Empowering EDTECH Platforms

Analytics and AI innovations have the potential to help the decision-making processes and to bring more business opportunities for stakeholders. This study explored how analytics and AI support decision-making in EdTech platforms. The interest in research on how artificial intelligence (AI) can be applied in the Education sector has grown significantly in the past decade. Using a comprehensive literature review, document analysis, and search analysis, the study emphasized the growing attention to analytics and AI-related topics in public companies’ annual fillings. Also, the study explored the types of decisions in EdTech platforms that can benefit from analytics and AI implementations. There is a broad range of decisions that can benefit from analytics and AI: personalized learning paths, early notifications or student dropout prediction are only a few of the possibilities that analytics and AI implementations can provide to EdTech platforms. The originality of this article consists of a review of the unique combination of stakeholders and decision types that can benefit from analytics and AI along with the general trend of the analytics and AI-related concepts in the official communications of the US public companies. This research contributes to a better understanding of how analytics and AI technologies can help the EdTech platforms provide better learning experiences to the students and better insights to decision-makers on educational offerings.

Authors

Institutions

Publication Details

Journal
ACROSS Journal of Interdisciplinary Cross-border Studies
Published
2025-03-27
DOI
https://doi.org/10.35219/across.2024.3.02
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Empowering EDTECH Platforms

Marian Stan, Mihai CIOBOTEA, Tudor URSEIU
ACROSS Journal of Interdisciplinary Cross-border Studies
Online Learning and Analytics
article

Empowering EDTECH Platforms

Marian Stan, Mihai CIOBOTEA, Tudor URSEIU
article en

Abstract

Analytics and AI innovations have the potential to help the decision-making processes and to bring more business opportunities for stakeholders. This study explored how analytics and AI support decision-making in EdTech platforms. The interest in research on how artificial intelligence (AI) can be applied in the Education sector has grown significantly in the past decade. Using a comprehensive literature review, document analysis, and search analysis, the study emphasized the growing attention to analytics and AI-related topics in public companies’ annual fillings. Also, the study explored the types of decisions in EdTech platforms that can benefit from analytics and AI implementations. There is a broad range of decisions that can benefit from analytics and AI: personalized learning paths, early notifications or student dropout prediction are only a few of the possibilities that analytics and AI implementations can provide to EdTech platforms. The originality of this article consists of a review of the unique combination of stakeholders and decision types that can benefit from analytics and AI along with the general trend of the analytics and AI-related concepts in the official communications of the US public companies. This research contributes to a better understanding of how analytics and AI technologies can help the EdTech platforms provide better learning experiences to the students and better insights to decision-makers on educational offerings.

ACROSS Journal of Interdisciplinary Cross-border StudiesVol. 8(3)
Carol I National Defence University (RO), Bucharest University of Economic Studies (RO)
Openalex Percentile: Top 90%
Online Learning and Analytics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.