Digital library
Textbooks, references and open learning resources.
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Data Analysis in the Psychological Sciences: A Practical, Applied, Multimedia Approach
Leyre Castro; J. Toby Mordkoff · University of Iowa Libraries · 2023
This open resources textbook contains 10 Units that describe and explain the main concepts in statistical analysis of psychological data. In addition to conceptual descriptions and explanations of the basic analyses for descriptive statistics, this textbook also explains how to conduct those analyses with common statistical software (Excel) and open-source free software (R).
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Conducting Mixed-Methods Research: From Classical Social Sciences to the Age of Big Data and Analytics
Viswanath Venkatesh; Susan (Sue) Brown; Yulia Sullivan · Virginia Tech Libraries · 2023
Scholars in the social sciences are increasingly expected to incorporate both quantitative and qualitative techniques and methods into their research. The growth of “mixed-methods” research is evident in social science disciplines ranging from psychology and management to marketing and information systems. This book is designed to provide principles, strategies, and guidance specifically for researchers in these disciplines so that they can use mixed-methods research more effectively. In thirteen chapters, Conducting Mixed-Methods Research takes readers through the research process, from defining research questions to writing articles using a mixed-methods approach. For those who are well trained in either qualitative or quantitative methods, the book shows them how to think about the purposes of mixed-methods research, design mixed-methods studies, and develop meta-inferences by integrating findings from both methods. Throughout, the discussion is grounded in examples taken from published research, carefully chosen to highlight best practices, thus opening a window into a broad body of mixed-methods research applications.
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Operating Systems and Infrastructure in Data Science
Josef Spillner · vdf Hochschulverlag · 2023
Modern data scientists work with a number of tools and operating system facilities in addition to online platforms. Mastering these in combination to manage their data and to deploy software, models and data as ready-to-use online services as well as to perform data science and analysis tasks is in the focus of Operating Systems and Infrastructure in Data Science. Readers will come to understand the fundamental concepts of operating systems and to explore plenty of tools in hands-on tasks and thus gradually develop the skills necessary to compose them for programming in the large, an essential capability in their later career. The book guides students through semester studies, acts as reference knowledge base and aids in acquiring the necessary knowledge, skills and competences especially in self-study settings. A unique feature of the book is the associated access to Edushell, a live environment to practice operating systems and infrastructure tasks.
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Culturally Responsive Computing: An Introduction into Computer Science, Security, and Technology
Devan Walton · ROTEL · 2024
"Culturally Responsive Computing" is an essential textbook that explores the intricate relationship between technology and global societies. It gives students and professionals a deep understanding of how cultural contexts shape and are shaped by computing practices, from algorithm design to user interface development. This book equips readers with the knowledge and skills to create inclusive, ethical, and culturally sensitive technological solutions for our diverse world.
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Introduction to Data Science Using Python
Afrand Agah · The Pennsylvania Alliance for Design of Open Textbooks (PA-ADOPT) · 2024
This book contains two parts, the first is designed to be used in an introductory programming course for students looking to learn Python, without having any prior experience with programming. Basic programming concepts are discussed, explained, and illustrated with a Python program. Ample programming questions are provided for practice. The second part of the book utilizes machine-learning concepts and statistics to accomplish data-driven resolutions. Python programs are provided to apply scientific computing to conclude statistically driven results.
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Prealgebra via Python Programming: First Steps to Perform Large Scale Computational Tasks in the Sciences and Engineerings
Sergio Rojas · Sergio Rojas · 2018
This book was written for students and instructors who want to learn how to use a computer for other than the most common uses, such as web browsing, document creation, or paying bills online. This book is for anyone who wants to perform computational tasks that they design. In other words, if you wish to learn how to program a computer, this book is for you. Because prealgebra is a subject that practically everyone is supposed to learn in grade school, it provides a platform to introduce basic computer programming concepts. Consequently, this book should also be of interest to students in middle or high school who want to learn how to program, and who are willing to invest the time and effort in learning a programming language that they could continue using throughout their schooling and in their professional life. Similarly, this book could also be of interest to pre-service and in-service mathematics teachers wishing to have at their disposal a complementary tool to assist in fostering understanding, competency, and interest in mathematics among their students. This book can be integrated with the teachers’ curriculum as way to tackle non-traditional math problems using an inexpensive modern computer language. By the end of the book, a reader will have learned enough to be able to write a preliminary, step-by-step one variable equation solver that can be expanded in the future to use with more complex equations. In other words, by the end of the book, you will be able to write code that programs their machines to solve equations. This code is foundational and readers are ecouraged to learn on their own how to build on it to suit their mathematics learning needs.
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Earth, Space, and Environmental Science Explorations with ArcGIS Pro
Wing Cheung · Wing Cheung
When I first started teaching Geographic Information Systems (GIS) over 15 years ago, there were only a handful of GIS tutorial books on the market. While a few of them focused on a particular theme, many of them were mainly technical publications with no unifying theme. These publications are perfect for teaching new users about basic GIS operations and continue to be invaluable to many users today. However, these publications consisted of tutorials focusing on vastly different real-world scenarios, and felt a little disjointed to integrate into a class that focuses on a specific field (e.g. Environmental Science, Geography, Urban Planning). Since then, I am happy to see that there has been a proliferation of publications that are not only focused on introducing the technology, but also provide an introduction to a specific field as well as GIS. It is with this consideration in mind that I wrote this book to not only introduce students to the tools in ArcGIS Pro, but also to provide a glimpse into some of the topics that may be covered in an introductory course in Geography, Environmental Science, or related disciplines. I aimed to achieve a balance of technical instruction and information about Earth, Space, and Environmental Sciences, to make this publication helpful for new GIS learners, as well as students who may be interested in learning about the applications of GIS in the Earth, Space, and Environmental Sciences. Before you begin with the book, please download and unzip the data for the book at https://tinyurl.com/ESESGIS. Each chapter will begin with a list of the technical objectives for the lab exercise, which is particularly useful to refer to should you need a refresher on how to perform a particular task at a later date. The list of technical objectives is followed by a short introduction that provides the context for the exercise. Subsequently, you will find the step-by-step directions for the exercises with questions embedded throughout (in yellow h
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Computer Science I
Chris Bourke · Chris Bourke · 2018
This textbook covers the traditional introductory Computer Science I topics but takes a unique approach. Topics are covered in a language-agnostic manner in the first part with supplemental parts that cover the same concepts in a specific language. The current version covers C, Java, and PHP. This textbook as been used in several Computer Science I sections over multiple years at the University of Nebraska-Lincoln
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Think Complexity: Exploring Complexity Science with Python
Allen Downey · Green Tea Press · 2018
Complexity science uses computation to explore the physical and social sciences. In Think Complexity, you'll use graphs, cellular automata, and agent-based models to study topics in physics, biology, and economics. Whether you're an intermediate-level Python programmer or a student of computational modeling, you'll delve into examples of complex systems through a series of worked examples, exercises, case studies, and easy-to-understand explanations. In this updated second edition, you will: Work with NumPy arrays and SciPy methods, including basic signal processing and Fast Fourier Transform Study abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machines Get Jupyter notebooks filled with starter code and solutions to help you re-implement and extend original experiments in complexity; and models of computation like Turmites, Turing machines, and cellular automata Explore the philosophy of science, including the nature of scientific laws, theory choice, and realism and instrumentalism Ideal as a text for a course on computational modeling in Python, Think Complexity also helps self-learners gain valuable experience with topics and ideas they might not encounter otherwise.
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The DEI Metadata Handbook: A Guide to Diverse, Equitable, and Inclusive Description
H. E. Wintermute; Heather Campbell; Christopher Dieckman · Iowa State University Digital Press · 2024
Written primarily for professionals in library and information science but with applicability to archives and other information management industries, this handbook provides an overview of metadata work that focuses on diversity, equity, and inclusion (DEI). DEI metadata work has several goals: enhancing diverse representation in descriptive metadata; improving discovery of diverse resources; and mitigating negative effects of inaccurate, outdated, or offensive terminology. Readers will gain a broad awareness of DEI-related issues in metadata creation and management; learn techniques for retroactively reviewing and updating existing metadata to address these issues; and develop strategies to create metadata that better meets DEI needs.
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Social Data Analysis
Mikaila Arthur; Roger Clark · Rhode Island College Digital Publishing · 2021
Social data analysis enables you, as a researcher, to organize the facts you collect during your research. Your data may have come from a questionnaire survey, a set of interviews, or observations. They may be data that have been made available to you from some organization, national or international agency or other researchers. Whatever their source, social data can be daunting to put together in a way that makes sense to you and others. This book is meant to help you in your initial attempts to analyze data. In doing so it will introduce you to ways that others have found useful in their attempts to organize data. You might think of it as like a recipe book, a resource that you can refer to as you prepare data for your own consumption and that of others. And, like a recipe book that teaches you to prepare simple dishes, you may find this one pretty exciting. Analyzing data in a revealing way is at least as rewarding, we’ve found, as it is to cook up a yummy cashew carrot paté or a steaming corn chowder. We’d like to share our pleasure with you.
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Arcade Expression Crash Course with COVID-19 data
Wing Cheung · Wing Cheung · 2022
Written for ArcGIS Pro 2.5
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Discrete Math with SageMath: Learn math with open-source software
Zunaid Ahmed; Hellen Colman; Samuel Lubliner · Zunaid Ahmed, Hellen Colman, Samuel Lubliner · 2025
Our book is intended to provide concise and complete instructions on how to use Sage to solve problems in Discrete Math. It is appropriate for a first or second year undergraduate course for math and computer science majors. Our goal is to streamline the learning process with SageMath. This approach helps students focus more on mathematics and reduces the friction of learning how to code. Our resources are designed for all math students, regardless of programming experience. The novelty of our project is that the textbook is authored by students under faculty supervision. With Open Pedagogy as a guiding praxis, we present this student-created textbook as a more effective alternative in promoting student learning and engagement. Students present the contents in new and inventive ways, from the overall voice of the textbook to the actual examples drawn from their and their peers' lives. The text began as a support textbook for our undergraduate Discrete Math course developed at Wright College, one of the City Colleges of Chicago. Despite the fabulous capabilities of SageMath, students in Discrete Math were often frustrated by the lack of specific documentation geared towards beginning undergrad students in Discrete Math. We developed an OER for our students to use this mathematical software effectively.
![The Data Renaissance: Analyzing the Disciplinary Effects of Big Data, Artificial Intelligence, and Beyond [Revised Edition]](/api/files/covers/otl-1718.webp)
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The Data Renaissance: Analyzing the Disciplinary Effects of Big Data, Artificial Intelligence, and Beyond [Revised Edition]
J.J. Sylvia IV · ROTEL · 2024
The Data Renaissance delves into the complexities of data's role in various industries and its broader impact on society. It highlights the challenges in investigating data practices, citing examples like TikTok, where algorithms and data handling are closely guarded secrets. The content, contributed by students under the guidance of an expert, covers a wide range of topics, including the ethical aspects of generative AI in education and the workplace, and case studies reflecting real-world experiences. This evolving text, intended to be updated with each class, serves as a dynamic resource for educators and students alike, offering insights and discussion guides for an in-depth understanding of the ever-changing landscape of data in our digital age.
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Technology in Schools
Gary Ackerman · hackscience.education · 2022
My purpose in writing this book is to give readers a view into the work of managing information technology in schools. IT professionals will notice differences (some nuanced and some significant) between the needs and expectations of IT users in business and IT in school. With the more complete and more accurate concept the nature of the computing environment necessary for successful schooling, which I intend to provide through this book, IT professionals will be better prepared to meet those needs. Educators will also benefit from this book by clarifying the nature of their IT needs and how these may be different from those that are familiar to IT professionals who are hired to work in your school.
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Practical Game Programming
Harris Wang; Walter Ridgewell · Athabasca University Press · 2026
Practical Game Programming provides a structured, accessible introduction to game development using C++ and the Allegro 5 library. Designed for upper-level undergraduate learners, it guides students through the complete development pipeline—from programming fundamentals and user input to graphics, audio, file management, and game timing. Advanced topics such as collision detection, multithreading, optimization, custom shaders, and networking are covered in depth. This OER emphasizes both technical skills and design principles, including game conception, prototyping, UI/UX, testing, and quality assurance. Each chapter includes exercises and projects, culminating in genre-based development challenges across action, platformer, adventure, arcade, puzzle, role-playing, strategy, and more. With a focus on applied learning and creative exploration, this text equips students to build professional-quality games and prepares them for real-world development environments.
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Discrete Mathematics for Information Technology
Simon Crothers · Kwantlen Polytechnic University · 2026
Discrete Mathematics for Information Technology is an applied, student-focused introduction to the mathematical foundations that underpin modern computing. Designed for learners in information technology and business contexts, this textbook bridges theory and practice by connecting core concepts, such as number systems, data representation, logic, proofs, relations, algorithms, Boolean algebra, and graph theory, to real-world applications in programming, networking, databases, and systems design. Each chapter is structured with clear explanations, worked examples, case studies, and programming-oriented exercises that reinforce both conceptual understanding and practical skills. Emphasis is placed on developing analytical thinking, problem-solving, and the ability to model and reason about digital systems with precision and confidence. As an open educational resource, the text is adaptable and accessible, supporting a wide range of teaching and learning environments. By integrating mathematical rigor with authentic IT scenarios, this book equips students with the essential tools needed to succeed in modern, data-driven and technology-focused careers.
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The Future is Now: Empowering Society Through AI Literacy
Jason Wrench; Sanae Elmoudden · Milne Open Textbooks · 2025
"The Future is Now: Empowering Society Through AI Literacy" aims to educate and empower a broad audience on the nuances of artificial intelligence, ensuring that readers are not only informed about what AI is and can do but are also prepared to engage with the technology ethically and responsibly. The book adopts a multidisciplinary approach, weaving together technical explanations, ethical considerations, and socio-economic insights to provide a comprehensive overview of AI's role in society today and its potential for the future.
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Programming Differential Privacy
Joseph Near; Chiké Abuah · Joseph P. Near and Chiké Abuah · 2025
This book offers a hands-on introduction to differential privacy, combining formal foundations with executable code and practical design patterns. The material has evolved through lecture notes, workshops, and collaborations with academics and practitioners, gradually expanding to cover both classical and modern topics.
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Beyond Coding
David Tuffley · Griffith University · 2025
In today’s competitive IT industry, technical skills alone are no longer enough to succeed. This book teaches essential soft skills that transform technical professionals into complete IT leaders. You will master clear communication for diverse audiences, build strong teams through collaboration and conflict resolution, and solve complex problems with structured thinking. The guide covers time management techniques, project management fundamentals, and stakeholder delivery methods. Additional modules address professional ethics, customer relations, cultural awareness, leadership influence, and personal growth. These practical skills complement your technical knowledge, creating competitive advantages in today’s IT industry. The book provides frameworks, tools, and strategies that help you advance your career, lead projects successfully, and adapt to changing workplace demands.