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SCIENCE INSTRUCTION FOR STUDENTS WITH DISABILITIES: CURRENT BEST PRACTICES AND FUTURE DIRECTIONS William J. Therrien, Ph.D. University of Iowa The research reported here was supported by the Institute of Education Sciences, U.S. Department of Education, through Grant R305B10005 to The University of Iowa. The opinions expressed are those of the authors and do not represent views of the Institute or the U.S. Department of Education.
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Overview of Talk State of science achievement for students with LD/EBD Meta-analyses Current Best Practices Inquiry Instruction Random Control Trial of the Science Writing Heuristic Future Directions
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Why should we care about science achievement? Tremendous job growth in STEM fields STEM fields pay on average 70% more than overall U.S. mean salary Even lowest paying STEM jobs pay livable wages Skills Critical thinking, problem solving Writing (technical), reading, math Potential to be reinforcing
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U.S. Science Achievement Only 29% of students scored at or above level 4 in science proficiency on the Program for International Student Assessment (PISA, 2009). One third of students in 4 th, 8 th and 12 th grades scored at proficient level on the NAEP (National Center for Education Statistics, 2011). Students with disabilities scored significantly below their peers
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Why do students with disabilities have difficulty in science? Language- receptive and expressive (Scruggs & Mastropieri, 1993). Core academic skills- reading, writing, math (Parmar, Deluca, & Janczak, 1994; Shepard & Adjogah, 1994; Steele, 2004). Knowledge acquistion and retention (Swanson & Sáez, 2003) Behavioral problems ( Cutting & Denckla, 2003).
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SCIENCE META-ANALYSES (Therrien, et al., 2011& Therrien et al., in prep)
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Meta-Analysis Examine effective classroom science instruction for students with LD and EBD Core Questions What classroom based instructional methods are effective at increasing science achievement? What dependent measure(s) are represented by the effect size(s) reported?
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Method Studies must have published in peer review journals 1980 or later focused on classroom based interventions Been experimental or quasi-experimental (also included single subject studies in EBD meta-analysis) Included school aged subjects with LD or EBD
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Method continued Total of 12 studies found in LD literature base 4 structured inquiry 4 mnemonic instruction 4 supplemental non-mnemonic Total of 11 studies found in EBD literature base 4 structured inquiry 2 mnemonic instruction 5 supplemental non-mnemonic
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Overall Results- LD
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Overall Results- EBD
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Instructional Approaches Structured inquiry LD ES=.727 EBD ES=.727 Core Instructional components Pre-teaching Focus on overall concepts Hands on experiences with extra supports Formative feedback (science process and content knowledge)
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Instructional Approaches Mnemonic LD ES= 1.997 EBD ES= 1.8 Keyword/pegword Powerful at improving students acquisition and retention of science facts
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Instructional Approaches Supplemental- other LD ES=.422 EBD ES=.350 Example interventions within this category Peer-assisted learning (Mastropieri et al., 2006) Pullout explicit instruction on science concepts and the scientific method (McCleery & Tindal, 1999) Teacher provided or student generated explanation (e.g., a frog’s eggs sink so they can’t be eaten by predators) for science facts (Scruggs, et al., 1994)
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Dependent Measures Majority were immediate assessment measures of science knowledge of skill acquisition Only a few delayed measures or generalization measures Non-academic measures Only 1 EBD group study included a measure of student behavior (ES=.08)
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Emerging Best Practices Attend to background knowledge (misconceptions) Focus on big ideas Explicit/ strategy instruction Structured inquiry with supports Formative feedback Supplemental instruction for science inquiry and content But…. still a lot to study
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INQUIRY INSTRUCTION
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Inquiry Instruction Shift to inquiry approaches over the last 25 years National Science Foundation, National Research Council and American Association for the Advancement of Science all advocate for an Inquiry approach to science instruction
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Inquiry Instruction So what does that mean exactly?
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Inquiry Instruction (Minner, 2010) Inquiry used in 3 ways: (1)what scientist do, (2) how students learn and (3) how teachers teach Inquiry science instruction can be characterized as having three aspects (1) the presence of science content, (2) student engagement with science content, and (3) student responsibility for learning, student active thinking, or student motivation within at least one component of instruction—question, design, data, conclusion, or communication.
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Inquiry instruction VERY broad definition Some view it more as a philosophy than a concrete teaching approach Often emphasizes process over content Has been criticized by others outside the field of science education for having no clear and replicable definition(Klahr, 2005) Overall ranges from pure discovery learning to structured, teacher directed with hands on material
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SCIENCE WRITING HEURISTIC: RANDOM CONTROL TRIAL (Hand & Keys, 1999)
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Student Template 1 Beginning ideas What are my questions? 2 TestsWhat did I do? 3 ObservationsWhat did I see? 4 ClaimsWhat can I claim? 5 EvidenceHow do I know? How can I support my claim? 6 ReadingHow do my ideas compare with other ideas? 7 ReflectionHow have my ideas changed? 8 WritingWhat is the best explanation to describe what I have learned? Teacher Template 1Exploration of pre-instruction understanding through individual or group concept mapping or working through a computer simulation. 2Pre-laboratory activities, including informal writing, making observations, brainstorming, and posing questions. 3Participation in laboratory activity. 4Negotiation phase I - writing personal meanings for laboratory activity. 5Negotiation phase II - sharing and comparing data interpretations in small groups. 6Negotiation phase III - comparing science ideas to textbooks for other printed resources. 7Negotiation phase IV - individual reflection and writing. 8Exploration of post-instruction understanding through concept mapping, group discussion, or writing a clear explanation.
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SWH- Inclusion of elements of best practice Attend to background knowledge Focus on big ideas Semi-structured inquiry with supports Formative feedback
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Sample and Setting Setting: Participating schools are located in urban, suburban, and rural districts in Iowa. Population: Students and their teachers in Grades 3 to 5 All students with special education needs included 48 elementary schools Dependent Measures Iowa Test of Basic Skills (ITBS) – Math, Reading, Science, plus subscales Cornell Critical Thinking Test (CTT) – Overall scores plus subscales
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Research Design and Methods Block-randomized design 48 elementary schools (24 treatment; 24 control) Treatment: SWH approach in science instruction Professional Development: 7 days – summer, 3 – school year Fidelity of implementation Two measures- Reformed Teacher Observation Protocol (RTOP) and Classroom Protocol of Effective Teaching (C-PET)
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PRELIMINARY RESULTS
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Cornell Critical Thinking Test 71 questions 4 subscales Induction: Looking for patterns or regularities Deduction: Identifying various instances of rules and laws. Observation and credibility: Judging whether an observation statement is reliable. Assumptions: Identifying assumptions in a given line of reasoning.
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Cornell Critical Thinking Test Results Overall Comparing Treatment (SWH) vs. Control Two-sample t-tests conducted on the 5 th grade CCT data SWH students (n=1,154) had significantly higher gains overall (p=.002), compared to control students (n=882)
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Comparing Treatment (SWH) vs. Control Two-sample t-tests conducted on the 5 th grade CCT data SWH students (n=1,154) had significantly higher gains in levels of induction (p=.010) compared to control students (n=882) Cornell Critical Thinking Test Results Induction
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Comparing Treatment (SWH) vs. Control Two-sample t-tests conducted on the 5 th grade CCT data SWH students (n=1,154), compared to control students (n=882), had significantly higher gains on deduction (p=.004) C ornell Critical Thinking Test Results Deduction
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However…. How about taking into account the clustered nature of the data? Initial modeling indicates overall results significant But what is the magnitude of the effect? Cohen’s d=.16 And then how about students with special needs? Well what do you think?
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FUTURE DIRECTIONS
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Future Directions RCT Last year of data collection Multilevel models, with students at Level 1, classrooms (i.e., teacher) at Level 2, and possibly building/district at Level 3 Conduct another RCT in a more diverse setting
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Future Directions Continued Special Education Development of instructional protocols and supports for students with special needs in science instruction
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Initial Support Model
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Core Instructional components Reject notion that we can’t address both process and content Instructional components will be based on component analyses from meta-analyses and;
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Core Instructional components What we know about effective instruction Combined strategy instruction and explicit instruction approach (Swanson, 1998, 1999, 2000, 2001): Segmentation (breaking tasks down) Graphic organizers Practice and review Directed questioning Controlling difficulty Small groupings and teacher interaction Strategy cues Formative feedback/ assessment (Black and Wiliam 2004) Opportunities to learn/ ALT
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Bill Therrien, University of Iowa, bill-therrien@uiowa.edubill-therrien@uiowa.edu Science Instruction for Students with Disabilities: Current Best Practices and Future Directions
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