Transforming Higher Education Through AI Technology: A Design Science Research Approach

This study addresses the pressing challenges in higher education—rising tuition costs, unsustainable student debt, and the growing disconnect between theoretical instruction and practical through the integration of artificial intelligence (AI) and digital twin technology within a Design Science Research (DSR) framework. By leveraging AI-driven agents and the concept of a “student digital twin,” the proposed system creates a dynamic, personalized learning environment. Central to the system is a comprehensive digital twin for each student that captures real-time data on learning styles, performance, and academic objectives. Despite challenges such as data privacy, technical complexity, and algorithmic bias, the iterative DSR approach offers a robust methodology for refining and scaling the system. Future research directions include empirical validation, the development of privacy-preserving mechanisms, and the integration of complementary technologies to foster a more accessible, responsive, and dynamic higher education landscape.

Institutions

Publication Details

Journal
Journal of the Association for Information Systems
Published
2025-08-15
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Transforming Higher Education Through AI Technology: A Design Science Research Approach

Journal of the Association for Information Systems
Digital Transformation in Industry
article

Transforming Higher Education Through AI Technology: A Design Science Research Approach

article en

Abstract

This study addresses the pressing challenges in higher education—rising tuition costs, unsustainable student debt, and the growing disconnect between theoretical instruction and practical through the integration of artificial intelligence (AI) and digital twin technology within a Design Science Research (DSR) framework. By leveraging AI-driven agents and the concept of a “student digital twin,” the proposed system creates a dynamic, personalized learning environment. Central to the system is a comprehensive digital twin for each student that captures real-time data on learning styles, performance, and academic objectives. Despite challenges such as data privacy, technical complexity, and algorithmic bias, the iterative DSR approach offers a robust methodology for refining and scaling the system. Future research directions include empirical validation, the development of privacy-preserving mechanisms, and the integration of complementary technologies to foster a more accessible, responsive, and dynamic higher education landscape.

Journal of the Association for Information Systems
California State University, Monterey Bay (US)
Quality Education
Openalex Percentile: Top 42%
Digital Transformation in Industry
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.

Transforming Higher Education Through AI Technology: A Design Science Research Approach · Journal of the Association for Information Systems (2025) | TGRS Research Map | TGRS