Responsible AI Use in Digital Universities: Supporting Academic Writing, Course Translation, and Autonomous Learning

Team name: Synergy System

Use of AI tools : If you used AI, please specify:

During this project, our team used several AI tools, including:

• ChatGPT

• Google Translate

• Grammarly

These tools were used for:

• research and information gathering;

• structuring ideas and organizing the report;

• improving academic writing;

• translating content between English and French;

• refining arguments and reflections.

External feedback & contributions :

These AI tools supported our work by helping us improve clarity, structure our analysis, and explore different perspectives on responsible AI use in higher education. However, all final ideas, reflections, and conclusions were critically reviewed and validated by our team.

Several people and discussions contributed to the improvement of our project:

• Chelza – AI Grand Challenge Coordinator – guidance and follow-up during the challenge;

• Johanna (T-Twice team) – feedback and critical questions about project scope and methodology;

• Noel and other participants – discussions on responsible AI use, cognitive dependency, and innovation;

• Fellow students and professors – exchanges on digital learning challenges and AI practices in universities.

Initial contribution: Please provide the link (URL) to your initial contribution on the platform: Responsible Use of Artificial Intelligence in Higher Education: Supporting Academic Writing, Learning Autonomy, and Cybersecurity Training

Final contribution:

Title:
Responsible AI Use in Digital Universities: Supporting Academic Writing, Course Translation, and Autonomous Learning

Introduction

Artificial intelligence is increasingly transforming higher education, especially in digital universities based on distance learning models. In these environments, students rely heavily on digital tools while being expected to work autonomously.

Our contribution explores how students use AI tools for academic writing, course translation, and learning support. We focus particularly on the realities of students in digital universities, where academic isolation, limited supervision, and language barriers often create learning difficulties.

Context and challenges

Students in digital universities frequently use AI tools to:

• translate technical courses;

• summarize lessons;

• structure reports;

• improve writing quality;

• support technical learning activities.

Although these tools can improve accessibility and productivity, they also raise concerns related to:

• academic integrity;

• plagiarism;

• excessive dependence on AI;

• reduced critical thinking.

Guided AI use

One important aspect of our proposal is the concept of “guided AI use.” Instead of simply accepting AI-generated answers, students would be encouraged to critically interact with AI outputs.

For example, students could:

• compare AI-generated summaries with their own analysis;

• identify errors or biases;

• justify their reasoning and final choices.

The goal is to transform AI into a collaborative learning assistant that supports creativity, critical thinking, and learner autonomy.

Reflection on the process

During Phase 2, our contribution evolved significantly through feedback, discussions, and comments received on the platform.

Initially, our project included cybersecurity training as a major component because several members of our team have cybersecurity backgrounds. However, feedback pointed out that the project became more coherent when focused specifically on academic writing, course translation, learner autonomy, and responsible AI use in digital universities.

Another important feedback highlighted the risks of excessive AI use and the tendency of students to seek quick solutions instead of engaging in deep learning. This encouraged us to strengthen the “guided AI use” approach and emphasize critical interaction with AI systems.

These discussions helped us better contextualize our proposal, clarify our objectives, and develop a more balanced perspective on the opportunities and risks of AI in higher education.

Conclusion

AI tools can become valuable educational support systems in digital universities if they are used responsibly. Our project promotes a balanced approach where AI supports learning, creativity, and autonomy without replacing students’ reasoning and critical thinking abilities.

Reflection on the process (importan

During Phase 2, our contribution evolved significantly through the feedback, discussions, and reflections shared on the platform.

At the beginning, our work mainly focused on the general use of AI tools by students in universities. However, several comments pointed out that the context was too broad and could apply to almost any institution. One important feedback suggested that we should better integrate the specific reality of digital universities and distance learning environments, particularly the challenges related to learner autonomy, academic isolation, and limited proximity supervision.

As a result, we reoriented our contribution toward the experience of students in digital universities such as Université Numérique Cheikh Hamidou Kane. We expanded the analysis by describing concrete situations faced by students, including difficulties in academic writing, translating technical courses written in English, and working independently in online learning environments.

Another important discussion focused on the risk of excessive AI use. Feedback highlighted that students often tend to seek the fastest solution instead of developing deeper understanding and critical thinking. This encouraged us to explore not only the benefits of AI, but also its limitations and the importance of responsible use. We therefore introduced the idea that AI should function as a collaborative learning assistant rather than a tool that replaces human reasoning.

We also integrated cybersecurity-related use cases in order to connect the project with our academic background and demonstrate practical examples of AI use in technical education.

This process greatly strengthened our final proposal. The contribution became more contextualized, more realistic, and more closely connected to the lived experiences of students in digital universities. It also allowed us to adopt a more balanced perspective by combining opportunities, risks, ethical concerns, and educational innovation regarding the use of AI in higher education.