A number of machine learning methods can be employed in the prediction of suicide attempts. However, many models do not predict new cases well in cases with unbalanced data. The present study improved prediction of suicide attempts via the use of a generative adversarial network.

The relation between children's guilt proneness and theory of mind (???) was examined in children (? = 96) aged 7- to 11-years. Guilt proneness was assessed with a self-report scenario-based measure and ToM was examined with a battery of first-order and second-order mental-state tasks. Hierarchical regression analysis revealed that second-order,…

Past research has shown that trauma-exposed refugee people frequently report less specific autobiographical memories, but the characteristics of their future episodic thinking remain largely unexplored. This study investigated the specificity and emotional valence of autobiographical memory and future episodic thinking produced by 120 Rohingya…

In this study, we investigate how the level of work control predictability affects employee creativity. Specifically, we examine whether supervisor and coworker support moderate the predictability-creativity relationship. We use survey data from 128 employee--supervisor dyads from a governmental organization in Belgium. Multilevel analyses…

This SAT® validity study focuses on SAT relationships with student outcomes in career and technical education (CTE) programs at two-year postsecondary institutions. This study draws upon two samples, one with 14,357 students initially enrolled at 55 two-year institutions and another with 46,098 students initially enrolled at 580 institutions.…

Socially anxious adolescents commonly experience impaired interpersonal functioning with unfamiliar, same-age peers. Yet, we lack short screening tools for assessing peer-related impairments. Recent work revealed that a parent-reported, three-item screening tool produced scores that uniquely related to social anxiety concerns. However, this tool…

Parents and teachers have identified the social inclusion of students with complex support needs as one of the most important components of school participation. Previous research has found that the opportunities for, and importance of, social contacts for students with complex support needs vary by educational placement. The purpose of this study…

Parents and teachers have identified the social inclusion of students with complex support needs as one of the most important components of school participation. Previous research has found that the opportunities for, and importance of, social contacts for students with complex support needs vary by educational placement. The purpose of this study…

This quantitative study was conducted to examine if student organization involvement predicted campus belonging in students at the University of Dayton. Using the 2018 and 2021 Multi-Institutional Study of Leadership instruments, all University of Dayton undergraduate students were invited to participate in the study. The COVID-19 pandemic…

Multimodal learning analytics (MMLA) has increasingly been a topic of discussion within the learning analytics community. The Society of Learning Analytics Research is home to the CrossMMLA Special Interest Group and regularly hosts workshops on MMLA during the Learning Analytics Summer Institute (LASI). In this paper, we articulate a set of 12…

Since there are no spaces between words to mark word boundaries in Chinese, it is common to see 2 identical neighboring characters in natural text. Usually, this occurs when there are 2 adjacent words containing the same character (we will call such a coincidental sequence of 2 identical characters "repeated characters"). In the present…

In this article, the authors share five strategies for using a primary teacher's existing picture book library to create engaging, standard-supporting lessons in mathematics. Because teachers choose the books they read according to their students' interests and concerns, the lessons they create are also more likely to be highly responsive to…

The primary objective of this study is to determine the predictive effect of emotional regulation strategies of 5-6-year-old children on their levels of resiliency. The sample group of the study consisted of 77 5-6-year-old children (38 (49.4%) girls; 39 (50.6%) boys) receiving education at kindergartens in Turkey. The data required for the study…

Predicting students at risk of academic failure is valuable for higher education institutions to improve student performance. During the pandemic, with the transition to compulsory distance learning in higher education, it has become even more important to identify these students and make instructional interventions to avoid leaving them behind.…

A Machine Learning framework for predicting enrollment is proposed. The framework consists of Amazon Web Services SageMaker together with standard Python tools for data analytics, including Pandas, NumPy, MatPlotLib, and ScikitLearn. The tools are deployed with Jupyter Notebooks running on AWS SageMaker. Based on three years of enrollment history,…