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The volume collects the papers presented at the Conference “Stat.Edu’21 -New Perspectives in Statistics Education”. The Conference was held at the Department of Political Sciences of the University of Naples Federico II (25-26 March 2021). The conference was the final event of the “ALEAS - Adaptive LEArning in Statistics”, an ERASMUS+ project (https://aleas-project.eu) developed in the period 2018-2021 to design and implement an Adaptive LEArning system able to offer personalised learning paths to students, with the purpose to provide them remedial advice to deal with the “statistics anxiety”.Stat.Edu’21 aimed at stimulating discussions, solicitations and contributions around the central theme of ALEAS, the development of adaptive learning systems in the field of Higher Education as a complementary tool for traditional courses and promote a community of practice in this field.The volume collects 12 papers reporting reflections and quantitative studies covering mainly three topics: the assessment of the effects of anxiety or more generally of a different attitude in the study of Statistics, tools and methods for the assessment of training paths and technology-based learning experiences Il volume raccoglie i contributi presentati alla conferenza “Stat.Edu’21 -New Perspectives in Statistics Education”. La Conferenza è stata ospitata dal Dipartimento di Scienze Politiche dell’Università degli Studi di Napoli Federico II (25-26 marzo 2021). La conferenza è stata organizzata come evento finale del progetto ERASMUS+ “ALEAS - Adaptive LEArning in Statistics” (https://aleas-project.eu) che si è svolto dal 2018 al 2021. Il progetto ha avuto l’obiettivo di sviluppare e implementare un sistema di apprendimento adattivo che offra percorsi di apprendimento personalizzati agli studenti, con lo scopo ultimo di aiutare gli studenti a fronteggiare l’ansia statistica.Stat.Edu’21 ha stimolato riflessioni, discussioni e contributi sul tema di ALEAS e sullo sviluppo di sistemi di apprendimento adattivo in ambito universitario come strumenti complementari ai corsi tradizionali e contribuito lo scambio di buone pratiche.Il volume comprende 12 contributi che propongono riflessioni e studi quantitativi in particolare su 3 temi: la valutazione degli effetti dell’ansia o più generalmente lo studio di diverse attitudini nello studio della statistica, strumenti e metodi per la valutazione dei percorsi di insegnamento e le esperienze di apprendimento basate sulla tecnologia.

Society & social sciences --- technology-based platforms, adaptive learning systems, statistical methods, statistics anxiety, higher education --- technology-based platforms, adaptive learning systems, statistical methods, statistics anxiety, higher education

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The volume collects the papers presented at the Conference “Stat.Edu’21 -New Perspectives in Statistics Education”. The Conference was held at the Department of Political Sciences of the University of Naples Federico II (25-26 March 2021). The conference was the final event of the “ALEAS - Adaptive LEArning in Statistics”, an ERASMUS+ project (https://aleas-project.eu) developed in the period 2018-2021 to design and implement an Adaptive LEArning system able to offer personalised learning paths to students, with the purpose to provide them remedial advice to deal with the “statistics anxiety”.Stat.Edu’21 aimed at stimulating discussions, solicitations and contributions around the central theme of ALEAS, the development of adaptive learning systems in the field of Higher Education as a complementary tool for traditional courses and promote a community of practice in this field.The volume collects 12 papers reporting reflections and quantitative studies covering mainly three topics: the assessment of the effects of anxiety or more generally of a different attitude in the study of Statistics, tools and methods for the assessment of training paths and technology-based learning experiences Il volume raccoglie i contributi presentati alla conferenza “Stat.Edu’21 -New Perspectives in Statistics Education”. La Conferenza è stata ospitata dal Dipartimento di Scienze Politiche dell’Università degli Studi di Napoli Federico II (25-26 marzo 2021). La conferenza è stata organizzata come evento finale del progetto ERASMUS+ “ALEAS - Adaptive LEArning in Statistics” (https://aleas-project.eu) che si è svolto dal 2018 al 2021. Il progetto ha avuto l’obiettivo di sviluppare e implementare un sistema di apprendimento adattivo che offra percorsi di apprendimento personalizzati agli studenti, con lo scopo ultimo di aiutare gli studenti a fronteggiare l’ansia statistica.Stat.Edu’21 ha stimolato riflessioni, discussioni e contributi sul tema di ALEAS e sullo sviluppo di sistemi di apprendimento adattivo in ambito universitario come strumenti complementari ai corsi tradizionali e contribuito lo scambio di buone pratiche.Il volume comprende 12 contributi che propongono riflessioni e studi quantitativi in particolare su 3 temi: la valutazione degli effetti dell’ansia o più generalmente lo studio di diverse attitudini nello studio della statistica, strumenti e metodi per la valutazione dei percorsi di insegnamento e le esperienze di apprendimento basate sulla tecnologia.

technology-based platforms, adaptive learning systems, statistical methods, statistics anxiety, higher education

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Ce travail de fin d'études se concentre sur le développement et l'analyse de Studit, un projet d’application éducative innovante conçue pour optimiser la productivité des sessions d'étude des étudiants en combinant des techniques d'apprentissage efficaces et les capacités de l'intelligence artificielle. Ce mémoire débute par une revue de la littérature qui explore les dernières avancées technologiques et les pratiques pédagogiques contemporaines, afin de contextualiser le projet dans le paysage éducatif actuel.

La seconde partie repose sur une étude exploratoire, incluant des entretiens avec des étudiants, visant à identifier les principaux obstacles organisationnels et productifs auxquels ils font face dans leur parcours académique. Ces échanges ont permis de valider les besoins auxquels Studit cherche à répondre et de proposer des fonctionnalités de l'application pour qu'elle réponde au mieux aux attentes des utilisateurs.

Une analyse concurrentielle détaillée a également été menée, comparant Studit à des solutions existantes telles que StudySmarter, Wooflash et StudyFetch. Cette analyse a permis de positionner Studit de manière distincte sur le marché des technologies éducatives, en mettant l'accent sur une personnalisation avancée et un parcours utilisateur optimisé. En dépit des défis économiques mis en lumière par la première projection des revenus et des coûts, l'intérêt pour Studit, soutenu par une stratégie marketing ciblée et un développement itératif, laisserait entrevoir une viabilité financière à moyen terme.

Ce mémoire participe modestement à la réflexion sur l'intégration des technologies numériques dans l'éducation, en explorant comment certains outils comme Studit pourraient répondre aux besoins spécifiques des étudiants pour un apprentissage plus personnalisé et efficace.

Studit --- LMS --- EdTech --- Adaptive Learning --- education --- Sciences sociales & comportementales, psychologie > Education & enseignement

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The present book contains all of the articles that were accepted and published in the Special Issue of MDPI’s journal Mathematics titled "Computational Intelligence and Human–Computer Interaction: Modern Methods and Applications". This Special Issue covered a wide range of topics connected to the theory and application of different computational intelligence techniques to the domain of human–computer interaction, such as automatic speech recognition, speech processing and analysis, virtual reality, emotion-aware applications, digital storytelling, natural language processing, smart cars and devices, and online learning. We hope that this book will be interesting and useful for those working in various areas of artificial intelligence, human–computer interaction, and software engineering as well as for those who are interested in how these domains are connected in real-life situations.

virtual dialogue assistant --- natural language processing --- machine learning --- online distance learning --- ubiquitous computing --- smart cars --- natural interfaces --- multimodal interaction --- smart devices --- gesture input --- voice input --- digital storytelling --- cultural heritage --- usability evaluation --- multi-platform evaluation --- fingerspelling recognition --- depth sensor --- finger attention --- receptive field --- inter-finger relation --- speaker diarization --- spontaneous speech processing --- voice activity detection --- overlapping speech detection --- speaker extractor models --- speaker number estimation --- model fusion --- quality estimation --- distant speech processing --- artificial neural networks --- agile global software engineering --- architectural knowledge management --- knowledge condensing --- edutainment applications --- emotions aware applications --- adaptive learning --- software architecture --- services --- formal concept analysis --- conceptual knowledge processing --- virtual reality --- human–computer interaction --- automatic speech recognition --- acoustic modeling --- highly inflected word forms --- acoustic background

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Attention in the AI safety community has increasingly started to include strategic considerations of coordination between relevant actors in the field of AI and AI safety, in addition to the steadily growing work on the technical considerations of building safe AI systems. This shift has several reasons: Multiplier effects, pragmatism, and urgency. Given the benefits of coordination between those working towards safe superintelligence, this book surveys promising research in this emerging field regarding AI safety. On a meta-level, the hope is that this book can serve as a map to inform those working in the field of AI coordination about other promising efforts. While this book focuses on AI safety coordination, coordination is important to most other known existential risks (e.g., biotechnology risks), and future, human-made existential risks. Thus, while most coordination strategies in this book are specific to superintelligence, we hope that some insights yield “collateral benefits” for the reduction of other existential risks, by creating an overall civilizational framework that increases robustness, resiliency, and antifragility.

strategic oversight --- multi-agent systems --- autonomous distributed system --- artificial superintelligence --- safe for design --- adaptive learning systems --- explainable AI --- ethics --- scenario mapping --- typologies of AI policy --- artificial intelligence --- design for values --- distributed goals management --- scenario analysis --- Goodhart’s Law --- specification gaming --- AI Thinking --- VSD --- AI --- human-in-the-loop --- value sensitive design --- future-ready --- forecasting AI behavior --- AI arms race --- AI alignment --- blockchain --- artilects --- policy making on AI --- distributed ledger --- AI risk --- Bayesian networks --- artificial intelligence safety --- conflict --- AI welfare science --- moral and ethical behavior --- scenario network mapping --- policymaking process --- human-centric reasoning --- antispeciesism --- AI forecasting --- transformative AI --- ASILOMAR --- judgmental distillation mapping --- terraforming --- pedagogical motif --- AI welfare policies --- superintelligence --- artificial general intelligence --- supermorality --- AI value alignment --- AGI --- predictive optimization --- AI safety --- technological singularity --- machine learning --- holistic forecasting framework --- simulations --- existential risk --- technology forecasting --- AI governance --- sentiocentrism --- AI containment