K-Math Workbook Grade 7
Published on 7. April 2017
Book
Paperback/Softback
74 pages
978-0-9981298-0-8 (ISBN)
Description
Strengthen your child's seventh-grade Math skills with next generation tools of the K-Math Workbook. In this workbook, all practice pages are fully organized by the Common Core State Standards (CCSS). The progressive practices and assessments integrate state-of-the-art tools in this workbook, so your child will strengthen skills for the state math exam and CCSS with fun! By scanning each Item's QR code with any smart device, one can instantly access these additional features such as detailed solutions, item drill, and more practices. By scanning the Exam QR code in the Exam Page, one can submit answers and get immediate feedback such as: grades, correct answers, solution steps, additional practices, and diagnosis reports. All of these options help students track their progress and locate areas for improvement. Fully aligned to standards with smart learning technologies, the K-Math Workbook is your child's pathfinder to math success.
More details
Language
English
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 280 mm
Width: 216 mm
Thickness: 4 mm
Weight
195 gr
ISBN-13
978-0-9981298-0-8 (9780998129808)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
JAEHWA CHOI is Associate Professor and Program Director of the Assessment, Testing, and Measurement program in the Graduate School of Education and Human Development at the George Washington University. His research interests include: Next Generation Assessment Models (Truncated or Semi-truncated Logistic Item Response Theory Models; Non-linear Growth Modeling for Latent Traits; Assessment Models for Machine/Artificial Intelligence), Intelligent Assessment Engineering Systems (Automatic Item Generation [AIG] using Machine Learning Techniques; Computer Adaptive Formative Assessment [CAFA] Models; Educational Big Data Analytic Systems; Problem Solving Artificial Intelligent System using Deep Learning Artificial Neural Network [DL ANN]; Diagnostic Assessment System using DL ANN), and Technology-enhanced STEM Education Applications (K-Math Workbook System using AIG for K-12 Math; CAFA Smart Assignment System for K-12 Math; Pathway to Advancement and Success in Statistics [PASS] System). In CAFA project, he is in charge of overall project management focused on assessment system design and psychometric models. He received a Ph.D. in Measurement, Statistics, and Evaluation from the University of Maryland, College Park. SUNHEE KIM is Associate Professor in Mathematics Division in the Howard Community College. Her research interests include optimization applications using MCMC methods, numerical analysis application to mathematical finance, and simulation based mathematics assessment. In CAFA project, she is in charge of Cognitive Knowledge Map and AIG item template development focused on Mathematics subject. She received Ph.D. in Applied Mathematics and Scientific Computation from the University of Maryland, College Park. KYONGIL YOON is Associate Professor in the Computer Studies Department in the Arts and Sciences School in Notre Dame of Maryland University. His research interests include computer vision, computational geometry, web 2.0, and computer enhanced mathematics education. In CAFA project, he is in charge of web system design, database and system development focused on computational algorithms and procedures. He received Ph.D. in computer science from the University of Maryland, College Park.