I am driven by a deep passion and need to make a difference and leave this world a little better than when I arrived. That's what keeps me going.
- Rick Hansen C.C.,O.B.C.
Yi Wu
Methodolgy
Education Policy Cycle (UNESCO Handbook, Volume 1, 2013)
As an interdisciplinary researcher specializing in global educational policy, my research methodology is anchored in the systematic cultivation of analytical competencies aimed at discerning and delineating policy challenges within the educational landscape. This approach encompasses a critical evaluation of both the intentional and inadvertent ramifications of prevailing educational policies. Additionally, it entails the application of rigorous social science research methodologies, specifically tailored to probe into the multifaceted dimensions of educational administration and policy. This integrative framework not only provides insights into the complex dynamics at play but also fosters a nuanced understanding that informs policy development and implementation.
More Specific Methodologically, I harness both quantitative and qualitative research techniques: employ descriptive and quasi-experimental quantitative methodologies using expansive national datasets and administrative data; additionally, delve into another strand of research that employs semi-structured interviews to generate comprehensive case studies in continuous, iterative partnerships with communities of practice. These include AI educators, policymakers, heads of educational institutions and services, students, and communities across local, national, and international contexts.
Recent Research and Publications:
In alignment with my interdisciplinary approach to educational policy, I have actively engaged in the following research projects and publications:
1. Analysis of Generative AI in Education through Historical Lens
Examining the rapid development of AI within the UC system by university-level students, this study utilizes a historical lens, theoretical analysis, and futuristic perspective. This comprehensive approach aids policymakers and researchers in understanding AI's historical evolution in education, aligning it with educational principles, and balancing opportunities and risks. It also helps in anticipating future trends. >> Learn more
2. Comparative Analysis of AI Education Policies
My policy brief, written in 2020, focused on the examination of AI education policies across different countries, including the United States, China, the UK, Australia, Japan, and South Korea. It delved into the qualitative dimensions through comprehensive case studies, illustrating the nuanced understanding of framing, goals, objectives, application, implementation, and reporting in the context of artificial intelligence and education. The brief relied primarily on secondary data analysis and content analysis, gathering information from existing government reports and scholarly research. >> Learn more
3. Quantitative and Qualitative Analysis of the AI Education in Elementary and Middle Schools
In this research, we utilized questionnaires with 449 students and 199 teachers, interviews with 12 experts, and an Ordinary Least Squares (OLS) statistical method to analyze factors influencing AI cognitive levels in elementary and middle schools. It found strong interest but identified challenges in learning channels, teacher experience, and curriculum, underscoring a need for collaborative efforts to promote AI education. >> Learn more
4. Quantitative and Qualitative Analysis of the Role of Education in a Social-Political Context
Currently, I am on new research utilizing both quantitative and qualitative methodologies. This work aims to explore college students' perceptions of facial recognition and human rights, examining how the national political system, socio-economic conditions, and educational methods influence these perceptions. Additionally, the study will discuss the potential role of educational policies in shaping views on human rights and democracy.