Article
Biodiversity Conservation
Lara Redolfi De Zan, Sarah Rossi de Gasperis, Vincenzo Andriani, Marco Bardiani, Alessandro Campanaro, Silvia Gisondi, Sonke Hardersen, Emanuela Maurizi, Fabio Mosconi, Gianluca Nardi, Livia Zapponi, Pasquale Rombola, Federico Romiti
Summary: In this study, CS data were used to investigate the distribution and conservation gaps of five large saproxylic beetles in Italy. The pre-alpine and Apennines arcs, north-eastern Sicily and eastern Sardinia were identified as hotspots for conservation.
Article
Psychology, Clinical
Walter P. Vispoel, Guanlan Xu, Murat Kilinc
Summary: This study expanded traditional generalizability theory models using structural equation modeling techniques to account for congeneric relationships and different sources of measurement error. The congeneric models showed better fit statistics, higher reliability estimates, and lower measurement error estimates compared to traditional models when applied to Big Five Inventory data.
JOURNAL OF PERSONALITY ASSESSMENT
(2021)
Article
Public Administration
Yang Zhao
Summary: In the era of media convergence, Internet users have diverse levels of access to current political information. Using selective exposure theory, this study used K-means clustering and multinomial logistic regression to examine the relationship between the Big Five personality traits and political information exposure, based on the 2017 Chinese National Survey Data Archive data. The results revealed that Internet users can be classified into three types based on their frequency of access: comprehensive, domestic modern, and apathetic. Highly extroverted individuals were more likely to regularly browse current political information from diverse sources, while highly agreeable individuals favored current political information relayed by domestic modern media. Individuals with high levels of neuroticism paid less attention to current political information.
CHINESE PUBLIC ADMINISTRATION REVIEW
(2023)
Article
Computer Science, Interdisciplinary Applications
David Touretzky, Christina Gardner-McCune, Deborah Seehorn
Summary: This article provides an in-depth examination of how K-12 students should be introduced to Machine Learning and the skills and knowledge they will gain. It discusses the AI4K12 Initiative, which is developing national guidelines for teaching AI in K-12, and outlines the organizational framework and structure of the guidelines. The article also emphasizes the importance of aligning with best practices from Learning Sciences and CS Education research, as well as other standards. It further explores the grade band progression chart for the AI4K12 Big Idea 3 (Learning), providing examples of both horizontal (across grade bands) and vertical (across concepts) progressions. The article concludes by discussing the use of these guidelines to create learning experiences that connect the Five Big Ideas, as well as free online tools that facilitate these experiences.
INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION
(2023)