication about the reliability of this similarity information. Similarity information was either reliably correct, uninformative or reliably incorrect, where reliably correct and reliably incorrect treatments provided participants with equivalent earning opportunities. Participants adjusted their decision-making to all three types of information. Adjustments, however, were asymmetric, with participants doing especially well when conforming to demonstrators who were reliably similar to them. The overall response, however, was more fluid and complex than this one case. This flexibility should attenuate the trade-offs commonly assumed to shape the evolution of frequency-dependent social learning strategies.

Learning Manipulation Through Information Dissemination

Much of the past learning and control literature has focused on the design of information acquisition processes for the demand side of information and has assumed that information supply is always genuine. However, in many economic and management settings, the information provider has incentives to strategically disseminate his/her private information, even in a possibly biased way. For example, a company may advertise deceptively to sell its products. In the paper “Learning Manipulation Through Information Dissemination,” Keppo, Kim, and Zhang take the perspective of an information provider and study the optimal manipulation of a learning process through the adaptive design of (mis)information. The authors explicitly characterize both the optimal manipulation policy and the learner’s belief process under such manipulation. They also extend their analysis to social learners who rely on public reviews to resist manipulation and show that social learning indeed mitigates misinformation in the long run.

The potential for effective reasoning guides children\u2019s preference for small group discussion over crowdsourcing

Communication between social learners can make a group collectively “wiser” than any individual, but conformist tendencies can also distort collective judgment. We asked whether intuitions about when communication is likely to improve or distort collective judgment could allow social learners to take advantage of the benefits of communication while minimizing the risks. In three experiments (n = 360), 7- to 10-year old children and adults decided whether to refer a question to a small group for discussion or “crowdsource” independent judgments from individual advisors. For problems affording the kind of ‘demonstrative’ reasoning that allows a group member to reliably correct errors made by even a majority, all ages preferred to consult the discussion group, even compared to a crowd ten times as large—consistent with past research suggesting that discussion groups regularly outperform even their best members for reasoning problems. In contrast, we observed a consistent developmental shift towards crowdsourcing independent judgments when reasoning by itself was insufficient to conclusively answer a question. Results suggest sophisticated intuitions about the nature of social influence and collective intelligence may guide our social learning strategies from early in development.

Can bifocal stance theory explain children's selectivity in active information transmission?

To shed light on the key premise of the bifocal stance theory (BST) that social learners flexibly take instrumental and ritual stances, we focus on developmental origins of child-led information transmission, or teaching, as a core social learning strategy. We highlight children's emerging selectivity in information transmission influenced by epistemic and social factors and call for systematic investigation of proposed stance-taking.