Frontiers in Psychology最新文献

The proliferation of artificial intelligence (AI) tools, which reflect the rapid advancements in technology, has led to their widespread use in various fields, including health, finance and education. The effective and efficient use of AI tools in education is closely related to teachers' awareness in this regard. The objective of this study is to comprehensively ex-amine the AI awareness status of teachers by employing a mixed-method approach. The present study is designed based on a triangulation design and is conducted with a sample of 260 teachers. The findings of the study demonstrate that teachers have a moderate level of AI awareness, and that this awareness improves through AI tool use, receiving training, following publications, and daily internet use. The qualitative findings of the study corroborate the quantitative findings in that they also demonstrate that teachers have limited awareness of conceptual perception, educational use, and positive-negative effects concerning AI tools. The findings further indicate that the majority of educators acknowledge the benefits of AI while also expressing concerns about its limitations, resulting in an ambivalent perception. The prevailing opinion among educators is that AI is not yet capable of replacing teachers due to its inability to replicate affective skills such as empathy and building rapport. However, it is also reported that the effectiveness of this phenomenon is contingent upon conscious utilization.

Students encounter many challenges to academic success. Whereas some students thrive in stressful environments, other students falter. Some students also encounter social and emotional factors that might detract from academic achievement, including negative emotions like stress and anxiety. Academic anxieties refer to negativity, nervousness, and avoidance associated with different academic domains, such as math anxiety, science anxiety, test anxiety, trait (general) anxiety, and writing anxiety. Not only do individuals with high academic anxiety experience stress, but high academic anxiety is associated with decreased academic performance in the specific domain. On average, d/Deaf, DeafBlind, and hard of hearing (DDBHH) people show decreased academic performance compared to hearing populations, but more research is needed to understand how academic anxieties may play a role in creating challenges for DDBHH students. In the present study, we explored the reliability of the Academic Anxiety Inventory (AAI) in a DDBHH sample (N = 145). In this study, each AAI item was presented in both American Sign Language (ASL) and English, providing additional accessibility to DDBHH participants. Results showed that each of the five subscales of the AAI had high reliability. Moreover, a factor analysis showed each of the hypothesized five subscales of the AAI were represented by corresponding factors in this sample. In this DDBHH sample, the AAI showed relatively low intercorrelation between domains of anxiety, demonstrating that the domains of anxiety are relatively independent and separable from one another. Additional results compared the DDBHH with a sample of hearing people from the original psychometric validation of the AAI and explored other relations between the AAI and language background. Overall, these results suggest that the AAI is a reliable and appropriate questionnaire for use with DDBHH participants. Understanding and addressing academic anxieties in DDBHH communities is a priority for encouraging academic achievement. Developing appropriate, culturally sensitive, and accessible ways to reduce the impact of these anxieties is vital to encourage DDBHH students to achieve their potential.

Introduction: The integration of artificial intelligence (AI) into education is rapidly increasing worldwide and governments actively promote teachers' positive attitudes toward AI and its use in instructional practices. Although prior research has highlighted the potential of AI in music education, limited studies have examined the factors influencing pre-service music teachers' intentions to use AI in teaching.

Methods: This study employed an online questionnaire based on an extended Unified Theory of Acceptance and Use of Technology (UTAUT) model. A total of 370 pre-service music teachers participated in the survey, and structural equation modeling was used to examine the determinants of their intentions to integrate AI into teaching.

Results: The proposed UTAUT model explained 62.4% of the variance in pre-service music teachers' intentions to use AI. The results indicated that social influence, performance expectancy, and effort expectancy positively predicted intentions to use AI, whereas education policy and facilitating conditions had negative direct effects. AI usage habit showed no significant effect. Notably, education policy demonstrated positive indirect effects through effort expectancy and social influence, indicating a dual mechanism of policy influence.

Discussion: The findings of this study provide insights into how individual, institutional, and policy-related factors jointly shape pre-service music teachers' intentions to adopt AI in education. This study then discussed implications for AI in music teacher training programs.

The existing microexpression training tool METT only trains the static microexpression recognition ability under neutral background, but does not train the dynamic microexpression recognition ability under expression backgrounds. Therefore, in the current study, the dynamic microexpression recognition ability test DMERT was used as pretest and posttest, the METT recognition techniques were guided and trained, and the dynamic microexpression training tool DMETT was established as a training tool for dynamic microexpression recognition ability. The experiment was conducted in 3 stages (pretest vs. training vs. posttest) × 7 (background expression: sadness vs. Disgust vs. fear vs. anger vs. surprise vs. happiness vs. Neutral) × 2 (background expression emotional arousal: 3 vs. 5) × 6 (dynamic microexpression: sadness vs. Disgust vs. fear vs. anger vs. surprise vs. happiness) × 2 (emotional arousal of dynamic microexpression: 1 → 2 → 3 → 2 → 1 vs. 3 → 4 → 5 → 4 → 3). The results showed that: (1) The DMETT could effectively improve dynamic microexpression recognition ability with good reliability and validity. (2) The METT recognition techniques were suitable for training dynamic microexpression recognition ability. (3) The DMETT could be used as a training tool of dynamic microexpression recognition ability, and can be further verified to serve as a measurement tool of microexpression learning ability in the future. (4) There was no gender difference in general dynamic microexpression recognition ability, but females outperformed males in general dynamic microexpression recognition learning with small effect sizes.

Objective: Student mental health has emerged as an increasingly prominent issue in sustainable educational healthcare systems. Accurately and promptly identifying students' depression and analyzing the key factors associated with it are crucial for improving student mental health.

Method: We propose an artificial intelligence algorithm, GLNet, that integrates Mamba and convolutional layers to extract features from students' demographic, academic, and lifestyle information for depression analysis. The performance of GLNet is validated on the publicly available Student Depression Dataset.

Results: GLNet achieves an accuracy of 88.84% on the Student Depression Dataset, outperforming other methods and verifying its effectiveness in student depression analysis. Factor contribution analysis indicates that academic pressure and financial stress may be associated with student depression, while healthy dietary habits and academic satisfaction may alleviate depression. Subgroup analysis further reveals that a higher Cumulative Grade Point Average may be positively correlated with depression in female students, and unhealthy dietary habits may be linked to depression among doctoral students.

Conclusion: GLNet can serve as a reliable tool for enhancing student mental health. It also provides valuable insights for educators to identify students at risk of depression, contributing to the optimization of student mental health intervention strategies.

Physical activity is an essential pillar for promoting health and comprehensive well-being throughout life. During the COVID-19 pandemic, lockdown and social restriction measures significantly transformed family routines and lifestyles, leading to an increase in sedentary behavior and negative effects on mental health. This article aims to analyze the influence of family support on mental health, mediated by physical activity and sedentary behaviors during the COVID-19 lockdown. A total of 1,345 Mexican adults (68.1% women) participated, responding to validated instruments: the Social Support for Physical Activity Scale, the Godin-Shephard Leisure-Time Physical Activity Questionnaire, the Youth Leisure-Time Sedentary Behavior Questionnaire, and the Positive and Negative Affect Schedule (PANAS). Structural equation modeling analyses showed a satisfactory model fit (χ²/df = 6.71, CFI = 0.931, RMSEA = 0.060). Family support was positively associated with active leisure and, more weakly, with passive leisure. Furthermore, active leisure was related to greater positive affect, while passive leisure was associated with psychological distress. These results highlight the protective role of the family in promoting physical activity and emotional regulation in lockdown contexts. It is recommended to design family intervention programs that integrate educational, affective, and behavioral components to foster active lifestyles and strengthen resilience for future health crises.

Background: Core self evaluations (CSE) are critical for preservice teachers' professional functioning, yet the emotional and attachment related processes that shape CSE remain understudied. This study tested whether academic emotions mediate associations between attachment orientations and CSE.

Methods: A sample of 307 preservice teachers completed self report measures of attachment anxiety and a composite of closeness and dependence, six discrete academic emotions (disappointment, interest, pride, shame, hope, pleasure), and the Core Self Evaluations Scale. We conducted correlational analyses, hierarchical multiple regression, and bootstrapped mediation analyses.

Results: Attachment orientations, academic emotions, and CSE were significantly intercorrelated. In hierarchical regression, attachment anxiety, the closeness and dependence composite, and the six academic emotions together accounted for 47% of variance in CSE (R² = 0.47). Disappointment emerged as the strongest negative predictor of CSE. Bootstrapped mediation models indicated that disappointment fully mediated the negative association between attachment anxiety and CSE, whereas interest and pride jointly mediated the positive association between the closeness and dependence composite and CSE.

Conclusion: Academic emotions, particularly disappointment, play a central role in translating attachment orientations into preservice teachers' core self evaluations. Interventions that reduce academic disappointment and cultivate interest and pride, alongside efforts to foster secure attachment related experiences, may bolster preservice teachers' professional self evaluations.

Introduction: Current explorations of the metaphorical relationship between emotions and water have primarily focused on the literary and linguistic dimensions, where emotions are expressed through the concepts and characteristics of water. However, the cognitive mechanisms underlying their metaphorical connection have not yet been systematically examined.

Methods: This study examined the metaphorical connection and mapping between emotional concepts and water flow via three experiments. Experiment 1 used the Stroop paradigm, presenting emotional words and water flow backgrounds simultaneously to measure participants' reaction times through button presses. Experiments 2 and 3 adopted the Semantic Priming paradigm: Experiment 2 activated emotional words prior to water flow words, while Experiment 3 activated water flow words first, with reaction times measured via button presses in both.

Results: Experiment 1 confirmed a significant metaphorical connection between emotional concepts and water flow (positive emotions-slow-flowing water, negative emotions-turbulent water). Experiments 2 and 3 revealed bidirectional priming effects: activation of positive emotion words accelerated responses to slow-flowing water words, while negative emotion words facilitated responses to turbulent water words; conversely, slow-flowing water words primed faster responses to positive emotion words, and turbulent water words primed faster responses to negative emotion words.

Conclusion: (1) There exists a significant metaphorical association between emotion concepts and water flow. (2) There exists a bidirectional mapping relationship between emotional concepts and water flow.

[This corrects the article DOI: 10.3389/fpsyg.2025.1643464.].

Background: How individuals conceive knowledge and knowing plays a crucial role in psychology education. While often examined at the domain level, the Theory of Integrated Domains in Epistemology (TIDE) suggests that epistemic beliefs may also vary at the level of specific topics.

Methods: We investigated whether epistemic beliefs of psychology students differ depending on the topic under consideration and tested the hypothesis that beliefs would cluster by subdisciplinary proximity (i.e., clinical vs. cognitive topics). Using the Epistemic Thinking Assessment (ETA), we implemented three scenarios addressing depression, schizophrenia, and language acquisition. A counterbalanced repeated-measures design was used with 480 first-year psychology students. Multilevel modeling was applied to distinguish topic effects from sequence effects.

Results: Results indicated significant variation in epistemic beliefs across topics, leading to the rejection of the subdisciplinary hypothesis. Students scored significantly higher on absolutism and lower on evaluativism when reasoning about schizophrenia compared to depression and language acquisition. Thus, the two clinical topics did not elicit similar profiles.

Conclusion: Findings confirm that epistemic beliefs are topic-specific within psychology and are driven by topic characteristics (e.g., perceived biological certainty) rather than disciplinary labels. These results highlight the need for granular, topic-specific approaches in epistemological assessments and critical thinking instruction.