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In the Spotlight

  • Now available! The Information Literacy User's Guide

    The Information Literacy User's Guide: An Open, Online Textbook
    The Information Literacy User's Guide: An Open, Online Textbook
    Deborah Bernnard, Greg Bobish, Daryl Bullis, Jenna Hecker, Irina Holden, Allison Hosier, Trudi Jacobson, Tor Loney

    Good researchers have a host of tools at their disposal that make navigating today’s complex information ecosystem much more manageable. Gaining the knowledge, abilities, and self-reflection necessary to be a good researcher helps not only in academic settings, but is invaluable in any career, and throughout one’s life. The Information Literacy User’s Guide will start you on this route to success.

    The Information Literacy User’s Guide is based on two current models in information literacy: The 2011 version of The Seven Pillars Model, developed by the Society of College, National and University Libraries in the United Kingdom and the conception of information literacy as a metaliteracy, a model developed by one of this book’s authors in conjunction with Thomas Mackey, Dean of the Center for Distance Learning at SUNY Empire State College. These core foundations ensure that the material will be relevant to today’s students.

    The Information Literacy User’s Guide introduces students to critical concepts of information literacy as defined for the information-infused and technology-rich environment in which they find themselves. This book helps students examine their roles as information creators and sharers and enables them to more effectively deploy related skills. This textbook includes relatable case studies and scenarios, many hands-on exercises, and interactive quizzes.

  • Real Analysis Textbook

    How We got from There to Here: A Story of Real Analysis
    How We got from There to Here: A Story of Real Analysis
    Robert Rogers, Eugene Boman

    The typical introductory real analysis text starts with an analysis of the real number system and uses this to develop the definition of a limit, which is then used as a foundation for the definitions encountered thereafter. While this is certainly a reasonable approach from a logical point of view, it is not how the subject evolved, nor is it necessarily the best way to introduce students to the rigorous but highly non-intuitive definitions and proofs found in analysis.
    This book proposes that an effective way to motivate these definitions is to tell one of the stories (there are many) of the historical development of the subject, from its intuitive beginnings to modern rigor. The definitions and techniques are motivated by the actual difficulties encountered by the intuitive approach and are presented in their historical context. However, this is not a history of analysis book. It is an introductory analysis textbook, presented through the lens of history. As such, it does not simply insert historical snippets to supplement the material. The history is an integral part of the topic, and students are asked to solve problems that occur as they arise in their historical context.
    This book covers the major topics typically addressed in an introductory undergraduate course in real analysis in their historical order. Written with the student in mind, the book provides guidance for transforming an intuitive understanding into rigorous mathematical arguments. For example, in addition to more traditional problems, major theorems are often stated and a proof is outlined. The student is then asked to fill in the missing details as a homework problem.

  • Dr. Diane Kiernan, SUNY ESF

    Natural Resources Biometrics
    Natural Resources Biometrics
    Diane Kiernan

    Natural Resources Biometrics begins with a review of descriptive statistics, estimation, and hypothesis testing. The following chapters cover one- and two-way analysis of variance (ANOVA), including multiple comparison methods and interaction assessment, with a strong emphasis on application and interpretation. Simple and multiple linear regressions in a natural resource setting are covered in the next chapters, focusing on correlation, model fitting, residual analysis, and confidence and prediction intervals. The final chapters cover growth and yield models, volume and biomass equations, site index curves, competition indices, importance values, and measures of species diversity, association, and community similarity.

Open Monograph Press Public Knowledge Project

For more information, please see Project Description  Questions, Suggestions, or Report an Issue, please contact: Cyril Oberlander, SUNY Geneseo, Library Director & PI for Open SUNY Textbooks: cyril@geneseo.edu