Over the years researchers have found the necessity to develop theories of behavior that are specific to family settings. These theories have been developed by people with a variety of areas of emphasis, from family therapists to gerontologists to child development specialists. In this chapter we will briefly discuss six such theories: Bioecological Model, Family Systems, Functionalism, Conflict Theory, Symbolic Interactionism, and Psychological Perspectives.

Table of Contents
Chapter 1: Theories That Help Us Understand Families
Chapter 2: How Children Learn and Understand Their World
Chapter 3: What is Culture and Why is it Important?
Chapter 4: How Does Gender Influence Children, Families and Communities?
Chapter 5: What is a Family?
Chapter 6: A Closer Look at Parenting
Chapter 7: Building Trusting Collaborative Relationships with Families
Chapter 8: Welcoming & Supporting Families
Chapter 9: Creating Positive Goal-Oriented Relationships with Strengths-Based Attitudes and Relationship-Based Practices

Over the years researchers have found the necessity to develop theories of behavior that are specific to family settings. These theories have been developed by people with a variety of areas of emphasis, from family therapists to gerontologists to child development specialists. In this chapter we will briefly discuss six such theories: Bioecological Model, Family Systems, Functionalism, Conflict Theory, Symbolic Interactionism, and Psychological Perspectives.

This introductory, algebra-based, two-semester college physics book is grounded with real-world examples, illustrations, and explanations to help students grasp key, fundamental physics concepts. This online, fully editable and customizable title includes learning objectives, concept questions, links to labs and simulations, and ample practice opportunities to solve traditional physics application problems.

College Success takes a fresh look at what it means, in today’s world, with today’s students, to be successful in college.Although many of the topics included—from study skills to personal health, from test-taking to managing time and money—will look familiar to those who have used student success texts that have been around for many editions, College Success takes a new approach. The focus is on realistic, practical tools for the students who need them. This is a book designed, frankly, for students who may have difficulty with traditional college texts. The style is direct and to the point. Information is presented concisely and as simply as possible. This is not a weighty tome that discusses student success—this is a manual for doing it.College student demographics have changed considerably in recent decades. More than a third of all students enroll not directly from high school but after a delay of some years. More students are working and have families. More students come from varied ethnic and cultural backgrounds. More students are the first in their family to attend college. More students have grown up with electronic media and now read and think in ways different from the previous generation. With these and so many other cultural changes, more students are not well prepared for a college education with the study skills and life skills they need to become successful students.For each student to get the most out of College Success and their college experience they must understand who they are as it relates to college. To that end, in every chapter students explore themselves, because success starts with recognizing your own strengths and weaknesses. Students make their own goals based on this self-assessment, determining what success in college really means for them as individuals. Interactive activities then help students learn the choices available to them and the possibilities for improving their skills. Skills are presented in step-by-step processes, tips for success in manageable highlighted displays. Most important, students always see the value of what they are reading—and how they can begin to apply it immediately in their own lives.College Success is intended for use in Freshmen Orientation, Study Skills or Student Success courses. A 2009 study revealed that currently nationwide, 34% of college freshmen do not return to their college for their sophomore year. This book is designed to help change that.

Communication in the Real World: An Introduction to Communication Studies overviews the time-tested conceptual foundations of the field, while incorporating the latest research and cutting-edge applications of these basics. Each chapter will include timely, concrete, and real-life examples of communication concepts in action. A key feature of this book is the integration of content regarding diversity and organizational communication in each chapter through examples and/or discrete sub-sections. Discussions of diversity are not relegated to feature boxes. Also integrated into the content are examples that are inclusive in terms of race, gender, sexuality, ability, age, marital status, religion, and other diverse identity characteristics.

Concepts of Biology is designed for the introductory biology course for nonmajors taught at most two- and four-year colleges. The scope, sequence, and level of the program are designed to match typical course syllabi in the market. Concepts of Biology includes interesting applications, features a rich art program, and conveys the major themes of biology.

About Construction Contracting: Business and Legal Principles, 2nd edition by Stuart H. Bartholomew: Exceptionally practical and authoritative, this introduction to construction contracting as it applies to typical, every-day situations explains “theoretical” ideas in terms of what really happens in practice. It emphasizes the more common case law holdings and industry customs that help avoid troublesome legal issues during the completion of a project. - Provided by previous publisher.

Table of Contents
1. Interface of the Law with the Construction Industry
2. Contract Formation, Privity of Contract, and Other Contract Relationships
3. The Prime Contract - An Overview
4. Prime Contract - Format and Major Components
5. Owner-Construction Contractor Prime Contract "Red Flag" Clauses
6. Labor Agreements
7. Purchase Order and Subcontract Agreements
8. Insurance Contracts
9. Surety Bonds
10. Joint-Venture Agreements
11. Bid and Proposals
12. Mistakes in Bids
13. Breach of Contract
14. Contract Changes
15. Differing Site Conditions
16. Delays, Suspensions, and Terminations
17. Liquidated Damages, Force Majeure, and Time Extensions
18. Allocating Responsibility for Delays
19. Constructive Acceleration
20. Common Rules of Contract Interpretation
21. Documentation and Records
22. Construction Contract Claims
23. Dispute Resolution

About the Author
Stuart “Bart” Bartholomew (1925-2013) joined the Navy as an engineer after enrolling at NROTC programs at the University of Washington. He earned bachelors and master’s degrees in civil engineering from UC Berkeley and made his post-Navy civilian career in heavy industry. He worked for legendary dam builder, Harvey Slocum on Bull Shoals Dam in Arkansas; Bhakra Dam in Punjab, India; Karnaphuli Dam in Bangladesh; port and rail facilities in Port Hedland, Western Australia; several segments of the Bay Area Rapid Transit system in San Francisco and the East Bay; and numerous marine, bridge, transportation and tunneling projects in the Midwest and on the East Coast.

He joined Fruin-Colnon Corporation, becoming a vice president and member of the board of directors before his retirement in the early 1980s. He was a Fellow and Life Member of the American Society of Civil Engineers and a member of both the Moles and Beavers heavy engineering construction associations for over 25 years and was honored by the Beavers with the annual Engineering Award for outstanding achievement in Heavy Engineering Construction. After retirement from industry he pursued a second career as a professor of Construction Management at California State University, Chico, during which time he wrote Construction Contracting.

Publication Information
Published in 2002 as ISBN 1-13-091055-4 | Rights reverted to estate 2022 | Published by the Open Education Initiative of the University Libraries at Virginia Tech 2022 as ISBN 978-1-957213-20-0 under CC BY NC SA 4.0.

(c) Estate of Stuart H. Bartholomew. Released with permission by the University Libraries at Virginia Tech under Creative Commons Attribution NonCommercial- ShareAlike (CC BY NC-SA) 4.0 License. https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode This material was previously published by Pearson Education, Inc.

Any derivatives of this work must comply with the requirements of the Creative Commons license and include the following statement, “This material was previously published by Pearson Education, Inc.”

Accessibility Statement: The Open Education Initiative at the University Libraries at Virginia Tech is committed to making its publications accessible in accordance with the Americans with Disabilities Act of 1990. The PDF and online versions of this book utilizes header structures and alternative text which allow for machine readability and navigation.

Note to users: This work may contain components (e.g., illustrations, or quotations) not covered by the license. Every effort has been made to identify these components but ultimately it is your responsibility to independently evaluate the copyright status of any work or component part of a work you use, in light of your intended use.

A Cool, Brisk Walk Through Discrete Mathematics, an innovative and non-traditional approach to learning Discrete Math, is available for low cost from Blurb or via free download.

This is Volume Two of the Crystal Ball series: Foundations for Data Science. The author titled the first volume “Introduction to Data Science” because it led readers through a dip-your-toes-in-the-water
experience. Readers took a brief tour through the various elements in this diverse field and got a feel for what it was all about. In Foundations, which is the next level, the reader's growing knowledge is further developed to a firm base on which to build everything else.

A perfect introduction to the exploding field of Data Science for the curious, first-time student. The author brings his trademark conversational tone to the important pillars of the discipline: exploratory data analysis, choices for structuring data, causality, machine learning principles, and introductory Python programming using open-source Jupyter Notebooks. This engaging read will allow any dedicated learner to build the skills necessary to contribute to the Data Science revolution, regardless of background.

Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought.

Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.”

Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.

How can we effectively and efficiently teach data science to students with little to no background in computing and statistical thinking? How can we equip them with the skills and tools for reasoning with various types of data and leave them wanting to learn more? This introductory data science course is our (working) answer to this question.
The source code for everything you see here can be found on GitHub.

The core content of the course focuses on data acquisition and wrangling, exploratory data analysis, data visualization, inference, modelling, and effective communication of results. Time permitting, the course also introduces additional concepts and tools like interactive visualization and reporting, text analysis, and Bayesian inference. A heavy emphasis is placed on a consistent syntax (with tools from the tidyverse), reproducibility (with R Markdown), and version control and collaboration (with Git and GitHub). In addition, out-of-class learning is supplemented with interactive tutorials. The goal of the course is to bring students from zero to being able to work in a team on a fully reproducible data science project analysing a dataset of their choice and answering questions they care about.

Data Science in a Box contains the materials required to teach (or learn from) the course described above, all of which are freely-available and open-source. They include course materials such as slide decks, lecture and live coding videos, homework assignments, guided labs, sample exams, a final project assignment, as well as materials for instructors such as pedagogical tips, information on computing infrastructure, technology stack, and course logistics.

Majority of the materials linked live in the GitHub repo serving this website.

Please note that Data Science in a Box uses a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

""Life is made up of a never-ending sequence of decisions. Many decisions – such as what to
watch on television or what to eat for breakfast – are rather unimportant. Other decisions –
such as what career to pursue, whether or not to invest all of one’s savings in the purchase
of a house – can have a major impact on one’s life. This book is concerned with Decision
Making, which the Oxford Dictionary defines as “the process of deciding about something
important”. We will not attempt to address the issue of what decisions are to be considered
“important”. After all, what one person might consider an unimportant decision may be
viewed by another individual as very important. What we are interested in is the process of
making decisions and what it means to be a “rational” decision maker""--Introductory paragraph.

Find 32 Youtube videos of lectures based on the Decision Making book through this link: http://faculty.econ.ucdavis.edu/faculty/bonanno/DM_Book.html.

Copyright information: You are free to redistribute this book in pdf format. If you make use of any part of this book you must give appropriate credit to the author. You may not remix, transform, or build upon the material without permission from the author. You may not use the material for commercial purposes.

This book provides a plainspoken and thorough introduction to the web for historians—teachers and students, archivists and museum curators, professors as well as amateur enthusiasts—who wish to produce online historical work, or to build upon and improve the projects they have already started in this important new medium. It begins with an overview of the different genres of history websites, surveying a range of digital history work that has been created since the beginning of the web. The book then takes the reader step-by-step through planning a project, understanding the technologies involved and how to choose the appropriate ones, designing a site that is both easy-to-use and scholarly, digitizing materials in a way that makes them web-friendly while preserving their historical integrity, and how to reach and respond to an intended audience effectively. It also explores the repercussions of copyright law and fair use for scholars in a digital age, and examines more cutting-edge web techniques involving interactivity, such as sites that use the medium to solicit and collect historical artifacts. Finally, the book provides basic guidance on insuring that the digital history the reader creates will not disappear in a few years.

Discrete Mathematics: An Open Introduction is a free, open source textbook appropriate for a first or second year undergraduate course for math majors, especially those who will go on to teach. The textbook has been developed while teaching the Discrete Mathematics course at the University of Northern Colorado. Primitive versions were used as the primary textbook for that course since Spring 2013, and have been used by other instructors as a free additional resource. Since then it has been used as the primary text for this course at UNC, as well as at other institutions.

Electromagnetics Volume 1 by Steven W. Ellingson is a 225-page, peer-reviewed open educational resource intended for electrical engineering students in the third year of a bachelor of science degree program. It is intended as a primary textbook for a one-semester first course in undergraduate engineering electromagnetics. The book employs the “transmission lines first” approach in which transmission lines are introduced using a lumped-element equivalent circuit model for a differential length of transmission line, leading to one-dimensional wage equations for voltage and current.

Suggested citation: Ellingson, Steven W. (2018) Electromagnetics, Vol. 1. Blacksburg, VA: VT Publishing. https://doi.org/10.21061/electromagnetics-vol-1 CC BY-SA 4.0

Three formats of this book are available:
Print (ISBN 978-0-9979201-8-5)
PDF (ISBN 978-0-9979201-9-2)
LaTeX source files

If you are a professor reviewing, adopting, or adapting this textbook please help us understand a little more about your use by filling out this form: http://bit.ly/vtpublishing-updates

Additional Resources
Problem sets and the corresponding solution manual are also available.
Community portal for the Electromagnetics series https://www.oercommons.org/groups/electromagnetics-user-group/3455/
Faculty listserv for the Electromagnetics series https://groups.google.com/a/vt.edu/d/forum/electromagnetics-g
Submit feedback and suggestions http://bit.ly/electromagnetics-suggestion

Table of Contents:
Chapter 1: Preliminary Concepts
Chapter 2: Electric and Magnetic Fields
Chapter 3: Transmission Lines
Chapter 4: Vector Analysis
Chapter 5: Electrostatics
Chapter 6: Steady Current and Conductivity
Chapter 7: Magnetostatics
Chapter 8: Time-Varying Fields
Chapter 9: Plane Waves in Lossless Media
Appendixes
A. Constitutive Parameters of Some Common Materials
B. Mathematical Formulas
C. Physical Constants

About the Author: Steven W. Ellingson (ellingson@vt.edu) is an Associate Professor at Virginia Tech in Blacksburg, Virginia in the United States. He received PhD and MS degrees in Electrical Engineering from the Ohio State University and a BS in Electrical & Computer Engineering from Clarkson University. He was employed by the US Army, Booz-Allen & Hamilton, Raytheon, and the Ohio State University ElectroScience Laboratory before joining the faculty of Virginia Tech, where he teaches courses in electromagnetics, radio frequency systems, wireless communications, and signal processing. His research includes topics in wireless communications, radio science, and radio frequency instrumentation. Professor Ellingson serves as a consultant to industry and government and is the author of Radio Systems Engineering (Cambridge University Press, 2016).

This textbook is part of the Open Electromagnetics Project led by Steven W. Ellingson at Virginia Tech. The goal of the project is to create no-cost openly-licensed content for courses in undergraduate engineering electromagnetics. The project is motivated by two things: lowering learning material costs for students and giving faculty the freedom to adopt, modify, and improve their educational resources.

Accessibility features of this book: Screen reader friendly, navigation, and Alt-text for all images and figures.

Publication of this book was made possible in part by the Open Education Faculty Initiative Grant program at the University Libraries at Virginia Tech. http://guides.lib.vt.edu/oer/grants

This textbook is intended for use in introductory Entrepreneurship classes at the undergraduate level. Due to the wide range of audiences and course approaches, the book is designed to be as flexible as possible. Theoretical and practical aspects are presented in a balanced manner, and specific components such as the business plan are provided in multiple formats. Entrepreneurship aims to drive students toward active participation in entrepreneurial roles and exposes them to a wide range of companies and scenarios.

This textbook provides a compact introduction to using the R programming language for data analysis. While there are good, freely available resources for learning these skills, they are generally not optimized for use in the classroom. Most fail to include a range of exercises, expect a high level of prior programming or mathematical experience, or only cover a specific niche aspect of data science. Moreover, the vast majority of these free sources do not include permissive licenses that make it easy to re-mix them and adapt it to a specific course. This textbook address these concerns by providing chapters designed to be covered in a single class period, a wide variety of exercises, and a Creative Commons license that allows others to make and republish their notes according to the needs of a specific curriculum.

Exploring Computer Science is intended for those with no experience with computer science at all. Its focus is on developing algorithms and solving problems. Python is used as the programming language.

Table of Contents:
Preface
Chapter 1: The Road Ahead
Chapter 2: Getting Started
Chapter 3: First Programs
Chapter 4: Types and Operations
Chapter 5: Making Decisions
Chapter 6: Going Back Again
Chapter 7: Algorithms
Chapter 8: Using Libraries
Chapter 9: Lists
Chapter 10: Functions