Modeling and Analyzing Inquiry Strategies in Open-Ended Learning Environments

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Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

The recent geopolitical conflicts in Europe have underscored the vulnerability of the current energy system to the volatility of energy carrier prices. In the prospect of defining robust energy systems ensuring sustainable energy supply in the future, the ...

This work proposes a decentralized architecture, where individual agents aim at solving a classification problem while observing streaming features of different dimensions and arising from possibly different distributions. In the context of social learning ...

We are interested in testing properties of distributions with systematically mislabeled samples. Our goal is to make decisions about unknown probability distributions, using a sample that has been collected by a confused collector, such as a machine-learni ...

Conversational tutoring systems (CTSs) offer a promising avenue for individualized learning support, especially in domains like persuasive writing. Although these systems have the potential to enhance the learning process, the specific role of learner cont ...

Over the past few decades, the debates have shifted from whether to how Computer Science (CS) should be introduced into formal education. Given the diverse ways to introduce CS into formal education, and the struggles many countries have faced, considerabl ...

Handwriting is an important skill in children development as well as in education that take years to be mastered. While keyboards and similar technological devices increasingly become more popular, new tools and engaging approaches are also required to kee ...

Purpose The aim of this study was to develop a novel approach for predicting the expression status of Epidermal Growth Factor Receptor (EGFR) and its subtypes in patients with Non-Small Cell Lung Cancer (NSCLC) using a Three-Dimensional Convolutional Neura ...

Learning in interdisciplinary spaces is key for generating new models of thinking (Aboelela et al., 2007, p. 341 in Tobi & Kampen, 2018); interdisciplinary thinking nurtures creativity and a critical enquiry of social challenges thanks to the entanglement ...

The paper presents ICAP (interactive, constructive, active and passive) as the theoretical framework to understand the role of informal learning spaces as an active learning tool when students have informal meetings to work on projects. Students in our En ...

Explainable Artificial Intelligence (XAI) seeks to render Artificial Intelligence (AI) models transparent and comprehensible, potentially increasing trust and confidence in AI recommendations. This research explores the realm of XAI within unsupervised edu ...

Finding optimal bidding strategies for generation units in electricity markets would result in higher profit. However, it is a challenging problem due to the system uncertainty which is due to the lack of knowledge of the strategies of other generation uni ...

Accurate real-time prediction of aerodynamic forces is crucial for the navigation of unmanned aerial vehicles (UAVs). This paper presents a data-driven aerodynamic force prediction model based on a small number of pressure sensors located on the surface of ...

The local physical properties - such as shape and flexibility - of the DNA double-helix is today widely believed to be influenced by nucleic acid sequence in a non-trivial way. Furthermore, there is strong evidence that these properties play a role in many ...

Proteins are foundational biomolecules of life playing a crucial role in a myriad of biological processes. Their function often requires interplay with other biomolecules, including proteins themselves. Protein-protein interactions (PPIs) are essential for ...

Although adults and children differ in self-vs.-other perception, a developmental perspective on this discriminative ability at the brain level is missing. This study examined neural activation for self-vs.-other in a sample of 39 participants spanning fou ...

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

Knowledge of a program's input format is essential for effective input generation in fuzzing. Automated input format reverse engineering represents an attractive but challenging approach to learning the format. In this paper, we address several challenges ...

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring datasets that can be used to build diagnosis algorithms capable of warning ma ...

Modeling and Analyzing Inquiry Strategies in Open-Ended Learning Environments

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Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Identification of typical district configurations: A two-step global sensitivity analysis framework

Learning From Heterogeneous Data Based on Social Interactions Over Graphs

Distribution Testing with a Confused Collector

Evaluating the Impact of Learner Control and Interactivity in Conversational Tutoring Systems for Persuasive Writing

Co-constructing an Effective, Sustainable and Scalable Primary School Computer Science Curricular Reform

The iReCheck project: using tablets and robots for personalised handwriting practice

Advancing EGFR mutation subtypes prediction in NSCLC by combining 3D pretrained ConvNeXt, radiomics, and clinical features

Designing the Future Workforce through STEAM Education

Work in progress: Imagining / Designing informal spaces for learning

Explainable AI for Unsupervised Machine Learning: A Proposed Scheme Applied to a Case Study with Science Teachers

Multi-agent reinforcement learning with graph convolutional neural networks for optimal bidding strategies of generation units in electricity markets

Machine-Learning-Enhanced Real-Time Aerodynamic Forces Prediction Based on Sparse Pressure Sensor Inputs

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Engineering novel protein interactions with therapeutic potential using deep learning-guided surface design

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Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

AIFORE: Smart Fuzzing Based on Automatic Input Format Reverse Engineering

Extensions of Peer Prediction Incentive Mechanisms

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis