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Aim: To examine resilience in Science, Technology, Engineering, and Mathematics (STEM) learning within an ecological model, identifying the psychological processes associated with resilient, and non-resilient learning to develop a framework for promoting STEM resilience. Sample and method: From a sample of secondary-school students (n = 4,936), 1,577 students who found their STEM lesson difficult were identified. Students were assessed on three resilience capabilities and asked to write a commentary on how they responded to the lesson. Results: Factor analysis revealed that resilience in STEM learning could be positioned within the ecological systems model, with students' resilience being comprised of three capabilities; the ability to quickly and easily recover (Recovery), remain focussed on goals (Ecological), and naturally adjust (Adaptive capacity). Using a linguistic analysis programme, we identified the prevalence of words within the student commentaries which related to seven psychological processes. Greater ability to recover was negatively related to negative emotional processes. To increase the specificity of this relationship, we identified high and low resilient students and compared their commentaries. Low resilient students used significantly more anger words. Qualitative analysis revealed interpersonal sources of anger (anger at teacher due to lack of support) and intrapersonal sources of anger (including rumination, expression and control, and seeking distraction). Conclusions: Anger is a key process that distinguishes students who struggle to recover from a difficult STEM lesson. An ecological systems model may prove useful for understanding STEM resilience and developing intervention pathways. Implications for teacher education include the importance of students' perceptions of teacher support.

Learning in Science, Technology, Engineering, and Mathematics (STEM) is challenging, leaving many students to give up on these subjects. Specifically, females are underrepresented in STEM industries. Identifying how male and female students deal with STEM learning challenges, and how this relates to learning outcomes, may inform teaching that best supports the preferences of individual students. This study asked secondary school students, who had just completed a STEM lesson that they reported as finding difficult (n = 3758; male = 51.2%), to write narratives about how they dealt with the lesson. Narratives were analyzed using a linguistic text analysis program to identify core psychological processes contained within the narratives from lessons in science n = 1305 (males = 46.3%), technology n = 589 (males = 63.7%), engineering n = 202 (males = 57.9%), and mathematics n = 1662 (males = 49.9%). Students were also asked to score how well they think they did in the difficult lesson (learning outcome). Pearson's correlations between students' use of core psychological processes and their perceptions of lesson success were computed separately for males and females. Common strategies emerged across the STEM subjects: for female students, positive learning outcomes were associated with positive emotions, social processes, rewards, and strategic thinking. For male students, positive learning outcomes were associated with motivation around the risk of failing, rationalizing the problem, and strategic thinking. Negative emotion was associated with a negative learning outcome for both broadly defined genders, but this was more evident across the subjects for females. We specify our understanding of this strategy by reporting data separately for the STEM subjects and the implications for STEM pedagogy.

This study enhances our understanding of the psychological factors influencing farmers' adoption of sustainable farming practices, specifically those related to achieving NetZero emissions. It achieves this by integrating various psychological theories with practical farming methods within the context of Behavioral-Adoption and Purpose-Driven contexts. The research consisted of two studies. Study 1 employed Exploratory Factor Analysis (EFA) to analyze responses from 438 UK farmers regarding their attitudes toward a series of Net Zero policy commitments, drawing on psychological theories including the Unified Theory of Acceptance and Use of Technology, the Theory of Planned Behavior, the Prototype Willingness Model, Implementation Intentions, Self-Determination Theory, Eudaimonia, and the Integrated Model of Health Literacy. The findings revealed a new Integrated Motivation Model for Sustainable Farming that comprises seven factors: Agricultural Commitment and Stewardship, Sustainable Farming Readiness and Confidence, Sustainable Incentive Engagement and Acceptance, Climate Adaptation Competence and Confidence, Net Zero Accountability and Reporting Commitment, Community Influence and Commitment in Sustainable Farming, and Innovation and Technological Competence. Study 2 validated these factors through the development of a 21-item Integrated Motivation Model for Sustainable Farming scale and use of Confirmatory Factor Analysis (CFA) to confirm the 7-factor structure using a subsample of 418 UK farmers from Study 1 and an additional 230 US farmers. Furthermore, Study 2 tested the concurrent validity of the new scale by demonstrating significant associations with reported sustainable farming behaviors. These findings underscore the complex interplay of motivational, cognitive, and social processes influencing sustainable farming practices. The integrated psychological model developed through this research provides parsimonious and valuable insights for policymakers to foster sustainable practices in farming effectively. The confirmation of this model across farming populations enhances its generalizability and potential to guide targeted interventions aimed at achieving behavioral change in pursuit of Net Zero targets in agriculture. [ABSTRACT FROM AUTHOR]

This study explores the intricate relationship between social media usage and the mental health of young individuals by leveraging the insights of 492 UK school headteachers. It adopts a novel multidisciplinary approach, integrating perspectives from psychology, sociology, education studies, political science, philosophy, media studies, linguistics, social work, anthropology, and health sciences. The application of thematic analysis, powered by ChatGPT-4, identifies a predominantly negative perspective on the impact of social media on young people, focusing on key themes across various disciplines, including mental health, identity formation, social interaction and comparison, bullying, digital literacy, and governance policies. These findings culminated in the development of the five-factor Comprehensive Digital Influence Model, suggesting five key themes (Self-Identity and Perception Formation, Social Interaction Skills and Peer Communication, Mental and Emotional Well-Being, Digital Literacy, Critical Thinking, and Information Perception, and Governance, Policy, and Cultural Influence in Digital Spaces) to focus the impacts of social media on young peoples' mental health across primary and secondary educational stages. This study not only advances academic discourse across multiple disciplines but also provides practical insights for educators, policymakers, and mental health professionals, seeking to navigate the challenges and opportunities presented by social media in the digital era. [ABSTRACT FROM AUTHOR]

To explore the importance of text cohesion, we conducted two experiments. We measured online (reading times) and offline (comprehension accuracy) processes for texts that were high and low cohesion. In study one (n?=?60), we manipulated referential cohesion using noun repetition (high cohesion) and synonymy (low cohesion). Students showed enhanced comprehension accuracy and faster comprehension responses for text that were high in referential cohesion. In study two (n?=?52), we examined connective text designs ("because", "and" and "no connective"). Students demonstrated enhanced reading times for text using a "because" connective. Additionally, we examined the individual differences (reading ability, science self-concept and self-esteem) as predictors of achievement with science comprehension tasks. Across both experiments reading ability predicted comprehension with both high (noun-repetition text and "and" text) and low cohesion text (synonym text and "no connective" text). These findings highlight the importance of good reading abilities and text cohesion for promoting science comprehension and learning.

This paper describes a new model of students' concern about indebtedness within a rank-based social norms framework. Study 1 found that students hold highly variable beliefs about how much other students will owe at the end of their degree. Students' concern about their own anticipated debt--and their intention of taking on a part-time job during term time--was best predicted not by the size of the anticipated debt, but by how they, often incorrectly, believed their debt ranked amongst that of others. Study 2 manipulated hypothetical debt amounts experimentally and found that the same anticipated debt was rated as 2.5 times more concerning when it ranked as the second highest being considered than when it was the fifth highest. Study 3 demonstrated that the model applies to evaluation of different types of debt (income contingent loans versus general debt).

The current paper presents a five-factor measurement model of anger summarizing scores on public-domain self-report measures of anger. Exploratory and confirmatory factor analyses of self-report measures of anger (UK, n = 500; USA, n = 625) suggest five replicable latent anger factors: anger-arousal, anger-rumination, frustration-discomfort, anger-regulation, and socially constituted anger. Findings suggested a 5-factor interpretation provided the best fit of the data. We also report evidence of measurement invariance for this 5-factor model of anger across gender, age, and ethnicity. The findings suggest a useful and parsimonious account of anger, summarizing over 50 years of research around the self-report measurement of anger. [ABSTRACT FROM AUTHOR]

This study investigated the characteristics of adolescents reporting very high levels of life satisfaction. Participants (N = 410) were divided into three life satisfaction groups: very high (top 10%), average (middle 25%), and very low (lowest 10%). Results revealed that very happy youths had significantly higher mean scores on all included school, interpersonal, and intrapersonal variables, and significantly lower mean scores on depression, negative affect, and social stress than youths with average and very low levels of life satisfaction. Life meaning, gratitude, self-esteem, and positive affect were found to have a significantly more positive influence on global life satisfaction for the very unhappy than the very happy. Findings suggest that very unhappy youths would benefit most from focused interventions aimed at boosting those variables having the most influence on their level of life satisfaction. Results are discussed in light of previous findings and suggestions for future directions are briefly discussed.