GenAI-Enhanced Learning: A Framework to Align the Third Level of Bloom’s Taxonomy

Authors

DOI:

https://doi.org/10.34190/ecel.24.1.4013

Keywords:

AI-enhanced Learning, Generative AI, Bloom’s Taxonomy, Learning Activities, Educational Technology, Kolb’s Experiential Learning Theory

Abstract

Since the first release of ChatGPT, every aspect of today’s world has been impacted. Artificial intelligence is no longer confined to high-tech companies or large industrial R&D departments. Countless smartphone applications are being continuously launched and immediately adopted by end users.  In view of this, ethical concerns have been raised in several studies, emphasizing the urgent need for the responsible use of generative AI. The education system is no exception. Students across academic levels now use generative AI for essay writing, coding, and project-based assignments. Pedagogical and EdTech researchers worldwide express increasing concern about the future of education. However, the detrimental effects of using these tools have become evident. Recent studies have observed a significant decline in students' competencies in fundamental subjects such as mathematics and languages.  Furthermore, the role of teachers extends beyond presenting information to students. Teaching is a complex process that involves providing learner support, closely guiding students, and offering learning paces tailored to their needs. While AI cannot replace educators, action plans are needed to adapt to the undeniable presence of generative AI in education. Thus, this study asks how we can harness the power of AI to assist teachers to design classroom activities, rather than focusing on student use of these tools or imposing bans in schools and universities. We therefore explored the alignment of Bloom’s Taxonomy levels with AI-enhanced learning, specifically leveraging the third level of Bloom’s Taxonomy, “Applying. This paper introduces a framework to assist teachers in designing workshops and learning activities. By applying acquired knowledge through AI-powered simulations, and grounding this approach in Kolb’s Experiential Learning Theory, the framework aims to reinforce cognitive domain concepts from Bloom’s Taxonomy while placing experiential learning at its core and offering substantial added value to the learning experience.

Author Biographies

Hafsa Toulali, Ecole Mohammadia d'Ingénieurs

Hafsa Toulali holds an Engineering degree in Telecommunications from the National School of Applied Sciences (ENSA), Morocco, and a Master’s degree in Smart-EdTech from Côte d’Azur University, France. She is a PhD student at Mohammadia School of Engineers (EMI), Morocco. Her research covers generative AI in education, instructional design, and gamification. hafsa.toulali@research.emi.ac.ma

Asmaâ Retbi, Mohammadia School of Engineers (EMI); Mohammed V University in Rabat, Morocco

Asmaâ Retbi is an Associate Professor at Mohammadia School of Engineers (EMI). She holds an Engineering degree in Computer Science from Institut National Des Postes et Télécomunications (INPT) and a PhD in Computer Science from Mohammadia School of Engineers (EMI), Morocco. Her research focuses on Machine Learning, Recommender systems, Generative IA, Blockchain Technology, Software Engineering, and Educational Technologies. retbi@emi.ac.ma

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Published

2025-10-17