Due to the COVID-19 pandemic, teacher preparation programs modified their practices to fit the delivery modes of school districts while developing new ways to prepare candidates. Governmental agencies established new guidelines to fit the drastic shift in education caused by the pandemic, and P-12 school systems made accommodations to support teacher education candidates. The pandemic disrupted all established systems and norms; however, many practices and strategies emerged in educator preparation programs that will have a lasting positive impact on P-20 education and teacher education practices. Such practices include the reevaluation of schooling practices with shifts in engagement strategies, instructional approaches, technology utilization, and supporting students and their families. Redefining Teacher Education and Teacher Preparation Programs in the Post-COVID-19 Era provides relevant, innovative practices implemented across teacher education programs and P-20 settings, including delivery models; training procedures; theoretical frameworks; district policies and guidelines; state, national, and international standards; digital design and delivery of content; and the latest empirical research findings on the state of teacher education preparation. The book showcases best practices used to shape and redefine teacher education through the COVID-19 pandemic. Covering topics such as online teaching practices, simulated teaching experiences, and emotional learning, this text is essential for preservice professionals, paraprofessionals, administrators, P-12 faculty, education preparation program designers, principals, superintendents, researchers, students, and academicians.

Ethical Practice of Statistics and Data Science is intended to prepare people to fully assume their responsibilities to practice statistics and data science ethically. Aimed at early career professionals, practitioners, and mentors or supervisors of practitioners, the book supports the ethical practice of statistics and data science, with an emphasis on how to earn the designation of, and recognize, "the ethical practitioner". The book features 47 case studies, each mapped to the Data Science Ethics Checklist (DSEC); Data Ethics Framework (DEFW); the American Statistical Association (ASA) Ethical Guidelines for Statistical Practice; and the Association of Computing Machinery (ACM) Code of Ethics. It is necessary reading for students enrolled in any data intensive program, including undergraduate or graduate degrees in (bio-)statistics, business/analytics, or data science. Managers, leaders, supervisors, and mentors who lead data-intensive teams in government, industry, or academia would also benefit greatly from this book. This is a companion volume to Ethical Reasoning For A Data-Centered World, also published by Ethics International Press (2022). These are the first and only books to be based on, and to provide guidance to, the ASA and ACM Ethical Guidelines/Code of Ethics.

The American Statistical Association (ASA) and the Association of Computing Machinery (ACM) have longstanding ethical practice standards that are explicitly intended to be utilized by all who use statistical practices or computing, or both. Since statistics and computing are critical in any data-centered activity, these practice standards are essential to instruction in the uses of statistical practices or computing across disciplines. Ethical Reasoning for a Data-Centered World is aimed at any undergraduate or graduate students utilizing data. Whether the career goal is research, teaching, business, government, or a combination, this book presents a method for understanding and prioritizing ethical statistics, computing, and data science - featuring the ASA and ACM practice standards. To facilitate engagement, integration with prior learning, and authenticity, the material is organized around seven tasks: Planning/Designing; Data collection; Analysis; Interpretation; Reporting; Documenting; and Engaging in Team Work. This book is a companion volume to Ethical Practice of Statistics and Data Science, also published by Ethics International Press (2022). These are the first and only books to be based on, and to provide guidance to, the American Statistical Association (ASA) and Association of Computing Machinery (ACM) ethical guideline documents.

Food Security, Poverty and Nutrition Policy Analysis: Statistical Methods and Applications, Third Edition combines statistical data analysis and computer literacy, applying the results to develop policy alternatives through a series of statistical methods for real world food insecurity, malnutrition and poverty problems. The book presents the latest uses of statistical methods for policy analysis using the open source statistical environment R, in addition to having the original Stata files and applications. A new chapter on obesity brings in new datasets for analysis to effectively demonstrate the use of such data for addressing policy issues. Finally, program evaluation methods which can be directly applied to the data on food security, nutrition, poverty indicators and causal factors are included. This unique, real-world data takes the reader through a "hands-on" approach toward econometric practice whereby they can also test the effects of policy and program interventions. Further, this is the first book to explore actual data with STATA and R statistical packages that also provides a line-by-line guide to the programming and interpretation of results.

More and more doctoral researchers are focusing on the social justice aspects of dissertation research problems and often not well guided for how to incorporate societal change issues within the dissertation format. Due to the current climate, this interest is likely to continue to increase. Many aim to enact change within their discipline, workplace, or communities as they conduct dissertation research across doctoral program areas. This book comprises of a diverse resource of methods strategies to incorporate social justice to prepare doctoral scholars to integrate social justice research within their methodology of choice for use across doctoral disciplines including education, business, social sciences, health sciences, and more. This book prepares doctoral scholars to incorporate research method strategies to address social justice aspects of doctoral research problems and offers diverse examples and illustrations for how, why, and where to incorporate social justice research within the realm of doctoral dissertation research. It incorporates both qualitative and quantitative methods and approaches.

Regardless of the discipline or country, creating quality education is multifaceted. At the center of any schooling practice are the educators, their schools, and the teacher education programs that license them. As the schools and faculties of education strive to provide the best practices to pre-service or in-service teachers, it becomes more critical to increase the quality of teacher education via various means to keep up with the demands of schooling in the 21st century. Interdisciplinary Approaches Toward Enhancing Teacher Education provides an overview of how innovation and research experience can enhance teacher education programs with a focus on competencies, skills, and strategies future teachers will need to cope with while teaching students' learning with diversity and facing linguistic, social, and environmental challenges. The book particularly investigates the potentiality of educational technology, innovative techniques, and digital storytelling to enhance education and bilingualism in intercultural contexts and multilingual settings. Covering topics that include performance assessment, teacher training, and professional development, and including many practical and diverse examples, this book is intended for TESOL, second or foreign language learning, and CUL programs and teacher-training institutions, as well as teachers, researchers, academicians, and students in interdisciplinary areas that include science, history, geography, language learning, bilingualism, intercultural competencies, classroom interaction, gamification, and educational technology.

If all humor does indeed come from pain, then American educational policymaking has been a petri dish brimming with hilarity. Even before Betsy DeVos ascended to her perch atop the U.S. Department of Education, her predecessors had offered up an excruciating decade of fodder for satire. Ably assisted by a bevy of billionaires, foundations, and advocacy think tanks, these policymakers unleashed a torrent of rhetorical gibberish and evidence-free "innovations" on the nation's children and their schools. Potential Grizzlies: Making the Nonsense Bearable is one researcher's attempt to laugh instead of cry. The book will bring back memories of policymakers from more innocent times, from Michelle Rhee to Arne Duncan to Chris Christie. Sit back and relax with fond thoughts of your favorite policies, from testing to school choice to "parent trigger." Or maybe just smile and imagine a day when policymakers turn to research evidence and knowledgeable educators to build a sound future for our children.

While there are many English books available on academic research methods and philosophy, many complain that they are difficult for budding, non-native English-speaking researchers to use and understand. Rather than hiding behind jargon, writers should describe and define the concepts for the benefit of non-native English speakers. Social Research Methodology and Publishing Results: A Guide to Non-Native English Speakers explains methods commonly used in the field of academic research, provides stimulus to non-native English-speaking researchers for successful implementation of academic research, and meets the need for an appropriate course framework and materials for teaching research methodology. Covering topics such as pragmatism, research design, and empirical modeling, this premier reference source is a dynamic resource for educators and administrators of higher education, pre-service teachers, librarians, teacher educators, non-native English-speaking researchers, and academicians.

Mapping the Travel Behavior Genome covers the latest research on the biological, motivational, cognitive, situational, and dispositional factors that drive activity-travel behavior. Organized into three sections, Retrospective and Prospective Survey of Travel Behavior Research, New Research Methods and Findings, and Future Research, the chapters of this book provide evidence of progress made in the most recent years in four dimensions of the travel behavior genome. These dimensions are Substantive Problems, Theoretical and Conceptual Frameworks, Behavioral Measurement, and Behavioral Analysis. Including the movement of goods as well as the movement of people, the book shows how traveler values, norms, attitudes, perceptions, emotions, feelings, and constraints lead to observed behavior; how to design efficient infrastructure and services to meet tomorrow's needs for accessibility and mobility; how to assess equity and distributional justice; and how to assess and implement policies for improving sustainability and quality of life. Mapping the Travel Behavior Genome examines the paradigm shift toward more dynamic, user-centric, demand-responsive transport services, including the "sharing economy," mobility as a service, automation, and robotics. This volume provides research directions to answer behavioral questions emerging from these upheavals.

Presents a useful guide for applications of SEM whilst systematically demonstrating various SEM models using Mplus Focusing on the conceptual and practical aspects of Structural Equation Modeling (SEM), this book demonstrates basic concepts and examples of various SEM models, along with updates on many advanced methods, including confirmatory factor analysis (CFA) with categorical items, bifactor model, Bayesian CFA model, item response theory (IRT) model, graded response model (GRM), multiple imputation (MI) of missing values, plausible values of latent variables, moderated mediation model, Bayesian SEM, latent growth modeling (LGM) with individually varying times of observations, dynamic structural equation modeling (DSEM), residual dynamic structural equation modeling (RDSEM), testing measurement invariance of instrument with categorical variables, longitudinal latent class analysis (LLCA), latent transition analysis (LTA), growth mixture modeling (GMM) with covariates and distal outcome, manual implementation of the BCH method and the three-step method for mixture modeling, Monte Carlo simulation power analysis for various SEM models, and estimate sample size for latent class analysis (LCA) model. The statistical modeling program Mplus Version 8.2 is featured with all models updated. It provides researchers with a flexible tool that allows them to analyze data with an easy-to-use interface and graphical displays of data and analysis results. Intended as both a teaching resource and a reference guide, and written in non-mathematical terms, Structural Equation Modeling: Applications Using Mplus, 2nd edition provides step-by-step instructions of model specification, estimation, evaluation, and modification. Chapters cover: Confirmatory Factor Analysis (CFA); Structural Equation Models (SEM); SEM for Longitudinal Data; Multi-Group Models; Mixture Models; and Power Analysis and Sample Size Estimate for SEM. Presents a useful reference guide for applications of SEM while systematically demonstrating various advanced SEM models Discusses and demonstrates various SEM models using both cross-sectional and longitudinal data with both continuous and categorical outcomes Provides step-by-step instructions of model specification and estimation, as well as detailed interpretation of Mplus results using real data sets Introduces different methods for sample size estimate and statistical power analysis for SEM Structural Equation Modeling is an excellent book for researchers and graduate students of SEM who want to understand the theory and learn how to build their own SEM models using Mplus.

The realm of higher education, much like everything else in a global and mobile world, has rapidly altered in the last few decades. More and more universities and seats of higher education are using strategies towards ' 'internationalization'; by increasing heterogeneity in rank, student composition, resource endowments, faculty profiles, and their social spaces. The essays in this volume take a critical look at universities across South Asia, more specifically, at the dynamics of student mobility and mobilizations existing in such localized social spaces, and compares these with their counterparts in universities across the world. While elite universities in South Asia, as elsewhere, have been caught in a stiff international competition and are aspiring for the highest ranks, students from the most excluded communities and remote parts of the country seek entry to badly endowed universities, facing obstacles during their courses, and upon seeking entry into employment. The volume evaluates such universities as spaces for mobility opportunity and mobilizations in a globally networked world. It combines local and international perspectives with thorough observations of the dynamics in localized university spaces while embedding them in transnational processes.