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Updated: Sep 23, 2025

Measuring the Functional Abilities of Children Aged 3-6 Years Old with Observational Methods and Computer Tools
Published on: June 20, 2020
Research on the Correlation between Multisource Big Data Virtual Assisted Preschool Education and the Development of
1School of Education, Shannxi Fashion Engineering University, Xi'an, Shaanxi 712000, China.
Fostering children's innovation ability is crucial for future success. Key factors like family involvement, teaching methods, and peer interaction positively influence this essential skill.
Area of Science:
- Educational Psychology
- Computer Science
- Data Science
Background:
- Innovation ability is a vital component of children's core literacy and a primary objective of science curricula.
- Developing innovation skills is essential for children to navigate scientific challenges in personal and social contexts and adapt to future life.
- Database design principles, including table structure, storage allocation, and indexing, are critical for system optimization and user experience.
Purpose of the Study:
- To investigate the influencing factors on children's innovation ability.
- To introduce an optimized FP-growth parallel algorithm for efficient data processing and load balancing in distributed systems.
Main Methods:
- A survey was conducted to identify and analyze factors influencing children's innovation ability, with statistical models used for evaluation.
- The study implemented a traffic-optimized FP-growth parallel algorithm (TFP) for database management, prioritizing minimal data transmission between nodes.
- Data storage utilized MySQL for system data and Hive for user-uploaded data, with the TFP algorithm enhancing the FP-growth algorithm's efficiency.
Main Results:
- The survey confirmed that family participation and investment, teacher instruction, and peer collaboration positively impact children's innovation ability.
- Experimental results demonstrated that the TFP algorithm achieves node load balancing and reduces inter-node communication, outperforming the traditional FP-growth parallel algorithm.
- Model evaluation confirmed the survey's findings, indicating a strong correlation between identified factors and children's innovation capacity.
Conclusions:
- Family, teachers, and peers play significant roles in cultivating children's innovation skills.
- The developed TFP algorithm offers a more efficient approach to parallel data processing compared to existing methods.
- Enhancing children's innovation ability is critical for their development and future readiness.
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