Potential Abstract:
This research study explores the integration of genetic algorithms and augmented reality visualization techniques to enhance learning experiences in the field of learning science. Leveraging open educational resources (OER), the study aims to investigate how the combination of these innovative technologies can facilitate deeper understanding and engagement among learners. By utilizing genetic algorithms to optimize learning pathways and augmented reality for immersive visualization of complex scientific concepts, this study seeks to provide a novel approach to teaching and learning in the digital age. Through a series of experimental interventions and data collection, the research will examine the impact of these technologies on student learning outcomes and attitudes towards science education.
Potential References:
- Analysis of suitable natural feature computer vision algorithms for augmented reality services
- Find, fuse, fight: genetic algorithms to provide engaging content for multiplayer augmented reality games
- Refinement and augmentation for data in micro open learning activities with an evolutionary rule generator
- Research on the scheduling method of distance learning process education resource based on augmented reality
- Augmented Intelligence: Deep Learning, Machine Learning, Cognitive Computing, Educational Data Mining
