The neural correlates of working memory training in typically developing children     

Jonathan S. Jones  Anna-Lynne R. Adlam  Abdelmalek Benattayallah  Fraser N. Milton 《Child development》2022,93(3):815-830

Working memory training improves children's cognitive performance on untrained tasks; however, little is known about the underlying neural mechanisms. This was investigated in 32 typically developing children aged 10–14 years (19 girls and 13 boys) using a randomized controlled design and multi-modal magnetic resonance imaging (Devon, UK; 2015–2016). Training improved working memory performance and increased intrinsic functional connectivity between the bilateral intraparietal sulci. Furthermore, improvements in working memory were associated with greater recruitment of the left middle frontal gyrus on a complex span task. Repeated engagement of fronto-parietal regions during training may increase their activity and functional connectivity over time, affording greater working memory performance. The plausibility of generalizable cognitive benefits from a neurobiological perspective and implications for neurodevelopmental theory are discussed.  相似文献   

Editorial          下载免费PDF全文

Howard T. Everson 《Educational Measurement》2018,37(2):3-3

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Roger A. Lohmann. (2016). Above the Bottom Line: Financial Management in Human Services. Washington,DC: NASW Press (322 pp., $46.00, paperback,ISBN# 978-0871014986)     

Karun K. Singh 《Journal of Teaching in Social Work》2018,38(2):238-240

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Editorial     

B. Sury 《Resonance》2018,23(7):723-725

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Genetic Polymorphism of Angiotensin II Type 1 Receptors and Their Effect on the Clinical Outcome of Captopril Treatment in Arab Iraqi Patients with Acute Coronary Syndrome (Mid Euphrates)     

Fadhaa A. Ghafil  Bassim I. Mohammad  Hussain S. Al-Janabi  Najah R. Hadi  Hayder A. Al-Aubaidy 《Indian journal of clinical biochemistry : IJCB》2021,36(1):81

Genetic variation in the angiotensin II type 1 receptor (AT1R) has an important effect on the outcome of acute coronary syndrome (ACS) initiated treatment with captopril. This study aims to investigate the impact of genetic polymorphism of AT1R (rs5186 and rs275651) on the ACS outcome in Iraqi patients treated with captopril. A total of 250 Iraqi individuals with ACS were included in this case—control study and they were divided into two study groups; Study group 1 included 125 participants who were prescribed captopril, 25 mg twice daily and study group 2 included 125 participants who received no captopril as part of their ACS treatment (control study). The AT1R gene (rs5186) CC genotype was found to be associated with ST-elevation myocardial infarction (STEMI) (Odd’s ratio (O.R) = 1.2, P = 0.7), while AC was associated with Non-ST-elevation myocardial infarction (NSTEMI) and unstable angina (UA) (O.R = 1.2, P = 0.8). AC genotype is more prone to have Percutaneous coronary intervention (PCI) after ACS attack (O.R = 1.2, P = 0.6). CC genotype had a risk to get less improvement (O.R = 1.6, P = 0.5), so might require higher doses of captopril during acute coronary insult. The AT1R gene (rs275651) AA genotype was associated with UA (O.R = 1.3, P = 0.9). AA and AT genotypes were more prone to have PCI after ACS attack (O.R = 3.9 P = 0.2, O.R = 3.5, P = 0.3 respectively) and thus requiring higher doses of captopril. We conclude that the AT1R rs5186, rs275651 genetic polymorphisms might partially affect the clinical outcome of ACS patients treated with captopril and might have captopril resistance which requires higher doses.  相似文献   

The Evolution of U.S. Museums and Science Centers as Informal Learning Environments     

Renee M. Clary 《Science & Education》2018,27(3-4):371-377

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The Historical Heart of Atmospheric Science     

Anthony J. Sadar 《Science & Education》2018,27(1-2):233-235

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What motivates enrolment in programming MOOCs?     

Piret Luik  Reelika Suviste  Marina Lepp  Tauno Palts  Eno Tõnisson  Merilin Säde  Kaspar Papli 《British journal of educational technology : journal of the Council for Educational Technology》2019,50(1):153-165

Learners who enrol in massive open online courses (MOOCs) have different backgrounds and tend to have different motivations than learners in traditional courses. Based on value-expectancy theory, an instrument was developed to measure motivation for enrolling in a programming MOOC. A study with 1229 adult participants in Estonian-language programming course “About Programming” was conducted to validate the instrument. Results of confirmatory factor analysis validated the 7-factor scale named factors influencing enrolment in MOOC (FIEM). FIEM comprises three factors of expectancies, three factors of values and one factor of social influence. The highest and lowest rated motivational factors influencing enrolment in programming MOOC are discussed in the paper. Interest in and expectations for the course, personal suitability of distance learning and suitability for family and work are the highest-rated motivational factors for those who enrol in MOOC. Usefulness related to own children, social influence and usefulness to related to certification were the lowest rated. The results of this study can be useful for designers of programming MOOCs and the developed scale might be used in future studies.  相似文献   

TAM and stages of adoption of blended learning in higher education by application of data mining techniques     

Antonio Víctor Martín-García  Fernando Martínez-Abad  David Reyes-González 《British journal of educational technology : journal of the Council for Educational Technology》2019,50(5):2484-2500

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Digital Module 16: Longitudinal Data Analysis     

Jeffrey R. Harring  Tessa L. Johnson 《Educational Measurement》2020,39(3):137-138

In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module begins with a nontechnical overview of longitudinal data analyses drawing distinctions with cross-sectional analyses in terms of research questions to be addressed. Nuances of longitudinal designs, timing of measurements, and the real possibility of missing data are then discussed. The three interconnected components of the LME model—(1) a model for individual and mean response profiles, (2) a model to characterize the covariation among the time-specific residuals, and (3) a set of models that summarize the extent that individual coefficients vary—are discussed in the context of the set of activities comprising an analysis. Finally, they demonstrate how to estimate the linear mixed effects model within an open-source environment (R). The digital module contains sample R code, diagnostic quiz questions, hands-on activities in R, curated resources, and a glossary.  相似文献