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Student performance, MOOC logs, knowledge tracing, standardized tests, learning analytics
15,192 datasets
A dataset from the State site of Ukraine, last updated on August 13, 2020. It describes the service territory and associated addresses for Kharkiv secondary school number 164 (Ü164) under the Kharkiv City Council. The data is provided in Excel format, likely containing administrative boundaries and location information for this educational institution.
From 2015-10-07 to 2020-06-18, Florida Atlantic University collected oceanographic and surface meteorological data from a moored station in the Indian River Lagoon near Jensen Beach, Florida. The Southeast Coastal Ocean Observing Regional Association (SECOORA) assembled and submitted the data to NOAA's National Centers for Environmental Information. Data are stored in netCDF files following Climate and Forecast (CF) metadata conventions.
Encompassing scalp electrophysiological (EEG) brain response recordings from 66 preschool children (40 in the main experiment, 26 in a replication). The data captures responses to visual letter strings and control stimuli (pseudofonts, familiar symbols, object drawings) presented in rapid streams. It was collected to investigate early left hemispheric cortical specialization for print in prereaders.
A 2020 study by Huixiang Wang compared multiple-viewpoint versus single-viewpoint video training for hip resurfacing surgery. The dataset contains results from 30 medical students, measuring pin trajectory deviations, Global Rating Scale scores, and pre/post knowledge test results. It provides objective metrics on the efficacy of a novel multi-camera surgical training system.
Ukrainian data from the eu_open_data platform, last updated in August 2020. The dataset describes the service areas of secondary educational institutions, likely containing geographic or administrative boundaries. It was published by the States site of Ukraine.
Coastal waters of Florida were monitored from station Indian River Lagoon - Vero Beach (IRL-VB) by Florida Atlantic University. The dataset contains oceanographic and surface meteorological data collected from 2015-10-07 to 2020-06-11 and submitted via the Southeast Coastal Ocean Observing Regional Association (SECOORA). Data are formatted in netCDF files following CF and ACDD metadata conventions.
Featuring MRI and histological data from a study validating the RAFFn MRI technique for measuring myelination and dysmyelination in mice with Type I mucopolysaccharidosis (MPS I). The data includes RAFF5 relaxation time constants correlated with histological myelin density (R2 = 0.68, P<0.001) and comparisons between MPS I mice and heterozygotes across brain regions like the striatum, internal capsule, and fornix. The study was authored by David Satzer and published in 2020.
This dataset contains vocalization data from songbirds (Lonchura striata domestica) used to validate an automated measure of imitative learning called Song Divergence. The data supports research on sensory-motor learning and vocal learning, correlating the automated metric with human evaluations of song learning and detecting song deterioration after deafening. It was published by author David G. Mets in 2020.
Coastal waters of Florida contain oceanographic and surface meteorological data collected from an in-situ moored station named Indian River Lagoon - Fort Pierce (IRL-FP). Florida Atlantic University collected the data, which was assembled by the Southeast Coastal Ocean Observing Regional Association (SECOORA) and submitted to NCEI. The data covers the period from October 7, 2015, to June 9, 2020.
Multiple pedestrian detection datasets are aggregated to support computer vision research and benchmarking. The content focuses on human-centric visual data for training and evaluating object detection models.
Supervised and unsupervised learning implementations characterize this collection of projects by Defcon27, last updated in September 2020. The repository contains an unknown number of datasets and scripts for statistical modeling and exploratory data analysis using Python 3.
Report 42m from the communal institution 'Poltava children's and youth sports school 'wedding'' details the receipt and use of funds from other sources of own revenues. The dataset is provided by the States site of Ukraine and was last updated on July 22, 2020. The data is available in an Excel XLSX format.
Experimental data from a reversal-learning regime conducted on a diverse panel of Drosophila melanogaster genotypes. It captures genetic variation in baseline learning ability and a consistent 1.3× increase in learning speed with reversal. The dataset provides measurements for analyzing the relationship between genotype and learning flexibility.
This dataset supports a study on suppressing overlearning in Independent Component Analysis (ICA) for removing muscular artifacts from electroencephalographic (EEG) records. The research demonstrates a subspace projection technique that improves artifact separation for short, high-density EEG signals compared to standard ICA methods. The author is Jan Sebek, with the data last updated in June 2020.
Data from a study investigating dopamine's role in motor skill learning and synaptic plasticity in rat primary motor cortex. The research, authored by Mengia-Seraina Rioult-Pedotti, challenges the traditional view of PKA modulation by demonstrating a key role for phospholipase C (PLC) activation. The dataset includes experimental results on forelimb reaching task performance and long-term potentiation measurements under various pharmacological conditions.
A collection of brain activity and functional connectivity measurements from a study investigating the role of the intraparietal sulcus in response inhibition. The study employed a stop-signal task and transcranial magnetic stimulation, with behavioral data including stop-signal reaction time (SSRT). The dataset was published by Takahiro Osada in 2020.
32 participants underwent pharmacology, scalp EEG, and computational modeling to study catecholaminergic regulation of learning rate in a dynamic environment. The dataset includes electrophysiological data like the P3 component and computational variables such as prediction-error magnitude and belief uncertainty. It provides evidence for the causal role of norepinephrine and dopamine systems in adapting learning to environmental change.
This dataset supports research on determining motor intent from targeted reaching motions disturbed by unexpected forces. It includes data from a study with eight human subjects, analyzing intended trajectories derived from feedforward and feedback controls. The modeling approach inverts control signals to estimate intent, with sensitivity to parameter uncertainties examined.
Specimens from the late Ediacaran Ediacara Member of South Australia reveal anatomical details of the frondose taxon Arborea arborea. The data supports evidence for tissue differentiation, fluid-filled holdfast discs, and fascicled tubular structures within the stalk. It is authored by Frances S. Dunn and published in 2020.
This dataset investigates environmental drivers of water salinity across Spanish rivers, assessing the extent and causes of salinization. It examines variation among river typologies and between reaches in good and poor ecological status as defined by the Water Framework Directive. The analysis identifies natural and anthropogenic factors, with land use being a primary driver affecting over one quarter of Spanish rivers.