Advancing Global South University Education with Large Language Models

TL;DR

This paper explores how integrating large language models like ChatGPT into courses at Telkom University in Indonesia can help improve higher education quality in the Global South amidst resource constraints.

Contribution

It presents an experimental plan for using LLMs to enhance teaching and learning in Global South universities, addressing resource and quality disparities.

Findings

Initial implementation in five courses at Telkom University.

Potential for LLMs to support teaching in resource-constrained settings.

Framework for integrating LLMs into higher education in the Global South.

Abstract

In recent years, it has been observed that the center of gravity for the volume of higher education has shifted to the Global South. However, research indicates a widening disparity in the quality of higher education between the Global South and the Global North. Although investments in higher education within the Global South have increased, the rapid surge in student numbers has resulted in a decline in public expenditure per student. For instance, the student-to-teacher ratio in the Global South is significantly higher compared to that in the Global North, which poses a substantial barrier to the implementation of creative education. In response, Telkom University in Indonesia has embarked on an experiment to enhance the quality of learning and teaching by integrating large language models (LLMs) such as ChatGPT into five of its courses-Mathematics, English, Computing, Computer Systems, and Creative Media. This article elucidates the ongoing experimental plan and explores how the integration of LLMs could contribute to addressing the challenges currently faced by higher education in the Global South.