Taming The Data Monster: Practical Data Collection and Analysis

Through case scenarios, this presentation will illustrate evidence-based tools for collecting data in the classroom. It will also share guidelines for analyzing data and discuss practical strategies and examples of making decisions about how to take and analyze data. Data collection is a mysterious entity for many professionals. In the age of increasing demand for accountability in schools and research that indicates that teachers who take data have improved outcomes for students, teachers report increasing pressure to produce data but frustration about efficient ways to collect and use it. They know they need to do it, but they really don’t know how to make sure they have the information they need. One of the most frequent concerns of teachers is trying to take data without having the collection process itself interfere with their instruction of the students. In addition, behavior analysts are tasked with basing decisions on data collected and are trained in a variety of data collection procedures that are both simple and intricate.  However, behavior analysts frequently do not have time to analyze all the data for a given classroom.  In addition, they often struggle with developing strategies for direct service providers, including teachers, that are easy to use while still providing accurate data.  As a result, educators often have data that is not analyzed, data that is taken inconsistently, or data that does not capture the true sample of performance of their students.   

Through the use of case studies and scenarios of classrooms and students, videos, visual examples and discussion, this presentation will focus on helping educators figure out how to integrate the guidelines for good data collection and analysis with practical tools for getting it done.  The presentation will include examples of data collection tools and strategies including paper and pencil as well as technology-based tools (e.g., apps), strategies for organization of materials and managing materials to track skills while working with students, and guidelines for taking data and methods for analyzing the data in an efficient manner to make decisions about students’ progress.  Guidelines for data collection and analysis will be based on research in the area of data collection with practical applications that can be used in classroom settings.  The examples shared are examples that have been used in a variety of types of classrooms and teachers have indicated they have been helpful in organizing their data collection and analysis process. 

This presentation will assist teachers and related service professionals in planning for and implementing data collection and analysis plans.  In addition, it will provide behavior analysts with strategies for assisting and training those involved in direct work with students with autism spectrum disorder through practical strategies that can integrated into instructional programs.  This presentation will help teachers to determine how to write goals that are data-friendly, select data collection strategies that are appropriate for the skill, and determine how much data is needed.  In addition, it will share strategies for the development of data analysis procedures that can be integrated into the practical considerations of educational programs.  Data collection forms for a variety of skills will be shared with the participants for their use in their own educational programs.