868 research outputs found

    Modernising European Legal Education (MELE) : Innovative Strategies to Address Urgent Cross-Cutting Challenges

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    This open access book presents innovative strategies to address cross-cutting topics and foster transversal competences. The modernization of European legal education presents a compelling challenge that calls for enhanced interdisciplinary collaboration among academic disciplines and innovative teaching methods. The volume introduces venues towards education innovation and engages with complex and emerging topics such as datafication, climate change, gender, and the aftermath of the COVID-19 pandemic. The insights presented not only emphasize the importance of preserving traditional approaches to legal disciplines and passing them on to future generations, but also underscore the need to critically reassess and revolutionize existing structures. As our societies become more diverse and our understanding of legitimacy, justice, and values undergoes transformations, it is imperative to reconsider the role of traditional values while exploring promising alternative approaches

    Reshaping Higher Education for a Post-COVID-19 World: Lessons Learned and Moving Forward

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    A Closer Look into Recent Video-based Learning Research: A Comprehensive Review of Video Characteristics, Tools, Technologies, and Learning Effectiveness

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    People increasingly use videos on the Web as a source for learning. To support this way of learning, researchers and developers are continuously developing tools, proposing guidelines, analyzing data, and conducting experiments. However, it is still not clear what characteristics a video should have to be an effective learning medium. In this paper, we present a comprehensive review of 257 articles on video-based learning for the period from 2016 to 2021. One of the aims of the review is to identify the video characteristics that have been explored by previous work. Based on our analysis, we suggest a taxonomy which organizes the video characteristics and contextual aspects into eight categories: (1) audio features, (2) visual features, (3) textual features, (4) instructor behavior, (5) learners activities, (6) interactive features (quizzes, etc.), (7) production style, and (8) instructional design. Also, we identify four representative research directions: (1) proposals of tools to support video-based learning, (2) studies with controlled experiments, (3) data analysis studies, and (4) proposals of design guidelines for learning videos. We find that the most explored characteristics are textual features followed by visual features, learner activities, and interactive features. Text of transcripts, video frames, and images (figures and illustrations) are most frequently used by tools that support learning through videos. The learner activity is heavily explored through log files in data analysis studies, and interactive features have been frequently scrutinized in controlled experiments. We complement our review by contrasting research findings that investigate the impact of video characteristics on the learning effectiveness, report on tasks and technologies used to develop tools that support learning, and summarize trends of design guidelines to produce learning video

    Examining the Relationships Between Distance Education Students’ Self-Efficacy and Their Achievement

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    This study aimed to examine the relationships between students’ self-efficacy (SSE) and students’ achievement (SA) in distance education. The instruments were administered to 100 undergraduate students in a distance university who work as migrant workers in Taiwan to gather data, while their SA scores were obtained from the university. The semi-structured interviews for 8 participants consisted of questions that showed the specific conditions of SSE and SA. The findings of this study were reported as follows: There was a significantly positive correlation between targeted SSE (overall scales and general self-efficacy) and SA. Targeted students' self-efficacy effectively predicted their achievement; besides, general self- efficacy had the most significant influence. In the qualitative findings, four themes were extracted for those students with lower self-efficacy but higher achievement—physical and emotional condition, teaching and learning strategy, positive social interaction, and intrinsic motivation. Moreover, three themes were extracted for those students with moderate or higher self-efficacy but lower achievement—more time for leisure (not hard-working), less social interaction, and external excuses. Providing effective learning environments, social interactions, and teaching and learning strategies are suggested in distance education

    Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions

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    As systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount. In response, Explainable AI (XAI) has emerged as a field of research with practical and ethical benefits across various domains. This paper not only highlights the advancements in XAI and its application in real-world scenarios but also addresses the ongoing challenges within XAI, emphasizing the need for broader perspectives and collaborative efforts. We bring together experts from diverse fields to identify open problems, striving to synchronize research agendas and accelerate XAI in practical applications. By fostering collaborative discussion and interdisciplinary cooperation, we aim to propel XAI forward, contributing to its continued success. Our goal is to put forward a comprehensive proposal for advancing XAI. To achieve this goal, we present a manifesto of 27 open problems categorized into nine categories. These challenges encapsulate the complexities and nuances of XAI and offer a road map for future research. For each problem, we provide promising research directions in the hope of harnessing the collective intelligence of interested stakeholders

    Accessibility of Health Data Representations for Older Adults: Challenges and Opportunities for Design

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    Health data of consumer off-the-shelf wearable devices is often conveyed to users through visual data representations and analyses. However, this is not always accessible to people with disabilities or older people due to low vision, cognitive impairments or literacy issues. Due to trade-offs between aesthetics predominance or information overload, real-time user feedback may not be conveyed easily from sensor devices through visual cues like graphs and texts. These difficulties may hinder critical data understanding. Additional auditory and tactile feedback can also provide immediate and accessible cues from these wearable devices, but it is necessary to understand existing data representation limitations initially. To avoid higher cognitive and visual overload, auditory and haptic cues can be designed to complement, replace or reinforce visual cues. In this paper, we outline the challenges in existing data representation and the necessary evidence to enhance the accessibility of health information from personal sensing devices used to monitor health parameters such as blood pressure, sleep, activity, heart rate and more. By creating innovative and inclusive user feedback, users will likely want to engage and interact with new devices and their own data

    Une Approche pour le M-Learning dans le Cloud

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    Le d´eveloppement rapide des r´eseaux sans fil et des technologies mobiles a jou´e un r^ole important dans l’´evolution de la vie quotidienne. La technologie mobile et ses services facilitent la communication et le contact entre les personnes, quel que soit le lieu o`u ils se trouvent. Les appareils portables d’aujourd’hui peuvent ^etre utilis´es pour acc´eder et g´erer de nombreux types de donn´ees, d’un simple texte `a des dossiers multim´edias plus complexes. On peut affirmer que les environnements ´educatifs ne se limitent pas aux ´ecoles ou aux universit´es. Avec l’utilisation de la technologie au sein des syst`emes ´educatifs, les moyens d’acc`es `a l’information ont chang´e et de nouveaux concepts tels que l’apprentissage mobile ont ´emerg´e. Ceci dit, ce nouveau paradigme d’apprentissage soul`eve de nombreux d´efis auxquels les chercheurs sont confront´es pour assurer l’accessibilit´e `a tous les ´etudiants, suivre le rythme inou¨ı de la technologie, des pr´ef´erences et du contexte d’apprentissage L’objectif de cette th`ese est de concevoir un syst`eme d’apprentissage plus adapt´e et de le mettre en œuvre en se basant sur des agents qui prennent en charge la sensibilisation au contexte et le contenu d’apprentissage personnalis´e `a l’aide du Cloud Computing. Le syst`eme fournit un contenu d’apprentissage dispens´e par le biais d’appareils mobiles et adapt´e aux pr´ef´erences et au style d’apprentissage de l’apprenant, et ceci dans le but d’augmenter la satisfaction de l’apprenant et faciliter la r´eussite de l’apprentissage. Le syst`eme comprend des avantages des applications mobiles, des syst`emes multi-agents, de la sensibilit´e au contexte, de la personnalisation p´edagogique et du Cloud Computing. La prise en charge de la sensibilisation au contexte et de la personnalisation est essentielle dans les syst`emes d’apprentissage mobiles, afin qu’ils puissent am´eliorer l’efficacit´e de l’apprentissage et rendre l’apprentissage pertinent d’un point de vue contextuel. Les agents sont habitu´es `a b´en´eficier de leurs avantages qu’ils soient autonomes, r´eactifs, proactifs et sociaux. Les ressources informatiques peuvent ^etre partag´ees entre plusieurs ordinateurs sur un r´eseau ; par cons´equent, seul l’agent de contexte de l’apprenant doit ^etre install´e sur les appareils mobiles de l’apprenant. Le Cloud Computing permet aux apprenants d’acc´eder au contenu d’apprentissage dans tous les lieux o`u la connexion Internet est disponible. Le syst`eme a ´et´e mis en œuvre et test´e avec des ´etudiants du d´epartement d’informatique de l’Universit´e de Middlesex, Londres, Royaume-Uni, ainsi qu’avec des ´etudiants du d´epartement des sciences et technologies de l’Universit´e de T´ebessa, Alg´erie. Les r´esultats exp´erimentaux d´emontrent l’utilit´e et l’efficacit´e de notre syst`eme dans la pratique. Les ´etudiants ont convenu que le mat´eriel de cours pr´esent sur leur ’smart phones’ est tr`es clair, le mat´eriel d’apprentissage recommand´e par le syst`eme est tr`es pertinent dans leur contexte, et le syst`eme d’apprentissage mobile sensible au contexte propos´e est tr`es pratique. Ce dernier repr´esente un outil d’apprentissage utile pour aider le processus d’apprentissage et cela peut promouvoir leurs int´er^ets d’apprentissage
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