Acknowledgements

All rights reserved. Any or all portions of this document may be reproduced and distributed without prior permission provided the source is cited as:


Dynamic Learning Maps Consortium. (2023, December). 2022–2023 Technical Manual—Instructionally Embedded Model. University of Kansas, Accessible Teaching, Learning, and Assessment Systems.

Acknowledgements


The publication of this technical manual update builds on the documentation presented in the 2021–2022 Technical Manual—Instructionally Embedded Model. This document represents further contributions to a body of work in the service of supporting a meaningful assessment system designed to serve students with the most significant cognitive disabilities. Hundreds of people have contributed to this undertaking. We acknowledge them all for their contributions.

Many contributors made the writing of this technical manual possible. Dynamic Learning Maps® (DLM®) staff who made significant writing contributions to this technical manual are listed below with gratitude.

W. Jake Thompson, Ph.D., Assistant Director for Psychometrics
Amy K. Clark, Ph.D., Associate Director for Operational Research

The authors also wish to acknowledge Ashley Hirt, Jeffrey Hoover, Elizabeth Kavitsky, Jennifer Kobrin, Brooke Nash, and Noelle Pablo for their role in developing, organizing, and compiling this manual. The authors also wish to acknowledge Amber Cavasos, Alson Cole, Karen Erickson, Sarah Koebley, Jessica Lancaster, and Delaney Wilson for their contributions to this manual. Finally, the authors wish to thank Lucas Cooper, Justin Dean, Aaron Gates, and Sara Lundberg for their editing and project management work. For a list of project staff who supported the development of this manual through key contributions to design, development, or implementation of the Dynamic Learning Maps Alternate Assessment System, please see the 2021–2022 Technical Manual—Instructionally Embedded Model.

We are also grateful for the contributions of the members of the DLM Technical Advisory Committee who graciously provided their expertise and feedback on the DLM system. Members of the Technical Advisory Committee during the 2022–2023 operational year include:

Russell Almond, Ph.D., Florida State University
Claudia Flowers, Ph.D., University of North Carolina at Charlotte
Robert Henson, Ph.D., University of North Carolina at Greensboro
Joan Herman, Ed.D., University of California, Los Angeles
James Pellegrino, Ph.D., University of Illinois Chicago
Edward Roeber, Ph.D., Michigan Assessment Consortium
David Williamson, Ph.D., Independent Consultant
Phoebe Winter, Ph.D., Independent Consultant