- Transitioning special populations
- Balancing new assessment systems within a state
“What role can learning models (LMs) play in improving assessment and instruction for all students, including special populations?” Sixty colloquium participants discussed this question, considering components of comprehensive assessment systems (formative, summative, interim). LMs have been proposed in developing both large-scale and classroom assessments. Assessments based on LMs promise to add value to current accountability models by measuring learners’ levels of understanding and revealing gaps in understanding that can inform instruction. This session highlights deliberations, identifies tensions between paradigms, and recommends next steps. Attendees will extend this conversation and weigh-in on efforts to advance inclusive instructionally-sensitive assessments for allstudents.
In October 2012, sixty educators, researchers, state consortia representatives, and assessment experts from throughout the US participated in a colloquium sponsored by a WestEd GSEG project’s dissemination event. At that time, the five consortia were designing and developing new assessment systems aligned to Common Core State Standards (CCSS). Comprehensive assessment systems are intended to inform instruction, however, CCSS do not describe the pathways along which students are expected to progress, nor do they address how the KSAs necessary for learning core concepts develop within and across grades. In other words, the CCSS describe what students are expected to know at the end of each grade, but not the learning pathways for typical learners or special student populations. Another question surfaced, “How might learning models and CCSS work together to support a robust instruction and assessment system that includes all students?”
Additionally, higher expectations are being established without benefit of clear models or agreed-upon practices for how best to support special student populations in meeting these expectations. Though limited, research suggests that some of these students may not follow the same learning pathways as more typical learners, because they may progress along pathways that differ across contexts and reflect inter- and intra-individual learning differences. They are more likely to progress along alternate or multiple pathways than their general education peers.
In terms of validity and effectiveness, models built from cognitive learning science have important implications for a) the design and development of comprehensive assessment systems, b) the inferences drawn from assessment results, and c) the instructional information gleaned from responses. To improve instruction and learning, research and theory-supported models of learning are needed “to identify the set of knowledge and skills that is important to measure for the task at hand, whether that be characterizing the competencies students have acquired thus far or guiding instruction to increase learning” (NRC, 2001). Without a clear understanding of how all students, including special population students, represent knowledge and develop competence, valid inferences about students’ thinking processes, including misconceptions, strengths, and abilities, and about how to effectively support student learning, are questionable.
An additional theme queried “What might a transition from the current accountability system to a comprehensive assessment system that informs instruction look like, particularly as it relates to special student populations?” For students with disabilities who receive special education there have been two alternatives for taking summative accountability assessments under IDEA: the regular assessment for all students or the Alternate Assessment based on Alternate Achievement Standards (1%). Several states also offered an Alternate Assessment based on Modified Achievement Standards (2%). These assessments provide test scores to determine Adequate Yearly Progress but do not provide tailored information to guide instructional decisions. A challenge for comprehensive assessment systems is that until now, summative assessments have not provided suitable information to support classroom-based instructional decisions for most students and particularly for special populations. At the same time, classroom (formative) assessment results have not been employed to aggregate scores up for school and district accountability purposes.