Revolutionizing Learning Outcomes: The Integration of Educational Management, Ai-Driven Methodologies, and Digital Tools

The rapid advancement of Artificial Intelligence (AI) has transformed educational practices, creating opportunities for more personalized and effective learning experiences. This study investigates the impact of AI-driven methodologies and digital tools on learning outcomes in higher education, with a particular focus on educational institutions in Beijing. The research integrates key constructs such as perceived ease of use, perceived usefulness, and adaptive feedback, with user acceptance serving as a mediating factor influencing students’ academic performance. A quantitative design was adopted, collecting survey data from 640 respondents, including 234 teachers and 367 students. The results reveal that students perceived all three factors—ease of use, usefulness, and adaptive feedback—as significantly enhancing learning outcomes through user acceptance. However, teachers indicated that perceived usefulness did not exert a significant influence on their acceptance of AI tools. These findings underscore the importance of usability and adaptive features in shaping positive attitudes toward AI in education. The study contributes to educational management by offering insights into the integration of AI technologies, while also outlining limitations and directions for future research.

Authors

Institutions

Publication Details

Journal
International Journal of Academic Research in Progressive Education and Development
Published
2025-12-09
DOI
https://doi.org/10.6007/ijarped/v14-i4/26442
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Revolutionizing Learning Outcomes: The Integration of Educational Management, Ai-Driven Methodologies, and Digital Tools

Nurfaradilla Mohamad Nasri, Yixiang Wang
International Journal of Academic Research in Progressive Education and Development
AI in Service Interactions
article

Revolutionizing Learning Outcomes: The Integration of Educational Management, Ai-Driven Methodologies, and Digital Tools

Nurfaradilla Mohamad Nasri, Yixiang Wang
article en

Abstract

The rapid advancement of Artificial Intelligence (AI) has transformed educational practices, creating opportunities for more personalized and effective learning experiences. This study investigates the impact of AI-driven methodologies and digital tools on learning outcomes in higher education, with a particular focus on educational institutions in Beijing. The research integrates key constructs such as perceived ease of use, perceived usefulness, and adaptive feedback, with user acceptance serving as a mediating factor influencing students’ academic performance. A quantitative design was adopted, collecting survey data from 640 respondents, including 234 teachers and 367 students. The results reveal that students perceived all three factors—ease of use, usefulness, and adaptive feedback—as significantly enhancing learning outcomes through user acceptance. However, teachers indicated that perceived usefulness did not exert a significant influence on their acceptance of AI tools. These findings underscore the importance of usability and adaptive features in shaping positive attitudes toward AI in education. The study contributes to educational management by offering insights into the integration of AI technologies, while also outlining limitations and directions for future research.

International Journal of Academic Research in Progressive Education and DevelopmentVol. 14(4)
National University of Malaysia (MY)
Openalex Percentile: Top 79%
AI in Service Interactions
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.