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.
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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
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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).