27 papers · ranked by Valyu relevance
Esen Ersoy, Deniz Özcan Kara
This study aims to investigate the impact of the Creative Problem-Solving (CPS)model on students’ creative thinking skills in mathematics education. Recent studies have shown that despite the emphasis on creativity and higher-order thinking skills in mathematics curricula, many students still struggle to generate…
Mete Ismayilzada, Renqing Cuomao, Daniil Yurshevich, Anna Sotnikova + 2 more
Creative problem-solving requires combining multiple cognitive abilities, including logical reasoning, lateral thinking, analogy-making, and commonsense knowledge, to discover insights that connect seemingly unrelated pieces of information. However, most existing benchmarks for large language models (LLMs) evaluate…
Yan Yang, Na Zhang, Quan Zhang
Many Chinese parents experience anxiety stemming from their financial circumstances, limited time available for parental accompaniment, and insufficient cultural enrichment within the home. Fearing that these factors may adversely affect their children's academic achievements, they recognize that it is particularly…
Yating Zeng, Jiayi Tao
The ability to utilize simulations to address problems is emphasized in current science standards, but learners often struggle with scientific tasks involving simulations. Understanding the gap between beginner and expert scientific problem solvers in simulation settings is useful for helping students to develop their…
Semahat Incikabi
Objective This study aimed to investigate the relationship between creativity components in numerical and spatial mathematical problem-solving contexts and to identify the characteristics of products generated by students with different levels of creativity. Methods The study involved 167 sixth-grade students (aged…
Sarah K. C. Dygert, Andrew F. Jarosz
Resolving misrepresentations is key when faced with ambiguous information. For example, problem-solvers may misrepresent the constraints of a problem, while readers may misrepresent parts of a sentence. This work investigates how a shared cognitive process might facilitate the restructuring of representations during…
Xinyu Li, Kaixun Yang, Jiali Wei, Yixin Cheng + 2 more
Information Problem Solving (IPS) is a critical competency for academic and professional success in education, work, and life. The advent of Generative Artificial Intelligence (GenAI), particularly tools like ChatGPT, has introduced new possibilities for supporting students in complex IPS tasks. However, empirical…
Shih-Yu Lo, Li-Jung Hsu
Research on construal level theory suggests that psychological distance enhances creativity, as people tend to be more creative when considering events or objects that are spatially or temporally distant. With immersive technologies, individuals can use different forms of digital representations (or avatars) for work…
Veronika Semmelrock, Benedetta Strizzolo, Francesco Zuccato, Gerhard Friedrich + 2 more
Combinatorial and optimization problems are fundamental to many industrial AI applications. Solving large-scale real-world instances of such problems typically requires careful problem formalization, specialized solvers, and expert-designed heuristics. Thus, experts need to specify not only what solutions are, but also…
Alexandru Oarga, Yilun Du
Generalization is a key challenge in machine learning, specifically in reasoning tasks, where models are expected to solve problems more complex than those encountered during training. Existing approaches typically train reasoning models in an end-to-end fashion, directly mapping input instances to solutions. While…
Leonard Bohnenkämper, Daria Frolova
Phylogenetic reconstruction is a fundamental problem in comparative genomics. As a theoretical problem in rearrangement studies, this has been modelled as the Small Parsimony Problem (SPP), in which ancestral genome structures have to be determined minimizing the number of rearrangement events occurring throughout the…
Authors not listed
This work establishes theoretical foundations for hierarchical quantum-classical algorithm design, where complex problems are decomposed across multiple spatial, temporal, or organizational scales with quantum and classical computation assigned to appropriate levels. We develop a mathematical framework that…
Kotaro Yamashiro, Takamitsu Iwata, Yuji Ikegaya, Yasushi Iimura + 11 more
Insight is a sudden transition from uncertainty to awareness of a solution, often preceded by non-conscious processing. Despite the ubiquity of insights in human cognition, the neural mechanisms underlying this pre-conscious restructuring phase remain largely unknown. Recent theoretical frameworks suggest that the…
Cameron Rouse Turner, Evan M. Russek, Amanda Seed, Emma Suvi McEwen + 3 more
A diversity of intelligences arises from the constraints under which animals evolve. However, characterizing how constraints shape intelligence is challenging because it requires relating the restrictions on cognitive mechanisms to those that affect their evolution. We demonstrate the potentially complex interaction…
Oviya Mohan, Dora Biro
Conventions can be defined as arbitrary and self-sustaining practices that emerge in a population and facilitate solving coordination problems. A recent study traced the formation of simple conventions in captive baboons in a touch-screen-based color-matching ‘game’. We replicated this task with human pairs under…
Tyrone B. Pretorius, Anita Padmanabhanunni
Background Problem-solving appraisal is an important cognitive process that influences how individuals manage and cope with stress. Negative appraisals of problem-solving ability are associated with adverse mental health outcomes. Methods We conducted a meta-analysis using a random-effects model to synthesize the…
Lisa Fontana, Sofia Bolcato, Julia Penndorf, Lucy M Aplin
Why some species thrive in urban environments while others do not is a central question in behavioral ecology. Behavioral innovations has been proposed as a key mechanism facilitating this adaptation. At the individual level, innovativeness varies with cognitive and behavioral traits. However, at the population level…
Veronika Semmelrock, Gerhard Friedrich
Answer set programming (ASP) aims to realize the AI vision: The user specifies the problem, and the computer solves it. Indeed, ASP has made this vision true in many application domains. However, will current ASP solving techniques scale up for large configuration problems? As a benchmark for such problems, we…
Misako Kimura, Yuuki Matsushita, Masayo Inoue, Shigeto Seno + 5 more
Insight is often described as a sudden shift in or formation of a conceptual representation, enabling humans to restructure existing knowledge and solve problems beyond conventional analytical approaches. Although prior computational studies have modeled aspects of insight using deep neural networks (DNNs) or…
Fatemeh Haji, Javier Delarosa Quiros, Peyman Najafirad
Combinatorial optimization (CO) underlies decision-making from logistics to chip design, where infeasible solutions are operationally unusable and small quality gains translate into substantial economic value. Recent work uses large language models (LLMs) to automate solver synthesis: generating executable solver…
Alp Kaan Kilci, Seyhan Bekir, Serhat Yalciner, Nahit Ozdayi
Background Mental process is a cornerstone of success in the rapid sports industry, where players must navigate high-pressure, dynamic environments. Cognitive flexibility is essential for adaptability and effective problem-solving, yet its relationship with negative psychological traits remains underexplored. This…
Shannon R. McWaters, James J. Kearsley, David W. Kikuchi, Timothy J. Polnaszek + 1 more
The ability of animals to innovate - solve novel problems - can shape their ecology and evolution. Here we investigate how individual traits and environmental complexity relate to successful solving of a novel problem. We presented foraging bumble bees (Bombus impatiens) with artificial flowers of…
J. de Curtò, I. de Zarzà
As foundation models grow in scale and diversity, coordinating multiple models into cooperative reasoning systems offers a path toward safer, more reliable AI. This chapter presents a multi-agent framework where solver models generate independent drafts, each undergoes structured critique and revision by a critic…
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Bayesian optimization (BO) has become increasingly important for experimental optimization across scientific domains, yet implementing BO pipelines requires significant programming expertise and familiarity with specialized frameworks. This creates a barrier for domain experts who could benefit from BO but lack the…
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A method has been introduced to derive the solution of the time-independent Schrodinger equation for the simple harmonic oscillator. A trial solution has been chosen as the product of the divergent part of the approximate asymptomatic solution of the Schrodinger equation and an unknown function. By inserting this trial…
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This paper introduces Post-Inspection Analysis (PIA), a concept for understanding and reverse engineering balanced equations of similar reactions. Here we explore the idea that balanced equations contain useable information observed by grouping and analysing similar equations, allowing us to uncover observations that…
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We present a unified theoretical framework that classifies and analyzes quantum enhancement strategies for classical algorithms, establishing design paradigms that systematically combine quantum subroutines with classical procedures. The theory identifies four fundamental enhancement mechanisms: quantum search…