Exploring Deviation in Inquiry Learning: Degrees of Freedom or Source of Problems?

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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 ...

Inclusive teaching is the intentional practice of recognising biases, working to mitigate their impact, and ensuring that students have equitable learning opportunities. In addition to improving students' sense of belonging and self efficacy, inclusive tea ...

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 ...

Training science and engineering students to become responsible citizens and professionals requires novel and creative pedagogical approaches, such as design thinking. This concept relies on processes and tools to develop creativity and problem-solving ski ...

In the current deep learning paradigm, the amount and quality of training data are as critical as the network architecture and its training details. However, collecting, processing, and annotating real data at scale is difficult, expensive, and time-consum ...

Objective. This study aims to design and implement the first deep learning (DL) model to classify subjects in the prodromic states of Alzheimer's disease (AD) based on resting-state electroencephalographic (EEG) signals. Approach. EEG recordings of 17 heal ...

Counting the number of times a patient coughs per day is an essential biomarker in determining treatment efficacy for novel antitussive therapies and personalizing patient care. Automatic cough counting tools must provide accurate information, while runnin ...

With the educational expansion, ever more students start a tertiary degree. At the École Polytechnique Fédérale de Lausanne, an engineering school, the number of bachelor students increased from 3'713 in 2010 to 6'330 in 2022. However, in Switzerland, a co ...

Objective To investigate the utility of an automatic deep learning (DL) method for segmentation of T2 maps in patients with idiopathic inflammatory myopathy (IIM) against healthy controls, and also the association of quantitative T2 values in patients with ...

Background: Healthy older adults show a decrease in motor performance and motor learning capacity as well as in working memory (WM) performance. WM has been suggested to be involved in motor learning processes, such as sequence learning. Correlational evid ...

Exploring Deviation in Inquiry Learning: Degrees of Freedom or Source of Problems?

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Learning From Heterogeneous Data Based on Social Interactions Over Graphs

Inclusive engineering classrooms: student teaching assistants' perspectives

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

Digital Intervention for Collaborative and Human-Centered Activities in Design-Based Learning Scenarios

AutoSynth: Learning to Generate 3D Training Data for Object Point Cloud Registration

An attention-based deep learning approach for the classification of subjective cognitive decline and mild cognitive impairment using resting-state EEG

A Multimodal Dataset for Automatic Edge-AI Cough Detection

Study Success And Failure Of STEM Students And The Connection To Their Learning Habits

Assessment of idiopathic inflammatory myopathy using a deep learning method for muscle T2 mapping segmentation

Targeting the frontoparietal network using bifocal transcranial alternating current stimulation during a motor sequence learning task in healthy older adults