Hasil untuk "Psychology"

Yiling Wu

Different types of reasoning impose different structural demands on representational systems, yet no systematic account of these demands exists across psychology, AI, and philosophy of mind. I propose a framework identifying four structural properties of representational systems: operability, consistency, structural preservation, and compositionality. These properties are demanded to different degrees by different forms of reasoning, from induction through analogy and causal inference to deduction and formal logic. Each property excludes a distinct class of reasoning failure. The analysis reveals a principal structural boundary: reasoning types below it can operate on associative, probabilistic representations, while those above it require all four properties to be fully satisfied. Scaling statistical learning without structural reorganization is insufficient to cross this boundary, because the structural guarantees required by deductive reasoning cannot be approximated through probabilistic means. Converging evidence from AI evaluation, developmental psychology, and cognitive neuroscience supports the framework at different levels of directness. Three testable predictions are derived, including compounding degradation, selective vulnerability to targeted structural disruption, and irreducibility under scaling. The framework is a necessary-condition account, agnostic about representational format, that aims to reorganize existing debates rather than close them.

Wei Xia, Yu Qing, Yuchen Fan

Abstract: Objective: The innovative behavior of university teachers is crucial for enhancing the overall education and teaching level of universities. This study aims to explore the influencing factors and potential mechanisms of university teachers’ innovative behavior. Methods: The Psychological Empowerment Scale, Innovative Behavior Scale, Organizational Identity Scale, and Knowledge Sharing Scale were administered to 661 Chinese college teachers. SPSS 25.0 was used for analysis, and the Bootstrap method was used to test the significance level of the mediating effect. Results: It is stated that the relationship between psychological empowerment and innovative behavior is influenced by the mediating effects of organizational identity and knowledge sharing, as well as the bidirectional chain mediation effect between organizational identity and knowledge sharing. Conclusion: This finding provides a reference for policymakers and educators in formulating intervention measures targeting the innovative behavior of university teachers.

Mengdi Jia, Zekun Qi, Shaochen Zhang et al.

Spatial reasoning is a key aspect of cognitive psychology and remains a bottleneck for current vision-language models (VLMs). While extensive research has aimed to evaluate or improve VLMs' understanding of basic spatial relations, such as distinguishing left from right, near from far, and object counting, these tasks cover only the most elementary layer of spatial reasoning and are largely approaching saturation in the latest reasoning models. In this work, we introduce OmniSpatial, a comprehensive and challenging benchmark for spatial reasoning, grounded in cognitive psychology. OmniSpatial covers four major categories: dynamic reasoning, complex spatial logic, spatial interaction, and perspective-taking, with 50 fine-grained subcategories. Through careful manual annotation, we construct over 8.4K question-answer pairs. Extensive experiments show that both open- and closed-source VLMs exhibit significant limitations in comprehensive spatial reasoning. We also explore two strategies-PointGraph (explicit scene graph cues) and SpatialCoT (novel-view chain-of-thought)-to bolster spatial reasoning.

Dimity Stephen

This study investigates the viability of distinguishing articles in questionable journals (QJs) from those in non-QJs on the basis of quantitative indicators typically associated with quality. Subsequently, I examine what can be deduced about the quality of articles in QJs based on the differences observed. I contrast the length of abstracts and full-texts, prevalence of spelling errors, text readability, number of references and citations, the size and internationality of the author team, the documentation of ethics and informed consent statements, and the presence erroneous decisions based on statistical errors in 1,714 articles from 31 QJs, 1,691 articles from 16 journals indexed in Web of Science (WoS), and 1,900 articles from 45 mid-tier journals, all in the field of psychology. The results suggest that QJ articles do diverge from the disciplinary standards set by peer-reviewed journals in psychology on quantitative indicators of quality that tend to reflect the effect of peer review and editorial processes. However, mid-tier and WoS journals are also affected by potential quality concerns, such as under-reporting of ethics and informed consent processes and the presence of errors in interpreting statistics. Further research is required to develop a comprehensive understanding of the quality of articles in QJs.

Michael S. Harré, Catherine Drysdale, Jaime Ruiz-Serra

Collective intelligence plays a central role in many fields, from economics and evolutionary theory to neural networks and eusocial insects, and is also core to work on emergence and self-organisation in complex-systems theory. However, in human collective intelligence there is still much to understand about how specific psychological processes at the individual level give rise to self-organised structures at the social level. Psychological factors have so far played a minor role in collective-intelligence studies because the principles are often general and applicable to agents without sophisticated psychologies. We emphasise, with examples from other complex adaptive systems, the broad applicability of collective-intelligence principles, while noting that mechanisms and time scales differ markedly between cases. We review evidence that flexible collective intelligence in human social settings is improved by a particular cognitive tool: our Theory of Mind. We then hypothesise that AIs equipped with a theory of mind will enhance collective intelligence in ways similar to human contributions. To make this case, we step back from the algorithmic basis of AI psychology and consider the large-scale impact AI can have as agential actors in a 'social ecology' rather than as mere technological tools. We identify several key characteristics of psychologically mediated collective intelligence and show that the development of a Theory of Mind is crucial in distinguishing human social collective intelligence from more general forms. Finally, we illustrate how individuals, human or otherwise, integrate within a collective not by being genetically or algorithmically programmed, but by growing and adapting into the socio-cognitive niche they occupy. AI can likewise inhabit one or multiple such niches, facilitated by a Theory of Mind.

Mengqi Chen, Bin Guo, Hao Wang et al.

Persuasion, as one of the crucial abilities in human communication, has garnered extensive attention from researchers within the field of intelligent dialogue systems. We humans tend to persuade others to change their viewpoints, attitudes or behaviors through conversations in various scenarios (e.g., persuasion for social good, arguing in online platforms). Developing dialogue agents that can persuade others to accept certain standpoints is essential to achieving truly intelligent and anthropomorphic dialogue system. Benefiting from the substantial progress of Large Language Models (LLMs), dialogue agents have acquired an exceptional capability in context understanding and response generation. However, as a typical and complicated cognitive psychological system, persuasive dialogue agents also require knowledge from the domain of cognitive psychology to attain a level of human-like persuasion. Consequently, the cognitive strategy-enhanced persuasive dialogue agent (defined as CogAgent), which incorporates cognitive strategies to achieve persuasive targets through conversation, has become a predominant research paradigm. To depict the research trends of CogAgent, in this paper, we first present several fundamental cognitive psychology theories and give the formalized definition of three typical cognitive strategies, including the persuasion strategy, the topic path planning strategy, and the argument structure prediction strategy. Then we propose a new system architecture by incorporating the formalized definition to lay the foundation of CogAgent. Representative works are detailed and investigated according to the combined cognitive strategy, followed by the summary of authoritative benchmarks and evaluation metrics. Finally, we summarize our insights on open issues and future directions of CogAgent for upcoming researchers.

Yongxin Deng, Xihe Qiu, Xiaoyu Tan et al.

Cognitive psychology investigates perception, attention, memory, language, problem-solving, decision-making, and reasoning. Kahneman's dual-system theory elucidates the human decision-making process, distinguishing between the rapid, intuitive System 1 and the deliberative, rational System 2. Recent advancements have positioned large language Models (LLMs) as formidable tools nearing human-level proficiency in various cognitive tasks. Nonetheless, the presence of a dual-system framework analogous to human cognition in LLMs remains unexplored. This study introduces the \textbf{CogniDual Framework for LLMs} (CFLLMs), designed to assess whether LLMs can, through self-training, evolve from deliberate deduction to intuitive responses, thereby emulating the human process of acquiring and mastering new information. Our findings reveal the cognitive mechanisms behind LLMs' response generation, enhancing our understanding of their capabilities in cognitive psychology. Practically, self-trained models can provide faster responses to certain queries, reducing computational demands during inference.

Francisco Zanartu, John Cook, Markus Wagner et al.

Misinformation about climate change is a complex societal issue requiring holistic, interdisciplinary solutions at the intersection between technology and psychology. One proposed solution is a "technocognitive" approach, involving the synthesis of psychological and computer science research. Psychological research has identified that interventions in response to misinformation require both fact-based (e.g., factual explanations) and technique-based (e.g., explanations of misleading techniques) content. However, little progress has been made on documenting and detecting fallacies in climate misinformation. In this study, we apply a previously developed critical thinking methodology for deconstructing climate misinformation, in order to develop a dataset mapping different types of climate misinformation to reasoning fallacies. This dataset is used to train a model to detect fallacies in climate misinformation. Our study shows F1 scores that are 2.5 to 3.5 better than previous works. The fallacies that are easiest to detect include fake experts and anecdotal arguments, while fallacies that require background knowledge, such as oversimplification, misrepresentation, and slothful induction, are relatively more difficult to detect. This research lays the groundwork for development of solutions where automatically detected climate misinformation can be countered with generative technique-based corrections.

Lakshika Vaishnav, Sakshi Singh, Kimberly A. Cornell

This paper investigates the impacts of the rapidly evolving landscape of generative Artificial Intelligence (AI) development. Emphasis is given to how organizations grapple with a critical imperative: reevaluating their policies regarding AI usage in the workplace. As AI technologies advance, ethical considerations, transparency, data privacy, and their impact on human labor intersect with the drive for innovation and efficiency. Our research explores publicly accessible large language models (LLMs) that often operate on the periphery, away from mainstream scrutiny. These lesser-known models have received limited scholarly analysis and may lack comprehensive restrictions and safeguards. Specifically, we examine Gab AI, a platform that centers around unrestricted communication and privacy, allowing users to interact freely without censorship. Generative AI chatbots are increasingly prevalent, but cybersecurity risks have also escalated. Organizations must carefully navigate this evolving landscape by implementing transparent AI usage policies. Frequent training and policy updates are essential to adapt to emerging threats. Insider threats, whether malicious or unwitting, continue to pose one of the most significant cybersecurity challenges in the workplace. Our research is on the lesser-known publicly accessible LLMs and their implications for workplace policies. We contribute to the ongoing discourse on AI ethics, transparency, and security by emphasizing the need for well-thought-out guidelines and vigilance in policy maintenance.

Borzoo Amirpour, Fatemeh Takallou, Danesh Valadbeigi

Background: Victimization in schools has become one of the most prevalent problems in the worldwide education system. This study explored the dimensions of victimization in sixth-grade male students in Kermanshah City, Iran and its association with subjective well-being in school and school bonding.Methods: The current study was conducted using a descriptive correlational design. The statistical population included all male students in the sixth grade in Kermanshah City, Iran in the academic year 2022-2023. A sample of 374 individuals was selected using the multi-stage cluster random sampling method. To collect information, the Multidimensional Victimization Scale (MPVS), School Bonding Questionnaire (SBQ), and Elementary School Students’ Subjective Well-Being (ESSSWBSS) were administered. Pearson’s correlation coefficient and multiple regression were performed using SPSS version 27 to analyze the data.Results: Pearson correlation analysis revealed a significant inverse association between victimization at school and its dimensions with subjective well-being in school (r=-0.37) and school bonding (r=-0.010). Furthermore, the results of multiple regression showed that school bonding (β=-0.15, P=0.009) and subjective well-being in school (β=-0.33, P=0.031) were significant negative explanatory variables of victimization at school.Conclusions: Risky behaviors such as feeling victimized can hinder students’ educational achievements. Therefore, it is recommended that school counselors identify students who feel victimized by their peers and provide them with appropriate educational interventions and workshops to enhance their subjective well-being in school and school bonding.

Ana Nieto-Carracedo, Consuelo Gómez-Iñiguez, Leticia A. Tamayo et al.

Emotional intelligence has been associated with academic achievement, which entails that improving emotional intelligence could lead to better academic achievement. However, the mechanisms of this relationship are not well known. This paper focuses on assessing relevant factors associated with academic achievement (emotional well-being, motivation, and learning strategies) as potential mediators of this link. A cross-sectional study with a sample of 96 high school students was conducted. They were assessed using the Mayer-Salovey-Caruso Emotional Intelligence Test, the Psychological Well-being Questionnaire, the Learning Strategies and Motivation Questionnaire, and their final grades. Results of a serial mediation analysis revealed that emotional intelligence is not directly associated with academic achievement but through mediating factors. Serial indirect effects show that emotionally intelligent students have higher levels of emotional well-being, which predicts better learning strategies and is, in turn, associated with academic achievement. Emotional intelligence also predicts greater motivation and better learning strategies (without the mediation of emotional well-being), which is ultimately also associated with academic achievement. Theoretical and instructional implications are discussed.

Elham Khalili-Basseri, Homeira Soleimannejad, Maryam Safara et al.

سابقه و هدف: ویژگی‌های عاطفی، شناختی و رفتاری نقش اساسی در کیفیت زندگی پرستاران دارد؛ بنابراین مطالعۀ حاضر با هدف بررسی نقش سلامت معنوی و سبک‌های مقابله‌ای در پیش‌بینی کیفیت زندگی پرستاران انجام شده است. روش کار: روش پژوهش حاضر توصیفی - همبستگی است. جامعۀ پژوهش تمامی پرستاران زن متأهل شاغل در مراکز درمانی دولتی و خصوصی شهر تهران در شش‌ماهۀ دوم سال 1401 بودند که 409 نفر به‌روش نمونه‌گیری دردسترس و از طریق شبکه‌های اجتماعی وارد مطالعه شدند. ابراز گردآوری اطلاعات پرسش‌نامه‌های سلامت معنوی پالوتزین و الیسون، سبک‌های مقابلۀ کالزبیک و همکاران و کیفیت زندگی سازمان بهداشت جهانی بود. تحلیل داده‌ها با استفاده از آزمون همبستگی پیرسون و رگرسیون چندگانه به‌شیوۀ هم‌زمان و با نرم‌افزار SPSS نسخۀ 24 انجام شد. در این پژوهش همۀ موارد اخلاقی رعایت شده است و مؤلفان مقاله تضاد منافعی گزارش نکرده‌اند. یافته‌ها: نتایج نشان داد همبستگی بین سلامت معنوی و راهبرد مسئله‌مدار با کیفیت زندگی پرستاران مثبت؛ اما همبستگی بین راهبرد اجتنابی و راهبرد هیجان‌مدار با کیفیت زندگی پرستاران منفی بود (۰۱/0>P). همچنین مؤلفه‌های سلامت معنوی ۹/۱۳% و سبک‌های مقابله‌ای 1/25% از واريانس کیفیت زندگی را تبيين ­کردند. نتیجه‌گیری: یافته‌های پژوهش اهمیت سبک‌های مقابله‌ای را که یکی از سازه‌های مهم فردی است و سلامت معنوی که یکی از سازه‌های مهم معنوی در بهبود کیفیت زندگی پرستاران است، نشان می‌‌دهد.

Luca M. Schulze Buschoff, Elif Akata, Matthias Bethge et al.

A chief goal of artificial intelligence is to build machines that think like people. Yet it has been argued that deep neural network architectures fail to accomplish this. Researchers have asserted these models' limitations in the domains of causal reasoning, intuitive physics, and intuitive psychology. Yet recent advancements, namely the rise of large language models, particularly those designed for visual processing, have rekindled interest in the potential to emulate human-like cognitive abilities. This paper evaluates the current state of vision-based large language models in the domains of intuitive physics, causal reasoning, and intuitive psychology. Through a series of controlled experiments, we investigate the extent to which these modern models grasp complex physical interactions, causal relationships, and intuitive understanding of others' preferences. Our findings reveal that, while some of these models demonstrate a notable proficiency in processing and interpreting visual data, they still fall short of human capabilities in these areas. Our results emphasize the need for integrating more robust mechanisms for understanding causality, physical dynamics, and social cognition into modern-day, vision-based language models, and point out the importance of cognitively-inspired benchmarks.

Igor Stamenović

Рад анализира садржај буле папе Николе V (1447–1455) упућене 24. октобра 1453. године српском деспоту Ђурђу Бранковићу (1427–1456). Текст буле стављен је у шири контекст антиосманске крсташке политике папства и његових савезника након османског заузимања Константинопоља 1453. године. Крсташки планови који су тада разматрани укључивали су и простор Српске деспотовине. Контакти деспота са папством и са напуљским краљем Алфонсом V Арагонским (1442–1458) у раду се посматрају као део јединственог процеса чији је крајњи циљ био придруживање српског деспота крсташком табору. Последица тих преговора је и издавање анализиране буле, чији садржај аутор сагледава из перспективе интереса папства и интереса Српске деспотовине. Предмет проучавања је и начин на који су верске тензије између фрањевачких мисионара и православних на граничном простору између краљевине Босне, краљевине Угарске и Српске деспотовине утицале на садржај буле и на њена каснија тумачења. Такође, рад пружа увид у коришћење црквене уније као средства у преговорима папства и деспотовине, дајући допринос разумевању сложеног и променљивог односа деспота Ђурђа према овом питању.

Zoltán Somhegyi

In this study I investigate several questions related to adaptive restoration, i.e. when a functioning piece of architecture operates with a different purpose to its original one, as well as the role of aesthetics in re-purposing, and the importance of the special forms of experience such a conversion provides. The questions connected to these architectural projects are not only theoretically inspiring, leading to diverse and broad fields of research in architecture, art and aesthetics, but are also crucial on a practical level, and hence require caution and precise consideration, given the impact the final results of such projects may have, as well as in terms of the effect and efficiency of the new space. Creative and adaptive re-purpose, modification or complete change of function can have wonderful potential, as well as, obviously, presenting serious hazards to avoid. What is equally important, however, is that this will also contribute to a strengthening of awareness of architecture and its aesthetic qualities, hence further promoting the idea of safeguarding and care of edifices and of tangible heritage.

Xin Liu, Martin Valcke, Kajsa Yang Hansen et al.

This paper attempts to demonstrate the usefulness of the linkage data from two international large-scale assessment studies, Teaching and Learning International Survey 2013 (TALIS) 2013 and Programme for International Student Assessment (PISA) 2012, in examining the effects of schools. Data from seven educational systems are used to link, and four critical issues with five selection criteria are applied to the data selected. The linking dataset facilitates the investigation of mathematics performance while considering individual learner characteristics, mathematics teacher variables in the classroom environment and the school-level variables. We extend the new avenue of research by developing a linked database geared to the specific mathematics teaching and learning domain to reflect the school mathematics educational environment. The case study using Singapore linkage data demonstrated the feasibility and potential of exploring school effectiveness. In Singapore, schools with teachers of a higher level of education and self-efficacy in teaching mathematics related to a higher level of school mathematics performance. The study offers a guideline and inspiration to the research community to exploit the rich information in both TALIS and PISA studies to facilitate school effectiveness studies.

Armineh Rahmanian, Sadegh Bolouki, S. Rasoul Etesami et al.

Models of opinion dynamics play a major role in various disciplines, including economics, political science, psychology, and social science, as they provide a framework for analysis and intervention. In spite of the numerous mathematical models of social learning proposed in the literature, only a few models have focused on or allow for the possibility of popular extreme beliefs' formation in a population. This paper closes this gap by introducing the Partisan Confidence (PC) model inspired by the foundations of the well-established socio-psychological theory of groupthink. The model hints at the existence of a tipping point, passing which the opinions of the individuals within a so-called "social bubble" are exaggerated towards an extreme position, no matter how the general population is united or divided. The results are also justified through numerical experiments, which provide new insights into the evolution of opinions and the groupthink phenomenon.

Alana Santana, Esther Colombini

Attention is a state of arousal capable of dealing with limited processing bottlenecks in human beings by focusing selectively on one piece of information while ignoring other perceptible information. For decades, concepts and functions of attention have been studied in philosophy, psychology, neuroscience, and computing. Currently, this property has been widely explored in deep neural networks. Many different neural attention models are now available and have been a very active research area over the past six years. From the theoretical standpoint of attention, this survey provides a critical analysis of major neural attention models. Here we propose a taxonomy that corroborates with theoretical aspects that predate Deep Learning. Our taxonomy provides an organizational structure that asks new questions and structures the understanding of existing attentional mechanisms. In particular, 17 criteria derived from psychology and neuroscience classic studies are formulated for qualitative comparison and critical analysis on the 51 main models found on a set of more than 650 papers analyzed. Also, we highlight several theoretical issues that have not yet been explored, including discussions about biological plausibility, highlight current research trends, and provide insights for the future.

Harisatunisa Harisatunisa

Higher number of students recruitment in Islamic Education Institutions is one indicator of an institution quality. Islamic educational institutions are currently required to be able to promote their institutions to expand the students’ recruitment. This paper aims to describe the implication of brand image in the promotion of Islamic educational institutions on student recruitment. The method used in this paper is literature review. Books, articles, websites, laws relating to brand image, brand management, higher education and marketing management are collected, read, compared, and analyzed to identify the roles of brand image in promoting the Islamic educational institutions. The results of this study indicate that there are three implications of brand image in the promotion of Islamic educational institutions on student recruitment: brand image is strengthening the position of Islamic educational institutions, brand image is illustrating the effectiveness of the institution, and the brand image can be used as a reference in designing the institution identity.

Andreia Sofia Teixeira, Szymon Talaga, Trevor James Swanson et al.

Understanding the cognitive and emotional perceptions of people who commit suicide is one of the most sensitive scientific challenges. There are circumstances where people feel the need to leave something written, an artifact where they express themselves, registering their last words and feelings. These suicide notes are of utmost importance for better understanding the psychology of suicidal ideation. This work gives structure to the linguistic content of suicide notes, revealing interconnections between cognitive and emotional states of people who committed suicide. We build upon cognitive network science, psycholinguistics and semantic frame theory to introduce a network representation of the mindset expressed in suicide notes. Our cognitive network representation enables the quantitative analysis of the language in suicide notes through structural balance theory, semantic prominence and emotional profiling. Our results indicate that the emotional syntax connecting positively- and negatively-valenced terms gives rise to a degree of structural balance that is significantly higher than null models where the affective structure was randomized. We show that suicide notes are affectively compartmentalized such that positive concepts tend to cluster together and dominate the overall network structure. A key positive concept is "love", which integrates information relating the self to others in ways that are semantically prominent across suicide notes. The emotions populating the semantic frame of "love" combine joy and trust with anticipation and sadness, which connects with psychological theories about meaning-making and narrative psychology. Our results open new ways for understanding the structure of genuine suicide notes informing future research for suicide prevention.