Abstract
As institutions expand access to international education, success is increasingly defined not by who enrolls, but by how well students thrive. In an era shaped by artificial intelligence, evolving expectations, and growing global competition, universities are being challenged to rethink how they measure international student outcomes.
This panel brings together institutional leaders and data experts to explore how universities can move beyond enrollment metrics toward more holistic measures of success, including belonging, wellbeing, persistence, and post-graduation impact. The panel will feature institutional case studies across the United States and Asia-Pacific, the session will highlight emerging approaches to evaluating student experiences and outcomes.
Panelists will also examine the role of AI and data analytics in shaping how success is defined and measured, raising important questions about what is valued and how institutions can maintain human-centered approaches.
Attendees will gain practical frameworks to align recruitment, student support, and evaluation efforts to foster more meaningful and inclusive student success.
Learning objectives
- Analyze how current approaches to international student success measurement extend beyond access and enrollment to include belonging, wellbeing, and long-term outcomes.
- Evaluate how institutions in the United States and Asia-Pacific are using data to assess and improve international student experiences and success.
- Identify practical strategies for aligning recruitment, student support, and evaluation frameworks to foster more inclusive and meaningful student outcomes.
- Assess the opportunities and limitations of AI and data analytics in measuring student success while maintaining a human-centered approach.
Target audience
- Higher education and institution programs that focus on student success
- Institutions that use AI tools to measure student success or want to learn
