25 papers · ranked by Valyu relevance
Dietrich Dörner, Joachim Funke
Computer-simulated scenarios have been part of psychological research on problem solving for more than 40 years. The shift in emphasis from simple toy problems to complex, more real-life oriented problems has been accompanied by discussions about the best ways to assess the process of solving complex problems.…
Ulrike Kipman, Stephan Bartholdy, Marie Weiss, Wolfgang Aichhorn + 1 more
'Günter Schiepek'] Complex problem solving (CPS) can be interpreted as the number of psychological mechanisms that allow us to reach our targets in difficult situations, that can be classified as complex, dynamic, non-transparent, interconnected, and multilayered, and also polytelic. The previous results demonstrated…
Patrick C. Kyllonen
Economic inequality has been described as the defining challenge of our time, responsible for a host of potential negative societal and individual outcomes including reduced opportunity, decreased health and life expectancy, and the destabilization of democracy. Education has been proposed as the “great equalizer” that…
Joachim Funke
What are consequential world problems? As “grand societal challenges”, one might define them as problems that affect a large number of people, perhaps even the entire planet, including problems such as climate change, distributive justice, world peace, world nutrition, clean air and clean water, access to education…
Patrick Kyllonen, Cristina Anguiano Carrasco, Harrison J. Kell
Complex problem solving (CPS) has emerged over the past several decades as an important construct in education and in the workforce. We examine the relationship between CPS and general fluid ability (Gf) both conceptually and empirically. A review of definitions of the two factors, prototypical tasks, and the…
Jens F. Beckmann, Damian P. Birney, Natassia Goode
In this paper we argue that a synthesis of findings across the various sub-areas of research in complex problem solving and consequently progress in theory building is hampered by an insufficient differentiation of complexity and difficulty. In the proposed framework of person, task, and situation (PTS), complexity is…
Da Zheng, Lun Du, Junwei Su, Yuchen Tian + 5 more
'Lanning Wei' 'Ningyu Zhang' 'Huajun Chen'] DA ZHENG∗† , Ant Group, China LUN DU∗ , Ant Group, China JUNWEI SU, The University of Hong Kong, China YUCHEN TIAN, Ant Group, China YUQI ZHU, Zhejiang University, China JINTIAN ZHANG, Zhejiang University, China LANNING WEI, Ant Group, China NINGYU ZHANG† , Zhejiang…
Jens F. Beckmann, Natassia Goode, Samuel Greiff, Ronny Scherer
In this paper we discuss how the lack of a common framework in Complex Problem Solving (CPS) creates a major hindrance to a productive integration of findings and insights gained in its 40+-year history of research. We propose a framework that anchors complexity within the tri-dimensional variable space of Person, Task…
Qianli Yang, Zhihua Zhu, Ruoguang Si, Yunwei Li + 2 more
Human intelligence is characterized by our remarkable ability to solve complex problems. This involves planning a sequence of actions that leads us from an initial state to a desired goal state. Quantifying and comparing problem-solving capabilities across species and finding its evolutional roots is a fundamental…
Juan Pablo Franco, Peter Bossaerts, Carsten Murawski
Many everyday tasks require people to solve computationally complex problems. However, little is known about the effects of computational hardness on the neural processes associated with solving such problems. Here, we draw on computational complexity theory to address this issue. We performed an experiment in which…
Michael Gr. Voskoglou, Sheryl Buckley
Computational thinking is a new problem solving method named for its extensive use of computer science techniques. It synthesizes critical thinking and existing knowledge and applies them to solve complex technological problems. The term was coined by J. Wing [1], but the relationship between computational and critical…
Hajo Broersma, Susan Stepney, Göran Wendin
For many decades, Moore's Law (Moore; 1965) gave us exponentially-increasing classical (digital) computing (CCOMP) power, with a doubling time of around 18 months. This cannot continue indefinitely, due to ultimate physical limits (Lloyd; 2000). Well before then, more practical limits will slow this increase. One such…
Gülce Kardeş, David Krakauer, Joshua Grochow
Cognitive science and theoretical computer science both seek to classify and explain the difficulty of tasks. Mechanisms of intelligence can be understood as leading to reductions in task difficulty. We map concepts from the computational complexity of a physical puzzle, the Soma Cube, onto cognitive problem-solving…
Juan Prada, Johannes Balkenhol, Özge Osmanoglu, Maral Afshar + 6 more
Decisions in biology happen fast and are driven by evolution to optimize survival chances. In platelets, this is achieved by organizing signaling cascades into rapid decision-funnels with modulatory crosstalk. We show that network decision processes underlying cellular decisions are tough to solve (equivalent to…
Daniel Strüber
—Modeling seeks to tame complexity during software development, by supporting design, analysis, and stakeholder communication. Paradoxically, experiences made by educators indicate that students often perceive modeling as adding complexity, instead of reducing it. In this position paper, I analyse modeling education…
Alexander V. Lebedev, Jonna Nilsson, Martin Lövdén
Researchers have proposed that solving complex reasoning problems, a key indicator of fluid intelligence, involves the same cognitive processes as solving working memory tasks. This proposal is supported by an overlap of the functional brain activations associated with the two types of tasks and by high correlations…
František Ďuriš
The question of how humans solve problem has been addressed extensively. However, the direct study of the effectiveness of this process seems to be overlooked. In this paper, we address the issue of the effectiveness of human problem solving: we analyze where this effectiveness comes from and what cognitive mechanisms…
Authors not listed
In philosophy and science, a first principle is a basic proposition or assumption that cannot be deduced from any other proposition or assumption. Ancient Greek philosophy Aristotle defined the first principle as “the first basis from which a thing is known.” First principles thinking (or reasoning from first…
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Nuclear Magnetic Resonance (NMR) structure determination is an important problem in education, industry, and research. Solving NMR spectra requires expert knowledge, critical thinking, and careful evaluation of multiple features of spectral data. This study explores the capabilities of large language models (LLMs) for…
Tunde Aderinwale, Rashidedin Jahandideh, Zicong Zhang, Bowen Zhao + 2 more
Various biological processes in living cells are carried out by protein complexes, whose interactions can span across multiple protein structures. To understand the molecular mechanisms of such processes, it is crucial to know the quaternary structures of these complexes. Although the structures of many protein…
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The Socratic method, grounded in iterative questioning and critical dialogue, offers a compelling framework for leveraging large language models (LLMs) to advance scientific reasoning and discovery in chemistry and materials science. In this paper, we explore how Socratic principles can be integrated into prompt…
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Rapid and robust simulation of chemical processes is critical to conduct process design, optimization, techno-economic analysis, and sustainability analysis. Yet, efficiently solving simulation models remains a challenge due to the highly coupled and nonlinear nature of the underlying algebraic equations that capture…
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We present a vector-based method to balance chemical reactions. The algorithm builds candidates in a deterministic way, removes duplicates, and always prints coefficients in the lowest whole-number form. For redox cases, electrons and protons/hydroxide are treated explicitly, so both mass and charge are balanced. We…
Tianfan Jin, Brett M Savoie
Contemporary machine learning algorithms have largely succeeded in automating the development of mathematical models from data. Although this is a striking accomplishment, it leaves unaddressed the multitude of scenarios, especially across the chemical sciences and engineering, where deductive, rather than inductive…
Authors not listed
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…