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Utilizing crowdsourcing and machine learning in education: Literature review
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It’s not Magic After All – Machine Learning in Snap! using Reinforcement Learning
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Accelerated Move for AI Education in China
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Machine Learning Interpretability: A Survey on Methods and Metrics
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Envisioning AI for K-12: What Should Every Child Know about AI?
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An Integrative Framework for Artificial Intelligence Education
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The Impact of Artificial Intelligence on Learning, Teaching, and Education: Policies for the Future. JRC Science for Policy Report.
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Artificial Intelligence and Inclusive Education
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Competence for Students’ Future: Curriculum Change and Policy Redesign in China
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Classroom Assessment to Support Teaching and Learning
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The Right Direction Needed to Develop White-Box Deep Learning in Radiology, Pathology, and Ophthalmology: A Short Review
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In Search of Deeper Learning
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What Can You Do with Educational Technology that is Getting More Human?
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Predicting Secondary School Students' Performance Utilizing a Semi-supervised Learning Approach
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Inclusive AI literacy for kids around the world
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Special Session: AI for K-12 Guidelines Initiative
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Applying Machine Learning to Improve Curriculum Design
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A Pragmatic Definition of the Concept of Theoretical Saturation
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A new generation of AI: A review and perspective on machine learning technologies applied to smart energy and electric power systems
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Engagement detection in online learning: a review
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Deep learning and its applications to machine health monitoring
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Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
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Self-directed language learning in a mobile-assisted, out-of-class context: do students walk the talk?
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Case Study of Baiyun and Caohai Lakes Implies How to Implement Wetland Restoration/Creation
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Design and Development of High School Artificial Intelligence Textbook Based on Computational Thinking
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Machine Learning in Agriculture: A Review
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From Machine Learning to Explainable AI
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A survey on deep learning for big data
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Deep learning for healthcare applications based on physiological signals: A review
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Processing of personal and medical data by judicial institutions in the context of the enforcement of Regulation EU 2016/679 – General Data Protection Regulation (GDPR)
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AI in Education needs interpretable machine learning: Lessons from Open Learner Modelling
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Adolescents' Self-regulation During Job Interviews Through an AI Coaching Environment
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Tensions in specifying computing curricula for K-12: Towards a principled approach for objectives
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Ontology-based Recommender System in Higher Education
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Classroom assessment and pedagogy
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Continual Lifelong Learning with Neural Networks: A Review
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Breve revisión de aplicaciones educativas utilizando Minería de Datos y Aprendizaje Automático
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Multimodal Machine Learning: A Survey and Taxonomy
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Do Students Develop Towards More Deep Approaches to Learning During Studies? A Systematic Review on the Development of Students’ Deep and Surface Approaches to Learning in Higher Education
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Efficient Processing of Deep Neural Networks: A Tutorial and Survey
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Recommending peers for learning: Matching on dissimilarity in interpretations to provoke breakdown
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Towards A Rigorous Science of Interpretable Machine Learning
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Detecting Student Emotions in Computer-Enabled Classrooms
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It’s Not about the Tools: The Management Engineer’s Role in Achieving Significant, Sustainable Change
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A critique of the deep and surface approaches to learning model
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The teaching of qualitative research methods in information systems: an explorative study utilizing learning theory
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Machine Learning: The State of the Art
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Learning outcomes and ways of thinking across contrasting disciplines and settings in higher education
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Data Mining: Concepts and Techniques
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ON QUALITATIVE DIFFERENCES IN LEARNING: I—OUTCOME AND PROCESS*
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Born in China, taught by AI
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Accountability in Human and Artificial Intelligence Decision-Making as the Basis for Diversity and Educational Inclusion
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Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence
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Media and Information Literacy: Challenges and opportunities for the World of Education
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Thematic Working Group 4 - State of the Art in Thinking About Machine Learning: Implications for Education
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NAPLAN online Automated scoring research
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Explaining decisions made with AI: Draft guidance for consultation - Part 1: The basics of explaining AI
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Preliminary study on the technical and legal aspects relating to the desirability of a standard-setting instrument on the ethics of artificial intelligence : 206 EX/42
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Explainable AI and the future of machine learning
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Exploring Echo-Systems: How Algorithms Shape Immersive Media Environments.
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Assessment as, for, and of Twenty-First Century Learning Using Information Technology: An Overview
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China looks to school kids to win the global AI race
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Regulation ( EU ) 2016 / 679 of the European Parliament and of the Council : General Data Protection Regulation
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Brief review of educational applications using data mining and machine learning
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WHY SHOULD MACHINES LEARN
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Michelle Deschênes is a doctoral student in educational technology at Laval University. Her research focuses on teachers' agency and professional development
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created professional development materials and led workshops across Canada as part of the CanCode program launched by Innovation, Science and Economic Development Canada
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Machine learning for human learners: opportunities, issues,…
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semi-supervised learning where the training set has some missing data and the algorithms are still able to learn from the incomplete data