Reading Essentials, student edition provides an interactive reading experience to improve student comprehension of science content. It makes lesson content more accessible to struggling students and supports goals for differentiated instruction. Students can highlight text and take notes right in the book!

Integrated iScience blends life, earth, and physical science topics in three courses, specific to each grade. Integrated iScience Course 1 focuses on the methods of science and covers topics in life, earth, and physical science. Units include: The Nature of Science, Exploring Life, Understanding Matter, and Understanding Energy. The text's pedagogy (chapter outlines, core concept maps, and overviews) reveals how the science disciplines are interrelated and integrated throughout the text. It continues to introduce basic concepts and key ideas while providing opportunities for students to learn reasoning skills and a new way of thinking about their environment. iScience meets students where they are through engaging graphic novel-style features and thought-provoking questions that encourage them to relate the science concepts to the world around them. The inquiry-based 5E lesson cycle provides active, hands-on explorations of the concepts. Includes: Integrated iScience Course 1 Print Student Edition

Reading Essentials, student edition provides an interactive reading experience to improve student comprehension of science content. It makes lesson content more accessible to struggling students and supports goals for differentiated instruction. Students can highlight text and take notes right in the book!

The Data Quality Assessment Framework shows you how to measure and monitor data quality, ensuring quality over time. You'll start with general concepts of measurement and work your way through a detailed framework of more than three dozen measurement types related to five objective dimensions of quality: completeness, timeliness, consistency, validity, and integrity. Ongoing measurement, rather than one time activities will help your organization reach a new level of data quality. This plain-language approach to measuring data can be understood by both business and IT and provides practical guidance on how to apply the DQAF within any organization enabling you to prioritize measurements and effectively report on results. Strategies for using data measurement to govern and improve the quality of data and guidelines for applying the framework within a data asset are included. You'll come away able to prioritize which measurement types to implement, knowing where to place them in a data flow and how frequently to measure. Common conceptual models for defining and storing of data quality results for purposes of trend analysis are also included as well as generic business requirements for ongoing measuring and monitoring including calculations and comparisons that make the measurements meaningful and help understand trends and detect anomalies. - Demonstrates how to leverage a technology independent data quality measurement framework for your specific business priorities and data quality challenges - Enables discussions between business and IT with a non-technical vocabulary for data quality measurement - Describes how to measure data quality on an ongoing basis with generic measurement types that can be applied to any situation

Based on the Cornell note-taking format, this resource incorporates writing into the learning process. Directly linked to the student text, this notebook provides a systematic approach to learning science by encouraging students to engage by summarizing and synthesizing abstract concepts in their own words

Based on the Cornell note-taking format, this resource incorporates writing into the learning process. Directly linked to the student text, this notebook provides a systematic approach to learning science by encouraging students to engage by summarizing and synthesizing abstract concepts in their own words