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Student performance, MOOC logs, knowledge tracing, standardized tests, learning analytics
12,453 datasets
OpenStreetMap data for education facilities in Sweden, including schools, kindergartens, colleges, and universities. The data is contributed by volunteers and exported by the Humanitarian OpenStreetMap Team. The dataset was last updated on 2026-05-15.
Ghana's education facilities, including schools, kindergartens, colleges, and universities, are mapped from OpenStreetMap. The data is compiled by the Humanitarian OpenStreetMap Team and was last updated on 2026-05-15. Completeness varies by region, with urban areas typically better mapped than remote ones.
OpenStreetMap data for Zambian education facilities, including schools, kindergartens, colleges, and universities. The Humanitarian OpenStreetMap Team (HOT) exported this data, which was last updated on 2026-05-15. Completeness varies by region, with urban areas likely being more thoroughly mapped than remote ones.
OpenStreetMap volunteer contributions provide a map of schools, kindergartens, colleges, and universities in Samoa. The Humanitarian OpenStreetMap Team (HOT) exports this data via HDX, last updated on 2026-05-15. Completeness varies, with urban areas likely better mapped than remote regions.
OpenStreetMap data for education facilities in Dominica, including schools, kindergartens, colleges, and universities. The dataset is exported by the Humanitarian OpenStreetMap Team and was last updated on 2026-05-15. Completeness varies by region, with urban areas likely better mapped than remote ones.
OpenStreetMap data on Tunisian education facilities includes schools, kindergartens, colleges, and universities. The Humanitarian OpenStreetMap Team (HOT) exported this data, which was last updated on 2026-05-15. Completeness of the volunteer-built map varies, with urban areas likely being better mapped than remote regions.
Education facilities across Denmark exported from OpenStreetMap. The data includes schools, kindergartens, colleges, and universities tagged via `amenity` or `building` keys. It was last updated on 2026-05-15 and is provided by the Humanitarian OpenStreetMap Team.
A mixed-methods study examines older adults' perceptions of AI virtual digital human influencers versus physician influencers in Chinese health short videos. The research employed questionnaires with 101 participants and an experimental design, reporting a Cronbach's alpha of 0.897. Jinglun Zhang published the study on figshare under a CC-BY-4.0 license in June 2026.
OpenStreetMap exports of education facilities in Uganda, provided by the Humanitarian OpenStreetMap Team (HOT). The data includes schools, kindergartens, colleges, and universities tagged via `amenity` or `building` keys. It was last updated on 2026-05-15.
OpenStreetMap data for education facilities in Tuvalu, including schools, kindergartens, colleges, and universities. The dataset was last updated on 2026-05-15 and is provided by the Humanitarian OpenStreetMap Team. Completeness of mapping varies by region, with urban areas likely being more complete than remote areas.
A severe harmful algal bloom involving Karenia species has affected large areas of the South Australian coastline, including Gulf St Vincent, Spencer Gulf and Investigator Strait. This project provides a rapid assessment dataset combining microscopy, qPCR-based species identification, rotifer bioassays, and brevetoxin screening. Outputs include baseline information on bloom toxicity and variability, species composition data, and a foundational dataset linking Karenia community structure with toxicological response.
Seven indicator layers for Papua New Guinea provide demographic, infrastructure, and hazard data aggregated at the second administrative level. The data is derived from HeiGIT's GAIA Pipeline, integrating open sources like WorldPop, OpenStreetMap, and Google Earth Engine. It was last updated on 2026-04-13.
Seven indicator layers provide demographic, environmental, infrastructure, accessibility, and hazard-related data for Timor Leste's administrative level 2 districts. The dataset is derived from HeiGIT's GAIA Pipeline, integrating open data from WorldPop, OpenStreetMap, and Google Earth Engine. It was last updated on 2026-04-13.
Risk assessment indicators for Saudi Arabia aggregated at the second administrative level (ADM2). The dataset includes eight thematic layers covering demographics, access to services, facilities, coping capacity, and exposure to flood and cyclone hazards. It was produced by HeiGIT using open data sources like WorldPop and OpenStreetMap and was last updated in April 2026.
Risk assessment indicators for Gabon aggregated at administrative level 2, derived from HeiGIT's GAIA Pipeline. The dataset includes layers for access to services, facilities, coping capacity, demographics, rural population, vulnerability, and flood exposure. It was last updated on 2026-04-13 and integrates data from sources like WorldPop, OpenStreetMap, and Google Earth Engine.
Seven indicator layers for Mexico, aggregated at admin level 2, derived from HeiGIT's GAIA Pipeline. The data integrates open sources including WorldPop, OpenStreetMap, and Google Earth Engine, and was last updated on 2026-04-13. It includes measures for access to services, facility counts, coping capacity, demographics, rural population, vulnerability, and flood exposure.
Seven indicator layers provide demographic, environmental, infrastructure, accessibility, and hazard-related data for Chile's administrative level 2 districts. The dataset is derived from HeiGIT's GAIA Pipeline, integrating open data from WorldPop, OpenStreetMap, and Google Earth Engine. It was last updated on 2026-04-13.
Seven indicator layers for Cameroon's administrative level 2 districts, derived from HeiGIT's GAIA Pipeline and last updated on 2026-04-13. The data integrates open sources like WorldPop, OpenStreetMap, and Google Earth Engine using HDX COD-AB boundaries. It includes measures for access to services, facility counts, demographics, vulnerability, and flood exposure to support structured risk assessment.
HeiGIT's GAIA Pipeline integrates open data from WorldPop, OpenStreetMap, and Google Earth Engine to produce seven indicator layers for disaster risk analysis. These layers include demographic, environmental, infrastructure, accessibility, and hazard-related data aggregated for Barbados's administrative level 2 districts. The dataset was last updated on 2026-04-13 and is licensed under CC-BY-SA-4.0.
Shweta Kulkarni's study provides geospatial evidence on tobacco retail outlet density around schools in Lao PDR. The dataset, last updated in 2026, contains results from auditing 233 outlets around 27 schools in Vientiane Capital between January and February 2024. It includes density and proximity metrics calculated within 250m to 1000m buffers in urban and rural districts.