I am passionate about the study of human learning, which encompasses improving individual learning efficiency and quality, examining the interaction between personal knowledge and the third world (as described by Popper), and working towards enhancing educational equity. Over the past decade, my experiences have been dedicated to this purpose. In a way, society as a whole serves as my university, with each experience contributing to the construction of the knowledge framework needed to address these issues.
Currently, my research is focused on meaningful learning and spaced learning. Optimizing learning intervals for improved creativity and comprehension is a relatively straightforward strategy to implement. In the era of AI, it is crucial for individuals to engage in 'deep learning' rather than simply mastering basic memorization and procedural knowledge.
I am working to use EEG to identify moments of insight and to capture the neural representation changes resulting from repetitive learning. The rationale for using EEG lies in its cost-effectiveness compared to MRI and MEG, as well as its potential for portability and consumer applications. I take pleasure in designing new experiments, drawing inspiration from the discrepancies between theory and real-life situations. Creating experiments with high ecological validity and providing meaningful growth experiences for participants is one of my greatest hobbies.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent