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Student performance, MOOC logs, knowledge tracing, standardized tests, learning analytics
13,387 datasets
The Digital Surficial Geologic-GIS Map of the Neches Bottom and Jack Gore Baygall Units and Vicinity, Big Thicket National Preserve, Texas is a geospatial dataset from the National Park Service Geologic Resources Inventory. It includes GIS data layers, tables, and supporting documentation, derived from an unpublished Lamar University map by Aronow (1982). The data is available in ESRI file geodatabase and OGC geopackage formats.
A digital geologic-GIS map of the Turkey Creek Unit and vicinity within Big Thicket National Preserve, Texas, adapted from an unpublished 1982 map by Aronow. The dataset is composed of GIS data layers and tables, available in ESRI file geodatabase and OGC geopackage formats, and was completed as part of the National Park Service's Geologic Resources Inventory program. It includes ancillary documents with geologic unit descriptions and metadata.
Big Thicket National Preserve and vicinity in Texas is covered by this digital surficial geologic map. The dataset is composed of GIS data layers and tables, available in multiple formats including an ESRI file geodatabase, OGC geopackage, and KMZ/KML. It was produced by the National Park Service's Geologic Resources Inventory program, adapted from an unpublished Lamar University map by Aronow (1982).
Spoken Marathi Dialect Identification Dataset is a collection of audio recordings for dialect recognition. It is hosted on Kaggle and described as a deep learning approach for dialect recognition. The dataset's specific size, collection method, and origin are not detailed in the provided metadata.
Best_contrastive_learning_mdd is a dataset hosted on Kaggle. Its title suggests a focus on contrastive learning techniques, potentially applied to a domain abbreviated as 'mdd'. The dataset's specific content, size, and origin are not detailed in the available metadata.
Deep learning questions likely contain educational or assessment material for the field. Published on Kaggle, the dataset's specific content and scope require verification after download. The author, organization, and update history are unknown.
A NOAA and NGA project assessing satellite-derived bathymetry data. The dataset likely contains refraction-corrected underwater depth measurements from 0 to 30 meters, derived from NASA's ICESat-2 satellite LiDAR. It was developed to improve the accuracy of coastal bathymetry products for navigation safety.
New Brunswick school enrolment data provides counts of students by grade, school, and district for each academic year, as recorded on September 30. The dataset is published by the Government of New Brunswick via the Socrata platform. It was last updated in February 2026.
Indian, Southern, and Pacific Ocean temperature profile data collected using ALACE (Autonomous LAgrangian Circulation Explorer) profiling drifters. Data were submitted by Jeff Sherman from the University of San Diego (UCSD). The dataset is archived under NOAA NCEI Accession 9700028.
Graphwalks is a long-context benchmark containing between 1,000 and 10,000 records, released by OpenAI in early 2026. It evaluates multi-hop reasoning by requiring models to execute graph operations, such as breadth-first search, on provided directed edge lists.
Colorado's Big Thompson River Valley subsurface geology is characterized using seismic refraction data. The dataset includes estimated velocities and thicknesses for layered-earth models, enabling construction of three cross sections depicting alluvium stratigraphy. The summary was provided by the USGS.
Number of parallel implementation units (PIUs) in the education sector, as reported by development donors. The dataset was created by the Global Partnership for Education as part of the 2011 Monitoring Exercise on Development Effectiveness in the Education Sector. It provides a snapshot of how education aid was delivered and managed by development partners and governments.
Coordinated technical cooperation measures the percentage of total technical cooperation from development partners delivered through coordinated programs aligned with recipient government priorities. The dataset originates from the 2011 Monitoring Exercise on Development Effectiveness in the Education Sector conducted by the Global Partnership for Education. It provides a snapshot of how education aid was delivered and managed by partners and governments during that period.
Endorsement years for Education Sector Plans or Transitional Education Plans by local donor partners are recorded. The data tracks when developing countries gain eligibility to apply for funding from the Global Partnership for Education. It is provided by the Global Partnership for Education.
Global Partnership for Education data tracks planned dates for Joint Sector Reviews (JSRs) conducted by Local Education Groups. JSRs are monitoring mechanisms for assessing progress, challenges, and funding within national education sectors. These reviews occur annually or biannually to measure progress against Education Sector Plans.
Global Partnership for Education data records the date of the most recent Joint Sector Review (JSR) for participating countries. JSRs are monitoring mechanisms where Local Education Group members assess progress, challenges, and funding in the education sector. The reviews occur annually or biannually, with conclusions documented in an aide-memoire.
Aggregating interview data from the Horizon project SENSE., focusing on stakeholder needs and challenges for STEAM education in Europe. The data was collected from five defined target groups, including young people, parents, educators, businesses, and policymakers. The methodological details are documented in a published report from June 2023.
QLOP is an educational dataset published on Kaggle. It likely contains data related to learning recommendations, such as student interactions or course features. The dataset's author, organization, and specific collection details are not provided in the metadata.
A list of courses approved for continuing education in the home inspection profession. The data is published by the State of Connecticut on the Data.gov platform and was last updated in March 2026. The specific number of courses, their content, and the available file formats suggest it is a catalog of approved training materials.
Thoria's Mandarin Most Common Words (TR-EN) dataset is a trilingual vocabulary resource for Mandarin learners. It provides translations and examples in Turkish and English, created by Stephanie Liu and Kamil Murat Yilmaz.