27 papers · ranked by Valyu relevance
Katibe Gizem Yığ, Ayşe Gökçe-Ulutaş, Neşe Sevim-Çırak
Teachers are expected to integrate technology effectively into instruction, which requires not only strong digital literacy but also well-developed computational thinking skills. In this context, this study examined the extent to which pre-service teachers’ computational thinking skills were predicted by demographic…
Ying-Hsun Lai
Introduction As education systems worldwide begin to accept and implement computational thinking, the educators of both elementary and higher education are considering the cultivation of students’ computational thinking abilities. It is hoped that students effectively analyze and deconstruct all kinds of complex issues…
Louka Konstantina, Papadakis Stamatios
A plethora of programming platforms purports to teach preschool-aged children computational thinking (CT) and coding skills. However, the empirical evidence to support their effectiveness is still in its early stages. A three-week didactic intervention using ScratchJr was conducted to investigate its effectiveness in…
Nagalaxmy Markandan, Kamisah Osman, Lilia Halim
Education digitization highly enthuses learners for deeper learning and developing thought processes in formulating problems and their solutions effectively in their real-life circumstances. Implementing computational thinking skills through programming in Malaysian primary and secondary school STEM curriculum create…
Gabor Aranyi, Kristof Kovacs, Ferenc Kemény, Orsolya Pachner + 3 more
'Balázs Klein' 'Eszter P. Remete' 'Liliana G. Ciobanu'] Computational thinking (CT) is a set of problem-solving skills with high relevance in education and work contexts. The present paper explores the role of key cognitive factors underlying CT performance in non-programming university students. We collected data from…
Hendrik Krone, Pierre Haritz, Thomas Liebig
The topics of Artificial intelligence (AI) and especially Machine Learning (ML) are increasingly making their way into educational curricula. To facilitate the access for students, a variety of platforms, visual tools, and digital games are already being used to introduce ML concepts and strengthen the understanding of…
Wan Chong Choi, Iek Chong Choi
Motivation, Attitude, and Achievement of Code.org in K-12 Programming Education Authors: ['Wan Chong Choi' 'Iek Chong Choi'] The Programming Computational Thinking Scale (PCTS) was utilized to evaluate computational thinking. Student motivation was measured using the Instructional Materials Motivation Survey (IMMS)…
Javier Bilbao, Eugenio Bravo, Olatz García, Carolina Rebollar
| | International Journal on | | | ISSN 2077-3528 | | --- | --- | --- | --- | --- | | | "Technical and Physical Problems of Engineering" | | | IJTPE Journal | | | | (IJTPE) | | www.iotpe.com | | | Published by International Organization of IOTPE | | | ijtpe@iotpe.com | | March 2024 | Issue 58 | Volume 16 | Number 1 |…
Friday Joseph Agbo, Solomon Sunday Oyelere, Jarkko Suhonen, Markku Tukiainen
'Markku Tukiainen'] Computational thinking (CT) has become an essential skill nowadays. For young students, CT competency is required to prepare them for future jobs. This competency can facilitate students’ understanding of programming knowledge which has been a challenge for many novices pursuing a computer science…
Chenyu Hou, Hua Yu, Gaoxia Zhu, John Derek Anas + 2 more
Computational Thinking (CT) is a foundational problem-solving skill, and gamified programming environments are a widely adopted approach to cultivating it. While large language models (LLMs) provide on-demand programming support, current applications rarely foster CT development. We present MazeMate, an LLM-powered…
Emine Akkaş Baysal, Nezahat Hamiden Karaca, Ayhan Pektaş, André Luiz Monezi Andrade + 1 more
Highlights What are the main findings?1. This study aims to examine associations within and across middle school children with and without congenital heart disease in terms of digital game addiction, computational thinking skills, and well-being. 2. Children with congenital heart disease show different patterns in…
Andrew J. Mertens, Eliana Colunga
Recent years have seen a dramatic increase in Computer Science (CS) education programs implemented at the K-12 level. This emphasis on CS education comes not only from the fact that computer skills are becoming an ever-more integral part of modern life, but also from a notion that learning how to program facilitates…
Giorgia Adorni, Alberto Piatti, Engin Bumbacher, Lucio Negrini + 4 more
thinking problems in education Authors: ['Giorgia Adorni' 'Alberto Piatti' 'Engin Bumbacher' 'Lucio Negrini' 'Francesco Mondada' 'Dorit Assaf' 'Francesca Mangili' 'Luca Maria Gambardella'] Abstract The field of computational thinking education has grown in recent years as researchers and educators have sought to…
Dorit Assaf, Giorgia Adorni, Elia Lutz, Lucio Negrini + 4 more
in Computational Thinking Authors: ['Dorit Assaf' 'Giorgia Adorni' 'Elia Lutz' 'Lucio Negrini' 'Alberto Piatti' 'Francesco Mondada' 'Francesca Mangili' 'Luca Maria Gambardella'] This paper addresses the incorporation of problem decomposition skills as an important component of computational thinking (CT) in K-12…
Felipe González-Pizarro, Claudia López, Andrea Vásquez, Carlos Castro
'Carlos Castro'] Abstract—While computational thinking arises as an essential skill worldwide, formal primary and secondary education in Latin America rarely incorporates mechanisms to develop it in their curricula. The extent to which students in the region acquire computational thinking skills remains largely…
Tao Hong, William R. Stauffer
Complex economic decisions are often combinatorial: they require individuals to select from many alternatives under strict constraints on time, resources, and energy. Combinatorial reasoning is the cognitive process that enables decision makers to construct and evaluate multiple potential solutions in the face of these…
Authors not listed
Step-by-step thinking is essential in all domains of chemical sciences and engineering. While machine learning tools are broadly used, algorithms that automate reasoning are far less common. We elaborate on seven categories of human reasoning activities and connect each to applications in chemical science and…
Andrew McCluskey, Miguel Rivera, Antonia Mey
The role of computing in the chemical sciences is changing. Previously the domain of the theoretical or computational chemist, advanced digital skills, including data analysis and simulation, are becoming extremely relevant to all. Here, we discuss the importance of integrating computing and digital skills into an…
Asim Iqbal, Hassan Mahmood, Greg J. Stuart, Gord Fishell + 1 more
Understanding the computational principles of the brain and replicating them on neuromorphic hardware and modern deep learning architectures is crucial for advancing neuro-inspired AI (NeuroAI). Here, we develop an experimentally-constrained biophysical network model of neocortical circuit motifs, focusing on layers…
Denisa Checiu, Mathias Bode, Radwa Khalil
From a brain processing perspective, the perception of creative thinking is rooted in the underlying cognitive process, which facilitates exploring and cultivating novel avenues and problem-solving strategies. However, it is challenging to emulate the intricate complexity of how the human brain presents a novel way to…
Oliver Lee, Malte Gather, Eli Zysman-Colman
We describe a new tool for the efficient management of computational chemistry. Digichem is a program that automates and simplifies nearly the entire computational pipeline, including large-scale batch submission of calculations, analysis and results parsing, the generation of 3D density plots and 2D graphs of…
Authors not listed
This comprehensive review examines the evolution of autonomous materials synthesis laboratories that integrate artificial intelligence with advanced robotics to accelerate discovery. Traditional materials development pipelines typically require 10-20 years, but self-driving laboratories (SDLs) and Materials…
Rohan Chandraghatgi, Hai-Feng Ji, Gail L. Rosen, Bahrad A. Sokhansanj
Recent advances in computational methods provide the promise of dramatically accelerating drug discovery. While math-ematical modeling and machine learning have become vital in predicting drug-target interactions and properties, there is untapped potential in computational drug discovery due to the vast and complex…
Hossein Moghimianavval, Ignacio Gispert, Santiago R. Castillo, Olaf B. W. H. Corning + 2 more
Constructing molecular classifiers that enable cells to recognize linear and non-linear input patterns would expand the biocomputational capabilities of engineered cells, thereby unlocking their potential in diagnostics and therapeutic applications. While several biomolecular classifier schemes have been designed, the…
Lewis Grozinger, Jesús Miró-Bueno, Ángel Goñi-Moreño
The programming of computations in living cells can be done by manipulating information flows within genetic networks. Typically, a single bit of information is encoded by a single gene’s steady state expression. Expression is discretized into high and low levels that correspond to 0 and 1 logic values, analogous to…
Yuanqi Du, Chenru Duan, Andres Bran, Anna Sotnikova + 5 more
Large language models (LLMs) have demonstrated outstanding capabilities in general problem-solving and been shown to improve productivity in certain domains. Thanks to their flexibility, recent work has leveraged them for diverse scientific applications, ranging from predictive modeling, scientific Q&A, and even as…
Authors not listed
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…