Results 81 to 90 of about 3,757,873 (288)

Moderating effect of teacher–student relationship and mediating role of self-efficacy on the relationship between peer-assisted learning and mathematics performance

Frontiers in Education
PurposeThe teacher–student relationship and self-efficacy will amplify the positive effect of peer-assisted learning on mathematics performance. A strong teacher–student relationship provides a supportive foundation, while higher self-efficacy equips ...
Bright Asare
doaj   +1 more source

A Review on Recent Trends of Bioinspired Soft Robotics: Actuators, Control Methods, Materials Selection, Sensors, Challenges, and Future Prospects

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker, Tamzid Ul Islam, Md. Robiul Islam   +2 more
wiley   +1 more source

Official pedagogic identities from South African policy – some implications for mathematics teacher education practice

Pythagoras, 2006
In South Africa the National Curriculum Statement for Grades 10 – 12 (General): Mathematics (DoE, 2003) together with the Norms and Standards for Educators (DoE, 2000a) are key policy documents that provide the official basis for mathematics education ...
Diane Parker
doaj   +1 more source

Large Language Model‐Based Chatbots in Higher Education

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci, Merve Eryilmaz, Ail K. Yetisen, Savas Tasoglu, Aydogan Ozcan   +4 more
wiley   +1 more source

The application of blended learning in mathematics teacher education: Protocol for a systematic review. [PDF]

PLoS One, 2023
Tong DH, Uyen BP, Ngan LK.
europepmc   +1 more source

Language Diversity in Mathematics Teacher Education: Challenges Across Three Countries

, 2016
This chapter focuses on the awareness and the practices of mathematics teacher educators in linguistically diverse classrooms across three countries—South Africa, Malawi, and Catalonia-Spain.
Anthony A Essien, N. Chitera, Núria Planas   +2 more
semanticscholar   +1 more source

Predicting Materials Thermodynamics Enabled by Large Language Model‐Driven Dataset Building and Machine Learning

Advanced Intelligent Systems, EarlyView.
Illustration of text data mining of rare earth mineral thermodynamic parameters with the large language model‐powered LMExt. A dataset is built with mined thermodynamic properties. Subsequently, a machine learning model is trained to predict formation enthalpy from the dataset.
Juejing Liu, Haydn Anderson, Noah I. Waxman, Vsevolod Kovalev, Byron Fisher, Elizabeth Li, Xiaofeng Guo   +6 more
wiley   +1 more source

Futures for Post-Pandemic Mathematics Teacher Education: responsiveness and responsibility in the Face of a Crisis. [PDF]

ZDM, 2023
Atweh B, Kaur B, Nivera G, Abadi A, Thinwiangthong S.   +4 more
europepmc   +1 more source

ELEMENTARY SCHOOL TEACHER’S OBSTACLES IN THE IMPLEMENTATION OF PROBLEM-BASED LEARNING MODEL IN MATHEMATICS LEARNING

JME (Journal of Mathematics Education), 2019
This study aims to describe the teachers' obstacles in applying problem-based learning model in Mathematics learning of elementary schools. This method of this study was a qualitative descriptive.
Vivi Astuti Nurlaily, H. Soegiyanto, B. Usodo   +2 more
semanticscholar   +1 more source

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

Advanced 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, Vitalii Kapitan, Andrey Ustyuzhanin   +2 more
wiley   +1 more source