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Ouaazki, Abdessalam

Nom
Ouaazki, Abdessalam
Affiliation principale
Fonction
Collaborateur.trice scientifique
Email
abdessalam.ouaazki@unine.ch
Identifiants
https://libra.unine.ch/handle/123456789/32227
_
0000-0002-5608-566X

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  • Publication
    Accès libre
    Generative AI-Enabled Conversational Interaction to Support Self-Directed Learning Experiences in Transversal Computational Thinking
    (2024-07)
    Ouaazki, Abdessalam 
    ;
    Bergram, Kristoffer 
    ;
    Juan Carlos Farah
    ;
    Denis Gillet
    ;
    Holzer, Adrian 
    As computational thinking (CT) becomes increasingly acknowledged as an important skill in education, self-directed learning (SDL) emerges as a key strategy for developing this capability. The advent of generative AI (GenAI) conversational agents has disrupted the landscape of SDL. However, many questions still arise about several user experience aspects of these agents. This paper focuses on two of these questions: personalization and long-term support. As such, the first part of this study explores the effectiveness of personalizing GenAI through prompt-tuning using a CT-based prompt for solving programming challenges. The second part focuses on identifying the strengths and weaknesses of a GenAI model in a semester-long programming project. Our findings indicate that while prompt-tuning could hinder ease of use and perceived learning assistance, it might lead to higher learning outcomes. Results from a thematic analysis also indicate that GenAI is useful for programming and debugging, but it presents challenges such as over-reliance and diminishing utility over time.
  • Publication
    Accès libre
    Care-Based Eco-Feedback Augmented with Generative AI: Fostering Pro-Environmental Behavior through Emotional Attachment
    (2024-04-11)
    Berney, Manon 
    ;
    Ouaazki, Abdessalam 
    ;
    Macko, Vladimir 
    ;
    Kocher, Bruno 
    ;
    Holzer, Adrian 
    Lights out! With the escalating climate crisis, eco-feedback has gained prominence over the last decade. However, traditional ap- proaches could be underperforming as they often use data-driven strategies and assume that people only need additional information about their consumption to change behavior. A proposed path to overcome this issue is to design eco-feedback to foster emotional connections with users. However, not much is known about the effectiveness of such designs. In this paper, we propose a novel care- based eco-feedback system. Central to the system is a Tamagotchi- inspired digital character named Infi who gets its life force from the user’s energy savings. Additionally, we harness the latest ad- vancements in generative artificial intelligence to enhance emo- tional attachment through conversational interactions that users can have with Infi. The results of a randomized controlled experi- ment (N=420) convey the fact that this design increases emotional attachment, which in turn increases energy-saving behavior.
  • Publication
    Accès libre
    On the Impact of Digital Boosts on Perceived Stress in a Self-Regulated Learning Experiment
    (2024-01-03)
    Ouaazki, Abdessalam 
    ;
    Macko, Vladimir 
    ;
    Bergram, Kristoffer 
    ;
    Marika Fenley
    ;
    Michael Fuchs
    ;
    Melfi, Giuseppe 
    ;
    Holzer, Adrian 
    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.
  • Publication
    Accès libre
    Leveraging ChatGPT to Enhance Computational Thinking Learning Experiences
    (2023-11)
    Ouaazki, Abdessalam 
    ;
    Bergram, Kristoffer 
    ;
    Holzer, Adrian 
    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.