Engineering education is concerned with many challenges according to our current environment characterized by a specific generation of students and a technological breakthrough that is accelerating with AI (Artificial Intelligence) solutions. In this context, we propose a teaching strategy based on an active learning approach and supported by an AI solution. We define five stages in our strategy within an iterative and adaptive learning process. Each stage addresses a subset of learning outcomes and is refined by the AI solution. Our pedagogical strategy is tested with two different student populations, in two distinct courses - considering both Project Based Learning and Problem Based Learning approaches - and according to both face-to-face and online contexts. Moreover, our teaching approach is evaluated by specified criteria in order to measure the impact of integrating the AI solution within the learning situations. Through our analysis, we associate the impact of the AI solution use to specific learning levels, and we rank specific learning factors for the achievement of learning outcomes. On the other hand, we assess the impact of our AI-driven approach on student engagement and motivation. We also identify the teacher’s added value through personalized and adaptive coaching. Our analysis is refined according to the student population and the addressed course. Besides, we compare the experimental group results with a control group. In this paper, we describe our teaching strategy and the associated learning situations. We focus on the impact of using an AI solution on learning outcomes achievement and on student performance.
Affiliations:
ESPRIT School of Engineering, Tunisia
Keywords:
Active learning
AI-Driven Pedagogy
Student Performance
online education
CDIO Standard 2
CDIO Standard 8
Year:
2024
Reference:
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on June 26, 2024 - 12:49 VigneshwaranThi...
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