Vol. 20 / 2025 – International Conference on Virtual Learning
Exploring the potential of e-learning in economic crisis prediction
Daniela GÎFU
This study explores e-learning’s potential to anticipate economic crises, positioning it as a key tool for global financial stability. By leveraging AI-driven text analysis — proven effective in financial forecasting — five predictive algorithms were assessed: exchange rate processing, logistic regression, linear regression, recurrent neural networks, and sentiment analysis. Using a 2008–2018 dataset, the goal is to develop an e-learning system that delivers reliable crisis predictions, enhancing proactive economic risk management.
Keywords:
financial forecasting,
economic crisis,,
e-learning,
predictive models,
AI
CITE THIS PAPER AS:
Daniela GÎFU,
"Exploring the potential of e-learning in economic crisis prediction",
International Conference on Virtual Learning,
ISSN 2971-9291, ISSN-L 1844-8933,
vol. 20,
pp. 143-142,
2025.
https://doi.org/10.58503/icvl-v20y202512