Dynamic Learning Maps: Charting the Course of Learning for Students with Significant Cognitive Disabilities

The landscape of education is constantly evolving, seeking more nuanced and effective ways to understand and support student learning. For students with significant cognitive disabilities, this evolution has led to the development of specialized assessment systems designed to capture their unique progress. Among these, Dynamic Learning Maps (DLM) stands out as a comprehensive approach that moves beyond traditional testing to map a student's learning journey in a more individualized and detailed manner.

Understanding the Core Concept: Beyond Linear Learning

Traditionally, learning is often conceptualized as a linear progression, where one skill builds directly upon another. Dynamic Learning Maps, however, present a more intricate view of learning as a dynamic landscape. This system visualizes a network of learning targets, recognizing that multiple skills are interconnected and related to numerous other skills. This shift in perspective acknowledges that learning is not a monolithic process but rather a complex web of interconnected knowledge and abilities.

The fundamental principle behind DLM is the understanding that there isn't a single, prescribed path to mastering a skill. Instead, it highlights multiple learning pathways, allowing for the recognition that students can achieve the same learning outcomes through diverse methods. This approach is crucial for students with significant cognitive disabilities, who may demonstrate their understanding and mastery in ways that differ from their peers.

The Dynamic Learning Maps System Explained

The DLM system is meticulously designed to map a student’s learning. This mapping is achieved through the integration of items and tasks that are embedded within the day-to-day instructional activities of students. A learning map, in essence, is a network of sequenced learning targets. The "dynamic" aspect of these maps signifies their ability to illustrate a learning landscape where multiple skills are related to many other skills, thereby showcasing not only the relationships between these skills but also the multiplicity of learning pathways available to students.

Essential Elements and Linkage Levels: Deconstructing Mastery

At the heart of the DLM system are the Essential Elements (EEs). These are alternative standards developed for students with special needs, specifically those with significant cognitive disabilities. For each Essential Element, there are skills organized into five distinct linkage levels: Initial Precursor, Distal Precursor, Proximal Precursor, Target, and Successor. These linkage levels progressively increase in rigor, starting from the Initial Precursor level and advancing to the highest level, Successor.

Read also: DLM Educator Portal Resources

The "Target" level is particularly significant as it represents the grade-level expectation for all students with significant cognitive disabilities. The DLM has developed comprehensive documentation that details the skills found within each linkage level in relation to the grade-level Essential Elements. This detailed mapping allows educators to pinpoint a student's current level of understanding and identify appropriate next steps for instruction.

The DLM assessment results are not derived from raw or scale scores. Instead, they are calculated using a sophisticated approach known as diagnostic classification modeling, or cognitive diagnostic modeling. This methodology is designed to determine whether a student has demonstrated mastery of specific skills. Based on the evidence gathered from the DLM assessments, a determination is made for each Essential Element tested: the student either mastered the skill or did not master it. For each Essential Element, a student may master up to five skills at different linkage levels. Consequently, a student’s overall performance in a subject is determined by the number of linkage levels mastered across all tested Essential Elements.

The "1% of 1%" and the Purpose of DLM

A critical aspect of the DLM is its intended population: students with the most significant cognitive disabilities for whom general state assessments, even with accommodations, are not appropriate. This aligns with federal requirements, such as the Every Student Succeeds Act (ESSA), which mandates that no more than 1% of students may participate in an alternate assessment in the grades assessed for each content area. This cap, effective from the 2017-2018 school year, signifies that DLM is reserved for a very specific group of students - those with the most complex needs. States exceeding this 1% may need to seek waivers from the U.S. Department of Education.

The DLM Alternate Assessment System serves multiple purposes. It helps educators facilitate student success by illustrating the intricate relationships among the knowledge, skills, and understandings necessary to meet academic content standards within the learning map model. This model plots individual concepts as nodes, with connections between these nodes illustrating the diverse ways students' knowledge, skills, and understandings develop over time. By using this model, educators can identify potential reasons why a student might be struggling with a particular concept and discover possible pathways for them to expand their knowledge and skills.

DLM Assessments: Structure and Administration

Dynamic Learning Maps assessments are developed through a rigorous, cyclical, and multi-step process. The assessments are delivered in short, instructionally relevant groups of items called "testlets," which share a common context. These testlets are developed using principles of evidence-centered design by subject-matter experts who also possess expertise in instructing students with significant cognitive disabilities.

Read also: A Guide to Dynamic Learning

Test items undergo multiple rounds of review by DLM staff, editors, and educators from DLM partner states. These reviewers are carefully trained to identify potential issues related to academic content, accessibility, and any potentially sensitive topics within the items. After review, testlets are field-tested in DLM states, and only those that meet specific standards are included in the final DLM assessments.

DLM assessments are administered online through the Kite® Student Portal. Two primary models of the assessment are available: Instructionally Embedded (IE) or Year-End (YE). The choice of model, as well as the subjects and grades to be assessed, is determined by the individual state. Regardless of the model, the assessment is composed of a series of testlets.

Instructionally Embedded (IE) Model

The IE model features two assessment windows: fall and spring. In this model, educators have a degree of choice regarding which English language arts (ELA) and mathematics Essential Elements are taught and assessed. Accountability scores are derived from students' cumulative ELA and mathematics assessment results throughout the year. This model allows for ongoing monitoring and adjustment of instruction based on student progress.

Year-End (YE) Model

The YE model has a single assessment window in the spring. In this model, all students within a particular grade are assessed on the same ELA and mathematics Essential Elements. The Kite system delivers testlets sequentially, adapting the linkage level of each testlet based on the student's performance on the preceding testlet. While educators may have the option to use instructionally embedded assessments prior to the spring assessment, the scores used for accountability are exclusively based on the spring assessment.

For science assessments, regardless of the model used for ELA and mathematics, states are typically required to administer them only in the spring. The science assessment is generally delivered in a manner similar to the YE model.

Read also: Inside Dynamic Prep's Tuition Program

Accessibility and Support: Ensuring Every Student Can Show What They Know

A cornerstone of the DLM assessment system is its commitment to accessibility. The assessments are designed to maximize accessibility for students with significant cognitive disabilities, offering multiple ways for them to demonstrate their knowledge, skills, and understandings. This design incorporates current research on communication, including the DLM core vocabulary - a list of words deemed highly useful for both social and academic communication.

Furthermore, educators from DLM partner states review the assessments at various stages of development, helping to minimize potential barriers for students with specific needs. Students taking DLM assessments have access to unique accessibility tools and supports that cater to their individual needs and preferences. Some of these tools are integrated into the online assessment system, while others are provided by the teacher. The selection of necessary tools and supports is a collaborative decision made by educators and Individualized Education Program (IEP) teams.

The DLM Accessibility Manual provides detailed guidance on the selection and use of these accessibility features, with a comprehensive list of available tools and supports often found in appendices.

Data Interpretation and Programmatic Insights

DLM results are typically provided to state departments of education and then loaded into data portals, such as WISEdash for Districts, for broader access and analysis. These portals allow users to compare student performance across different schools and districts. For example, the performance dashboard enables users to compare the percentage of students performing at each performance level within a school or district. By filtering data by a full academic year and focusing on "At Target" and "Advanced" levels, stakeholders can gain insights into school and/or district success in specific grades and prior grades.

Users can also utilize these dashboards to compare the percentage of students within specific demographic groups performing at the "At Target" or "Advanced" levels across different schools within a district. This granular level of data analysis can help identify achievement gaps and inform targeted interventions. Additionally, the dashboard can be used to quickly identify students performing within a specific range at a particular school or grade level, facilitating personalized support.

It's important to note that DLM results are provided for students in grades 3 through 11. Data presented in systems like WISEdash is gathered from various collections throughout the year, with districts and schools updating student information. Some records may be reported as "unknown" due to matching challenges in the data loading process. Additionally, a "No DLM" category exists to represent students who were enrolled by a specific count date but were not tested with DLM.

Resources and Further Exploration

The DLM consortium, comprised of 20 states plus the District of Columbia, offers a wealth of resources for educators, parents, and students. Even for states not part of the consortium, valuable resources are available. Essential Elements Linkage Maps, for instance, are available for each of the DLM standards, defining the target standard and providing precursor skills for students who have not yet reached the target level. These maps serve as mini-maps derived from the larger learning map model, offering a visual representation of the progression of skills.

For educators, the professional development site, managed by partners at the University of North Carolina at Chapel Hill, provides over 50 instructional modules and other resources. These include books to read with children, writing tools for students with physical limitations, and communication supports for those struggling with verbal expression.

Parent interpretive guides are also available, tailored to specific assessment models (Instructionally Embedded or Year-End) and content areas (ELA, math, science). These guides help parents understand their child's DLM assessment results and individual student reports, fostering a collaborative approach to supporting student learning.

Released testlets, which are examples of actual testlets students might encounter, are also provided. These released testlets showcase the same rigor, design, and quality as current DLM testlets and offer a glimpse into what students see on-screen during the assessment.

tags: #dynamic #learning #maps #explained

Popular posts: