Hasil untuk "Philosophy. Psychology. Religion"

O. Yu. Boytsova, I. N. Yablokov

The relevance of addressing the understanding of the geography of religion as a section of religious studies is on the one hand due to the growing popularity of this discipline in the modern scientific space,  and on the other its insufficient conceptualisation. The high interest in the geography of religion on the part of the scientific community is caused by its focus on the comprehension of theoretical and practical problems related to the spatial characteristics of religious life. Nowadays, the study of territorial aspects of the coexistence of different religious traditions acquires a special urgency due to the combination of globalisation trends and the desire to preserve authentic identity. Historically, the problem field and scientific apparatus of the geography of religion has been formed with reliance on theoretical developments and methodological tools of philosophy and various scientific disciplines, which supports terminological and methodological polyphony within this discipline and hinders its conceptualisation. The aim of this work is to identify possible grounds for attributing the geography of religion to the sections of religious studies. To achieve this goal the following tasks were solved: the origins of the formation of geography of religion were revealed; the approach to the formation of geography of religion from the perspective of geographical science was analysed; the influence of philosophy of religion on the methodological foundations of geography of religion was shown; the main vectors of interrelation between geography of religion and religious studies were determined. The research is limited to the European tradition of studying the relationship between religion and geography. The study is based on the texts of the classics of philosophical thought, as well as the works of Russian and foreign scholars devoted to the comprehension of the geography of religion as a scientific discipline. To reconstruct the thinkers' position on the issues raised, to identify their dependence on the intellectual context and to compare them, such methods as historical and philosophical analysis of the text, discourse analysis and comparative analysis were used. The result of the study was the substantiation of the conclusion about the possibility and expediency of attributing the geography of religion to the branches of religious studies. Such positioning of geography of religion does not contradict the modern understanding of the problem field and tasks of this discipline as they are formulated within the framework of geographical science, and at the same time allows us to identify promising research strategies in interaction with various religious studies disciplines such as: philosophy of religion, history of religion, anthropology of religion, sociology of religion and psychology of religion.

Indah Sari Dewi. Z

: Juvenile delinquency is behavior carried out by young children due to social neglect so that deviant behavior is formed. Delinquency does not appear without factors influencing it, one of which is when adolescents conform to their peers. The influence of peer conformity on juvenile delinquency is weakened when adolescents have emotional intelligence. By having emotional intelligence, adolescents can express their emotions appropriately and have adaptive emotional regulation. The purpose of this study was to find out whether emotional intelligence can moderate the influence of peer conformity on juvenile delinquency. This study is quantitative with research subjects of as many as 350 adolescents. Measurement using Self Report Delinquency (SRD), Peer Conformity Disposition Scale (PCSD), and Wong and Law Emotional Intelligence Scale (WLEIS) instruments. Data analysis using Moderated Regression Analysis (MRA). The results showed that emotional intelligence did not act as a moderator on the influence of peer conformity on juvenile delinquency (β=0.558; p=0.081).

V. El Sawah, A. Bhardwaj, A. Pryke-Hobbes et al.

Clinical psychology students frequently report feeling underprepared for the interpersonal demands of therapeutic work, highlighting the need for accessible opportunities to practise core counselling skills before seeing real clients. Advances in artificial intelligence (AI) now enable simulated interaction partners that may support early skills development. This study examined postgraduate clinical psychology students' perceptions of two AI-based simulations: a text-based chatbot (ChatGPT) and a voice-based avatar (HeyGen). Twenty-four students completed two brief cognitive-behavioural role-plays (counterbalanced), one with each tool, and provided both quantitative ratings and qualitative feedback on perceived usefulness, skill application, responsiveness and engagement, and perceived skill improvement. Both AI tools were evaluated positively across dimensions. However, the avatar was rated significantly higher than the chatbot for perceived usefulness, skill application, and perceived skill improvement, and qualitative comments highlighted the added value of voice-based interaction for conveying social and emotional cues. These findings suggest that AI-driven simulation may supplement early-stage clinical skills training, with voice-based avatars offering additional benefits. Future work should test whether such simulated interactions translate to objective improvements in real therapeutic performance.

Qiantong Wang

This paper explores hallucination phenomena in large language models (LLMs) through the lens of language philosophy and psychoanalysis. By incorporating Lacan's concepts of the "chain of signifiers" and "suture points," we propose the Anchor-RAG framework as a novel approach to mitigate hallucinations. In contrast to the predominant reliance on trial-and-error experiments, constant adjustments of mathematical formulas, or resource-intensive methods that emphasize quantity over quality, our approach returns to the fundamental principles of linguistics to analyze the root causes of hallucinations in LLMs. Drawing from robust theoretical foundations, we derive algorithms and models that are not only effective in reducing hallucinations but also enhance LLM performance and improve output quality. This paper seeks to establish a comprehensive theoretical framework for understanding hallucinations in LLMs and aims to challenge the prevalent "guess-and-test" approach and rat race mentality in the field. We aspire to pave the way for a new era of interpretable LLMs, offering deeper insights into the inner workings of language-based AI systems.

Zhipeng Bao, Qianwen Li

Despite rapid advances in autonomous driving technology, current autonomous vehicles (AVs) lack effective bidirectional human-machine communication, limiting their ability to personalize the riding experience and recover from uncertain or immobilized states. This limitation undermines occupant comfort and trust, potentially hindering the adoption of AV technologies. We propose PACE-ADS (Psychology and Cognition Enabled Automated Driving Systems), a human-centered autonomy framework enabling AVs to sense, interpret, and respond to both external traffic conditions and internal occupant states. PACE-ADS uses an agentic workflow where three foundation model agents collaborate: the Driver Agent interprets the external environment; the Psychologist Agent decodes passive psychological signals (e.g., EEG, heart rate, facial expressions) and active cognitive inputs (e.g., verbal commands); and the Coordinator Agent synthesizes these inputs to generate high-level decisions that enhance responsiveness and personalize the ride. PACE-ADS complements, rather than replaces, conventional AV modules. It operates at the semantic planning layer, while delegating low-level control to native systems. The framework activates only when changes in the rider's psychological state are detected or when occupant instructions are issued. It integrates into existing AV platforms with minimal adjustments, positioning PACE-ADS as a scalable enhancement. We evaluate it in closed-loop simulations across diverse traffic scenarios, including intersections, pedestrian interactions, work zones, and car-following. Results show improved ride comfort, dynamic behavioral adjustment, and safe recovery from edge-case scenarios via autonomous reasoning or rider input. PACE-ADS bridges the gap between technical autonomy and human-centered mobility.

Wenhan Dong, Yuemeng Zhao, Zhen Sun et al.

As large language models (LLMs) are increasingly used in human-centered tasks, assessing their psychological traits is crucial for understanding their social impact and ensuring trustworthy AI alignment. While existing reviews have covered some aspects of related research, several important areas have not been systematically discussed, including detailed discussions of diverse psychological tests, LLM-specific psychological datasets, and the applications of LLMs with psychological traits. To address this gap, we systematically review six key dimensions of applying psychological theories to LLMs: (1) assessment tools; (2) LLM-specific datasets; (3) evaluation metrics (consistency and stability); (4) empirical findings; (5) personality simulation methods; and (6) LLM-based behavior simulation. Our analysis highlights both the strengths and limitations of current methods. While some LLMs exhibit reproducible personality patterns under specific prompting schemes, significant variability remains across tasks and settings. Recognizing methodological challenges such as mismatches between psychological tools and LLMs' capabilities, as well as inconsistencies in evaluation practices, this study aims to propose future directions for developing more interpretable, robust, and generalizable psychological assessment frameworks for LLMs.

Zhaoyang Cao, Lael Schooler, Reza Zafarani

Memory, a fundamental component of human cognition, exhibits adaptive yet fallible characteristics as illustrated by Schacter's memory "sins".These cognitive phenomena have been studied extensively in psychology and neuroscience, but the extent to which artificial systems, specifically Large Language Models (LLMs), emulate these cognitive phenomena remains underexplored. This study uses human memory research as a lens for understanding LLMs and systematically investigates human memory effects in state-of-the-art LLMs using paradigms drawn from psychological research. We evaluate seven key memory phenomena, comparing human behavior to LLM performance. Both people and models remember less when overloaded with information (list length effect) and remember better with repeated exposure (list strength effect). They also show similar difficulties when retrieving overlapping information, where storing too many similar facts leads to confusion (fan effect). Like humans, LLMs are susceptible to falsely "remembering" words that were never shown but are related to others (false memories), and they can apply prior learning to new, related situations (cross-domain generalization). However, LLMs differ in two key ways: they are less influenced by the order in which information is presented (positional bias) and more robust when processing random or meaningless material (nonsense effect). These results reveal both alignments and divergences in how LLMs and humans reconstruct memory. The findings help clarify how memory-like behavior in LLMs echoes core features of human cognition, while also highlighting the architectural differences that lead to distinct patterns of error and success.

Shintaro Sakai, Jisun An, Migyeong Kang et al.

Prior clinical psychology research shows that Western individuals with depression tend to report psychological symptoms, while Eastern individuals report somatic ones. We test whether Large Language Models (LLMs), which are increasingly used in mental health, reproduce these cultural patterns by prompting them with Western or Eastern personas. Results show that LLMs largely fail to replicate the patterns when prompted in English, though prompting in major Eastern languages (i.e., Chinese, Japanese, and Hindi) improves alignment in several configurations. Our analysis pinpoints two key reasons for this failure: the models' low sensitivity to cultural personas and a strong, culturally invariant symptom hierarchy that overrides cultural cues. These findings reveal that while prompt language is important, current general-purpose LLMs lack the robust, culture-aware capabilities essential for safe and effective mental health applications.

Yuan Yao, Dan Guo, Fang-Lin Liu et al.

Sleep disruption is common in older adults and has been linked to many negative health outcomes, including impaired cognitive, emotional, and interpersonal functioning and maladaptive metabolic changes. Sleep disturbance is the most common symptom in depressive patients, and it was formerly thought to be a major secondary manifestation of depression. Many longitudinal studies have identified insomnia as an independent risk factor for the development of emerging or recurrent depression in older adults, with bidirectional relationships between sleep quality and depression. This narrative review summarizes recent research or evidence on the sleep–depression association in older adults, as well as the potential common mechanisms underlying the comorbidity of sleep and depression disorders, focusing on the clock system, neurochemical substrates, and neurocircuits. A better understanding of the pathophysiological mechanisms underlying sleep disturbance and depression can assist psychiatrists in better managing this comorbidity.

Ana Dwi Kusuma, Emil El Faisal, Dahlia Dahlia

Penelitian ini dilakukan bertujuan untuk mengetahui upaya peningkatan hasil belajar peserta didik melalui media quiziz di SMA Negeri 6 Palembang. Penelitian ini menggunakan metode penelitian Tindakan kelas (PTK), dengan 4 tahap yang harus dilakukan yaitu tahap perencanaan, tindakan, pengamatan dan refleksi. Kegiatan dilakukan dengan 3 siklus yaitu pra siklus, siklus 1 dan siklus 2. Subyek pada penelitian ini berjumlah 38 peserta didik. Instrumen yang digunakan untuk mengetahui hasil belajar peserta didik yaitu menggunakan tes pilihan ganda. Pada pra siklus didapatkan hasil rata-rata nilai nya 6,1 dan persentase ketuntasan hanya 37% dengan jumlah 14 peserta didik yang tuntas. Pada siklus I  didapatkan hasil rata-rata 7,1 dengan persentase ketuntasan naik menjadi 66% dan jumlah peserta didik mengalami kenaikan menjadi 25 peserta didik. Pada siklus II didapatkan hasil rata-rata nilai 8,0 dan 35 peserta didik medapatkan nilai tuntas dengan persentase ketuntasan naik menjadi 92%. Berdasarkan hasil penelitian tersebut dapat disimpulkan bahwa penggunaan quiziz dapat meningkatkan hasil belajar peserta didik pada mata pelajaran PPKn.

Julian Coda-Forno, Marcel Binz, Jane X. Wang et al.

Large language models (LLMs) have significantly advanced the field of artificial intelligence. Yet, evaluating them comprehensively remains challenging. We argue that this is partly due to the predominant focus on performance metrics in most benchmarks. This paper introduces CogBench, a benchmark that includes ten behavioral metrics derived from seven cognitive psychology experiments. This novel approach offers a toolkit for phenotyping LLMs' behavior. We apply CogBench to 35 LLMs, yielding a rich and diverse dataset. We analyze this data using statistical multilevel modeling techniques, accounting for the nested dependencies among fine-tuned versions of specific LLMs. Our study highlights the crucial role of model size and reinforcement learning from human feedback (RLHF) in improving performance and aligning with human behavior. Interestingly, we find that open-source models are less risk-prone than proprietary models and that fine-tuning on code does not necessarily enhance LLMs' behavior. Finally, we explore the effects of prompt-engineering techniques. We discover that chain-of-thought prompting improves probabilistic reasoning, while take-a-step-back prompting fosters model-based behaviors.

Zhenhua Wang, Wei Xie, Baosheng Wang et al.

Large Language Models (LLMs) have gradually become the gateway for people to acquire new knowledge. However, attackers can break the model's security protection ("jail") to access restricted information, which is called "jailbreaking." Previous studies have shown the weakness of current LLMs when confronted with such jailbreaking attacks. Nevertheless, comprehension of the intrinsic decision-making mechanism within the LLMs upon receipt of jailbreak prompts is noticeably lacking. Our research provides a psychological explanation of the jailbreak prompts. Drawing on cognitive consistency theory, we argue that the key to jailbreak is guiding the LLM to achieve cognitive coordination in an erroneous direction. Further, we propose an automatic black-box jailbreaking method based on the Foot-in-the-Door (FITD) technique. This method progressively induces the model to answer harmful questions via multi-step incremental prompts. We instantiated a prototype system to evaluate the jailbreaking effectiveness on 8 advanced LLMs, yielding an average success rate of 83.9%. This study builds a psychological perspective on the explanatory insights into the intrinsic decision-making logic of LLMs.

Fabrice Harel-Canada, Hanyu Zhou, Sreya Muppalla et al.

Evaluations of creative stories generated by large language models (LLMs) often focus on objective properties of the text, such as its style, coherence, and diversity. While these metrics are indispensable, they do not speak to a story's subjective, psychological impact from a reader's perspective. We introduce the Psychological Depth Scale (PDS), a novel framework rooted in literary theory that measures an LLM's ability to produce authentic and narratively complex stories that provoke emotion, empathy, and engagement. We empirically validate our framework by showing that humans can consistently evaluate stories based on PDS (0.72 Krippendorff's alpha). We also explore techniques for automating the PDS to easily scale future analyses. GPT-4o, combined with a novel Mixture-of-Personas (MoP) prompting strategy, achieves an average Spearman correlation of 0.51 with human judgment while Llama-3-70B with constrained decoding scores as high as 0.68 for empathy. Finally, we compared the depth of stories authored by both humans and LLMs. Surprisingly, GPT-4 stories either surpassed or were statistically indistinguishable from highly-rated human-written stories sourced from Reddit. By shifting the focus from text to reader, the Psychological Depth Scale is a validated, automated, and systematic means of measuring the capacity of LLMs to connect with humans through the stories they tell.

Amy Rayland, Jacob Andrews

An increasing number of psychological interventions are shifting to online modes of delivery. One such intervention is peer-to-peer support, which in this context may provide internet users living with mental health disorders an opportunity to connect with and support others living with similar conditions. This paper presents a call for further research into how platforms such as Facebook could be used as channels for peer support and the mechanisms that may underlie their effectiveness. We discuss the background of peer support, how it has transitioned online, and consider theories and models that may have relevance. We also consider the importance of moderation within online peer support and the development of specific social network–based online interventions. We conclude that for social network sites to be used as peer-to-peer support interventions, more research is needed to understand their effectiveness, the role of moderation in these communities, and the mechanisms that produce the benefits experienced by users.

Charlene Ryan, Hélène Boucher, Gina Ryan

Parents play a variety of important roles in their children's musical development. However, whether they impact upon children's music performance education and experience has only begun to be considered. The current study sought to examine whether student perception of parent involvement in music and performance education is related to their experience of music performance anxiety. Sixty-two piano students aged 11 to 17 completed a questionnaire regarding their piano studies, their parents’ involvement in them, and their parents’ prior music education. They also completed measures of performance anxiety and self-esteem. Results indicated that parents’ prior music education was significantly associated with performance anxiety in their children. Participant age, self-esteem, and practice time were also significant variables. Measures of parent involvement in music studies and parent response to weak performances were not found to be significantly related to performance anxiety scores. Implications of these findings and directions for furthering this line of research are discussed.

Edna Paola Fresneda-Patiño, Gabriel Jacobo Sánchez Coral

Con este documento queremos proponer una caracterización de nuestra experiencia como docentes que hemos situado nuestras prácticas investigativas desde la Educación Matemática Crítica y la Etnomatemática, en la que confluye una idea de sujeto político que transforma las concepciones de ser profesor(a) de matemáticas. Nosotros coincidimos hace algunos años en un congreso académico internacional en el que se discutían propuestas investigativas y prácticas pedagógicas enmarcadas en perspectivas alejadas de enfoques cognitivistas y más próximas a dimensiones sociales, políticas y culturales. Allí, compartimos nuestros trabajos académicos y años más tarde nos reencontramos en el II Encuentro de la Red de Educadores Matemáticos Críticos, notando que, si bien nuestros intereses no habían cambiado, estábamos interesados en reconocer la voz del sujeto al relatar sus experiencias investigativas situadas desde enfoques sociales, políticos y culturales de la educación matemática. Para ello usamos las narrativas orales y escritas para estudiar y reflexionar sobre nuestras propias experiencias como docentes de matemáticas. Para lograrlo, teóricamente nos fundamentamos en las ideas del enfoque social, político y cultural, especialmente, en la Educación Matemática Crítica y la Etnomatemática, caracterizando tanto la idea de sujeto político como de contexto sociopolítico. Con relación a la metodología, retomamos la idea de experiencia de Jorge Larrosa y las características de la investigación biográfico-narrativa, usando particularmente los escritos autobiográficos producidos por los autores del presente documento. Buscamos dar vida a la voz del sujeto al narrar sus propias experiencias como docentes e investigadores de carne y hueso que intentan privilegiar en el aula de clase espacios de discusión sobre asuntos sociales, políticos y culturales que se inscriben en los contextos cotidianos de las escuelas colombianas. Además, reconocemos la importancia de usar las matemáticas como herramienta que nos permite leer, interpretar y transformar el mundo y las condiciones de nuestra sociedad actual, reconociéndonos como sujetos políticos agentes de cambio  

Eliza Kosoy, Emily Rose Reagan, Leslie Lai et al.

Developmental psychologists have spent decades devising experiments to test the intelligence and knowledge of infants and children, tracing the origin of crucial concepts and capacities. Moreover, experimental techniques in developmental psychology have been carefully designed to discriminate the cognitive capacities that underlie particular behaviors. We propose that using classical experiments from child development is a particularly effective way to probe the computational abilities of AI models, in general, and LLMs in particular. First, the methodological techniques of developmental psychology, such as the use of novel stimuli to control for past experience or control conditions to determine whether children are using simple associations, can be equally helpful for assessing the capacities of LLMs. In parallel, testing LLMs in this way can tell us whether the information that is encoded in text is sufficient to enable particular responses, or whether those responses depend on other kinds of information, such as information from exploration of the physical world. In this work we adapt classical developmental experiments to evaluate the capabilities of LaMDA, a large language model from Google. We propose a novel LLM Response Score (LRS) metric which can be used to evaluate other language models, such as GPT. We find that LaMDA generates appropriate responses that are similar to those of children in experiments involving social understanding, perhaps providing evidence that knowledge of these domains is discovered through language. On the other hand, LaMDA's responses in early object and action understanding, theory of mind, and especially causal reasoning tasks are very different from those of young children, perhaps showing that these domains require more real-world, self-initiated exploration and cannot simply be learned from patterns in language input.

Erika Erzsébet Vörös

Several sites in East Asia have been identified as Potalaka, originally thought to be located near the southern seas of India. The basis of this phenomenon is built upon the nature of Avalokiteśvara as a mediator between sentient beings and buddhas, the nature of Potalaka as a boundary between their worlds, and Buddhist philosophy. The belief in the abode of Avalokiteśvara bodhisattva on Earth incorporates various places into a Buddhist world transcending borders. This paper examines Korean beliefs about Potalaka and Avalokiteśvara through legends about Naksan Temple, with special emphasis on their relationship with mountain and sea worship. At the same time, the study attempts to connect the beliefs with the philosophical background of Hwaŏm tradition, which is in close relation with this ritual site. The aim of this approach is to point out the unique and universal, as well as the local and translocal elements in Korean narratives about Potalaka. In other words, the paper searches for patterns that are to be found in the wider Buddhist world and characteristics that are created by the specific religious environment of Korean culture.

Lystiana Nurhayat Hakim

The aims of this study is to find out TEYL students’ perception and experience in using Cartoon Story Maker and Comic Life in creating short story for young learners and to identify their obstacles and problems in using those applications. This qualitative study has been conducted in a TEYL class in one English Department in West Java. The sample of the study consisted of thirty students. Questionnaires and interviews were used as data collection techniques in this study. The questionnaires were used to collect evidence from students about their experience and perception towards the use of CSM and Comic Life in creating short story for young learners. The questionnaires used in this study focus on exploring students’ experience and perception toward the use CSM and Comic Life in creating short story for young learners, whereas  interview was used to explored more the data about obstacles faced by the students in using CSM and Comic Life. The data collected from the respondents were gathered together to be analyzed using qualitative analysis of interactive models. The results of this study are TEYL students have positive perception toward the use of CSM and Comic Life in creating short story for young learners, CSM is easier and more suitable to use than Comic Life in creating story for young learners, and the obstacles faced by students are choosing appropriate template for young learners, writing text in text tool or bubble, and record the voice in audio bubble.

Frances Garrett, Sophie Chase

Co-authored between a professor and student, this essay discusses how an experiential learning assignment of “deep listening” was integrated into an online course on histories of Buddhist meditation. Paired with a group art project, the work provided not only an opportunity to practice critical communication skills, but also a sense of connection and community, which is especially important during the conditions of pandemic isolation. The course design relied on pedagogical principles specifically aimed at supporting student well-being, such as trauma-informed teaching. We reflect on how grounding course design in inclusive, anti-oppressive and care-focused principles may enable new outcomes in teaching and learning beyond this pandemic year.