Exploring the Computational Effects of Advanced Deep Neural Networks on Logical and Activity Learning for Enhanced Thinking Skills
Jilin International Studies University · Merced College · +1 more institution
Abstract
The Logical and Activity Learning for Enhanced Thinking Skills (LAL) method is an educational approach that fosters the development of critical thinking, problem-solving, and decision-making abilities in students using practical, experiential learning activities. Although LAL has demonstrated favorable effects on children’s cognitive growth, it presents various obstacles, including the requirement for tailored instruction and the complexity of tracking advancement. The present study presents a model known as the Deep Neural Networks-based Logical and Activity Learning Model (DNN-LALM) as a potential solution to tackle the challenges above. The DNN-LALM employs sophisticated machine learning methodologies to…
Citation impact
- FWCI
- 17.14
- Percentile
- 100%
- References
- 21
Authors
3Topics & keywords
- Experiential learning
- Cognition
- Logical reasoning
- Computer science
- Artificial intelligence
- Recall
- Artificial neural network
- Tracking (education)