Lit L Bit S Classroom
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Lit'l Bit's Classroom
A plethora of children’s wit and wisdom as told through their daily lives with a childcare teacher. All are conversations she heard during her eleven years of working in preschool center. T he insight and humor of the children is revealed quite cleverly. The author’s love for children comes through strongly as you read the collection. This is a one of a kind work, very unique and sometimes hilarious. Also contains many craft ideas and helpful hints for preschool teachers and/or parents. Working with children is the most rewarding thing I have ever done. These years have been a very educational experience. If I planted one seed along the way, I feel I have done my part. The title, “Lit’l Bit,” was a nickname from years ago. One day I couldn’t reach something on a shelf, and I said, “I’m not big enough.” My husband replied, “Oh, you’re such a little bit,” and the name stuck.
Promoting Inclusive Education Through the Integration of LGBTIQ+ Issues in the Classroom
Author: Palacios-Hidalgo, Francisco Javier
language: en
Publisher: IGI Global
Release Date: 2023-07-20
As diversity based on gender identity and sexual orientation remains a target for discrimination, exclusion, and violence in multiple contexts, it is necessary to advocate for comprehensive and quality sexuality and gender education to achieve equity and equality. This co-edited book provides a comprehensive reflection on how education professionals can foster inclusive education in terms of diversity based on gender identity and sexual orientation that impacts positively both LGBTIQ+ and non-LGBTIQ+ students. Promoting Inclusive Education Through the Integration of LGBTIQ+ Issues in the Classroom offers theoretical considerations and practical examples of how LGBTIQ+ issues can be addressed in education, including instances of curriculum responses, teacher training, and recommendations for supporting LGBTIQ+ students. Its target audience includes international teachers of all areas and educational stages, educators, curriculum developers, instructional designers, principals, school boards, academicians, researchers, administrators, and policymakers. The chapters cover theoretical background, practical examples, and guidelines and recommendations for LGBTIQ+-inclusive education policymaking. This book serves as a reference for anyone interested in making education more inclusive in terms of diversity based on gender identity and sexual orientation.
Analytics Modeling in Reliability and Machine Learning and Its Applications
This book presents novel research and application chapters on topics in reliability, statistics, and machine learning. It has an emphasis on analytical models and techniques and practical applications in reliability engineering, data science, manufacturing, health care, and industry using machine learning, AI, optimization, and other computational methods. Today, billions of people are connected to each other through their mobile devices. Data is being collected and analysed more than ever before. The era of big data through machine learning algorithms, statistical inference, and reliability computing in almost all applications has resulted in a dramatic shift in the past two decades. Data analytics in business, finance, and industry is vital. It helps organizations and business to achieve better results and fact-based decision-making in all aspects of life. The book offers a broad picture of current research on the analytics modeling and techniques and its applications in industry. Topics include: l Reliability modeling and methods. l Software reliability engineering. l Maintenance modeling and policies. l Statistical feature selection. l Big data modeling. l Machine learning: models and algorithms. l Data-driven models and decision-making methods. l Applications and case studies in business, health care, and industrial systems. Postgraduates, researchers, professors, scientists, engineers, and practitioners in reliability engineering and management, machine learning engineering, data science, operations research, industrial and systems engineering, statistics, computer science and engineering, mechanical engineering, and business analytics will find in this book state-of-the-art analytics, modeling and methods in reliability and machine learning.