Loading...
Loading...
Student performance, MOOC logs, knowledge tracing, standardized tests, learning analytics
15,235 datasets
HeiGIT's Morocco Risk Assessment Indicators dataset aggregates demographic, environmental, infrastructure, accessibility, and hazard-related data at administrative level 2. It integrates open data from WorldPop, OpenStreetMap, and Google Earth Engine using HDX COD-AB boundaries. The dataset was last updated on 2026-04-27.
HeiGIT's Greenland Risk Assessment Indicators dataset provides demographic, environmental, infrastructure, accessibility, and hazard-related data aggregated at admin level 2. It integrates open data from WorldPop, OpenStreetMap, and Google Earth Engine via the GAIA Pipeline. The dataset was last updated on 2026-04-27.
Seven indicator tables for Guinea Bissau aggregated at administrative level 2, derived from HeiGIT's GAIA Pipeline. The data integrates open sources like WorldPop, OpenStreetMap, and Google Earth Engine. It was last updated on 2026-04-27.
Twelve randomized controlled trials published between 2019 and 2025 were included in this meta-analysis. The study quantifies the effects of virtual reality interventions on anxiety symptoms among women undergoing gynecological examinations or surgeries. It was authored by Yuehan Lv and shared on figshare in May 2026.
A systematic review and meta-analysis of 12 randomized controlled trials published between 2019 and 2025. The study quantifies the effects of virtual reality interventions on anxiety symptoms in women undergoing gynecological examinations or surgeries. It was authored by Yuehan Lv and shared on figshare in May 2026.
352 K-12 teachers from a large urban school district in Indonesia participated in a quantitative survey assessing four constructs: General Digital Competence, AI-Specific Competence, Teacher Self-Efficacy for AI Integration, and Attitudes Toward Generative AI in Education. The dataset, authored by Emmanuel Nana Kwesi Ofori Darko and last updated in May 2026, contains results from a correlational study, with the hierarchical regression model explaining 62% of the variance in teachers' attitudes.
Experimental statistics track the percentage of students progressing to further learning or employment after completing A Levels or equivalent qualifications. The Greater London Authority published these figures, which require sustained participation in an education destination for the first two terms post-KS5. Data for small cohorts is suppressed to protect student privacy, and all totals are rounded to the nearest 10.
Ten-year pupil projections from the most recent academic year of School Census data, covering National Curriculum Years from Reception to Year 11. The dataset provides central forecasts and 95% prediction intervals at Subregion, Region, and England levels. It is an experimental dataset produced by the Greater London Authority, with figures potentially subject to minor revisions.
A methodology paper incorporates spatial statistics techniques like Nearest Neighbor and Ripley's K function for cartographic quality control. The work evaluates an orthoimage generated from a PRISM scene of the ALOS satellite. Results show the orthoimage is accurate at a 1:25,000 scale and classified as Class A according to the Brazilian positional accuracy standard.
172 participants from a single-center Chinese health-examination cohort were categorized by quantitative computed tomography (QCT) to evaluate ultrasound attenuation and metabolic biomarkers for non-invasive assessment of hepatic steatosis. The dataset, authored by Zejun Ma and last updated in 2026, includes USAT values and serum levels of ALT, AST, and ferritin. Three predictive models were evaluated, with the USAT-only model achieving an AUC of 0.847 for detecting imaging-defined steatosis.
A single-center Chinese health-examination cohort of 172 participants was used to evaluate models for noninvasive hepatic fat fraction categorization. The dataset includes ultrasound attenuation values and serum levels of ALT, AST, and ferritin, referenced against quantitative computed tomography categories. The study was authored by Zejun Ma and last updated in May 2026.
Supplementary file 2 from a study by Zejun Ma, last updated in May 2026. The dataset likely contains clinical measurements from 172 participants used to evaluate models for non-invasive assessment of hepatic steatosis. The study compared ultrasound attenuation and metabolic biomarkers against quantitative computed tomography-derived fat fraction categories.
A study of 172 participants from a single-center Chinese health-examination cohort, conducted by Zejun Ma and last updated in May 2026. It evaluates models combining ultrasound attenuation and metabolic biomarkers for non-invasive categorization of hepatic fat fraction, using quantitative computed tomography as a reference.
A single-center Chinese health-examination cohort of 172 participants used to evaluate models for non-invasive hepatic fat fraction categorization. The dataset includes ultrasound attenuation values and serum levels of ALT, AST, and ferritin, referenced against quantitative computed tomography categories. It was authored by Zejun Ma and last updated in May 2026.
A dataset of 172 participants from a single-center study evaluating models for noninvasive assessment of hepatic fat fraction categories in metabolic dysfunction-associated steatotic liver disease (MASLD). The data includes ultrasound attenuation values and serum levels of ALT, AST, and ferritin, referenced against quantitative computed tomography categories. The dataset was authored by Zejun Ma and last updated in May 2026.
416 university students aged 17–23 from two Kazakh universities participated in a six-week intervention study. Data includes pre-post scores on the Chen Internet Addiction Scale and Ryff Psychological Well-Being Scale, collected by Gulzhan Niyazova. The dataset was last updated on 2026-05-22.
416 university students aged 17–23 from two Kazakh universities participated in a six-week blended learning intervention. The dataset includes pre-post psychometric scores from the Chen Internet Addiction Scale and Ryff Psychological Well-Being Scale, showing a 7.1% reduction in problematic internet use. Gulzhan Niyazova authored this study, which was last updated in May 2026.
A 2026 study by Gulzhan Niyazova collected data from 416 university students aged 17–23 in Kazakhstan. It includes pre- and post-intervention scores for internet addiction and psychological well-being, alongside behavioral process indicators. The dataset is stored in a DOCX file.
416 university students aged 17–23 from two Kazakh universities participated in a six-week blended learning intervention in 2026. The dataset likely contains pre-post measurements of problematic internet use (Chen Internet Addiction Scale) and psychological well-being (Ryff Scale) collected by Gulzhan Niyazova. Process indicators of digital behavior change are also included.
A 2026 study by Gulzhan Niyazova collected data from 416 university students aged 17–23 in Kazakhstan. The dataset likely contains pre- and post-intervention scores from the Chen Internet Addiction Scale and Ryff Psychological Well-Being Scale, measuring changes after a six-week educational program. The data is stored in a DOCX file and published under a CC-BY-4.0 license.