Results 31 to 40 of about 130,583 (259)

Creativity Profile of Students in Constructing Mathematics Learning Media

open access: yesJTAM (Jurnal Teori dan Aplikasi Matematika), 2023
Students must be equipped with creativity as a 21st century skill. The research objective was to obtain a profile of student creativity in constructing learning media. The method used is observation and in-depth interviews.
Wiwin Sri Hidayati, Lia Budi Tristanti
doaj   +1 more source

KEMAMPUAN REPRESENTASI MATEMATIS CALON GURU MATEMATIKA PADA MATA KULIAH TEORI PELUANG

open access: yesJupitek, 2022
In understanding mathematics learning, representation is considered an entry point in solving various complex mathematical problems. The ability of mathematical representation is related to the expression of mathematical ideas using various ways ...
Marthinus Yohanes Ruamba   +2 more
doaj   +1 more source

(Re)Constitution of the mathematics teacher’s professional practice

open access: yesRevista Prática Docente, 2022
This bibliographic study aims to investigate aspects that influence the constitution and modification of the mathematics teachers’ practice. By carrying out two searches on the Capes Periodicals Portal, one with the terms future teacher and mathematics ...
Eduardo Pereira de Oliveira Rossa   +1 more
doaj   +1 more source

Mathematics teachers learning with video: the role, for the didactician, of a heightened listening [PDF]

open access: yes, 2014
This article addresses two main questions, how do mathematics teachers learn from using video? and, what is the role of the didactician? A common problem is reported in the difficulty of keeping teacher discussion of video away from judgment and ...
Coles, Alf T
core   +2 more sources

An analysis of mathematics understanding of prospective student-teachers of mathematics

open access: yesJurnal Riset Pendidikan Matematika, 2021
This quantitative-qualitative descriptive study aims to reveal the mathematics understanding of prospective student-teachers, describe the types of their mistakes in mathematics understanding, and recommend appropriate teaching of mathematics understanding. The subjects were 34 first-year students taking the Geometry course in the Mathematics Education
openaire   +2 more sources

Examining interpersonal aspects of a mathematics teacher education lecture

open access: yesLUMAT
In this paper we present findings from an initial phase of a more extensive study focussed on ways in which prospective mathematics teachers negotiate meaning from mathematics teacher education situations.
Andreas Ebbelind, Tracy Helliwell
doaj   +1 more source

A Case for Proof Making for Prospective Middle School Teachers [PDF]

open access: yes, 2004
In this article, we discuss how we, as mathematics teacher educators, might help our prospective middle school teachers develop a disposition toward mathematics that involves making sound arguments and, more generally, making proofs about mathematical ...
Cavey, L.   +2 more
core   +1 more source

AI in chemical engineering: From promise to practice

open access: yesAIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew   +4 more
wiley   +1 more source

A Classification of Mathematical Modeling Problems of Prospective Mathematics Teachers

open access: yesJournal of Educational Issues, 2020
The purpose of this research is to classify the mathematical modelling problems produced by pre-service mathematics teachers in terms of the number of variables and to determine the mathematical modelling skills and mathematical skills used in solving the problems in each class.
openaire   +2 more sources

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

open access: yesAdvanced Intelligent Systems, EarlyView.
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy   +2 more
wiley   +1 more source

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