Adolescents' digital career aspirations: Evidence for gendered pathways in a digital future

Introduction Computers and technology are still perceived as a male domain. As a result of this “digital gender gap” boys aspire careers in the information and communication technology (ICT) branches much more than girls. Guided by the situated expectancy-value theory of motivated behavioral choices, the present study aims to shed light on the predictors of digital career aspirations. Methods Self-report questionnaires were completed by 1018 Austrian adolescents (52.3% girls; 72% non-immigrants; Mage = 13.55, SDage = 0.88) attending 61 Grade 7 and 8 classes located in 17 vocational secondary schools between April and June 2019. Individual and class-level predictors of digital career aspirations were investigated with multilevel modeling. Results Hierarchical linear models revealed that boys, younger adolescents, and second-generation immigrant adolescents had higher levels of digital career aspirations compared to girls, older adolescents, and non-immigrants. Hours spend with the laptop per day, digital self-efficacy and media appraisal positively predicted digital career aspirations on the individual level, while a higher number of immigrants in the classes and higher levels of teacher discussions about media were significant positive predictors on the class level. The model explained 17% of the individual level and 52% of the class level variance. Cross-level interactions were nonsignificant. Conclusions These results have major implications for educational practice. Most importantly, educational interventions should enhance girls' digital self-efficacy believes and media appraisal. Furthermore, teachers should increase their discussion about digital media as they foster adolescents' digital career aspirations and might prevent future gender segregation in the ICT sector.publishedVersio

Threshold corrections to the radiative breaking of electroweak symmetry and neutralino dark matter in supersymmetric seesaw model

We study the radiative electroweak symmetry breaking and the relic abundance of neutralino dark matter in the supersymmetric type I seesaw model. In this model, there exist threshold corrections to Higgs bilinear terms coming from heavy singlet sneutrino loops, which make the soft supersymmetry breaking (SSB) mass for up-type Higgs shift at the seesaw scale and thus a minimization condition for the Higgs potential is affected. We show that the required fine-tuning between the Higgsino mass parameter mu and the SSB mass for up-type Higgs may be reduced at the electroweak scale, due to the threshold corrections. We also present how the parameter mu depends on the SSB B-parameter for heavy singlet sneutrinos. Since the property of neutralino dark matter is quite sensitive to the size of mu, we discuss how the relic abundance of neutralino dark matter is affected by the SSB B-parameter. Taking the SSB B-parameter of order of a few hundreds TeV, the required relic abundance of neutralino dark matter can be correctly achieved. In this case, dark matter is a mixture of bino and Higgsino, under the condition that gaugino masses are universal at the grand unification scale.Comment: 27 pages, 3 figures; references added, discussion about RGEs added, the version published on PR

Information processing of social exclusion: Links with bullying, moral disengagement and guilt

The Social Information Processing (SIP) theory and the Social Cognitive Theory of Moral Agency were integrated to investigate the associations between SIP and bullying, guilt, and moral disengagement. Participants were 341 children and early adolescents (Mage = 11.14). Two social exclusion vignettes were administered to assess three SIP steps (step 2: Attribution of hostile intent; step 3: Selection of antisocial goals, and step 4: Generation of aggressive responses). Guilt was assessed through five vignettes. A self-report measure was used to assess moral disengagement and peer nominations were used to assess bullying perpetration. Moderated mediation analyses were performed to test the hypotheses. Findings indicated that attribution of hostile intent was associated with selection of antisocial goals, which in turn, was associated with the generation of aggressive responses among participants with high levels of bullying and low levels of guilt and moral disengagement. Results are discussed in terms of their theoretical and practical relevance.publishedVersio

Normative and appearance performance-approach goal structures: Two-level factor structure and external linkages

While personal performance-approach goals (PAp goals) have already been successfully bifurcated into normative and appearance PAp goals, the same distinction has not yet been applied to performance-approach goal structures (PAp goal structures). The present study therefore aimed to (a) test the factorial two-level structure of PAp goal structures to establish whether a distinction between normative and appearance components is empirically supported, and (b) explore relations to achievement and approach-oriented achievement goals (mastery-approach goals, normative and appearance personal PAp goals). This study relied on a sample of 1,004 secondary school students (53.38% females, 49 classes). Results from multilevel confirmatory factor analyses revealed that a model with two separate normative and appearance PAp goal structure factors on the individual student level, and one overall PAp goal structure factor on the classroom level fit the data best. On the individual student level, normative PAp goal structures positively predicted achievement, whereas appearance PAp goal structures negatively predicted achievement. Each PAp goal structure type showed the strongest relation to the matching personal PAp goal, but no relations to mastery-approach goals were found. On the classroom level, the high associations between the overall PAp goal structure and personal PAp goals raised concerns on their empirical distinctiveness

“They think that I should defend”: effects of peer and teacher injunctive norms on defending victimized classmates in early adolescents

Norms have been suggested as important characteristics of the social-ecological context for defending victimized peers, but little is known about the contribution of student perceived injunctive norms (regarding the appropriateness of defending) imposed by peers and teachers. To investigate the role of these norms in defending, a sample of 751 early adolescents (51% female; Mageat Time 1:13 years) was assessed at two time points. Defending, as measured by peer- and self-ratings, decreased slightly over a six-month timespan. Three-level models (with time, students, and classrooms as the levels) indicated that both individual- and classroom-level perceived peer injunctive norms (but not teacher injunctive norms) had positive effects on defending over time regardless of the source of the information on defending (peers or self). These findings support programs that encourage defending through peer norms

Within-Person Variation of Affective Well-Being during and after Exercise: Does the Person–Exercise Fit Matter?

Affective well-being is positively linked to regular exercise. Therefore, it is important to identify the factors that influence intra-individual variability of affective well-being. This study investigated (1) whether affective responses vary within an individual and (2) how affective responses are associated with a motive–incentive fit and a skill–task fit. A total of 107 adults (66% females, Mage = 41.79 years old, 58% doing no exercise) took part in three exercise sessions in a random order. Each session lasted 30 min with a break of 10 min between. The sessions were similarly structured but covered diverse activity incentives (e.g., figure vs. social contact vs. aesthetic movements). Intraclass correlation coefficients showed a very high within-person variation of affective valence and enjoyment across the exercise sessions. The results of multi-level regression analyses revealed that associations between perceived competence, considered to be an indicator of the skill–task fit, and affective well-being were moderate to high, whereas those between motive–incentive fit and affective well-being were low to moderate

Asteroid Flyby Cycler Trajectory Design Using Deep Neural Networks

Asteroid exploration has been attracting more attention in recent years. Nevertheless, we have just visited tens of asteroids while we have discovered more than one million bodies. As our current observation and knowledge should be biased, it is essential to explore multiple asteroids directly to better understand the remains of planetary building materials. One of the mission design solutions is utilizing asteroid flyby cycler trajectories with multiple Earth gravity assists. An asteroid flyby cycler trajectory design problem is a subclass of global trajectory optimization problems with multiple flybys, involving a trajectory optimization problem for a given flyby sequence and a combinatorial optimization problem to decide the sequence of the flybys. As the number of flyby bodies grows, the computation time of this optimization problem expands maliciously. This paper presents a new method to design asteroid flyby cycler trajectories utilizing a surrogate model constructed by deep neural networks approximating trajectory optimization results. Since one of the bottlenecks of machine learning approaches is the computation time to generate massive trajectory databases, we propose an efficient database generation strategy by introducing pseudo-asteroids satisfying the Karush-Kuhn-Tucker conditions. The numerical result applied to JAXA's DESTINY+ mission shows that the proposed method is practically applicable to space mission design and can significantly reduce the computational time for searching asteroid flyby sequences

Transition to emerging adulthood during the COVID-19 pandemic: Changes in anxiety and the role of inclusion/exclusion experiences

The study investigated a developmentally sensitive group, emerging adults going through a critical post-secondary educational transition in tandem with the first wave of the COVID pandemic in Finland. The participants (n = 330) were surveyed initially during their first year in secondary education, and again during the pandemic, right after their graduation in summer 2020. According to latent change score models, there was a small mean level increase in anxiety but interestingly, the increase was stronger among individuals with fewer prior anxiety symptoms and fewer prior experiences of loneliness. However, during-pandemic experiences of social inclusion and living with parents were protective against an increase in anxiety symptoms. Findings from this longitudinal study add to the understanding of the complexity of the COVID impact on mental health and the intertwined dynamics of social relations and mental well-being among emerging adults.</p

Measuring emotions in mathematics: the Achievement Emotions Questionnaire—Mathematics (AEQ-M)

Understanding the structure, antecedents, and outcomes of students’ emotions has become a topic of major interest in research on mathematics education. Much of this work is based on the Achievement Emotions Questionnaire—Mathematics (AEQ-M), a self-report instrument assessing students’ mathematics-related emotions. The AEQ-M measures seven emotions (enjoyment, pride, anger, anxiety, shame, hopelessness, boredom) across class, learning, and test contexts (internal structure). Based on control-value theory, it is assumed that these emotions are evoked by control and value appraisals, and that they influence students’ motivation, learning strategies, and performance (external relations). Despite the popularity and frequent use of the AEQ-M, the research leading to its development has never been published, creating uncertainty about the validity of the proposed internal structure and external relations. We close this gap in Study 1 (N = 781 students, Grades 5–10, mean age 14.1 years, 53.5% female) by demonstrating that emotions are organized across contexts and linked to their proposed antecedents and outcomes. Study 2 (N = 699 students, Grade 7 and 9, mean age 14.0 years, 56.9% female) addresses another deficit in research on the AEQ-M, the lack of evidence regarding the assumption that emotions represent sets of interrelated affective, cognitive, motivational, and physiological/expressive components. We close this gap by evaluating extended AEQ-M scales, systematically assessing these components for five core mathematics emotions (enjoyment, anger, anxiety, hopelessness, boredom). Our work provides solid grounds for future research using the AEQ-M to assess emotions and their components in the domain of mathematics