Preface: Connecting Learning Design and Learning Analytics

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Model-free Reinforcement Learning (RL) generally suffers from poor sample complexity, mostly due to the need to exhaustively explore the state-action space to find well-performing policies. On the other hand, we postulate that expert knowledge of the syste ...

This article reviews significant advances in networked signal and information processing (SIP), which have enabled in the last 25 years extending decision making and inference, optimization, control, and learning to the increasingly ubiquitous environments ...

Background Early exposure to Computer Science (CS) and Computational Thinking (CT) for all is critical to broaden participation and promote equity in the field. But how does the introduction of CS and CT into primary school curricula impact learning, perce ...

The motor learning process entails plastic changes in the brain, especially in brain network reconfigurations. In the current study, we sought to characterize motor learning by determining changes in the coupling behaviour between the brain functional and ...

We propose ordering-based approaches for learning the maximal ancestral graph (MAG) of a structural equation model (SEM) up to its Markov equivalence class (MEC) in the presence of unobserved variables. Existing ordering-based methods in the literature rec ...

Nowadays, the integration of home automation systems with smart thermostats is a common trend, designed to enhance resident comfort and conserve energy. The introduction of smart thermostats that can run machine learning algorithms has opened the door for ...

Order, regularities, and patterns are ubiquitous around us. A flock of birds maneuvering in the sky, the self-organization of social insects, a global pandemic or a traffic jam are examples of complex systems where the macroscopic patterns arise from the m ...

What conceptions do teachers hold about learning activities to develop students’ transversal skills? This qualitative exploration at a research-intensive engineering school draws on interviews and focus groups to explore teachers’ ideas about developing in ...

In data-parallel optimization of machine learning models, workers collaborate to improve their estimates of the model: more accurate gradients allow them to use larger learning rates and optimize faster. In the decentralized setting, in which workers commu ...

Motor skill learning is a crucial process at all ages. However, healthy aging is often accompanied by a reduction in motor learning capabilities. This study characterized the brain dynamics of healthy older adults during motor skill acquisition and identif ...

Preface: Connecting Learning Design and Learning Analytics

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Computationally Efficient Reinforcement Learning: Targeted Exploration leveraging Simple Rules

Networked Signal and Information Processing: Learning by multiagent systems

How are primary school computer science curricular reforms contributing to equity? Impact on student learning, perception of the discipline, and gender gaps

Brain connectome correlates of short-term motor learning in healthy older subjects

Novel Ordering-based Approaches for Causal Structure Learning in the Presence of Unobserved Variables

PePTM: An Efficient and Accurate Personalized P2P Learning Algorithm for Home Thermal Modeling

Human-Robot Swarm Interaction: An Explorative Path to Foster Complex Systems Understanding

Are engineering teachers ready to leverage the power of play to teach transversal skills?

Beyond Spectral Gap: The Role of the Topology in Decentralized Learning

Early motor skill acquisition in healthy older adults: brain correlates of the learning process