Association for Behavior Analysis International

Many schools, learning centers, and agencies find themselves awash in learner data, much of which is never analyzed or used to make immediate decisions about a learner’s program. The Morningside Model of Generative Instruction encourages efficient data collection, by emphasizing that the primary role of data should be to encourage timely and effective decision making. This symposium will describe how MMGI designers carefully select data to be collected, and how those data are organized to optimize decision making by learners, teachers, and school administrators. First, Austin Seabert, a consultant at The Performance Thinking Network, will describe the design and implementation of a revised progress monitoring system to facilitate quicker and more effective decisions by classroom teachers. Second, Morningside Academy’s School Psychologist and Vice-Principal, Julian Gire, will describe how MMGI’s placement testing and new progress monitoring assessment system were subsequently modified due to the COVID-19 pandemic. Next, Morningside Academy’s Associate Director, Andrew Kieta, will detail the development of a teacher coaching system informed by the data collected and analyzed via the new, modified progress monitoring system described in the first two talks. Lastly, Morningside Academy faculty member Bailee Scheuffele will describe the development of a new Curriculum Based Assessment (CBA) within the new progress monitoring system to assess emerging sentence-writing repertoires in order to make more-informed curriculum decisions.

Morningside Model of Generative Instruction features a multi-tiered assessment system. At the Micro level, Morningside teachers use Precision Teaching to collect daily measurements on several academic pinpoints. The Meta level consists of placement tests and progress monitoring tests to validate data at the Micro level, diagnose potential obstacles to desired growth, and predict performance on end of the year tests. Those end-of-the-year assessments make up the Macro level, where standardized, norm-referenced tests are used to evaluate student growth across an entire school year. Implementing this system requires timely assessment administration, clear communication of results to all relevant individuals, and most importantly, effective instructional decision making based on assessment data. This has proven particularly challenging at the Meta level, prompting a one year revision project. This presentation will describe a process improvement methodology involved with the creation of a new system, including: Defining the assessment problem, outlining features and capabilities of an ideal assessment system, identifying resource limitations, system design, testing and rollout, and feedback. Data will be presented that show how and why redesign decisions were made as well as their effect in improving MMGI’s assessment system.

The onset of the COVID-19 pandemic forced schools to figure out how to adequately serve their students in the on-line environment. While the disruption caused to instruction has been well documented, the challenges of remote assessment have received less attention. As the pandemic continues, schools must not only work to maintain student’s academic achievement but also to further it. However, how can student progress be assessed in the online learning environment? The Morningside Model of Generative Instruction details a multi-tiered system of assessment, which is made up of dozens of assessments across different subject matters, and which guide the placement of students and ongoing progress monitoring efforts. The most pressing problem is that all of these assessments and their associated protocols were designed to be administered in person, not online. This talk will outline the process of designing, implementing, and revising Morningside’s placement testing process and recently redesigned progress monitoring system to ensure the collection of the best data possible. The speaker will present lessons learned, as well as future use of the online assessments once we are back to in person school.