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Student performance, MOOC logs, knowledge tracing, standardized tests, learning analytics
12,510 datasets
The Physical Education Teachers' Embodied Professional Literacy Scale (PE-TEPLS) is a psychometrically validated instrument for assessing K-12 physical education teachers. It contains a 45-item structure across five dimensions, developed by Zhi Li through a mixed-method study involving Delphi consultation and a survey of 1,665 PE teachers in China. The dataset was last updated on 2026-05-15.
A dataset from a study of 36 preschool-aged children (mean age 38 months) investigating the relationship between engagement and word learning from screen media. The research, authored by Aaron R. Glick, compares behavioral and holistic measures of engagement collected from webcam video, parents, and experimenters. It was last updated on May 15, 2026.
A 2026 study of 1070 students from five tertiary institutions in Harare, Zimbabwe, examining awareness and utilization of campus-based mental health services. The dataset, authored by Omega Mukubvu, includes questionnaire responses on barriers, facilitators, and preferences for accessing mental health support. Data were analyzed using descriptive statistics and multivariate logistic regression.
25 studies (coded A01–A25) from a scoping review on Game Learning Analytics, extracted by an anonymous author and last updated on 2026-05-31. The spreadsheet synthesizes visualization approaches, metrics, tools, and audiences used to analyze gameplay log data from educational and serious games.
A 2026 cross-sectional study of 436 dental students, interns, and faculty at a teaching institution in Navi Mumbai assessed HBV knowledge, occupational exposure, and vaccination status. Blood samples from 275 participants were analyzed for anti-HBs, anti-HBc, and HBsAg serological markers. The dataset was created by Sanpreet Singh Sachdev and is available on figshare under a CC-BY-4.0 license.
A study of 21 first-year medical students learning cardiac anatomy, comparing traditional 2D materials to immersive 3D virtual reality. Prefrontal hemodynamic activity was monitored with functional near-infrared spectroscopy (fNIRS), and cognitive load was assessed via questionnaire and pre/post-learning tests. The dataset, created by Erika Johannessen and last updated in May 2026, contains results demonstrating neural dynamics differences and classifier performance for cognitive load.
21 first-year medical students were randomly assigned to learn cardiac anatomy using either 2D materials or 3D VR while their prefrontal hemodynamic activity was monitored. The dataset likely contains fNIRS neural data and cognitive load questionnaire scores from three learning periods, collected by Erika Johannessen and last updated in 2026. Deep learning classifiers using fNIRS features achieved up to 92% accuracy in distinguishing cognitive load levels.
A study of 21 first-year medical students learning cardiac anatomy, comparing immersive 3D virtual reality to traditional 2D materials. The dataset includes pre- and post-learning assessment scores, subjective cognitive load questionnaire results, and functional near-infrared spectroscopy (fNIRS) neuroimaging data. It was authored by Erika Johannessen and last updated on 2026-05-05.
A multibeam sonar survey mapped a shelf valley system up to 220 meters deep and extending over 90 kilometers across the continental shelf at the northern end of Australia's Great Barrier Reef. The data supports a new conceptual model for the formation of tidally incised shelf valleys, challenging the predominant fluvial erosion theory. This dataset is hosted by the Australian Ocean Data Network and was last updated in June 2026.
A digital dataset from the Department of Energy, Environment and Climate Action provides multiple spatial layers for modeled coastal hazards around Port Phillip Bay. The data includes storm tide inundation, erosion, and groundwater hazard extents for various Sea Level Rise scenarios, such as 0m, 0.2m, 0.5m, 0.8m, 1.1m, and 1.4m. The product was last updated on 2026-04 09 and is accompanied by technical reports from CSIRO (2022), Water Technology (2023), and Kennedy (2022).
Lechen Dong published this dataset on 2026-05-11 to support the reproducibility of machine-learning models for detecting Self-Consistent Field convergence failures. It contains structural coordinates and extracted time-series features for over 1,400 molecules from QM9 and QM40 parent sets. The data is pre-partitioned into training, validation, and test splits for direct use with a Gradient Boosting Classifier.
42 studies from 2014 to 2025 synthesize evidence on antimicrobial resistance and stewardship programs in Saudi Arabia. MRSA prevalence had a pooled estimate of 24.3%, and stewardship programs demonstrated 15–40% reductions in inappropriate prescribing. This systematic review was authored by figshare admin karger and uploaded in April 2026.
Government of Yukon data assesses the quality and confidence of digitized stream catchment areas for regional sediment samples. Rankings for sample location, catchment area, surface material, slope, and aspect are combined into reliability indices for mineral exploration targeting. The dataset includes assessments of data precision and bias from quality control samples and standard reference materials.
A systematic review of 23 empirical studies from five continents explores how teachers adapt curricula in language-diverse primary mathematics classrooms. The analysis of 833 screened articles from Web of Science, Scopus, and ERIC reveals four key curriculum-making starting points. This 242.2 KB document, authored by Derya Sahin-Ipek and last updated in May 2026, synthesizes convergences and divergences shaped by policy tensions and teacher agency.
SCAR-B_UWC131A data contain physical and chemical measurements of the atmosphere collected during 29 research flights over Brazil from August 17 to September 20, 1995. The dataset focuses on the effects of sulfate aerosols and smoke from biomass burning on atmospheric processes, cloud formation, and radiation. It was gathered by the University of Washington's Cloud and Aerosol Research Group using instruments aboard a Convair C-131A aircraft.
A five-year, multi-cohort study followed 240 first-year university students to evaluate the impact of a mobile chatbot learning assistant. Pavel Smutny authored this research document, which compares a decision-tree-based chatbot with an LLM-driven version on learning outcomes, student perceptions, and motivation. The dataset, last updated in May 2026, contains the full study results and discussion in a 1.5 MB document.
2240 women aged 20–45 from the US NHANES 2007–2020 survey, with 10% having gestational diabetes mellitus (GDM). The data was analyzed by Mengmeng Ye to assess the Zhejiang University (ZJU) index as a predictor of GDM and to evaluate mediation by inflammatory markers. The dataset was last updated on 2026-05-08.
Port Phillip Bay Coastal Hazard Assessment is a digital dataset of modelled erosion, inundation, and groundwater hazard scenarios for the Port Phillip Bay region. The data includes extents for 1% Annual Exceedance Probability events across multiple sea level rise scenarios, from 0m to 1.4m. The product was developed with technical reports from CSIRO (2022), Water Technology (2023), and Kennedy (2022).
Public genomic data for the foodborne pathogen Vibrio parahaemolyticus supports machine learning models for source differentiation. The dataset underpins models achieving an AUC greater than 0.95 in distinguishing clinical from environmental isolates based on pangenome assemblies. It facilitates the discovery of virulence-associated genes, such as vspR, sctC5, and tdh1, for seafood safety risk assessment.
Seven first-order coastal cells delineate the entire Northern Ireland coastline. Boundaries were identified using historical Ordnance Survey maps, aerial photographs, and expert geomorphological knowledge, and are classified as either littoral drift divides or sediment sinks. This spatial tool is designed for calculating sediment budgets and managing coastal change.