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Student performance, MOOC logs, knowledge tracing, standardized tests, learning analytics
12,457 datasets
Data Sheet 4 contains a mixed-methods study on medical and dental trainees' perceptions of AI in healthcare. The study includes quantitative survey data from 154 participants and qualitative interview data from 16 participants in the United Arab Emirates. The dataset, authored by Asma F. Syeda and last updated in June 2026, is a 110.5 KB PDF report.
154 survey responses and 16 qualitative interviews from medical and dental trainees in the United Arab Emirates, collected by Asma F. Syeda. The study examines knowledge, attitudes, and educational needs regarding artificial intelligence in healthcare, with data last updated in June 2026.
154 survey responses and 16 qualitative interviews from medical and dental trainees in the United Arab Emirates explore their knowledge, attitudes, and educational needs regarding AI in healthcare. The explanatory sequential mixed-methods study was authored by Asma F. Syeda and last updated in June 2026. Findings highlight moderate AI awareness, limited formal training, and strong support for structured, ethically grounded AI education.
Australian Ocean Data Network hosts data from a year-long field experiment examining the survival of Acropora tenuis coral spat on artificial settlement devices. The study, conducted from November 2018 to December 2019, tracked recruit survival on lattice-grid and grooved-tile devices deployed at Backnumbers Reef on the Great Barrier Reef. Survival was assessed via in situ images taken at multiple time points up to 376 days post-settlement.
OpenStreetMap exports from 2026-05-05 contain features tagged as education amenities on Bouvet Island. The Humanitarian OpenStreetMap Team (HOT) compiled this dataset, which likely includes points for schools, colleges, and universities. Attributes may include names, addresses, capacities, and source information.
Mahdie Yazdani's dataset from figshare, last updated May 2026, contains experimental results on treating simulated mine water. The 11.0 MB dataset likely includes time-dependent measurements of heavy metal retention (Pb, Zn, Fe) under varying operational conditions. The study investigated factors like draw solution concentration, pH levels, ultrasonic parameters, and membrane orientation.
11 Science Dataset layers provide BRDF and Albedo quality metrics at 500-meter resolution, produced daily using a 16-day rolling window of VIIRS/JPSS1 satellite data. The algorithm applies the RossThick/Li-Sparse-Reciprocal kernel-driven model to reconstruct surface anisotropic effects and compute black-sky and white-sky albedo. Researchers can use these model parameters to derive albedo estimates for any solar illumination angle, supporting studies of surface energy balance and climate.
NASA's VNP43MA1N product provides daily Bidirectional Reflectance Distribution Function (BRDF) and albedo model parameters at a 1 km resolution globally. It is generated using a 16-day rolling window of data from the VIIRS/NPP satellite, applying the RossThick/Li-Sparse-Reciprocal kernel-driven model. The dataset includes 24 Science Dataset layers, such as the fiso, fvol, and fgeo kernel weights for multiple spectral bands, enabling researchers to model surface anisotropy and calculate albedo.
VIIRS/JPSS1 satellite data provides daily global land surface albedo and anisotropy model parameters at a 500-meter resolution. The algorithm uses a 16-day rolling window of observations and the RossThick/Li-Sparse-Reciprocal kernel-driven model to generate three parameters (fiso, fvol, fgeo) for three spectral bands. Researchers can use these model parameters with a polynomial to derive black-sky albedo for any solar angle or estimate instantaneous blue-sky albedo.
May 2026 OpenStreetMap export of Peruvian education facilities compiled by the Humanitarian OpenStreetMap Team. The dataset includes features tagged as kindergarten, school, college, or university. It likely contains attributes such as name, address, capacity, and operator type.
OpenStreetMap features for education facilities across Indonesia, matching tags for kindergarten, school, college, and university. The Humanitarian OpenStreetMap Team (HOT) maintains this export, which was last updated on 2026-05-05. Features likely include attributes such as name, address, capacity, and operator type.
New South Wales contains a spatial dataset of over 220,000 km of river length, with each discrete reach classified using the River Styles Framework. The dataset was developed by Macquarie University and is maintained by the NSW Department of Climate Change, Energy, the Environment and Water. It was last updated on May 12, 2026.
An OpenStreetMap export from 2026-05-05 includes features across Algeria tagged as kindergartens, schools, colleges, or universities. The Humanitarian OpenStreetMap Team (HOT) compiled this dataset, which likely contains points of interest with attributes like name, address, and capacity. Features are available in multiple geospatial formats including KML, GEOJSON, SHP, and GEOPACKAGE.
OpenStreetMap features for educational facilities across Spain, including kindergartens, schools, colleges, and universities. The dataset is an export from the Humanitarian OpenStreetMap Team (HOT) and was last updated in May 2026. Features may include attributes such as name, address, capacity, and operator type.
OpenStreetMap features in Thailand tagged as 'kindergarten', 'school', 'college', or 'university' under the 'amenity' or 'building' keys. The dataset was last updated on 2026-05-05 and is provided by the Humanitarian OpenStreetMap Team (HOT). Features may have attributes such as name, address, capacity, and source information.
OpenStreetMap features for education-related amenities and buildings in the British Indian Ocean Territory. The dataset is an export by the Humanitarian OpenStreetMap Team and was last updated on 2026-05-05. It includes features tagged as kindergartens, schools, colleges, or universities.
New South Wales primary school locations are provided as a point feature dataset. The data is part of the NSW Features of Interest Category, managed by Spatial Services, and was initially published on 29/09/2021. It includes both public and private primary schools catering to children aged 5 to 12.
A point feature dataset representing combined primary and secondary school locations in New South Wales, Australia. The data is provided by Spatial Services, a business unit of the Department of Customer Service NSW, and is part of the NSW Features of Interest Category. It was initially published on 29/09/2021 and has been updated to align with the GDA2020 geodetic standard.
Botswana student experiences of ICT access and use in a rural public junior secondary school's Computer Awareness programme. The dataset contains qualitative questionnaire data from 25 students, analyzed via reflexive thematic analysis. It was authored by Irina Zlotnikova and last updated on 2026-05-26.
A physics-informed cluster graph neural network (PCGNN) model for predicting piezoelectric tensors, developed by Chunlin Yu and last updated in May 2026. The model applies controlled strain perturbations to crystal structures and reconstructs macroscopic tensors through symmetry-consistent aggregation. On the Materials Project test set, PCGNN achieved a mean absolute error of 0.135 C/m², outperforming baseline models.