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Elise M. Walck-Shannon; Heather D. Barton; Shaina F. Rowell; Douglas L. Chalker; Angela Fink – CBE - Life Sciences Education, 2025
Recently, our course team transformed a large-enrollment introductory genetics course from being predominantly lecture based to active learning based. During class sessions, students engaged in problem solving, which occurs when a student attempts to solve a problem without knowing the path to complete it. We designed class activities…
Descriptors: Active Learning, Genetics, Learning Activities, Inquiry
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Mayara S. Bianchim; Melitta A. McNarry; Alan R. Barker; Craig A. Williams; Sarah Denford; Lena Thia; Rachel Evans; Kelly A. Mackintosh – Measurement in Physical Education and Exercise Science, 2024
This study aimed to develop and validate machine learning models to predict intensities in children and adolescents with cystic fibrosis (CF) across different accelerometry brands and placements. Thirty-five children and adolescents with CF (11.6 ± 2.8 yrs; 15 girls) and 28 healthy youth (12.2 ± 2.7 yrs; 16 girls) performed six activities whilst…
Descriptors: Models, Prediction, Children, Adolescents
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Kaito Kawakami; Francesca Procopio; Kaili Rimfeld; Margherita Malanchini; Sophie von Stumm; Kathryn Asbury; Robert Plomin – npj Science of Learning, 2024
Academic underachievement refers to school performance which falls below expectations. Focusing on the pivotal first stage of education, we explored a quantitative measure of underachievement using genomically predicted achievement delta (GPA[delta]), which reflects the difference between observed and expected achievement predicted by genome-wide…
Descriptors: Genetics, Prediction, Academic Achievement, Grade Point Average
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Kaitlin E. Bountress; Daniel Bustamante; Mohammad Ahangari; Fazil Aliev; Steven H. Aggen; Eva Lancaster; The Spit for Science Working Group; Roseann E. Peterson; Jasmin Vassileva; Danielle M. Dick; Ananda B. Amstadter – Journal of American College Health, 2025
Objective: The purpose of this study was to test whether COVID impact interacts with genetic risk (polygenic risk score/PRS) to predict alcohol use disorder (AUD) symptoms. Method: Participants were n = 455 college students (79.6% female, 51% European Ancestry/EA, 24% African Ancestry/AFR, 25% Americas Ancestry/AMER) from a longitudinal study…
Descriptors: COVID-19, Pandemics, Alcohol Abuse, Symptoms (Individual Disorders)
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Dai Zhang; Yanghui Xie; Longsheng Wang; Ke Zhou – npj Science of Learning, 2024
Arithmetic ability is critical for daily life, academic achievement, career development, and future economic success. Individual differences in arithmetic skills among children and adolescents are related to variations in brain structures. Most existing studies have used hypothesis-driven region of interest analysis. To identify distributed brain…
Descriptors: Mathematics Skills, Prediction, Arithmetic, Academic Achievement
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Czenilriene J. Santander; Sharon Y. Lee; Gloria Peters; Carmen J. Marsit; Laura R. Stroud – Merrill-Palmer Quarterly: A Peer Relations Journal, 2024
Despite growing interest in placental epigenetics, the combined impact of prenatal stress and socioeconomic status on placental methylation is still largely understudied. We conducted a study to examine the associations of prenatal stress and socioeconomic factors (household income, Hollingshead socioeconomic index) with placental methylation.…
Descriptors: Stress Variables, Pregnancy, Socioeconomic Status, Prenatal Influences
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Rachael W. Cheung; Chloe Austerberry; Pasco Fearon; Marianna E. Hayiou-Thomas; Leslie D. Leve; Daniel S. Shaw; Jody M. Ganiban; Misaki N. Natsuaki; Jenae M. Neiderhieser; David Reiss – Child Development, 2024
Parenting and children's temperament are important influences on language development. However, temperament may reflect prior parenting, and parenting effects may reflect genes common to parents and children. In 561 U.S. adoptees (57% male) and their birth and rearing parents (70% and 92% White, 13% and 4% African American, and 7% and 2% Latinx,…
Descriptors: Genetics, Nature Nurture Controversy, Child Development, Language Acquisition
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Ellen C. Masters; Kevin M. Antshel; Wendy R. Kates; Natalie Russo – Journal of Autism and Developmental Disorders, 2025
Background: Sensory processing differences are reported both in children with ADHD and in children with autism. Given the substantial overlap between autism and ADHD, the current study examined which sensory features were uniquely predictive of autistic traits after controlling for ADHD symptoms, age, IQ, and sex in a sample of children and…
Descriptors: Attention Deficit Hyperactivity Disorder, Symptoms (Individual Disorders), Sensory Integration, Autism Spectrum Disorders
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Joseph C. Y. Lau; Emily Landau; Qingcheng Zeng; Ruichun Zhang; Stephanie Crawford; Rob Voigt; Molly Losh – Autism: The International Journal of Research and Practice, 2025
Many individuals with autism experience challenges using language in social contexts (i.e., pragmatic language). Characterizing and understanding pragmatic variability is important to inform intervention strategies and the etiology of communication challenges in autism; however, current manual coding-based methods are often time and labor…
Descriptors: Artificial Intelligence, Models, Pragmatics, Language Variation