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10 results for “Primary Science”
Dataset for the publication "The TACS Model: Understanding Teachers' Adoption of Computer Science Pedagogical Content in Primary School"
<p>This dataset contains the quantitative teacher data used to analyse an in service teacher training program for Computer Science that took place from September 2019 to March 2020 in the Canton Vaud in Switzerland. Approximately 180 teachers from the the 5th and 6th grade in primary school (ages 9-11) participated in 3 days of training sessions. At the end of each training session, teachers were asked to fill in a web-based questionnaire providing information relating to their perception of the training sessions and adoption of the computer science activities. The surveys were analysed from three perspectives which are detailed in the corresponding article (the professional development program's perspective, the activities' perspective, the teacher's perspective). The present repository thus contains three csv files, one per analysis. A README is included and provides additional information regarding :</p> <p>- the requirements for re-use. </p> <p>- the survey instrument used</p> <p>- the specific content of the 3 csv files</p>
Supplementary material 10: Institutional collection dashboard: specimens from the collection of the California Academy of Sciences (CAS) from: Integrating and visualizing primary data from prospective and legacy taxonomic literature - Biodiversity Data Journal 3: e5063 (12 May 2015) https://doi.org/10.3897/BDJ.3.e5063
Dashboard charts showing only specimens from the collection of the California Academy of Sciences. This page shows data from species-rank treatments. When viewed using a browser (such as Google Chrome) with an internet connection, this page sends a series of queries to Plazi and integrates the results with the Google Charts API to produce 37 interactive dashboard charts.
Dataset for the evaluation of student-level outcomes of a primary school Computer Science curricular reform
<p>Dataset for the evaluation of student-level outcomes of a primary school Computer Science curricular reform<br> =======================================================</p> <p>• If you publish material based on this dataset, please cite the following :</p> <p> • The Zenodo repository : Laila El-Hamamsy, Barbara Bruno, Jessica Dehler Zufferey, and Francesco Mondada (2023). Dataset for the evaluation of student-level outcomes of a primary school Computer Science curricular reform [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7489244</p> <p> • The associated peer reviewed article that will appear in the International Journal of STEM education : El-Hamamsy, L., Bruno, B., Audrin, C., Chevalier, M., Avry S., Dehler Zufferey, J., and Mondada, F. (2023). How are Primary School Computer Science Curricular Reforms Contributing to Equity? Impact on Student Learning, Perception of the Discipline, and Gender Gaps. arXiv, to appear in the International Journal of STEM Education. https://doi.org/10.48550/arXiv.2306.00820</p> <p>• License: This work is licensed under a Creative Commons Attribution 4.0 International license (CC-BY-4.0)</p> <p>• Creator: El-Hamamsy, L., Bruno, B., Dehler Zufferey, J., and Mondada, F.</p> <p>• Date: May 2nd 2023</p> <p>• Subject: Computer Science; Curricular Reform; Elementary Education; Learning Achievement; Computational Thinking; Perception Survey; Equity; Gender Gaps</p> <p>• Dataset format: CSV</p> <p>• Dataset collection: January 2021 to May 2022</p> <p>• Dataset size : < 100 kB</p> <p>• Dataset content : three excel files. We provide the detailed description of each of the files below. The original questions are available in the associated publication [1]. Please note that these datasets contain missing values due to students either not being present for all data collections or not having the associated teacher-related data.</p> <p>• Abbreviations :<br> - CS : Computer Science<br> - CT : Computational Thinking<br> - PD : Professional Development</p> <p>• Funding : This work was funded by the the NCCR Robotics, a National Centre of Competence in Research, funded by the Swiss National Science Foundation (grant number 51NF40_185543)</p> <p> </p> <p># References</p> <p>[1] El-Hamamsy, L., Bruno, B., Audrin, C., Chevalier, M., Avry S., Dehler Zufferey, J., and Mondada, F. (2023). How are Primary School Computer Science Curricular Reforms Contributing to Equity? Impact on Student Learning, Perception of the Discipline, and Gender Gaps. arXiv, to appear in the International Journal of STEM Education. https://doi.org/10.48550/arXiv.2306.00820</p>
Safety and Effectiveness of the Sight Sciences VISCO™360 Versus SLT in Primary Open Angle Glaucoma
ClinicalTrials.gov study NCT02928289. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Cedar Creek Ecosystem Science Reserve site, station Unknown, study of aboveground net primary productivity in units of gramsPerMeterSquaredPerYear on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Cedar Creek Ecosystem Science Reserve (CDR) contains aboveground net primary productivity measurements in gramsPerMeterSquaredPerYear units and were aggregated to a yearly timescale.
Teaching the process of science with primary literature: Using the CREATE pedagogy in ecological courses
<p>There have been numerous calls for improved pedagogical practices in biological education, and there is a clear need for such improvements in ecology and related curricula. Most ecology-related texts lack pedagogy and are designed to be content-rich. National initiatives, such as Vision & Change, provide guidance on undergraduate biology education, including increasing use of evidence-based active learning, and taking a more conceptual and science practice skills approach. Biology education research is rich with evidence-based teaching practices, which reveal that active learning approaches implemented in thoughtful ways lead to strong learning gains relative to lecture-based course delivery. CREATE (Consider, Read, Elucidate the hypothesis, Analyze and interpret data, Think of the next Experiment) integrates evidence-based active pedagogical practices into one approach to STEM education that focuses heavily on the process of science and science practice skills rather than content delivery by replacing the textbook with selected journal articles. The approach focuses on deep reading and analysis of primary literature; immersing students in the literature is an advantage of the pedagogy. CREATE was developed and tested in other biological disciplines (genetics, molecular biology) that have long been at the forefront of pedagogical best practices in biology. We transformed two upper-level undergraduate ecological courses (Conservation Biology & Biodiversity and Ecology) into CREATE courses. We provide examples of assignments, student work, and assessments of the approach, illustrating the various ways CREATE can be successfully implemented. The approach can be adopted in part, to ease into it and test it out, or in whole. We recommend that ecology teachers consider making their courses more active if they have not already done so; adopting pedagogical practices embedded within CREATE can be a way to achieve active learning. The CREATE approach and other evidence-based pedagogical best practices lead to strong learning gains and more inclusive learning environments.</p>
Teaching the process of science with primary literature: Using the CREATE pedagogy in ecological courses
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National Translational Science Network of Precision-based Immunotherapy for Primary Liver Cancer
ClinicalTrials.gov study NCT04145141. IPD Sharing: YES. Countries: 1. Publications: 0.
Outdoor Science Education and Child Well-being in Primary Schools: Protocol for a Cluster Randomized Controlled Trial on Learning, Connection to Nature, Eco-anxiety, and Stress
ClinicalTrials.gov study NCT07147634. IPD Sharing: NO. Countries: 1. Publications: 0.
Science Education Research in Primary Schools: A Bibliometric Analysis
<p>Bibliometric Data</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.