91 research outputs found
Can Maths Apps Add Value to Young Children's Learning? A Systematic Review and Content Analysis
Educational maths applications (apps) are
an emerging trend in children’s learning
environments aiming to raise their mathematical
attainment. However, with over 200,000
educational apps available within the App Store
(Apple, 2014), deciding which apps to use poses
a significant challenge to teachers, parents,
and policy makers. The current study aimed to
advance our understandings of whether and how
educational maths apps can support children’s
learning, as well as outline gaps in current
research evidence and practice. In doing so, the
current study included: /
• A systematic review (Part 1) to synthesise the
current evidence on educational maths apps
for young children in the first three years of
compulsory school (e.g., ages 4-7 years in
England; ages 5-8 years in the USA). /
• A content analysis (Part 2) to examine the
content and design features of different
educational maths apps and how they may
support children’s learning
Understanding how educational maths apps can enhance learning: A content analysis and qualitative comparative analysis
Educational applications (apps) are ubiquitous within children's learning environments and emerging evidence has demonstrated their efficacy. However, it remains unclear what the active ingredients (ie, mechanisms), or combination of ingredients, of successful maths apps are. The current study developed a new, open-access, three-step framework for assessing the educational value of maths apps, comprised of type of app, mathematical content and app design features. When applied to a selection of available maths apps previously evaluated with children in the first 3 years of school (the final sample included 23 apps), results showed that practice-based apps were the most common app type tested (n = 15). Basic number skills, such as number representation and relationships, were the most common area of mathematics targeted by apps (n = 21). A follow-up qualitative comparative analysis showed observed learning outcomes with maths apps were enhanced when apps combined the following: a scaffolded and personalised learning journey (programmatic levelling) and explanations of why answers were right or wrong (explanatory feedback), as well as praise, such as ‘Great job!’ (motivational feedback). This novel evidence stresses the significance of feedback and levelling design features that teaching practitioners and other stakeholders should consider when deciding which apps to use with young children. Directions for future research are discussed
Pennsylvania Folklife Vol. 27, No. 4
• The Dialect Church Service in the Pennsylvania German Culture • Witchcraft Belief in a Pennsylvania German Family • German Settlement of Northern Chester County in the 18th Century • Medical Practice in Philadelphia at the Time of the Yellow Fever Epidemic, 1793 • Folkloric Aspects of the Common Law in Western Pennsylvania, 1790-1799 • Runaway Advertisements: A Source for the Study of Working-Class Costumehttps://digitalcommons.ursinus.edu/pafolklifemag/1078/thumbnail.jp
Understanding how educational maths apps can enhance learning: A content analysis and qualitative comparative analysis
Educational applications (apps) are ubiquitous within children's learning environments and emerging evidence has demonstrated their efficacy. However, it remains unclear what the active ingredients (ie, mechanisms), or combination of ingredients, of successful maths apps are. The current study developed a new, open‐access, three‐step framework for assessing the educational value of maths apps, comprised of type of app, mathematical content and app design features. When applied to a selection of available maths apps previously evaluated with children in the first 3 years of school (the final sample included 23 apps), results showed that practice‐based apps were the most common app type tested (n = 15). Basic number skills, such as number representation and relationships, were the most common area of mathematics targeted by apps (n = 21). A follow‐up qualitative comparative analysis showed observed learning outcomes with maths apps were enhanced when apps combined the following: a scaffolded and personalised learning journey (programmatic levelling) and explanations of why answers were right or wrong (explanatory feedback), as well as praise, such as ‘Great job!’ (motivational feedback). This novel evidence stresses the significance of feedback and levelling design features that teaching practitioners and other stakeholders should consider when deciding which apps to use with young children. Directions for future research are discussed. Practitioner notes: What is already known about this topic Educational apps have been shown to support maths attainment in the first 3 years of school. Several existing frameworks have attempted to assess the educational value of some of these maths apps. Emerging experimental evidence also demonstrates the benefits of specific app design features, including feedback and levelling. What this paper adds Practice‐based maths apps are the most common type of app previously evaluated with young children. These evaluated maths apps have mostly focused on basic number skills. The combination of explanatory and motivational feedback, with programmatic levelling (either dynamic or static), was a necessary condition for enhancing learning outcomes with maths apps. Implications for practice and policy The inclusion of feedback and levelling in maths apps should be considered by app developers when designing apps, and by educational practitioners and parents when deciding which apps to use with their children. Further consideration is also needed for the development of educational apps that include a broad range of maths skills
Chronic inflammatory arthritis drives systemic changes in circadian energy metabolism
SignificanceRheumatoid arthritis (RA) is a debilitating chronic inflammatory disease in which symptoms exhibit a strong time-of-day rhythmicity. RA is commonly associated with metabolic disturbance and increased incidence of diabetes and cardiovascular disease, yet the mechanisms underlying this metabolic dysregulation remain unclear. Here, we demonstrate that rhythmic inflammation drives reorganization of metabolic programs in distal liver and muscle tissues. Chronic inflammation leads to mitochondrial dysfunction and dysregulation of fatty acid metabolism, including accumulation of inflammation-associated ceramide species in a time-of-day-dependent manner. These findings reveal multiple points for therapeutic intervention centered on the circadian clock, metabolic dysregulation, and inflammatory signaling
16th Annual Environmental Law Institute
Materials from the 16th Annual Environmental Law Institute held by UK/CLE in May 2000
Gender differences in behavioral regulation in four societies: The United States, Taiwan, South Korea, and China
The current study investigates gender differences in behavioral regulation in four societies: the United States, Taiwan, South Korea, and China. Directly assessed individual behavioral regulation (Head–Toes–Knees–Shoulders, HTKS), teacher-rated classroom behavioral regulation (Child Behavior Rating Scale, CBRS) and a battery of school readiness assessments (mathematics, vocabulary, and early literacy) were used with 814 young children (ages 3–6 years). Results showed that girls in the United States had significantly higher individual behavioral regulation than boys, but there were no significant gender differences in any Asian societies. In contrast, teachers in Taiwan, South Korea, as well as the United States rated girls as significantly higher than boys on classroom behavioral regulation. In addition, for both genders, individual and classroom behavioral regulation were related to many aspects of school readiness in all societies for girls and boys. Universal and culturally specific findings and their implications are discussed
The multiplex bead array approach to identifying serum biomarkers associated with breast cancer
Introduction Breast cancer is the most common type of cancer seen in women in western countries. Thus, diagnostic modalities sensitive to early-stage breast cancer are needed. Antibody-based array platforms of a data-driven type, which are expected to facilitate more rapid and sensitive detection of novel biomarkers, have emerged as a direct, rapid means for profiling cancer-specific signatures using small samples. In line with this concept, our group constructed an antibody bead array panel for 35 analytes that were selected during the discovery step. This study was aimed at testing the performance of this 35-plex array panel in profiling signatures specific for primary non-metastatic breast cancer and validating its diagnostic utility in this independent population. Methods Thirty-five analytes were selected from more than 50 markers through screening steps using a serum bank consisting of 4,500 samples from various types of cancer. An antibody-bead array of 35 markers was constructed using the Luminex (TM) bead array platform. A study population consisting of 98 breast cancer patients and 96 normal subjects was analysed using this panel. Multivariate classification algorithms were used to find discriminating biomarkers and validated with another independent population of 90 breast cancer and 79 healthy controls. Results Serum concentrations of epidermal growth factor, soluble CD40-ligand and proapolipoprotein A1 were increased in breast cancer patients. High-molecular-weight-kininogen, apolipoprotein A1, soluble vascular cell adhesion molecule-1, plasminogen activator inhibitor-1, vitamin-D binding protein and vitronectin were decreased in the cancer group. Multivariate classification algorithms distinguished breast cancer patients from the normal population with high accuracy (91.8% with random forest, 91.5% with support vector machine, 87.6% with linear discriminant analysis). Combinatorial markers also detected breast cancer at an early stage with greater sensitivity. Conclusions The current study demonstrated the usefulness of the antibody-bead array approach in finding signatures specific for primary non-metastatic breast cancer and illustrated the potential for early, high sensitivity detection of breast cancer. 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Credible knowledge: A pilot evaluation of a modified GRADE method using parent-implemented interventions for children with autism
Abstract
Background
Decision-making in child and youth mental health (CYMH) care requires recommendations that are developed through an efficient and effective method and are based on credible knowledge. Credible knowledge is informed by two sources: scientific evidence, and practice-based evidence, that reflects the "real world" experience of service providers. Current approaches to developing these recommendations in relation to CYMH will typically include evidence from one source or the other but do not have an objective method to combine the two. To this end, a modified version of the Grading Recommendations Assessment, Development and Evaluation (GRADE) approach was pilot-tested, a novel method for the CYMH field.
Methods
GRADE has an explicit methodology that relies on input from scientific evidence as well as a panel of experts. The panel established the quality of evidence and derived detailed recommendations regarding the organization and delivery of mental health care for children and youth or their caregivers. In this study a modified GRADE method was used to provide precise recommendations based on a specific CYMH question (i.e. What is the current credible knowledge concerning the effects of parent-implemented, early intervention with their autistic children?).
Results
Overall, it appeared that early, parent-implemented interventions for autism result in positive effects that outweigh any undesirable effects. However, as opposed to overall recommendations, the heterogeneity of the evidence required that recommendations be specific to particular interventions, based on the questions of whether the benefits of a particular intervention outweighs its harms.
Conclusions
This pilot project provided evidence that a modified GRADE method may be an effective and practical approach to making recommendations in CYMH, based on credible knowledge. Key strengths of the process included separating the assessments of the quality of the evidence and the strength of recommendations, transparency in decision-making, and the objectivity of the methods. Most importantly, this method combined the evidence and clinical experience in a more timely, explicit and simple process as compared to previous approaches. The strengths, limitations and modifications of the approach as they pertain to CYMH, are discussed
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