EDUCATIONAL BENEFIT: MODULE II Tonya Green February 26-27, 2012 Mississippi Department of Education • Gain understanding of Educational Benefit • Briefly consider the Requirements for Educational Benefit • Consider data sources to ensure Educational Benefit • Guidance on analyzing data for Educational Benefit The use of student data to improve instruction is a central tenet of current education policy (American Recovery and Reinvestment Act 2009). Various accountability mandates including those in ESEA stress the importance of data-informed decision making. Current efforts to improve school performance are calling on teachers to base their instructional decisions on data. More and more, teachers are expected to assess students frequently and to use a wide variety of assessment data in making decisions about their teaching (Hamilton et al. 2009; Schmoker 1996; U.S. Department of Education 2004). • Teacher knowledge and skills in putting data to use—that is, in identifying students’ specific needs and planning instruction tailored to those needs through a process known as a Multidisciplinary Team • Prepare written evaluation report (should be integrated multidisciplinary report) • Determine eligibility • Identify areas of strength and need, set goals, and determine appropriate services • Link goals directly to the IFSP, IEP, ITP, BIP • Continuous Progress Monitoring • Frequent Review/Revisions U.S. Department of Education, Office of Planning, Evaluation and Policy Development, Teachers’ Ability to Use Data to Inform Instruction: Challenges and Supports, Washington, D.C., 2011. “Coming together is a beginning; Learning together is progress; Working together is success.” Henry Ford • Find the relevant pieces of data in the data system or display available to them (data location) • Understand what the data signify (data comprehension) • Figure out what the data mean (data interpretation) • Select an instructional approach that addresses the situation identified through the data (instructional decision making) • Frame instructionally relevant questions that can be addressed by the data in the system (question posing) U.S. Department of Education, Office of Planning, Evaluation and Policy Development, Teachers’ Ability to Use Data to Inform Instruction: Challenges and Supports, Washington, D.C., 2011. • Universal screening data (e.g.,MAPS, DIBELS, iSTEEP, AIMSWEB) • State assessments (MCT2/SATP) • Classroom assessments (curriculum-based) • Eligibility data (current and related to learning the standards) • Behavioral assessments (discipline reports) • Vocational assessments (ICAP) • Progress monitoring (RTI, IEP) • Other information (e.g., grades and attendance reports) • Understand the value of subscale scores and item-level data • Utilize student data to plan differentiated instruction based on student needs • Synthesize multiple data sources to inform instructional practices • Use data to inform decisions about identification, eligibility, services, and instructional planning U.S. Department of Education, Office of Planning, Evaluation and Policy Development, Teachers’ Ability to Use Data to Inform Instruction: Challenges and Supports, Washington, D.C., 2011. • • • • Compare data to a verbal statement (APP/SPR-Self Assessment) Understand alignments of data to learning goals (Universal, CBM, Common Core Standards) Interpret progress monitoring through histograms ( a three year period) Distinguish between class and individual data to revise programming (unique need) Data should guide both instruction (academic and behavioral) as well as transition, at elementary, middle, and high school. National Joint Committee on Learning Disabilities; 2011 Vision ↔ Desired Outcome Insert Indicators here. • Provide infrastructure and resources for effective assessment • Provide leadership and logistical support to multidisciplinary assessment team members • Examine relationship between curriculum, standards, and accountability measure • Foster implementation of positive school practices based on research • Clarify that intra-individual differences occur as a pattern of strengths and weaknesses in performance and/or achievement within specific domains, such as behavior, cognition, communication, and academics • • • American Recovery and Reinvestment Act of 2009, S. 1, 111th Congress, 1st Session. (2009). Chen, E., M. Heritage, and J. Lee. (2005). Identifying and monitoring students’ learning needs with technology. Journal of Education for Students Placed At Risk, 10(3): 309 332. Elementary and Secondary Education Act of 2001, H.R. 1, 107th Congress. (2002).