---
title: AI in Global Higher Ed
url: https://www.ml-quant.com/papers/repec/igg-jismd0-v-16-y-2025-i-1-p-1-24/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:igg:jismd0:v:16:y:2025:i:1:p:1-24
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fservices.igi-global.com%2Fresolvedoi%2Fresolve.aspx%3Fdoi%3D10.4018%2FIJISMD.365913%3Bh%3Drepec%3Aigg%3Ajismd0%3Av%3A16%3Ay%3A2025%3Ai%3A1%3Ap%3A1-24
featured: 2025-01-08
citations: unknown
topic: ML & AI Methods
---


# AI in Global Higher Ed

Research shows China, the US, and England are leading in AI education research, with future trends including AI-VR integration, sentiment analysis, and predictive student performance models.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fservices.igi-global.com%2Fresolvedoi%2Fresolve.aspx%3Fdoi%3D10.4018%2FIJISMD.365913%3Bh%3Drepec%3Aigg%3Ajismd0%3Av%3A16%3Ay%3A2025%3Ai%3A1%3Ap%3A1-24
- Identifier: RePEc:igg:jismd0:v:16:y:2025:i:1:p:1-24
- Released: 2025-01-08
- First featured: Quant Letter No. 81 (2025-01-08): https://www.ml-quant.com/issues/2025-01-08/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: ML & AI Methods

## Related

- [High-Accuracy Stock Market Prediction Using Machine Learning Techniques](https://www.ml-quant.com/papers/ssrn/5235296/): The paper investigates advanced machine learning techniques for stock market prediction, concluding that deep learning models combined with sentiment features perform better than traditional methods.
- [Stock Price Crash Prediction Based on Multimodal Data Machine Learning Models](https://www.ml-quant.com/papers/ssrn/4575784/): The paper suggests a machine learning framework that predicts stock market crashes by combining market data, graph data, and sentiment analysis, with LightGBM showing superior accuracy.
- [Stock Index Prediction with Machine Learning](https://www.ml-quant.com/papers/repec/taf-raaexx-v-31-y-2024-i-4-p-618-637/): The research uses sentiment analysis and machine learning to predict stock indexes, highlighting the impact of investor sentiment and exchange rates on the Shanghai Composite Index.
- [Mamba: Linear-Time Sequence Modeling with Selective State Spaces](https://www.ml-quant.com/papers/arxiv/2312.00752/): Sequence Modeling: Mamba, a neural network architecture that doesn't use attention or MLP blocks, provides faster inference and better performance in language, audio, and genomics than Transformers.
- [Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality](https://www.ml-quant.com/papers/arxiv/2405.21060/): The research identifies a link between state-space models and Transformers in deep learning, leading to the creation of a faster language modeling architecture, Mamba-2.
- [Octo: An Open-Source Generalist Robot Policy](https://www.ml-quant.com/papers/arxiv/2405.12213/): Octo is a large transformer-based policy for robotic manipulation, trained on a vast dataset, that can be instructed via language or images and adapted to new domains.