Can AI teach me employability? A multi-national study in three countries

Area of Science:

• Educational Technology
• Artificial Intelligence in Education
• Higher Education Pedagogy

Background:

• Growing need for scalable and engaging educational tools in Higher Education (HE).
• Limitations of existing online learning platforms like Massive Open Online Courses (MOOCs).
• Emerging potential of Artificial Intelligence (AI) and Large Language Models (LLMs) in educational delivery.

Purpose of the Study:

• To evaluate the impact and effectiveness of an AI teacher on HE students.
• To assess student engagement, satisfaction, and completion rates with an AI-delivered course.
• To compare the efficacy of AI-based virtual teachers against MOOC platforms.

Main Methods:

• Utilized an AI avatar, OIMISA, powered by a fine-tuned Large Language Model (LLM) for teaching.
• Delivered a 9-lesson course on employability and transferable skills to 207 HE students across three countries.
• Collected data on student engagement, satisfaction, and course completion rates.

Main Results:

• Achieved a noteworthy course completion rate exceeding 47%.
• Observed high levels of student engagement across all participating cohorts.
• Reported high student satisfaction rates with the AI teacher experience.

Conclusions:

• AI-based virtual teachers demonstrate significant potential for HE students globally.
• The AI teacher model shows comparable or superior outcomes to MOOC platforms in terms of engagement and satisfaction.
• This study highlights a viable, innovative approach to online learning in higher education.