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This study explores the relationship between multiple intelligences and academic achievement among grade five pupils in selected public schools in Olongapo City, Philippines. Grounded in Howard Gardner's Theory of Multiple Intelligences, the research examines the profile of 321 respondents, including age, gender, parents' educational attainment and occupation, and family monthly income. The study describes the students' multiple intelligences across nine dimensions: naturalistic, linguistic, spatial, musical, bodily-kinesthetic, interpersonal, intrapersonal, logicalmathematical, and existential. Additionally, it assesses the academic performance of the pupils as reflected in their general point average grades. Employing a descriptive survey method, the research utilizes a questionnaire composed of demographic information and McKenzie's (1999) Multiple Intelligences Survey. Data analysis involves various statistical tools, including frequency counts, percentages, weighted means, t-tests, Analysis of Variance (ANOVA), and Pearson Product Moment Correlation Coefficient. Results indicate that respondents predominantly possess Naturalistic, Musical, Verbal, and Interpersonal intelligences. Surprisingly, no significant differences were observed in the perception of multiple intelligences when grouped according to profile variables such as age, sex, parents' educational attainment and occupation, and family monthly income. A slight negative correlation (r = -0.213, p < 0.01) was found between academic performance and multiple intelligence, suggesting that as multiple intelligence scores increase, there is a slight decrease in academic performance. The study concludes with recommendations for educators and schools to incorporate multiple intelligence theory into teaching strategies and curriculum development. These include enhancing course syllabi, providing necessary facilities and equipment, encouraging teacher professional development, and creating special programs for children with unique intelligences. The findings contribute to the ongoing dialogue about the role of multiple intelligences in education and its potential impact on academic achievement in the Philippine context. [ABSTRACT FROM AUTHOR]

Copyright of Retos: Nuevas Perspectivas de Educación Física, Deporte y Recreación is the property of Federacion Espanola de Asociaciones de Docentes de Educacion Fisica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

For primates, expressions of fear are thought to be powerful social signals. In laboratory settings, faces with fearful expressions have reliably evoked valence effects in inferior temporal cortex. However, because macaques use so called "fear grins" in a variety of different contexts, the deeper question is whether the macaque inferior temporal cortex is tuned to the prototypical fear grin, or to conspecifics signaling fear? In this study, we combined neuroimaging with the results of a behavioral task to investigate how macaques encode a wide variety of fearful facial expressions. In Experiment 1, we identified two sets of macaque face stimuli using different approaches; we selected faces based on the emotional context (i.e., calm vs. fearful), and we selected faces based on the engagement of action units (i.e., neutral vs. fear grins). We also included human faces in Experiment 1. Then, using fMRI, we found that the faces selected based on context elicited a larger valence effect in the inferior temporal cortex than faces selected based on visual appearance. Furthermore, human facial expressions only elicited weak valence effects. These observations were further supported by the results of a two-alternative, forced-choice task (Experiment 2), suggesting that fear grins vary in their perceived pleasantness. Collectively, these findings indicate that the macaque inferior temporal cortex is more involved in social intelligence than commonly assumed, encoding emergent properties in naturalistic face stimuli that transcend basic visual features. These results demand a rethinking of theories surrounding the function and operationalization of primate inferior temporal cortex. [ABSTRACT FROM AUTHOR]

Artificial intelligence technologies are improving the marketing toolkit, making it possible to process large amounts of data faster and more efficiently than ever before. Machine learning, a subset of AI, uses algorithms that can predict which ads will be most effective in specific situations, allowing for optimized ad targeting. This research explores the issues of coevolution and distribution of machine and human intelligence in various social practices, including marketing and advertising. The authors describe the key approaches to studying the visual component of advertising and suggest revising traditional methods of analyzing advertising messages. The tracking of biometric data combined with AI-based methods that capture human emotions while viewing video content is proposed as a promising direction for such analysis. This paper presents the results of a pilot study based on analytical face-tracking technology using AI, where the subject of the experiment was the analysis of video fragments that may have an impact on the emotional state of the viewer. The AI software platform used was Amazon Rekognition, and the results show that AI analytics provide the ability to track the level of audience engagement in perceiving video content, which helps to improve communication effectiveness. This allows the use of AI to make recommendations for the development of more directed and engaging advertising messages. [ABSTRACT FROM AUTHOR]

The study of collective intelligence has focused in the last years on crowdsourcing and artificial swarm intelligence. Currently, large online communities have demonstrated their effectiveness but even if the contributions in this domain are significant, it remains essential to question the functioning of collective intelligence in small groups, especially since the gain in popularity of brainstorming strategies, focus groups and co-working practices. In this context, we conducted a qualitative systematic review using Prospero, PRISMA protocol and bias assessment to identify the factors currently recognised as impacting on the emergence of collective intelligence in small groups. These factors were then organised according to the different levels of abstraction observed in research about collective intelligence. From this work, collective intelligence appears as the crystallization of emerging properties that manifest themselves in interactions and whose possibility of existing is intrinsically linked to meta-cognition and meta-communication processes. [ABSTRACT FROM AUTHOR]

Introduction: The aim of this study is to reveal the effect of scientific attitude and intelligence on STEM (science, technology, engineering and mathematics) motivation using Structural Equation Modelling (SEM). It is possible to say that there is a reciprocal relationship between attitudes towards science, intelligence and motivation towards STEM. Motivation is closely and positively related to STEM, scientific attitude, intelligence and organizational development. When female students are supported and motivated positively, it is possible for them to be successful in STEM. It is possible to say that female students are the female leadership candidates of the future. Female leader candidates can play a role in future organizational development. Female leader candidates who are supported and motivated by their environment can take their place in organizational development. There is a gap in the research literature on this subject in Türkiye. This study fills an important gap in terms of sampling, research method and data analysis. Method: In the study, personal information form, Attitude Towards Scientific Research Scale, Multiple Intelligences Self-Perception Scale and STEM Value-Expectation Rating Scale were applied to 159 female undergraduate students who are disadvantaged in STEM field and studying at Ege University Ödemiş Faculty of Health Sciences. Results: It is possible to say that most female students have positive attitudes towards scientific research. According to the research results, as the reluctance to help researchers and negative attitudes towards research increase, motivation towards STEM decreases. As positive attitudes towards research and researchers increase, motivation towards STEM increases. In addition, increases in verbal–linguistic intelligence, logical-mathematical intelligence, spatial intelligence, interpersonal intelligence, intrapersonal intelligence and natural intelligence lead to an increase in positive attitudes towards research and thus STEM motivation. Conclusion: When the value expectations of future female leadership candidates for the STEM field were evaluated, it was found that 81.13% of the students had a medium level of value expectation evaluation level for the STEM field. This situation suggests that female students are not positively motivated for STEM in the family, school and peer environment. [ABSTRACT FROM AUTHOR]

B. F. Skinner’s work in the field of verbal behaviour represented a movement of global significance. However, in today’s age, even those who appreciate its profound importance in the archives of psychology accept that it did not sufficiently account for complex human language. Recent advances in psychological science have led to the emergence of a post-Skinnerian account of human language and cognition known as Relational Frame Theory (RFT). The current paper introduces RFT, describing empirically supported examples of its relevance in educational psychology. Attention is given to 1) social, emotional and mental health support through RFT informed models such as Acceptance & Commitment Therapy (ACT) and Discoverer, Noticer, Adviser–Values (DNA-V) and 2) cognitive and attainment skills development through programmes such as Strengthening Mental Abilities with Relational Training (SMART) and Promoting the Emergence of Advanced Knowledge (PEAK). Reflections on future directions are offered. [ABSTRACT FROM AUTHOR]

This study investigated the correlation between teachers' multiple intelligences and pupils' Language Assessment for Primary Grades (LAPG) performance in selected elementary schools in Olongapo City during SY 2017-2018. A descriptive research design was employed, involving 138 Grade IV teachers as respondents. Data was collected through questionnaires and analyzed using descriptive and inferential statistics. The study found that most teachers assessed themselves as having verbal-linguistic intelligence (26.8%), followed by interpersonal intelligence (24.6%). Pupils achieved a "near mastery" level on the LAPG. Significant differences in teachers' multiple intelligences were observed based on educational qualification and years of service. A weak but significant positive correlation (r=0.173, p<0.05) was found between teachers' logical-mathematical intelligence and pupils' LAPG scores. The study was limited to Grade IV teachers and pupils in Olongapo City, potentially affecting generalizability. The findings suggest that teachers' multiple intelligences, particularly logical-mathematical intelligence, may influence pupils' language assessment performance. This implies the need for considering multiple intelligences in teacher hiring, development, and instructional strategies to potentially enhance student outcomes. [ABSTRACT FROM AUTHOR]

Several U.S. government investigations have examined the 6 January 2021 attack on the US Capitol, and all assign at least some blame to intelligence failure. Their reports tended to focus on poor dissemination of intelligence and inadequacies in social media analysis as main defects. What the reports oddly ignore is how inadequate human intelligence (HUMINT) collection may have contributed to that failure. Would better HUMINT collection have made a different in helping prevent the attack? This article evaluates the key findings of January 6 as an alleged intelligence failure event, how HUMINT has been collected in the U.S. on extremist groups, and the feasibility of using such collection for preventive strategies. ‘January 6’ offers a unique case study on the inherent obstacles to domestic intelligence collection, especially in a polarized political environment. [ABSTRACT FROM AUTHOR]

Objective Background Methods Results Conclusion Implications To evaluate the fairness of a machine learning (ML) model designed to assess the need for home visiting services, focusing on its performance across family characteristics.ML models are increasingly used in family‐centered services; however, their fairness remains underexplored, particularly concerning family sociodemographic factors and service contexts.This study assessed the fairness of an ML model developed for home visiting services examining false negative rates (FNRs) across subgroups, particularly focusing on the intersection of maternal ethnicity and nativity.The ML model reduced FNRs from 52.9% to 22.1%, with the most notable improvements for children of Black mothers and with family characteristics associated with high risk. However, the model was less effective for children of Asian and foreign‐born Hispanic mothers.Although the ML model substantially reduced FNRs across various family subgroups, disparities were observed.Understanding fairness in ML models requires a thoughtful approach, considering service context and impact on the families from diverse backgrounds. Continued research and collaboration are necessary for fair and inclusive use of ML models for family‐centered services. [ABSTRACT FROM AUTHOR]

This study aimed at exploring the relationship between happiness and social intelligence among the orphans in Riyadh city. The researcher applied the descriptive analytical methodology. The sample of the research consisted of 215 orphans (males/females). To achieve the objectives of the study, the researcher used Oxford Happiness List Scale, translated by Abdel-Khaleq (2003) and the Social Intelligence Scale, prepared by Abu Hashem (2008).The study concluded a set of results, they are: The level of happiness is low among the orphans. There is a high level of social intelligence (social awareness dimension and problem solving dimension) and there is also a medium level for the social skills dimension. There is a positive (direct) statistically significant correlation between happiness and social intelligence. There are statistically significant differences on the happiness scale due to the variable of place of residence (family home / outside family home) in favor of the sample members who reside at family home. Likewise, there are statistically significant differences on the social intelligence scale due to the variable of place of residence (family home/outside family home) in favor of the sample members who reside at family home. Whereas, there are no statistically significant differences between the mean scores of the orphans in Riyadh city in the feeling of happiness due to gender (males/females).Likewise, there are no statistically significant differences between the mean scores of the orphans in Riyadh city in social intelligence due to gender (males/females). There are statistically significant differences between the average ranks of the scores of (father’s loss) group and the average ranks of the scores of each of the two groups (mother’s loss, parents’ loss) on the social intelligence scale and feeling of happiness scale in the direction of the group ((father’s loss)..Eventually, social intelligence contributes to predicting the feeling of happiness among the orphans in Riyadh city. The study recommended providing counseling programs contributing to enhancing orphans’ happiness level. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to develop a framework for the perceived intelligence of VAs and explore the mechanisms of different dimensions of the perceived intelligence of VAs on users' exploration intention (UEI) and how these antecedents can collectively result in the highest level of UEI. Design/methodology/approach: An online survey on Amazon Mechanical Turk is employed. The model is tested utilizing the structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) approach from the collected data of VA users (N = 244). Findings: According to the SEM outcomes, perceptual, cognitive, emotional and social intelligence have different mechanisms on UEI. Findings from the fsQCA reinforce the SEM results and provide the configurations that enhanced UEI. Originality/value: This study extends the conceptual framework of perceived intelligence and enriches the literature on anthropomorphism and users' exploration. These findings also provide insightful suggestions for practitioners regarding the design of VA products. [ABSTRACT FROM AUTHOR]

Artificial intelligence has evolved since its inception in the 1950s, resulting in the creation of large language models that are trained on extensive data sets to understand and generate content, such as OpenAI's ChatGPT, which launched in November 2022. Modern technology that is easy to access and free to use, like ChatGPT, is changing the educational landscape as it is an example of a large language model – an artificial intelligence network – that can process and generate text that reads as though it were written by a person. Using a survey and semi-structured interviews, this exploratory mixed-method study examined social work educators' experiences of addressing students' use of ChatGPT and found that although they are uncomfortable with addressing ChatGPT use with their students, they believe it is necessary to communicate its ethical use to them. Results also suggested that while using ChatGPT as a learning tool is valid, it can be overused. ChatGPT use gives students a false sense of having mastered academic material, and institutional guidelines are needed to address concerns regarding academic integrity and plagiarism. Moreover, instructors should address students' use of ChatGPT with their institutions and take intentional steps to ethically and creatively integrate artificial intelligence models into the social work curriculum. [ABSTRACT FROM AUTHOR]

This paper examines the pervasive discourse of disruption in OER literature by recounting a facilitated conversation hosted at the 2023 Open Education Global conference held in Edmonton, Alberta. This dialogue used Bacchi's "what is the problem represented to be" (WPR) approach to structure the conversation in four movements. The first movement problematized the concept of OER by discussing the educational challenges OER supposedly addresses, such as the high cost of textbooks. The second movement considered the genealogy, historical development, and philosophical underpinnings of OER. The third movement accounted for the disruptors within the OER movement, exploring what OER have disrupted and discussing if disruption is even a legitimate goal of OER. The fourth and final movement pivoted to examine resistors and forms of resistance to OER, including the protection of intellectual property rights, copyright concerns, and Marcuse's idea of repressive tolerance. This single conversation generated a small but important piece of social intelligence within a much larger dialogue about open education, open pedagogy, and OER during a time of flux (characterized by intense politicization, the relentless progression of educational technology, the intensification of marketization, and the growing popularity of all-inclusive textbooks). This social intelligence can be used to guide the next transition phase for OER development. While the conversation does not offer tidy solutions or even clear recommendations, it does suggest that the next wave of OER practitioners would always do well to focus on the goals OER can achieve, not what they hope to disrupt. [ABSTRACT FROM AUTHOR]

It has become increasingly important to provide equal educational opportunities to all students for quality and sustainable education in classrooms with rapidly increasing diversity. In this context, communication skills, social intelligence and intercultural sensitivity are important competences that can affect teacher performance and efficiency in classrooms. Despite the importance of these competencies, empirical studies examining the relationships between these variables are scarce. Consequently, this study aimed to investigate the relationships between teacher candidates' communication skills and their intercultural sensitivity and social intelligence levels through the application of structural equation modeling (SEM). The participants were selected from among the teacher candidates studying at Kütahya Dumlupınar University, a public university in Türkiye, using simple random sampling method. The results indicated that teacher candidates had high levels of communication skills, intercultural sensitivity and social intelligence. In addition, while there was a significant positive relationship between communication skills and intercultural sensitivity level and social intelligence level at low level, there was a significant positive relationship between intercultural sensitivity and social intelligence level at medium level. Furthermore, communication skills and intercultural sensitivity were found to be significant predictors of social intelligence and intercultural sensitivity had a partial mediating role in the relationship between communication skills and social intelligence. In the study, it was concluded that teacher candidates' communication skills predicted social intelligence through intercultural sensitivity. [ABSTRACT FROM AUTHOR]

Copyright of Methaodos: Social Science Journal / Methaodos: Revista de Ciencias Sociales is the property of Departamento de Ciencias de la Comunicacion y Sociologia, Universidad Rey Juan Carlos and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article delves into the dynamics of human interaction with artificial intelligence (AI), emphasizing the optimization of these interactions to enhance human productivity. Employing a Grounded Theory Literature Review (GTLR) methodology, the study systematically identifies and analyzes themes from literature published between 2018 and 2023. Data were collected primarily from the Scopus database, with the Web of Science used to corroborate findings and include additional sources identified through a snowball effect. At the heart of this exploration is the pivotal role of socio-emotional attributes such as trust, empathy, rapport, user engagement, and anthropomorphization—elements crucial for the successful integration of AI into human activities. By conducting a comprehensive review of existing literature and incorporating case studies, this study illuminates how AI systems can be designed and employed to foster deeper trust and empathetic understanding between humans and machines. The analysis reveals that when AI systems are attuned to human emotional and cognitive needs, there is a marked improvement in collaborative efficiency and productivity. Furthermore, the paper discusses the ethical implications and potential societal impacts of fostering such human-AI relationships. It argues for a paradigm shift in AI development—from focusing predominantly on technical proficiency to embracing a more holistic approach that values the socio-emotional aspects of human-AI interaction. This shift could pave the way for more meaningful and productive collaborations between humans and AI, ultimately leading to advancements that are both technologically innovative and human-centric. [ABSTRACT FROM AUTHOR]

Developmental psychologists have long-established socio-cognitive abilities as fundamental to human intelligence and development. These abilities enable individuals to enter, learn from, and contribute to a surrounding culture. This drives the process of cumulative cultural evolution, which is responsible for humanity's most remarkable achievements. AI research on social interactive agentsmostly concerns the emergence of culture in amulti-agent setting (often without a strong grounding in developmental psychology). We argue that AI research should be informed by psychology and study socio-cognitive abilities enabling to enter a culture as well. We draw inspiration fromthe work of Michael Tomasello and Jerome Bruner, who studied socio-cognitive development and emphasized the influence of a cultural environment on intelligence. We outline a broader set of concepts than those currently studied in AI to provide a foundation for research in artificial social intelligence. Those concepts include social cognition (joint attention, perspective taking), communication, social learning, formats, and scaffolding. To facilitate research in this domain, we present The SocialAI school--a tool that offers a customizable parameterized suite of procedurally generated environments. This tool simplifies experimentation with the introduced concepts. Additionally, these environments can be used both with multimodal RL agents, or with pure-text Large Language Models (LLMs) as interactive agents. Through a series of case studies, we demonstrate the versatility of the SocialAI school for studying both RL and LLM-based agents. Our motivation is to engage the AI community around social intelligence informed by developmental psychology, and to provide a user-friendly resource and tool for initial investigations in this direction. Refer to the project website for code and additional resources: https://sites.google.com/view/socialai-school. [ABSTRACT FROM AUTHOR]

The successful adoption of social innovations, such as renewable energy systems or pollution reduction plans in cities, depends, to a large extent, on the willingness and participation of the population in their development and implementation. We present an agent‐based model (ABM) to analyze the process of citizen acceptability of a social innovation that uses a variety of agents to represent individual citizens and relevant groups of citizens. Citizen agents make use of the HUMAT cognitive decision‐making model, based on psychosocial theories, to decide on their support for the social innovation considering how their needs will be satisfied if they decide to support (or not) the innovation project, and the influence exerted by the agents in their environment. The ABM was initially developed to represent the urban and transport planning superblock project in the city of Vitoria‐Gasteiz (Spain). The ABM simulations make it possible to study the evolution of public acceptance of social innovation, with the results providing insights to the social dynamics and individual factors that affect the acceptance of the project, enabling an evaluation of how to devise new policies that increase public acceptance. Sufficiently generic to be easily adaptable to different types of social innovations, the ABM is a powerful tool to explore different scenarios and design strategies that foster the acceptance and sustainable adoption of social innovations. [ABSTRACT FROM AUTHOR]

Background: Cooperative learning provides an opportunity for the development and improvement of social skills by emphasizing the importance of social interaction in fostering both academic and social intelligence. This study examined the application of cooperative learning in teaching traditional Chinese culture at Chinese universities using a mixed methods approach. Methods: This study adopted a mixed methods approach inclusive quantitative phase involved a true experimental design with pre- and post-tests with control group. The study focused on Chinese university students, and a cluster sampling approach was utilized to select 60 participants. Quantitative assessments were conducted using performance tests, the Motivated Strategies for Learning Questionnaire (MSLQ) by Paul Pintrich, and the Social Skills Inventory (SSI) by Riggio, while qualitative insights were gathered through post-experiment interviews with 10 participants. The qualitative data in this study were collated and analyzed using NVivo, integrating interviews, group discussions, questionnaires, and more. Quantitative data were analyzed by mixed analysis of variance (ANOVA) method. Data were analyzed with SPSS software. Results: Mixed analysis revealed that main effect of time in performance score was found to be statistically significant [F(1) = 19.25, P < 0.001]. This indicates a significant change in scores from the pre-test to the post-test across both groups. Additionally, the main effect of the group was also found to be significant [F(1) = 5.81, P = 0.019], suggesting a notable difference in scores between the control and experimental groups. Regarding motivation, it is evident that the main effect of time had a significant impact [F(1) = 59.60, P < 0.001], signifying a substantial change in motivation levels from pre-test to post-test across both groups. In social skills, it is evident that the main effect of time had a significant impact [F(1) = 25.67, P < 0.001], indicating a considerable change in skill levels from pre-test to post-test across both groups. Conclusion: These findings underscore the potential of cooperative learning to mobilize students' enthusiasm for learning and enhance their independent learning ability, cooperative participation, and competitive consciousness, thus effectively improving the teaching quality of Chinese traditional culture in universities. [ABSTRACT FROM AUTHOR]

The current paper reports four consecutive studies that were conducted to link sexual health with a new construct of sexual intelligence by developing and validating a new scale to measure sexual intelligence. Sexual intelligence was defined as "the ability to perceive, understand and respond to sexual needs and desires in a personal and social context." Sexual Intelligence Scale (SIS), comprising of 8 items in English and 2 factors (sexual knowledge & sexual behavior), was developed and validated by involving 959 respondents in the process of 4 consecutive studies. The validity of SIS was tested step by step for its face, content, factorial, convergent, discriminant, and predictive validities. The reliability was measured through internal consistency and item-total & item-scale correlations. The study found significantly higher levels of sexual intelligence in men as compared to women. Sexual intelligence, moreover, had significant positive correlations with age, education, emotional intelligence, social intelligence, sexual health, and satisfaction with life. Sexual health was linked with sexual intelligence and the SIS was accepted as a reliable and valid tool to measure sexual intelligence. [ABSTRACT FROM AUTHOR]

This study seeks to investigate the fundamental role of restaurant employees' job engagement, which is related to their emotional intelligence and adaptive behavior at work. A self-reported questionnaire was used to collect data from frontline employees working in the full-service restaurant industry. The results presented that employees' ability to appraise others' emotions and use their own emotions is positively related to job engagement whereas their ability to understand and regulate their own emotions is not. Employees' job engagement is positively associated with their interpersonal and service offering adaptive behavior. The theoretical and managerial implications of the study findings were discussed. [ABSTRACT FROM AUTHOR]

The Social Intelligence Hypothesis (SIH) is one of the leading explanations for the evolution of cognition. Since its inception a vast body of literature investigating the predictions of the SIH has accumulated, using a variety of methodologies and species. However, the generalisability of the hypothesis remains unclear. To gain an understanding of the robustness of the SIH as an explanation for the evolution of cognition, we systematically searched the literature for studies investigating the predictions of the SIH. Accordingly, we compiled 103 studies with 584 effect sizes from 17 taxonomic orders. We present the results of four meta‐analyses which reveal support for the SIH across interspecific, intraspecific and developmental studies. However, effect sizes did not differ significantly between the cognitive or sociality metrics used, taxonomy or testing conditions. Thus, support for the SIH is similar across studies using neuroanatomy and cognitive performance, those using broad categories of sociality, group size and social interactions, across taxonomic groups, and for tests conducted in captivity or the wild. Overall, our meta‐analyses support the SIH as an evolutionary and developmental explanation for cognitive variation. [ABSTRACT FROM AUTHOR]

Social-emotional competencies are complex actions that include skills, knowledge and attitudes to maintain effective and satisfactory social interactions. As well as, managing one's own and other people's emotions in different environments. They are vital for healthy coexistence in higher education. The purpose of this research was to establish the evidence of validity and reliability for the scale of socioemotional competencies of university teachers. Scale constructed under the pentagonal model approach of Bizquerra and Pérez (2007). The study is crosssectional and instrumental. A non-probabilistic convenience sample of 237 teachers from public and private universities in Lima (Peru), from different professional careers, aged between 24 and 70 years, male and female, was used. Satisfactory evidence of content-based validity was found for the criteria of clarity, pertinence, and relevance for each of the items using Aiken's V technique. For validity based on the internal structure of the construct, a Penta dimensional model and a bi-factor model were contrasted by confirmatory factor analysis, with better fit values for the second model (CFI and TLI > 0.95, RMSEA and SRMR < 0.07, = ω h = 0.90, ECV and PUC > 0.95), and favorable evidence of convergent and discriminant validity was also found. For both the overall score and the scores for each factor, there were coefficients denoting high reliability (ordinal α and ω > 0.90). [ABSTRACT FROM AUTHOR]

With the rapid advance of mobile internet, communication technology and the Internet of Things (IoT), the tourism industry is undergoing unprecedented transformation. Smart tourism offers users personalized and customized services for travel planning and recommendations. Location-based social networks (LBSNs) play a crucial role in smart tourism industry by providing abundant data sources through their social networking attributes. However, applying LBSNs to smart tourism is a challenge due to the need to deal with complex multi-source information modeling and tourism data sparsity. In this article, to fully harness the potential of LBSNs using deep learning technologies, we propose an knowledge-driven personalized recommendation method for smart tourism. Representation learning techniques can effectively modeling the contextual information (e.g., time, space, and semantics) in LBSNs, while the data augmentation strategy of contrastive learning techniques can explore user personalized travel behaviors and alleviate data sparsity. To demonstrate the effectiveness of the proposed approach, we conducted a case study on trip recommendation. Furthermore, the patterns of human mobility are revealed by exploring the effect of contextual data and tourist potential preferences. [ABSTRACT FROM AUTHOR]

Copyright of Pamukkale Medical Journal is the property of Pamukkale Journal of Medicine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Research question: This study aimed to provide a better understanding of Dual Career competencies among elite athletes. To that effect, we evaluated how elite athletes perceive the importance and their possession of Dual Career competencies. We also analysed the relationship between Dual Career competencies and career effectiveness, such as medal success, dual career compatibility, and dropout. Research methods: The study employed a quantitative research paradigm. Data from a cross-sectional survey of elite athletes (n = 1,115) from Germany were utilised. t-Tests were used to analyse differences in the perceived importance and possession of Dual Career competencies. Logistic regression models revealed the effects of competencies on career effectiveness. Results and Findings: The perceived importance of all competencies was rated significantly higher than their perceived possession. Several competencies were significantly correlated with the three career adaptability measures. For instance, of the social intelligence and adaptability dimension, the variable 'Understanding the importance of rest and recuperation' was positively correlated with dual career compatibility. Implications: Career construction theory was confirmed in the context of athletes' Dual Careers. This emphasised that both careers could be at different stages. Athletes and support providers should be aware that different competencies are required for goal achievement depending on which target outcomes they prioritise. [ABSTRACT FROM AUTHOR]

This exploratory study examines the socio-technical dynamics of Artificial Intelligence Companions (AICs), focusing on user interactions with AI platforms like Replika 9.35.1. Through qualitative analysis, including user interviews and digital ethnography, we explored the nuanced roles played by these AIs in social interactions. Findings revealed that users often form emotional attachments to their AICs, viewing them as empathetic and supportive, thus enhancing emotional well-being. This study highlights how AI companions provide a safe space for self-expression and identity exploration, often without fear of judgment, offering a backstage setting in Goffmanian terms. This research contributes to the discourse on AI's societal integration, emphasizing how, in interactions with AICs, users often craft and experiment with their identities by acting in ways they would avoid in face-to-face or human-human online interactions due to fear of judgment. This reflects front-stage behavior, in which users manage audience perceptions. Conversely, the backstage, typically hidden, is somewhat disclosed to AICs, revealing deeper aspects of the self. [ABSTRACT FROM AUTHOR]

The purpose of our article is to analyze dominant functions of social intel­ligence of the teachers of preschool educational establishments in the conditions of war in Ukraine. Methods of the research. The following theoretical methods of the research were used to solve the tasks formulated in the article: a categorical method, structural and functional methods, the methods of the analysis, systematization, modeling, generalization. In our research we also used empirical methods, such as the statement study. The results of the research. The functions of “understanding the actions of other people and influencing them”, “understanding oneself and modeling behavior in accordance with the person’s needs, his/her goals and abilities” are distinguished by us. We consider the level of the development of the specified characteristics of these functions to be indicators of the development of these functions. So, as a result, we distinguish between interpersonal and personal intelligence. Conclusions. We consider the dominant functions of social intelligence to be “the ability to express spontaneous judgments about other people” and “to predict the behavior of others”. These functions are noted to actualize the so-called “social gift”, that is the ability to adequately express oneself about the surrounding subjects of people. The function of “adaptation to life situations” is also distinguished by us. This function is noted to significantly affect the develop­ment of general abilities and personal qualities, facilitates the formation of cog­nitive competence, which allows people to perceive the events of social life with a minimum of surprises and with maximum of personal benefit. The functions of “solving practical tasks and situations of everyday life” and “social adaptation” are also highlighted. This function actualizes a high level of the individual’s ability to solve daily tasks, including complex situations and situations of cognitive dissonance.

Abstract Social anxiety is highly prevalent among nursing students and is associated with poor mental health. However, the underlying mechanism in such an association remains unclear. This study aimed to examine the potential mediating role of social intelligence in the association between social anxiety and mental health using the Stress-Coping Model (SCM) as the theoretical framework. A cross-sectional study was conducted among 748 nursing students recruited from a Chinese University from December 2022 to March 2023. Students completed an online questionnaire to assess their social anxiety, social intelligence, and mental health. The PROCESS SPSS Macro (model 4) was used to test the mediation effect of social intelligence on the association between social anxiety and mental health. The results showed that nursing students had moderate levels of social anxiety, social intelligence, and mental health, which varied according to their profile characteristics. Social anxiety was negatively associated with mental health, and the association was partially mediated by social intelligence. Our study offers fresh insights into the impact of social anxiety on mental health and sheds light on the intricate mediating role of social intelligence. These findings offer valuable insights for research and clinical endeavors aimed at formulating psychosocial interventions to enhance the mental health of nursing students.

The aim of the study is to establish digital humanism as a driving force for technological change in the context of the Internet and artificial intelligence paradigm, based on social interaction between humans and digital technologies. The article uses general philosophical and special scientific methods of cognition, in particular, analysis, synthesis, generalisation and modelling, structural and functional, Agile, axiological, synergistic methods. The conceptual foundations of digital humanism as a concept of modern development, which not only promotes technological progress but also takes into account the challenges and opportunities of the Internet and artificial intelligence in the social interaction of humans with technology, are analysed using this methodology. The authors identify the problems of digital humanism and the ways to overcome them, aimed at ensuring that the development of technology serves the social wellbeing of the individual and improves the quality of life of society. The authors analyses new trends in digital humanism in the age of the Internet and artificial intelligence, which can provide access to information, education, medical services, etc., making people's lives more comfortable and productive. The concept of digital humanism promotes the convergence of technology with human values and needs. Identifying the impact on technological change and social interaction with Artificial Intelligence contributes to the creation of a humane and just society. [ABSTRACT FROM AUTHOR]

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The article emphasises that for the actors of the security and defence sector, solving various communication situations is a constant and important task which can become difficult to perform if the social intelligence abilities are not sufficiently developed. A comparative analysis of the peculiarities of social intelligence abilities of higher education students of higher education institutions of the security and defence sector, who study in the specialities of “Law” and “Psychology”, was carried out. It is emphasized that the specificity of the social situation of the study participants' intellectual abilities development is due to certain features: lockdowns and quarantines of 2020–2021 with the vast majority of distance education, which were caused by the spread of the COVID-19 virus infection; martial law, which has been in force since February 2022. The senior students of Kharkiv National University of Internal Affairs and the Military Law Institute of Yaroslav Mudryi National Law University took part in the study. The empirical data were obtained using J. Guilford’s psychodiagnostic methodology for studying social intelligence. It has been found that the general level of social intelligence of most of the surveyed cadets corresponded to the average level. It has been shown that the general level of social intelligence of the cadets studying “Psychology” was higher than that of the cadets studying “Law”. It has been revealed that the differences in the level of social intelligence of the surveyed groups of cadets were due to a statistically significantly higher level of development of the ability to predict the consequences of the behaviour of others in typical conditions among cadets studying “Psychology” and a more developed ability to understand the logic of interaction situations and the significance of people's behaviour in these situations. It has been established that the most developed ability of social intelligence of the study participants studying in the speciality “Law” was the ability to understand the change in the meaning of similar verbal reactions of a person depending on the context of the situation that caused them. It has been argued that the specific social conditions of personality formation of higher education students in recent years have not significantly affected the level of development of their social intelligence abilities. The main directions of development of social intelligence abilities of cadets studying in different specialities are presented.

The article analyses the general concept of human success from various psychological and scientific perspectives, as well as the concept of “a police officer’s professional success” separately, since it plays an important role for both the individual and society at the present stage of society development. The author emphasises that at the scientific and legislative levels there are no explanations and clarifications as to who is a professionally successful police officer. The study provides a generalised analysis of police officers’ powers, among which the main ones are highlighted which every police officer must perform regardless of their position, length of service and other factors. The importance of professional training of police officers during their service is also emphasised. To determine the level of success of a police officer’s professional activity, it is proposed to take into account a combination of two components – external and internal. The external component of police officers’ activity includes professional development, which is characterized by the level of performance of the main professional tasks based on knowledge of the principles and powers of the National Police of Ukraine at the legislative level. The internal component includes individual psychological properties of a police officer, which to a certain extent ensure efficient and high-quality performance of functional duties. In addition, the importance of social intelligence as a means of effective and comfortable interaction with the public is emphasised. Particular attention is paid to the coping strategy of a police officer, which allows him/her to effectively cope with stressful situations arising during the performance of official tasks. Through the analysis of the main powers of police officers, the need for them to have emotional intelligence, which includes such components as empathy, understanding, recognition and the ability to manage their own and other people’s emotions, is determined. Moreover, the article shows the importance for police work of such an individual property of a person as the level of internality, which determines the ability of a person to control and manage his/her behaviour, take responsibility for his/her own actions, influence the formation and development of such internal factors as motivation, efficiency of decision-making in stressful situations. Finally, it is concluded that the interrelation of external and internal components is important for determining the level of professional success of a police officer.

Background: Transition from education to the workforce has been recognised as difficult and linked to ‘reality shock.’ Due to the unprecedented circumstances of the COVID-19 pandemic, many student nurses opted in for NHS emergency placements and prematurely transitioned to the workplace, which calls for an in-depth investigation of the work readiness and transition experiences of this cohort.Aim: The aim of this study was to investigate self-perceived work readiness, the effectiveness of support provided by the universities and the NHS as well as explore the experiences of student nurses who responded to the COVID-19 crisis to understand the impact of this early transition to the clinical workforce.Design: A mixed methods study was conducted. It included two stages: (1) an online survey consisting of a work readiness questionnaire and close- and open-ended questions about received support; and (2) online semi-structured interviews that were thematically analysed.Methods: Participants were nursing students from Scottish universities who took on emergency NHS placements. Thirty-three (30 females and 3 males) participants completed the survey and 8 of them (all female) participated in semi-structured interviews. The Work Readiness Scale for graduate nurses along with questions about the support received were completed in the first stage of the study.Results: Organisational acumen was perceived by participants as higher than social intelligence, work competence and personal work characteristics. Three superordinate themes emerged: (1) participants expressed appreciation of and need for coordination of support from the university and the NHS as a key factor in easing into their role; (2) they indicated the sense of obligation as the key driver for taking up this placement; (3) placement was seen as an opportunity to understand their role and develop their professional identity.Conclusions: The findings found the importance of support from the clinical placement and academic teams to help with the integration and application of theory into practice. [ABSTRACT FROM AUTHOR]

Recent advances in generative artificial intelligence (AI) and multimodal learning analytics (MMLA) have allowed for new and creative ways of leveraging AI to support K12 students' collaborative learning in STEM+C domains. To date, there is little evidence of AI methods supporting students' collaboration in complex, open‐ended environments. AI systems are known to underperform humans in (1) interpreting students' emotions in learning contexts, (2) grasping the nuances of social interactions and (3) understanding domain‐specific information that was not well‐represented in the training data. As such, combined human and AI (ie, hybrid) approaches are needed to overcome the current limitations of AI systems. In this paper, we take a first step towards investigating how a human‐AI collaboration between teachers and researchers using an AI‐generated multimodal timeline can guide and support teachers' feedback while addressing students' STEM+C difficulties as they work collaboratively to build computational models and solve problems. In doing so, we present a framework characterizing the human component of our human‐AI partnership as a collaboration between teachers and researchers. To evaluate our approach, we present our timeline to a high school teacher and discuss the key insights gleaned from our discussions. Our case study analysis reveals the effectiveness of an iterative approach to using human‐AI collaboration to address students' STEM+C challenges: the teacher can use the AI‐generated timeline to guide formative feedback for students, and the researchers can leverage the teacher's feedback to help improve the multimodal timeline. Additionally, we characterize our findings with respect to two events of interest to the teacher: (1) when the students cross a difficulty threshold, and (2) the point of intervention, that is, when the teacher (or system) should intervene to provide effective feedback. It is important to note that the teacher explained that there should be a lag between (1) and (2) to give students a chance to resolve their own difficulties. Typically, such a lag is not implemented in computer‐based learning environments that provide feedback. Practitioner notes What is already known about this topic Collaborative, open‐ended learning environments enhance students' STEM+C conceptual understanding and practice, but they introduce additional complexities when students learn concepts spanning multiple domains. Recent advances in generative AI and MMLA allow for integrating multiple datastreams to derive holistic views of students' states, which can support more informed feedback mechanisms to address students' difficulties in complex STEM+C environments. Hybrid human‐AI approaches can help address collaborating students' STEM+C difficulties by combining the domain knowledge, emotional intelligence and social awareness of human experts with the general knowledge and efficiency of AI. What this paper adds We extend a previous human‐AI collaboration framework using a hybrid intelligence approach to characterize the human component of the partnership as a researcher‐teacher partnership and present our approach as a teacher‐researcher‐AI collaboration. We adapt an AI‐generated multimodal timeline to actualize our human‐AI collaboration by pairing the timeline with videos of students encountering difficulties, engaging in active discussions with a high school teacher while watching the videos to discern the timeline's utility in the classroom. From our discussions with the teacher, we define two types of inflection points to address students' STEM+C difficulties—the difficulty threshold and the intervention point—and discuss how the feedback latency interval separating them can inform educator interventions. We discuss two ways in which our teacher‐researcher‐AI collaboration can help teachers support students encountering STEM+C difficulties: (1) teachers using the multimodal timeline to guide feedback for students, and (2) researchers using teachers' input to iteratively refine the multimodal timeline. Implications for practice and/or policy Our case study suggests that timeline gaps (ie, disengaged behaviour identified by off‐screen students, pauses in discourse and lulls in environment actions) are particularly important for identifying inflection points and formulating formative feedback. Human‐AI collaboration exists on a dynamic spectrum and requires varying degrees of human control and AI automation depending on the context of the learning task and students' work in the environment. Our analysis of this human‐AI collaboration using a multimodal timeline can be extended in the future to support students and teachers in additional ways, for example, designing pedagogical agents that interact directly with students, developing intervention and reflection tools for teachers, helping teachers craft daily lesson plans and aiding teachers and administrators in designing curricula. What is already known about this topic Collaborative, open‐ended learning environments enhance students' STEM+C conceptual understanding and practice, but they introduce additional complexities when students learn concepts spanning multiple domains. Recent advances in generative AI and MMLA allow for integrating multiple datastreams to derive holistic views of students' states, which can support more informed feedback mechanisms to address students' difficulties in complex STEM+C environments. Hybrid human‐AI approaches can help address collaborating students' STEM+C difficulties by combining the domain knowledge, emotional intelligence and social awareness of human experts with the general knowledge and efficiency of AI. What this paper adds We extend a previous human‐AI collaboration framework using a hybrid intelligence approach to characterize the human component of the partnership as a researcher‐teacher partnership and present our approach as a teacher‐researcher‐AI collaboration. We adapt an AI‐generated multimodal timeline to actualize our human‐AI collaboration by pairing the timeline with videos of students encountering difficulties, engaging in active discussions with a high school teacher while watching the videos to discern the timeline's utility in the classroom. From our discussions with the teacher, we define two types of inflection points to address students' STEM+C difficulties—the difficulty threshold and the intervention point—and discuss how the feedback latency interval separating them can inform educator interventions. We discuss two ways in which our teacher‐researcher‐AI collaboration can help teachers support students encountering STEM+C difficulties: (1) teachers using the multimodal timeline to guide feedback for students, and (2) researchers using teachers' input to iteratively refine the multimodal timeline. Implications for practice and/or policy Our case study suggests that timeline gaps (ie, disengaged behaviour identified by off‐screen students, pauses in discourse and lulls in environment actions) are particularly important for identifying inflection points and formulating formative feedback. Human‐AI collaboration exists on a dynamic spectrum and requires varying degrees of human control and AI automation depending on the context of the learning task and students' work in the environment. Our analysis of this human‐AI collaboration using a multimodal timeline can be extended in the future to support students and teachers in additional ways, for example, designing pedagogical agents that interact directly with students, developing intervention and reflection tools for teachers, helping teachers craft daily lesson plans and aiding teachers and administrators in designing curricula. [ABSTRACT FROM AUTHOR]

Introduction: The extant study was conducted over a cross-sectional period and aimed to assess the effect of intrapersonal on the interpersonal dimensions of Emotional Intelligence among University Students. Methods: A literature survey was carried out, and the study's hypotheses were framed. Utilising a standardised Emotional Intelligence Scale, a widely accepted and validated measurement tool in the field, for measurement, the survey was disseminated in digital and physical formats. The researchers employed the snowball sampling technique to distribute the questionnaires and recruit volunteers for the study. The data collection period spanned from August 2023 through September 2023. The demographic information of the individuals was described using the SPSS 25 software, while the dataset for the personal and social competencies was analysed using the SmartPLS software. Results and discussion: The research reveals a statistically significant association between the variables under investigation. Specifically, there exists a negative correlation between Motivation and Social Skills, as well as between Self-regulation and Social Awareness. These findings open up exciting opportunities for future research, inspiring further exploration into the development of intrapersonal and interpersonal competencies among students. [ABSTRACT FROM AUTHOR]

In contemporary higher education within STEM fields, fostering and assessing sustainability competencies is essential for promoting lifelong learning with a comprehensive understanding of the relationships between innovation and environmental, social, and economic factors. However, training and grading processes for these competencies face significant challenges due to the intricate, adaptable, and multi-modal nature of current academic models. Better understandings and approaches to educating higher education STEM students in sustainability are paramount. Therefore, we have conducted a data-driven analysis on 159,482 records from 22 STEM programs at Tecnologico de Monterrey between 2019 and 2022, employing data science methodologies. These competencies align with the four dimensions of the UNESCO program "Educating for a Sustainable Future": social, environmental, economic, and political. The study aims to identify the primary challenges faced by students in developing sustainability competencies within this flexible and multi-modal academic environment. Notably, the analysis revealed a widespread distribution of courses with sustainability competencies across all semesters and programs. By the end of the first semester, 93.5% of students had been assessed in at least one sustainability competency, increasing to 96.7% and 97.2% by the end of the second and third semesters, respectively. Furthermore, findings indicate that sustainability competencies are assessed 21 times on average by the end of the sixth semester, with varying levels of development. Interestingly, no significant differences were observed in competency development based on gender, age, or nationality. However, certain competencies such as Commitment to sustainability, Ethical and citizen commitment, and Social Intelligence posed notable challenges across programs and semesters. [ABSTRACT FROM AUTHOR]

The Multiple Intelligences (MI) Theory by Howard Gardner emphasises that individuals have a unique blend of "capabilities" ("intelligences"), differing significantly from the traditional concept of intelligence measured by conventional intelligence quotient (IQ) tests. This cross-sectional, multiinstitutional study aimed to compare the MI of medical students from three Malaysian medical schools, investigate the effects of demographic factors on the MI of students with diverse cultural and socio-economic backgrounds, and examine the effects of MI on academic performance. The MI Inventory was used to assess the MI of medical students. Path analysis was carried out using the SmartPLS software version 2.0. Inter-institutional differences in MI were observed among the students. University A students (53.51 ± 21.99) scored significantly higher than University B students (46.70 ± 20.34) in the naturalist domain (p = 0.05). University A students also scored significantly higher (58.35 ± 21.30) than University B (50.26 ± 19.49; p = 0.014) and University C students (46.90 ± 21.58; p = 0.008) in the musical/rhythmic domain. In the verbal/linguistic domain, University A students (47.94 ± 21.06) scored significantly higher than University C students (39.05 ± 19.23; p = 0.05). Path analysis highlighted a statistically significant effect of family income on the musical intelligence (β = 0.220, t = 2.005, p < 0.05), a domain closely related to verbal/linguistic intelligence. Students from all three medical schools consistently achieved the lowest score in the verbal/linguistic domain and the highest score in the intrapersonal intelligence domain. These findings suggest the need for interventions to enhance language proficiency among medical students. Emphasising MI would make medical education more comprehensive, ultimately enhancing learning in their academic pursuit. [ABSTRACT FROM AUTHOR]

This essay questions the framing of socioemotional development as a separate concomitant of cognitive development in gifted individuals. Rather, it argues, first, that socioemotional development of the gifted is not separate from giftedness. Second, socioemotional development is not even cleanly and clearly separable from cognitive development. Third, giftedness and even intelligence do not reside inside the person—they are not personal properties but rather interactions of persons with tasks and situations. In sum, giftedness needs to be viewed in a holistic context that encompasses integrated cognitive, socio-emotional, task, and situational contextual elements. [ABSTRACT FROM AUTHOR]

The widespread application of mobile robots holds significant importance for advancing social intelligence. However, as the complexity of the environment increases, existing Obstacle Avoidance Path Planning (OAPP) methods tend to fall into local optimal paths, compromising reliability and practicality. Therefore, based on the Spider-Wasp Optimizer (SWO), this paper proposes an improved OAPP method called the LMBSWO to address these challenges. Firstly, the learning strategy is introduced to enhance the diversity of the algorithm population, thereby improving its global optimization performance. Secondly, the dual-median-point guidance strategy is incorporated to enhance the algorithm's exploitation capability and increase its path searchability. Lastly, a better guidance strategy is introduced to enhance the algorithm's ability to escape local optimal paths. Subsequently, the LMBSWO is employed for OAPP in five different map environments. The experimental results show that the LMBSWO achieves an advantage in collision-free path length, with 100% probability, across five maps of different complexity, while obtaining 80% fault tolerance across different maps, compared to nine existing novel OAPP methods with efficient performance. The LMBSWO ranks first in the trade-off between planning time and path length. With these results, the LMBSWO can be considered as a robust OAPP method with efficient solving performance, along with high robustness. [ABSTRACT FROM AUTHOR]

Copyright of Pamukkale University Journal of Education is the property of Pamukkale University Journal of Education and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Cuadernos de Psicología del Deporte is the property of Cuadernos de Psicologia del Deporte and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Al-Adab / Al-ādāb is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Artificial intelligence (AI) drives new modes of learning and improves the workflow of instructors. Nevertheless, there are concerns about academic integrity, plagiarism, and the reduction of critical thinking in higher education. Therefore, it is important to record and analyze university social sciences students' attitudes toward AI, which is a significant predictor of later use of AI technologies. A sample of 190 university students (82.45% female) from a Greek social sciences department was selected. Descriptive statistics revealed that students' attitudes toward AI were mostly positive. A principal components analysis confirmed a three-component solution of attitudes toward AI, comprising cognitive, behavioral, and emotional dimensions. Comparative analysis of the three components indicated that the emotional dimension was the highest ranked, followed by the cognitive and behavioral dimensions. Pairwise correlation analyses revealed that the strongest correlate of cognitive, behavioral, and emotional components of attitudes toward AI was the future frequency of AI use, followed by general feelings of safety with technology. In conclusion, students display more emotional and cognitive favorable dispositions toward AI. The social background of the students and the prospective future use of AI play a key role in the formulation of attitudes toward AI. University educators need to provide more teaching and learning about AI to improve students' attitudes toward AI and future AI use. [ABSTRACT FROM AUTHOR]