Loading...
Loading...
Student performance, MOOC logs, knowledge tracing, standardized tests, learning analytics
12,518 datasets
386 survey responses from university students analyzed via structural equation modeling to understand technology acceptance. The research, authored by Li Wang, extends the UTAUT2 model to examine determinants like performance expectancy and hedonic motivation. Results indicate flow experience mediates and personal innovativeness moderates the intention to use AI for personalized English learning.
386 valid survey responses from university students collected via convenience sampling. The data was analyzed using structural equation modeling with SmartPLS 4.0 software to examine determinants of AI tool adoption for personalized English learning. The dataset, authored by Li Wang and last updated in May 2026, is shared under a CC-BY-4.0 license.
386 valid questionnaires collected from university students via convenience sampling. The dataset analyzes determinants of intention to use generative AI tools for personalized English learning, employing an extended UTAUT2 model. Structural equation modeling was performed using SmartPLS 4.0 software.
A survey of university students collected 386 valid questionnaires to analyze determinants of their intention to use generative AI tools for personalized English learning. The study employed structural equation modeling using SmartPLS 4.0 software. The dataset was uploaded by Li Wang on figshare and last updated on 2026-05-05.
386 valid survey responses from university students, collected via convenience sampling. The dataset was analyzed using structural equation modeling with SmartPLS 4.0 software. The research was authored by Li Wang and last updated on 2026-05-05.
A repository containing curated datasets of room-temperature ionic conductivities for lithium-based and sodium-based solid-state electrolytes. The materials include CSV files for Li, Na, and combined datasets, a Jupyter notebook for regression modeling, and supplementary Excel tables and figures. All data was obtained through a combination of large language model-assisted extraction and manual curation to support the associated research article.
Parsa Seyfourian, Lydia C. Marks, Leslie D. Claar, Yasmeen Nahas, Miles Keating, Christof Koch & Irene Rembado created this dataset of 21,909 manually annotated frames extracted from 145 videos. The frames were used to train the General Model for the Pupil-DLC deep learning pipeline. The dataset was published on figshare under a CC-BY-4.0 license on June 4, 2026.
6,266 annotated mural images form a multi-source dataset for detection, segmentation, and 3D validation of damage types. The dataset was constructed by Hu Yanfeng and last updated on 2026-05-02. It supports a proposed framework for 2D damage recognition and 3D semantic mapping of mural heritage.
A cross-sectional survey of parents of children with chronic gastrointestinal diseases in Poland. The dataset likely contains responses from a study measuring parental satisfaction, health literacy, e-health literacy, internet use, and perceived stress. The data was collected via a paper-and-pencil survey administered in five university gastroenterology centers.
Western China clinical nurses provided responses via an anonymous online questionnaire in June-July 2025. The dataset contains survey results from 302 active nurses, analyzed for relationships between digital literacy, psychological resilience, and work stress. Yan Wu authored this cross-sectional study, which was published on figshare in April 2026.
Jie Guo published a dataset on 2026-05-18 comparing optimized federated learning schemes. The dataset likely contains performance metrics for schemes integrating adaptive channel pruning with multi-key homomorphic encryption. It was tested on MNIST and CIFAR-10 datasets to evaluate communication overhead and privacy.
Jie Guo's experimental results, shared on figshare in May 2026, describe an optimized federated learning scheme. The 5.5 KB XLS file likely contains tabular data comparing the performance of the proposed method against traditional algorithms. The scheme integrates adaptive channel pruning and multi-key homomorphic encryption to reduce communication overhead and resist collusion attacks.
Exploratory factor analysis results from a pilot study of youth aged 15–19 living in Naples, Italy, to measure educational poverty. The dataset, shared by author Cristina Davino on figshare, identifies three underlying dimensions: Family, School, and Environment. It is a small dataset (9.5 KB) last updated in May 2026.
594 radiosonde launches provide vertical profiles of atmospheric conditions across nine South African sites from August to September 2000. The Vaisala RS80 sondes measured pressure, air temperature, relative humidity, wind speed, and wind direction from the surface to 30 km altitude. This data was collected to augment the regional sounding network during the SAFARI 2000 Dry Season Campaign.
Guangdong Province survey data from 568 educators, used to analyze factors affecting employee retention. The dataset was created by Zhengda Yao and last updated on 2026-05-18. It supports a study on push-pull factors like training, compensation, burnout, and engagement.
568 survey responses from educators in Guangdong Province were collected to examine factors affecting employee retention. The dataset was created by Zhengda Yao and last updated on 2026-05-18. It supports analysis using Partial Least Squares Structural Equation Modeling and Multi-Group Analysis.
Zhengda Yao's dataset contains survey responses from 568 educators in Guangdong Province, China, used to study employee retention factors. The data was analyzed using Partial Least Squares Structural Equation Modeling and Multi-Group Analysis. The dataset was last updated on May 18, 2026, and is shared under a CC-BY-4.0 license.
Saudi Arabian public university students participated in a quasi-experimental study on ChatGPT-mediated learning. The dataset contains pre-test scores for reading comprehension from 60 male preparatory-year students. It was authored by Naji Alyami and last updated on 2026-05-18.
60 male preparatory-year students at a Saudi Arabian public university participated in a quasi-experimental study on reading comprehension. Post-test scores show a statistically significant difference between the ChatGPT-mediated mind mapping group and the control group, with a medium-to-large effect size. The dataset, shared by Naji Alyami, contains the Mann-Whitney U test results for these scores.
568 survey responses from educators in Guangdong Province examine retention factors. The data likely contains responses on push and pull factors like training, compensation, burnout, and engagement. Zhengda Yao published this dataset on figshare in 2026 under a CC-BY-4.0 license.