The Future of Learning Environments


Milly Chambers (Editor)

Series: Education in a Competitive and Globalizing World
BISAC: EDU000000; EDU034000

This book contains five chapters on the future of learning environments. Chapter one delves into a distinctive educational advancement involving a mixed-methods evaluation of an inventive pedagogical intervention. The authors in chapter two use a social-ecological approach to examine the influence of school climate on young people’s functioning in terms of resilience, wellbeing, and moral identity. Chapter three reports the development and validation of a new school climate questionnaire with a unique focus on facilitating and monitoring system-wide school reform. Chapter four aims to contribute to the discourse on the future of learning environments by presenting a novel approach to optimization that combines the power of reinforcement learning and constraint programming. The aim of chapter five is to investigate teachers’ beliefs and their perceptions of the extent to which they implement a constructivist-oriented learning environment; examine whether the perceived implementation differs from observations of teachers’ practice; and possible reasons for any anomalies.

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Table of Contents


Chapter 1. Using Learning Environment Criteria in Evaluating the Effectiveness of a Mobile Application for Teaching and Learning
Barry J. Fraser¹, Noi-Keng Koh², and Chiew-Hong Ng³
¹Curtin University, Australia
²Fintech Academy, Singapore
³Nanyang Technological University, Singapore

Chapter 2.
School-Level Environment: The Role of School Climate in Promoting Resilience, Wellbeing and Moral Identity in Young People
Jill M. Aldridge¹, PhD and Meghan J. Blackstock², BA, LLB
¹School of Education, Curtin University, Western Australia
²National School Improvement Partnerships, Perth, Western Australia

Chapter 3. A Teacher School Climate Questionnaire for Facilitating and Monitoring System-Wide School Reform
Jill M. Aldridge¹, Paul E. Rijken², and Barry J. Fraser¹
¹Curtin University, Perth, Australia
²University of Adelaide, Adelaide, Australia

Chapter 4. Reinforcement Learning from Constraint Programming Feedback for Optimization Tasks
Jing Su¹, Suku Nair¹, and Leo Popokh²
¹AT&T Center for Virtualization, Southern Methodist University, Dallas, TX, USA
²Hewlett Packard Enterprise, Dallas, TX, USA

Chapter 5. Teacher Beliefs: Factors Affecting the Implementation of Constructivist-Oriented Learning Environments
Monika von Oppell, PhD and Jill M. Aldridge, PhD
School of Education, Curtin University, Bentley, Western Australia


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