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Examining Hypermedia as a Means to Improve Access to the General Education Curriculum for Students with Reading Difficul

Examining Hypermedia as a Means to Improve Access to the General Education Curriculum for Students with Reading Difficulties. Dr. Matthew T. Marino Washington State University 2007. Overview. Context for this investigation Students with LD in reading and poor readers

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Examining Hypermedia as a Means to Improve Access to the General Education Curriculum for Students with Reading Difficul

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  1. Examining Hypermedia as a Means to Improve Access to the General Education Curriculum for Students with Reading Difficulties Dr. Matthew T. Marino Washington State University 2007

  2. Overview • Context for this investigation • Students with LD in reading and poor readers • Adolescents and expository texts • Barriers to the accommodations process • Improving reading comprehension • Technology in education • Can hypermedia improve access to the general education curriculum? • Current Research

  3. Students with Learning Disabilities (LD) • Students with LD comprise the largest subgroup of students served under IDEA (U.S. Department of Education, 2002) • The number of students age 12 to 17 identified with LD has increased 44% in the past 10 years (Lyon et al, 2001) • Only 62% of students with LD graduate with a diploma (U.S. Department of Education, 2002) • Educational costs for students with LD are 1.6 times that of regular education students (Special Education Expenditure Project [SEEP], 2003) • Students served under IDEA must be provided with access to the general education curriculum to the greatest extent possible(IDEA, 1997) Review of Literature

  4. LD Identification Process & Implications • IQ-achievement discrepancy identification is changing • LD in reading defined • IQ does not strongly correlate with reading achievement or rate of reading development(Share, McGee, & Silva, 1989; Vellutino, Scanlon, & Lyon, 2000) • IQ does not predict a student’s ability to read or profit from remediation(Siegel, 1988; Vellutino et al., 2000) Review of Literature

  5. LD in Reading and Poor Readers • Poor readers defined (Vellutino et al., 2000) • Poor readers show many of the same characteristics as students with LD in reading (Fletcher et al., 1994; Stanovich and Siegel, 1994) • Students with LD in reading and poor readers possess virtually indistinguishable reading growth curves in grades 1 through 12 (Vellutino et al., 2000) • For the purposes of this study, students with LD in reading will be combined with poor readers and referred to as students with reading difficulties (RD) • Students with RD in this study scored below the 25% on standardized measures of reading achievement during the academic year prior to this study. Review of Literature

  6. Statement of the Problem • More than 12.4 million students experience significant difficulties learning to read(National Center on Educational Statistics, 2003). • Students with RD are failing to make adequate yearly progress in the general education curriculum(Lyon et al., 2001; Mastropieri, Scruggs, & Graetz, 2003; U.S. Department of Education, 2003). • Traditional methods of instruction (e.g., lectures based on readings in expository texts) are not effective for students with RD(Lapp, Flood, & Ranck-Buhr, 1995; Maccinin, Gagnon, & Hughes, 2002). • The number of students with RD in inclusive classrooms is increasing(Lyon et al. 2001). Review of Literature

  7. Expository text defined Students with RD… Often lack prior knowledge (Gersten, Fuchs, Williams, & Baker, 2001) Are unaware of the text structures they are reading(Meyer, Brandt, & Bluth, 1980) Retrieve information randomly (Wilson & Rupley, 1997) Have difficulty determining essential information (Engert & Thomas, 1987) Do not utilize text cues (Gersten et al, 2001) Fail to recognize when they are not comprehending new information (Gersten et al., 2001) Adolescents and Expository Texts Review of Literature

  8. This Leads To… • Low levels of reading comprehension(Gersten et at., 2001) • An inability to formulate questions and hypotheses(Wilson & Rupley, 1997) • Failure to make abstract connections(Engert & Thomas, 1987) • Frustration, lower motivation, expected failure(McKinney, Osborne, & Schulte, 1993) What do we do for these students? Review of Literature

  9. Barriers to the Accommodations Process • Teachers at the secondary level feel pressured to progress through the curriculum (Mastropieri, Scruggs, & Graetz, 2003) • Teachers’ ability to provide meaningful accommodations is hampered by large class sizes and a lack of resources (Lancaster, Schumaker, & Deshler, 2002) • Many general education teachers do not have the time or expertise to provide meaningful accommodations (Mastropieri et al., 2003) How can we improve this process? Review of Literature

  10. Improving Reading Comprehension • Modify instructional materials to match the student’s reading ability(Mastropieri & Scruggs, 2004) • Present information using multiple modalities(MacArthor, Ferretti, Okolo, & Cavalier, 2001) • Offer repeated reading and practice opportunities(Jenkins, Stein, & Wysocki, 1984; Bryant, 2003) • Provide students with opportunities to gain additional background knowledge quickly (MacArthor et al., 2001) How can we do this? Review of Literature

  11. Consider Technology • Current policy calls for the increased use of technology to support student learning(U.S. Department of Education, 2003) • Technology use in regular education classrooms is rapidly increasing(U.S. Department of Education, 2003; Vannatta & O’Bannon, 2002 ) • Technology may improve access to the general education curriculum(Pucket, 2004; Behrmann & Jerome, 2002; Edyburn, 2002; Fisher & Frey, 2001) • Technology should be used in concert with other instructional methods (e.g., classroom discourse)(Yerrick, 2000; De La Paz & MacArthor, 2003; Fuchs, Fuchs, & Kazdan, 1999) Review of Literature

  12. Can Technology Improve Access to the General Education Curriculum? • Hypermedia defined • Hypermedia may eliminate the overuse of expository texts(Lancaster et al., 2002) Hypermedia provides: • Information on demand(McKenna, Reinking, Labbo, & Keiffer, 1999) • Tools that support cognitive processes(Lajoie, 1993) • Built-in accommodations by allowing teachers to modify task difficulty and select appropriate readability levels(Edyburn, 2000; Behrmann & Jerome, 2002; Pucket, 2004) Review of Literature

  13. Hypermedia Research • Hypermedia allows teachers to monitor student progress and resource use (McKenna et al., 1999) • Students and teachers report positive outcomes from using hypermedia (Lancaster et al.,, 2002; Garthwait, 2004; Lewis, 2000) • There are a limited number of studies examining the efficacy of hypermedia as a means of improving comprehension for students with RD (Maccini, Gagnon, & Hughes, 2002) • Research with students in regular education classrooms is promising, but inconclusive (Oliver, 1999; Land, 2000; Liu, 2004) Review of Literature

  14. Need for Current Research • Preliminary research examining the effects of technology-based textual modifications (e.g., readability levels within hypermedia programs) is inconclusive (MacArthur et al., 2001). • Research is needed to determine the types of comprehension instruction that are most beneficial for low ability readers in secondary content area courses (Report of the National Reading Panel, 2000). • Additional research is needed to determine which cognitive tools are most beneficial to students with RD in middle school science classes (Liu, 2004). Review of Literature

  15. Theoretical framework • Knowledge Construction Through Conceptual Change (KCTCC) expands on the theory of Schema Change(Winn, 2004). • Perpetual cycle of learning where prior knowledge directs how individuals seek, identify, and interpret information(Neisser, 1976). • The way in which individuals construct knowledge can not be predicted or supported using teacher directed instructional designs(Duffy & Jonassen, 1992). • KCTCC is most effective in problem-based learning environments that incorporate technology(Winn, 2004). Review of Literature

  16. Universal Design for Learning (UDL) UDL supports KCTCC by: • Assuming students enter learning experiences with varying degrees of prior knowledge (Hitchcock, Meyer, Rose, & Jackson, 2002). • Using technology to incorporate video clips, graphic organizers, illustrations, and text modifications into the curriculum (Mastropieri, Scruggs, Bakken, & Whedon, 1996). • Allowing learners to access information quickly using multiple modalities (MacArthur, Ferretti, Okolo, & Cavalier, 2001). Review of Literature

  17. Why Middle School Science? • Science is one of the most difficult subjects for students with RD to learn due to its complex vocabulary and theoretical nature (Mastropieri et al., 2003). • Students with RD in middle school science classes typically read at the 4th or 5th grade level (Mastropieri et al., 2003). • If textual modifications and cognitive tools can improve access to the middle school science curriculum, their application in other content areas may yield similar results. Review of Literature

  18. * Research Purpose Statement of the research problem: • There is a need to determine whether hypermedia can improve access to the general education curriculum for students with RD and low ability readers (Lyon and Moats, 1997; MacArthur et al., 2001; National Reading Panel, 2000). For the purposes of this study: • Low ability readers are defined as students scoring < 50% on the Degrees of Reading Power (DRP) subtest of the Connecticut Mastery Test. The DRP is a norm-referenced measure of reading achievement(Touchstone Applied Science Associates, 2004). • Students with reading difficulties (RD) are defined as scoring < 25% on the DRP. Research Questions

  19. * Research Questions • Are there posttest differences on the science posttest and solutions forms measure between students with RD (<25th percentile) and those who are not RD (25th - 50th percentile)? • Are there posttest differences on the science posttest and solution forms measure between students who participated in the 4th grade readability condition and those who participated in the 8th grade readability condition? • Is there an interaction between reading ability (i.e., students <25th percentile and students in the 26th - 50th percentile) and treatment condition (4th grade readability and 8th grade readability)? If so, what is the nature of the interaction? • Is there a relationship between students’ reading ability, use of cognitive tools, and their comprehension of scientific concepts and processes as measured on the posttest and solutions form measure? If so, what is the nature of the relationship? Research Questions

  20. * Research Design Methods Design

  21. * Threats to Validity Methods Design

  22. * Setting • Four middle schools in New England volunteered to participate in the study • Schools were selected based on: 1) administrative consent, 2) 100% teacher agreement to participate, and 3) available technology resources Setting & Participants

  23. * Student Demographic Data • 50% male, 50% female • 87% White, 5% African American, 4% Asian, 4% Hispanic • 89% have a computer at home they can use • 54% have a personal computer Response to the statement: “I am good at using computers” 32% strongly agree 62% agree 5% disagree 1% strongly disagree Setting & Participants

  24. * Participants • Students (N = 1153) were grouped based on 2004 DRP scores • Group 1 - Students with RD ( < 25% on DRP) • Group 2 - Poor readers (26 - 50% on DRP) • Group 3 - Proficient readers ( > 50% on DRP) • Students from groups 1 (n = 113) and 2 (n = 189) were randomly assigned at the student level within each class to either the 4th grade readability or 8th grade readability condition. • Students in group 3 (n = 851) received text from the program at the 8th grade level Setting & Participants

  25. * The Intervention: Alien Rescue Instrumentation

  26. Pre/Posttest 25 item paper & pencil multiple choice test Reliability of .85 established in previous study (Pedersen & Williams, 2004) 19 items assess knowledge and comprehension (e.g., A world would have a magnetic field if________ ) 6 items assess students’ ability to apply knowledge (e.g., Scientist want to measure Mars’ atmosphere. What instrument would they use ______ ?) Six solution forms One paper and pencil solution form for each alien species Two column form that requires students to analyze, synthesize, and evaluate data from the Alien Rescue program Scaffolds the learning process through prompts (e.g., magnetic field) Contains open-ended and narrative response items Piloted with 300 students (Marino, 2005) Established inter-rater reliability of .90 * Performance Measures Instrumentation

  27. * Procedures Methods

  28. * Preliminary Analyses • Students who were absent more than 3 days (20%) of the intervention were excluded from analyses. • Independent samples t-test results, t (302) = 1.22, p =.22, d = .01 indicated that there were no significant differences (DRP group 1 vs. 2) on the pretest measure. • Principal component factor analysis of posttest measures (posttest & solutions forms) indicates 68% of variability was explained by posttest. • Solutions forms grouped into one subscale (total score) with one factor solution reliability of .94. Analysis

  29. * Analysis: Research questions 1 - 3 • Compute descriptive statistics • Separate two-way ANOVA’s • DRP group (DRP group 1 vs. DRP group 2) and treatment condition (4th grade text vs. 8th grade text) as between-subjects independent variables. Posttest and combined solutions forms scores (total score) as dependent variables. Analysis & Results

  30. * Results: Research Questions 1 - 3 RQ1: Differences by DRP group • Results of the ANOVA for the posttest were not significant F (1, 298) = 3.552, p = .060, d = 0.01 • Results of the ANOVA for total score were significant F (1, 281) = 3.974, p = .047, d = 0.01 RQ2: Differences by treatment (4th vs. 8th grade text) • Results of the ANOVA for the posttest were not significant F (1, 298) = 0.369, p = .554, d =.001. • Results of the ANOVA for total score were not significant F (1, 281) = 0.03, p = .872, d < .001. RQ3: Interaction between treatment and DRP group • Results of the ANOVA for posttest were not significant F (1, 298) = 2.56, p = .111, d = .008 • Results of the ANOVA for total score were not significant F (1, 281) = 1.28, p = .259, d = .004 Results

  31. * Student Learning • Paired samples t-test (pre/posttest) with DRP groups collapsed was significant (t = 25.719, p < .001, d = 1.5) • Posttest mean was 14.22 (56%) on a 25-point scale On Solutions Forms (216-point scale) • DRP 1 mean score 142.05 (66%) • DRP 2 mean score 151.77 (70%) Did they use the built-in cognitive tools? Results

  32. * Analysis Research Question 4 • Group cognitive tools into four categories (Lajoie, 1993; Liu, 2004; Liu & Bera, 2005) • Tools that share cognitive overload (e.g., databases) • Tools that support cognitive process (e.g., field journal) • Tools that support out-of-reach activities (e.g., astroengineering) • Tools that support hypothesis testing (e.g., telemetry) • Obtain correlations between students’ use of tools and performance on posttest and total score • Separate one-way ANOVAs with tool use category as the dependent variable and DRP group as independent variable. • Simultaneous multiple linear regression analysis to determine how tool use (by category) predicts performance on posttest and total score measures Analysis & Results

  33. * Results Research Question 4 • The strongest correlation was between tools that share cognitive overload and the posttest (r = .224). • ANOVA (tool use DV, DRP IV) was significant for each of the four tool categories. Cog. overload F (2, 954) = 12.60, p < .001, d = .03 Cog. process F (2, 954) = 4.86, p = .008, d = .01 Out-of-reach F (2, 954) = 3.07, p = .047, d = .006 Hypothesis F (2, 954) = 5.57, p = .004, d = .01 • Scheffe’s post hoc analysis indicates significant differences between students by DRP groups Analysis & Results

  34. * Results of Multiple Regression - RQ4 • Multiple regression indicates main effects for tools that share cognitive overload and tools that support out-of-reach activities on posttest scores. • A significant interaction between DRP group and tools that support cognitive overload was present on the posttest regression analysis. • A significant interaction between DRP group and hypothesis testing was present on the solution form regression analysis. What does this tell us? Analysis & Results

  35. * Interpreting the Multiple Regression Analysis On the Posttest Regression Analysis: For every unit increase in the SQRT of cognitive overload • We predict a .792 unit increase in posttest score for students in DRP groups 1 & 2. • We predict a .33 unit increase for students in DRP group 3. For every unit increase in the SQRT of tools that support out-of-reach activities students’ scores on the posttest decrease by .674 units. On the Solutions Form Regression Analysis: • Students in DRP 3 gained 7.886 units for each unit gain using tools that support hypothesis testing. • Students in DRP groups 1 & 2 gained 1.264 units for each unit gain using tools that support hypothesis testing. Analysis & Results

  36. * Discussion • Students in DRP groups 1 and 2 (<50%) performed in similar ways during the intervention. • There was a lack of treatment effect due to readability level of text. • Students used cognitive tools differently depending on their reading ability level. Discussion

  37. * Implications • Students need systematic, explicit, scaffolded instruction to utilize cognitive tools(Gersten & Baker, 1998) • Opportunities for students to reflect on and have immediate feedback regarding tool use(Swanson & Hoskyn, 1998) • Inclusion of tools that support cognitive overload and out-of-reach activities(Land, 2000; Liu, 2004; Williams & Peterson, 2004) • Technology and content area training for special education teachers(Sharpe & Hawes, 2003) • Increased collaboration between special education and regular education teachers(Moore & Keefe, 2001) • Improved instructional strategies for general education teachers(Washburn-Moses, 2005) Implications

  38. * Limitations • Paper and pencil assessments • Levels and types of classroom discourse • Tool use data highly skewed • Student differences with problem-based learning • Sample (SES, representation of minority populations) • Teacher effects Limitations

  39. * Questions?

  40. Links • Descriptives by DRP group • Descriptives by Treatment Condition • Two-Way ANOVA Posttest • Two-Way ANOVA Total Score • Tool Category Correlations • Posttest Multiple Regression • Total Score Multiple Regression • Scheffe’s Post Hoc for Tool Use • Threats to Validity • Cell sizes for low ability readers • Teacher Effects • Research Questions

  41. * Descriptive Statistics by Reading Ability Maximum Posttest Score = 25 Maximum Total Score = 216 RQ 1 -3 Results

  42. * Descriptive Statistics by Treatment Condition Maximum Posttest Score = 25 Maximum Total Score = 216 RQ 1 - 3 Results

  43. * Posttest Two-Way ANOVA RQ 1 -3 Results

  44. * Total Score Two-Way ANOVA RQ 1 - 3 Results

  45. * Tool Category Correlations RQ 4 Results

  46. * Scheffe’s Post Hoc Analysis for Tool Use RQ 4 Results

  47. * Multiple Regression Posttest MR 4 Results

  48. * Multiple Regression Total Score MR 4 Results

  49. * Teacher Effects Results of one-way ANOVA with posttest and solution form scores as dependent variables and Teacher as the independent variable were significant. Posttest F (15, 1190) = 16.131, p < .001, d = 0.17 Solutions Forms F (15, 1153) = 112.334, p < .001, d = .59 Results

  50. * Cell sizes for low ability readers Group 1 Group 2 Text presented at 4th grade level Text presented at 8th grade level Power analysis indicates optimum group sizes of 68 (f = .20, d = .57) to achieve a power of .80. Methods

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