Published on 09 September 2025

STEM Education Literature Dataset from 2020-2024

View Dataset
BIN QUSHEM, UMAR

Description

AbstractThis dataset provides secondary literature data on STEM Education collected from peer-reviewed databases such as Web of Science, Scopus, and ACM. The collection contains significant information about the scientific literature, including intervention studies conducted between 2020 and 2024. The data fields' key characteristics include Domain, Education Level, TEL Practices, Learning Technologies, LA Practices, Learning Analytics Techniques, Study Designs, Theories, Countries, Populations, Learning Strategies, Learning Measures, Impact Areas, Learning Outcomes, Challenges and Limitations. This dataset aims to provide a thorough trajectory of STEM educational research works as well as an overview of numerous technologies and analytics methods that have contributed to the expansion of this growing discipline.

Citations (0)

Mentions (0)

Metrics

Dataset Index

1.9

FAIR Score

77%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Zenodo

Assigned Domain

Subfield

Artificial Intelligence

Field

Computer Science

Domain

Physical Sciences

Confidence Score

65%

Source

Open Alex

Keywords

STEMEducationEducation TechnologiesAnalytics Practices

Normalization Factors

FT

13.46

CTw

1.00

MTw

1.00