22 papers · ranked by Valyu relevance
Erica Niemiec, Catherine Insel, Juliet Y. Davidow
Adaptive value-based learning is a complex challenge supported by neurobiological systems based in the striatum and hippocampus, with important implications for both everyday behaviors and for mental health. In adults, these systems have been shown to compete, complement, and integrate; less is known about this…
Andrés Holgado-Sánchez, Holger Billhardt, Alberto Fernández, Sascha Ossowski
Agreement Technologies refer to open computer systems in which autonomous software agents interact with one another, typically on behalf of humans, in order to come to mutually acceptable agreements. With the advance of AI systems in recent years, it has become apparent that such agreements, in order to be acceptable…
Jaeeon Lee, Jay A. Hennig, Vanessa Frelih, Samuel J. Gershman + 1 more
Value computation is fundamental to the survival of animals. Classical models suggest value is stored in synaptic weight through plasticity whereas more recent theories propose that recurrent network dynamics can encode and update value independently of synaptic change. Although these two mechanisms are not mutually…
Xixi Yang, Qi Nie, Dawit Dibekulu
The research is motivated by the strategic integration of moral and value education into China’s college English curriculum and the critical role of textbooks as value carriers in EFL education. Despite growing attention to value integration in EFL materials, empirical studies on moral and value representation in oral…
Wen-Liang Zhou, Hanna Yousuf, Yann S. Mineur, Marina R. Picciotto
Activity of the mesolimbic system is essential for adaptive performance of reward-related behaviors. Within this system, dopaminergic (DAergic) neurons play a critical role in driving motivation to obtain rewards and encoding predictions and error signals during reinforcement learning. However, activity of DAergic…
Xulu Sun, Alison E. Comrie, Ari E. Kahn, Emily J. Monroe + 12 more
Learning where and when rewards like food and water are available is essential for survival^1,2^. In the simplest cases where resource availability is stable, animals can learn reward contingencies by integrating outcomes across repeated samples of each option. In more natural settings, however, reward availability is…
Jianning Chen, Masakazu Taira, Kenji Doya
Behavioral strategies can change in response to environmental and internal states, either gradually or abruptly, enabling flexible adaptation. Such strategy regulation is central to meta-learning, the ability to learn to learn. Previous studies analyzed temporal or condition-dependent strategy change using models and…
Poojita Chinmay, Mohammed Khan, Zhidong Wang, Nivan Lakshman + 1 more
Rising healthcare costs in the United States, with estimates suggesting up to 25% of spending is wasteful, have created an urgent need for cost-conscious, value-based care (VBC). VBC aims to improve patient outcomes relative to costs, yet its integration into medical education remains inconsistent, leaving future…
Yuanchun Liu, Mingzhao He, Jinmeng Dou
Introduction This study addresses persistent challenges in China's humanistic and liberal education, including cultural disjunction, weakened value guidance, and insufficient integration of knowledge into practice. To overcome these limitations, this study proposes a four-in-one “infusive” educational model based on…
Ruggero Basanisi, Emmanuel Daucé, Etienne Combrisson, Mehdi Khamassi + 2 more
Understanding the neural and computational mechanisms underlying goal-directed causal learning is a central challenge in both cognitive neuroscience and artificial intelligence. This cognitive function depends on balancing reward maximization with information seeking. Although substantial progress has been made in…
Authors not listed
Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…
Dhruva V. Raman, Christopher R. Dunne, Katie Davyson, Timothy O’Leary
Animals inhabit continually changing environments where it is not always possible to infer causes of relevant changes, such as the appearance of a new threat. In such nonstationary settings, learning a predictive model is challenging because a surprising observation could be due to chance, or due to systematic but…
Chenxi Li, Enuo Wang, Jon Andoni Duñabeitia
This study examines how German textbooks provide learning-behavioral affordances for sustainability-oriented intercultural competence development. Drawing on Klieme’s competence-model logic, ESD, intercultural competence research, learning behavior theory, and affordance theory, it treats “sustainable intercultural…
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As the utilization of artificial intelligence (AI) and generative AI (GenAI) is expanding in the educational field, presenting significant implications for STEM disciplines, it is bringing opportunities to enhance how chemistry and chemical engineering are taught and learned. This perspective critically explores the…
Mehrabi, Amirreza, Morphew, Jason W. + 4 more
Adaptive learning often diagnoses precisely yet intervenes weakly, yielding help that is mistimed or misaligned. This study presents evidence supporting an instructor-governed feedback loop that converts concept-level assessment evidence into vetted micro-interventions. This adaptive learning algorithm contains three…
Amirreza Mehrabi, Jason Morphew, Breejha S. Quezada, N. Sanjay Rebello
Adaptive learning often diagnoses precisely yet intervenes weakly, yielding help that is mistimed or misaligned. This study presents evidence supporting an instructor-governed feedback loop that converts concept-level assessment evidence into vetted micro-interventions. This adaptive learning algorithm contains three…
Aria Eshraghi, Lauren K Logsdon
Microbiology education in veterinary curricula requires students to integrate complex foundational knowledge with clinical application, yet traditional lecture-based approaches often emphasize memorization over higher-order reasoning. In this study, we evaluated the impact of integrating clinically oriented, case-based…
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Quantitative Structure Activity Relationship (QSAR) remains an effective tool for early-stage chemical modelling and virtual screening in drug design. The advancements in this field are led by two core paradigms, 1) descriptor engineering, where complex fixed-length vectors of compounds are generated and conventional…
Xin Bian, Andre Brown, Bruno Marques
Digital storytelling is increasingly employed in sustainability education to communicate complex place-based environmental issues. However, it remains unclear how primary school students encode concept-dense content during brief narrative viewing, and how such encounters relate to content knowledge (CK) and place-based…
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Realizing the promise of artificial intelligence (AI) to accelerate scientific progress and deliver technological impact depends on how effectively AI can be integrated into real-world decision- making processes. As Peter Norvig states, “Somewhat remarkably, almost all AI research until very recently has assumed that…
Mario Brcic, Stjepan Frljic
With AI advancing fast, educators face a dilemma: allow the tool or ban it. Conflicting evidence that it both helps and hurts learning only deepens the confusion. The allow-or-ban framing is a false dichotomy; the relevant design question is placement. Used well, AI can scale feedback, examples, practice, and…
Jie Gao, Yongan Yu, Junzhu Su, Yiran Lin + 2 more
Adaptive learning refers to educational technologies that track learners' learning progress and adapt the instructional process based on individual learners' learning performance. It is increasingly recognized as critical for developing an effective learning support tool. Vision language models (VLMs) have seen…