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of 3 716
pro vyhledávání: '"P. Leinonen"'
Motivation: Students learning to program often reach states where they are stuck and can make no forward progress. An automatically generated next-step hint can help them make forward progress and support their learning. It is important to know what
Externí odkaz:
http://arxiv.org/abs/2411.18151
Autor:
Carpentieri, Alberto, Leinonen, Jussi, Adie, Jeff, Bonev, Boris, Folini, Doris, Hariri, Farah
Accurate surface solar irradiance (SSI) forecasting is essential for optimizing renewable energy systems, particularly in the context of long-term energy planning on a global scale. This paper presents a pioneering approach to solar radiation forecas
Externí odkaz:
http://arxiv.org/abs/2411.08843
Autor:
Zhuo, Zewen, Belevich, Ilya, Leinonen, Ville, Jokitalo, Eija, Malm, Tarja, Sierra, Alejandra, Tohka, Jussi
Segmentation of cellular structures in electron microscopy (EM) images is fundamental to analyzing the morphology of neurons and glial cells in the healthy and diseased brain tissue. Current neuronal segmentation applications are based on convolution
Externí odkaz:
http://arxiv.org/abs/2411.02562
Computing educators and researchers have used programming process data to understand how programs are constructed and what sorts of problems students struggle with. Although such data shows promise for using it for feedback, fully automated programmi
Externí odkaz:
http://arxiv.org/abs/2411.00414
There is a great need for data in computing education research. Data is needed to understand how students behave, to train models of student behavior to optimally support students, and to develop and validate new assessment tools and learning analyti
Externí odkaz:
http://arxiv.org/abs/2411.10455
Weather and climate data are often available at limited temporal resolution, either due to storage limitations, or in the case of weather forecast models based on deep learning, their inherently long time steps. The coarse temporal resolution makes i
Externí odkaz:
http://arxiv.org/abs/2410.18904
Autor:
MacNeil, Stephen, Rogalska, Magdalena, Leinonen, Juho, Denny, Paul, Hellas, Arto, Crosland, Xandria
Large language models (LLMs) present an exciting opportunity for generating synthetic classroom data. Such data could include code containing a typical distribution of errors, simulated student behaviour to address the cold start problem when develop
Externí odkaz:
http://arxiv.org/abs/2410.09193
Autor:
Kerslake, Chris, Denny, Paul, Smith IV, David H, Prather, James, Leinonen, Juho, Luxton-Reilly, Andrew, MacNeil, Stephen
Introductory programming courses often emphasize mastering syntax and basic constructs before progressing to more complex and interesting programs. This bottom-up approach can be frustrating for novices, shifting the focus away from problem solving a
Externí odkaz:
http://arxiv.org/abs/2410.03063
Autor:
Reeves, Brent N., Prather, James, Denny, Paul, Leinonen, Juho, MacNeil, Stephen, Becker, Brett A., Luxton-Reilly, Andrew
Generative AI (GenAI) and large language models in particular, are disrupting Computer Science Education. They are proving increasingly capable at more and more challenges. Some educators argue that they pose a serious threat to computing education,
Externí odkaz:
http://arxiv.org/abs/2407.09231
Autor:
Koutcheme, Charles, Dainese, Nicola, Hellas, Arto, Sarsa, Sami, Leinonen, Juho, Ashraf, Syed, Denny, Paul
The emergence of large language models (LLMs) has transformed research and practice across a wide range of domains. Within the computing education research (CER) domain, LLMs have garnered significant attention, particularly in the context of learnin
Externí odkaz:
http://arxiv.org/abs/2407.04873