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  • Publication
    Accès libre
    Care-Based Eco-Feedback Augmented with Generative AI: Fostering Pro-Environmental Behavior through Emotional Attachment
    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
    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
    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.