Tangible vs. Virtual Representations: when Tangibles Benefit the Training of Spatial Skills

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Reflective writing is known as a useful method in learning sciences to improve the metacognitive skills of students. However, students struggle to structure their reflections properly, limiting the possible learning gains. Previous works in educational tec ...

Data analyses in particle physics rely on an accurate simulation of particle collisions and a detailed simulation of detector effects to extract physics knowledge from the recorded data. Event generators together with a geant-based simulation of the detect ...

This article reports on the current state of the OBI DICT project, a bilingual e-dictionary of oracle-bone inscriptions (OBI), incorporating artificial intelligence (AI) image recognition technology. It first provides a brief overview of the development of ...

Vision Transformers (ViTs) demonstrate remarkable performance in image classification through visual-token interaction learning, particularly when equipped with local information via region attention or convolutions. Although such architectures improve the ...

Computer systems rely heavily on abstraction to manage the exponential growth of complexity across hardware and software. Due to practical considerations of compatibility between components of these complex systems across generations, developers have favou ...

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 ...

Computer simulations are often used as support material for science education, as they can engage students through inquiry-based learning, promote their active interaction in the experimentation phase, and help them visualize abstract concepts. For instanc ...

In this work, we tackle the task of estimating the 6D pose of an object from point cloud data. While recent learning-based approaches have shown remarkable success on synthetic datasets, we have observed them to fail in the presence of real-world data. We ...

Reinforcement learning (RL) is crucial for learning to adapt to new environments. In RL, the prediction error is an important component that compares the expected and actual rewards. Dopamine plays a critical role in encoding these prediction errors. In my ...

Distributed learning has become a promising computational parallelism paradigm that enables a wide scope of intelligent applications from the Internet of Things (IoT) to autonomous driving and the healthcare industry. This paper studies distributed learnin ...

Monitoring forests, in particular their response to climate and land use change, requires studying long time scales. While efficient deep learning methods have been developed to process short time series of satellite imagery, leveraging long time series of ...

Students learn more when they are actively engaged in the learning process. While hands-on activities, labs and projects are moments when students are active, the learning benefits can be amplified with coaching strategies. This activity will enable studen ...

This work studies the learning process over social networks under partial and random information sharing. In traditional social learning models, agents exchange full belief information with each other while trying to infer the true state of nature. We stud ...

As computational thinking (CT) becomes increasingly acknowledged as an important skill in education, self-directed learning (SDL) emerges as a key strategy for developing this capability. The advent of generative AI (GenAI) conversational agents has disrup ...

Light and sound waves can move objects through the transfer of linear or angular momentum, which has led to the development of optical and acoustic tweezers, with applications ranging from biomedical engineering to quantum optics. Although impressive manip ...

In this thesis we explore the applications of projective geometry, a mathematical theory of the relation between 3D scenes and their 2D images, in modern learning-based computer vision systems. This is an interesting research question which contradicts the ...

Orthogonal frequency-division multiplexing (OFDM) is widely used to mitigate inter-symbol interference (ISI) from multipath fading. However, the open nature of wireless OFDM systems makes them vulnerable to jamming attacks. In this context, pilot jamming i ...

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 ...

Objective. A key challenge of virtual reality (VR) applications is to maintain a reliable human-avatar mapping. Users may lose the sense of controlling (sense of agency), owning (sense of body ownership), or being located (sense of self-location) inside th ...

The beta spectrum of the main transition of the 171Tm was measured using a double focalizing spectrometer. The instrument was lately improved in order to reduce its low energy threshold to 34 keV. We used the spectrometer to measure the energy end-point of ...

Tangible vs. Virtual Representations: when Tangibles Benefit the Training of Spatial Skills

Chattez avec Graph Search

Metacognition meets AI: Empowering reflective writing with large language models

Reweighting simulated events using machine-learning techniques in the CMS experiment

The Current State of the OBI DICT Project: A Bilingual e-Dictionary of Oracle-Bone Inscriptions with AI Image Recognition

AdaNCA: Neural Cellular Automata as Adaptors for More Robust Vision Transformer

Secure Interface Design Leveraging Hardware/Software Support

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

Teacher-Mediated and Student-Led Interaction with a Physics Simulation: Effects on the Learning Experience

Match Normalization: Learning-Based Point Cloud Registration for 6D Object Pose Estimation in the Real World

Unveiling the complexity of learning and decision-making

One-Bit Byzantine-Tolerant Distributed Learning via Over-The-Air Computation

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

How to support students to develop coaching and peer teaching skills

Social Opinion Formation and Decision Making Under Communication Trends

Generative AI-Enabled Conversational Interaction to Support Self-Directed Learning Experiences in Transversal Computational Thinking

Wave-momentum shaping for moving objects in heterogeneous and dynamic media

Incorporating Projective Geometry into Deep Learning

Adversarial Training for Jamming-Robust Channel Estimation in OFDM Systems

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

Customizing the human-avatar mapping based on EEG error related potentials during avatar-based interaction

Measurement of the 171Tm beta spectrum