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An interdisciplinary research team from Feng Chia University, consisting of Fu-Guei Wang from the Bachelor's Program in Artificial Intelligence Technology and Applications and Yu-Chieh Chen from the Department of Business Administration, recently won First Prize for Best Paper at the 2026 International Conference on Big Data and ERP Academic and Practical Applications. Supervised by Professor Ju-Juan Wu of the Department of Business Administration, the team’s research on higher education transformation and the AI talent gap stood out among more than 200 submissions from across the Asia-Pacific region, showcasing the university’s strong research capabilities and successful interdisciplinary collaboration.
Professor Ju-Juan Wu (left) from the Department of Business Administration and student Yu-Chieh Chen (right) accepted the First Prize for Best Paper on behalf of the team at the 2026 International Conference on Big Data and ERP.
Organized by the Chinese ERP Society, the International Conference on Big Data and ERP Academic and Practical Applications was held on March 21 at National Central University. The conference attracted more than 200 submissions from academia and industry throughout the Asia-Pacific region. Following multiple rounds of rigorous anonymous review, only 67 papers covering emerging topics such as AI applications, ESG sustainability, and financial technology were selected for presentation.
The award-winning paper, “Transformation of Higher Education in the Age of Artificial Intelligence: Exploring the Evolution of Information-Related Curricula and Industry Talent Demand,” addresses a pressing challenge shared by both students and industry. As a student in the AI program, Fu-Guei Wang has long been concerned with whether information technology education aligns with practical industry needs. Applying statistical methods and text-mining techniques, she systematically analyzed curriculum structures across universities and cross-referenced the findings with large-scale job market data to identify the competencies most sought after for AI-related positions in Taiwan.
Meanwhile, Yu-Chieh Chen, who previously studied in an information technology program at another university before joining the Department of Business Administration, brought a unique interdisciplinary perspective to the project. Her academic background enabled her to provide valuable insights into differences within information education systems. She actively contributed to data analysis, manuscript preparation, and conference presentations, enriching the data-driven research with managerial perspectives and practical business insights.
Reflecting on her second participation in the conference, Fu-Guei Wang shared that this year’s work featured more rigorous approaches to data anonymization and data visualization. More importantly, she incorporated AI tools into the research workflow, significantly reducing the time required for manual labeling and trial-and-error processes. “Learning how to empower myself through AI tools has been my greatest takeaway,” she noted. She added that under Professor Ju-Juan Wu’s dedicated mentorship over the past two years, she not only developed comprehensive research skills but also expanded her perspective from technical analysis to broader discussions of educational policy.
Representing the team at the conference, Yu-Chieh Chen emphasized that the transformation of higher education in the AI era is an issue of growing importance across sectors, and this sense of mission motivated her throughout the project. “It was incredibly rewarding to present our findings and exchange ideas with experts from academia and industry, especially after receiving such positive feedback from the judges,” she said. She added that preparing for the presentation deepened her appreciation for the meticulous nature of academic research and expressed gratitude to Professor Ju-Juan Wu and Fu-Guei Wang for their guidance and collaboration throughout the project.
The Feng Chia University faculty-and-student team poses for a group photo, celebrating their first-place achievement.
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