Results 81 to 90 of about 102,050 (305)

Do student teachers experience self-worth threats in computational thinking?

Computers in Human Behavior Reports
Theory: The successful implementation of computational thinking into primary schools requires that primary school teachers feel safe and confident in teaching this topic to young learners. However, many student teachers face low expectancy of success and
Veronika Barkela, Areum Han, Anke Maria Weber   +2 more
doaj   +1 more source

Computational Practices, Educational Theories, and Learning Development

Problemos, 2018
[full article, abstract in English; abstract in Lithuanian] Many countries are adopting computing (or informatics) in schools, for pupils from 5 years of age. Educational philosophies (and learning theories) that such curricula might be based on are not clear in curriculum documentation.
Passey, Don, Dagienė, Valentina, Atieno, Loice, Baumann, Wilfried   +3 more
openaire   +4 more sources

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

Complexity, theory and praxis: researching collaborative learning and tutoring processes in a networked learning community [PDF]

, 2003
This paper explores the complexity of researching networked learning and tutoring on two levels. Firstly, on the theoretical level, we argue that the nature of praxis in networked environments (that is, learning and tutoring) is so complex that no ...
De Laat, M., Maarten De Laat, Lally, Vic, Lally, V., Vic Lally, De Laat, Maarten F.   +5 more
core   +1 more source

Reinforcement learning: Computational theory and biological mechanisms [PDF]

HFSP Journal, 2007
Reinforcement learning is a computational framework for an active agent to learn behaviors on the basis of a scalar reward signal. The agent can be an animal, a human, or an artificial system such as a robot or a computer program. The reward can be food, water, money, or whatever measure of the performance of the agent.
openaire   +2 more sources

Workflow for Design of Experiments‐Based Modeling of Species Transport and Growth Kinetics in GaN Hydride Vapor Phase Epitaxy

Advanced Engineering Materials, EarlyView.
A novel workflow for investigating hydride vapor phase epitaxy for GaN bulk crystal growth is proposed. It combines Design of experiments (DoE) with physical simulations of mass transport and crystal growth kinetics, serving as an intermediate step between DoE and experiments.
J. Tomkovič, G. Lukin, H. Torkashvand, A. Kerschbaum, M. Müller, S. Besendörfer, J. Heitmann, J. Friedrich   +7 more
wiley   +1 more source

Agent-Based Computational Economics [PDF]

Agent-based computational economics (ACE) is the computational study of economies modeled as evolving systems of autonomous interacting agents. Starting from initial conditions, specified by the modeler, the computational economy evolves over time as its
Leigh Tesfatsion
core  

An Improved Extreme Learning Machine Based on Full Rank Cholesky Factorization

MATEC Web of Conferences, 2018
Extreme learning machine (ELM) is a new novel learning algorithm for generalized single-hidden layer feedforward networks (SLFNs). Although it shows fast learning speed in many areas, there is still room for improvement in computational cost.
Liu Zuozhi, Wu JinJian, Wang Jianpeng
doaj   +1 more source

A Co-Evolutionary Computing for Statistical Learning Theory [PDF]

International Journal of Fuzzy Logic and Intelligent Systems, 2005
Learning and evolving are two basics for data mining. As compared with classical learning theory based on objective function with minimizing training errors, the recently evolutionary computing has had an efficient approach for constructing optimal model without the minimizing training errors.
openaire   +1 more source

Toward Knowledge‐Based Workflows: A Semantic Approach to Atomistic Simulations for Mechanical and Thermodynamic Properties

Advanced Engineering Materials, EarlyView.
Knowledge‐based atomistic workflows are presented for mechanical and thermodynamic properties. By coupling modular simulations with ontology‐aligned metadata and provenance, Fe case studies on elastic behavior, defects, thermal properties, and Hall–Petch strengthening reveal how FAIR, queryable, and reusable simulation data can be generated. Mechanical
Abril Azócar Guzmán, Hoang‐Thien Luu, Sarath Menon, Tilmann Hickel, Nina Merkert, Stefan Sandfeld   +5 more
wiley   +1 more source