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Ouaazki, Abdessalam
Nom
Ouaazki, Abdessalam
Affiliation principale
Fonction
Collaborateur.trice scientifique
Email
abdessalam.ouaazki@unine.ch
Identifiants
Résultat de la recherche
2 Résultats
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- PublicationAccès libreOn the Impact of Digital Boosts on Perceived Stress in a Self-Regulated Learning Experiment(2024-01-03)
; ; ; ; Self-regulated learning (SRL) has been adopted as a successful strategy for promoting deeper learning and improving academic performance. In this context, digital boosts have been used to empower learners by expanding their competencies and helping them reach their objectives. However, existing literature has primarily focused on the academic performance-related outcomes of digital boosts, while their potential effects on emotional and psychological aspects like stress and well-being remain comparatively under-explored. In this study, we address this gap by studying the impact of digital boosts on perceived stress, in addition to study time. We have designed a digital SRL support system, through which we have delivered digital feedback boosts. To evaluate this system, we conducted a pilot study with 60 university students. Our digital boosts have helped students keep a steady study time. However, they have caused an increase in perceived stress, especially among students who did not attain their study time plans. - PublicationAccès libreLeveraging ChatGPT to Enhance Computational Thinking Learning Experiences(2023-11)
; ; Given the pervasive reliance on technology in modern society, teaching Computational Thinking (CT) abilities is becoming increasingly relevant. These abilities, such as modeling and coding, have become crucial for a larger audience of students, not only those who wish to become software engineers or computer scientists. Recent advances in Large Language Models (LLMs), such as ChatGPT, provide powerful assistance to complete computational tasks, by simplifying code generation and debugging, and potentially enhancing interactive learning. However, it is not clear if these advances make CT tasks more accessible and inclusive for all students, or if they further contribute to a digital skills divide, favoring the top students. To address this gap, we have created and evaluated a novel learning scenario for transversal CT skills that leveraged LLMs as assistants. We conducted an exploratory field study during the spring semester of 2022, to assess the effectiveness and user experience of LLM-augmented learning. Our results indicate that the usage of ChatGPT as a learning assistant improves learning outcomes. Furthermore, contrary to our predictions, the usage of ChatGPT by students does not depend on prior CT capabilities and as such does not seem to exacerbate prior inequalities.