Accessibility in Higher Education: Learning from Faculty Attitudes Ellen Perlow, Ph.D. CHES Doctoral Student, Special Education, Texas Woman’s University Faculty Sponsors: Michael Wiebe, Ph.D.; Mark Hamner, Ph.D. Texas Woman’s University Student Research Symposium Platform Session IV-C-ACT 601 Wednesday, April 23, 2008– 9-10:20 am http://www.a4access.org/twu2008.html http://www.a4access.org/twu2008.txt This document is available in alternative formats upon request. [slide 1] Accessibility in Higher Education: Learning from Faculty Attitudes Ellen Perlow, Ph.D. CHES Doctoral Student, Special Education, Texas Woman’s University Faculty Sponsors: Michael Wiebe, Ph.D.; Mark Hamner, Ph.D. Texas Woman’s University Student Research Symposium Platform Session IV-C ACT 601-Wednesday, April 23, 2008 – 9-10:20 am http://www.a4access.org/twu2008.html http://www.a4access.org/twu2008.txt This document is available in alternative formats upon request. [slide 2] Presentation Outline* *Please see Presentation Supplement for definition of terms, referenced legislation, and references. I. Research Purpose, Questions, Hypotheses II. Literature Review III. Research Methodology: Institutional Review Board, Participants, Instruments, Data Analysis IV. Results V. Conclusions, Future Research and Advocacy VI. Acknowledgments … Audience Questions [slide 3] Brief Definition of Terms* *Please see Presentation Supplement for more extensive definitions, referenced legislation, and cited references. 1. Accessibility: ability to access, state of being achievable, obtainable (Pickett… 2000) 2. Access Needs: From conception throughout the life course, living beings, by definition, require access to certain elements to sustain life… 3. People/Students with Access Needs = humans with such needs 4. Universal Design: “design of products and environments to be usable by all people, to the greatest extent possible, without the need for adaptation or specialized design. –Ron Mace” (North Carolina State University. Center for Universal Design, 2008) 5. Universal Design Principles: See Supplement, slide 7 (NCSU. CUD, 1997) 6. Universal Design for Learning: evidence-based framework that applies the principles of Universal Design to design and delivery of educational curricula (CAST, 2008a, 2008b, 2008c) 7. Assistive Technology: "Any aid, device or tool, compensatory strategy… that improves a person's functional capability.” (University of Kentucky , 2000?) 8. IDEA: "Individuals with Disabilities Education [Improvement] Act of 2004", P.L. 108-446 : http://idea.ed.gov/ 9. NCLB: "No Child Left Behind Act of 2001," P.L. 107-110: http://www.ed.gov/nclb/ *Please see Presentation Supplement for more extensive definitions, referenced legislation, and cited references. (University of Kentucky Interdisciplinary Human Development Institute, 2000 [slide 4] Research Purpose Via review of a pair of IRB-approved studies, demonstrate that, in the context of higher education: 1. Students with access needs, including veterans, diversity population of critical interest 2. Faculty attitudes critical to academic/career success of students [with access needs] (Dean and Camp, 1998; Fichten, 1988; Flores & Rodriguez, 2006; Hengst, 2004; Rao, 2004). 3. Faculty attitudes are key to campus culture of accessibility. 4. Accessibility, Universal Design for Learning are best practices for institutional effectiveness (Illinois Center for Information Technology Accessibility: http://www.cita.uiuc.edu/) [slide 5] Quantitative Research Questions A. Do postsecondary faculty attitudes toward access issues and students with access needs vary among different academic disciplines? B. Are there correlations between at least 2 of the following 5 variables that would help to explain these attitudes? 1. Experience/Knowledge 2. Negative Experience 3. Comfort Level 4. Confidence Level 5. Interest Level [slide 6] 1. There are no differences* between postsecondary faculty attitudes toward access issues/ people/students with access needs based on the faculty’s academic discipline. a. Statistically: Null Hypothesis: mu1 = mu2 = … mk b. Alternative Hypothesis: At least two differ.* 2. There is no correlation* between one or more pairs or combinations of 5 variables that help to explain faculty attitudes toward access issues. a. Statistically: Null Hypothesis: r = 0 (no correlations) b. Alternative Hypothesis: 1 or more correlations* exist. *alpha level = .05 [slide 7] Photograph of U.S. Army and Air Force service members caring for wounded troops. http://www.defenselink.mil/news/newsarticle.aspx?id=31234 (retrieved 4/23/2008). U.S. Casualties – Afghanistan/Iraq Wars: See: http://www.defenselink.mil/news/casualty.pdf Today, advances in science, medicine and technology have increased survival rates on wars' battlefields, despite acquisition of often complex and lifelong access needs (Gawande, 2004; U.S. Defense and Veterans Brain Injury Center, 2008; Tanielan and Jaycox, 2008; Warden, 2006). A moment for reflection. [slide 8] Literature Review 1. More than 30 years U.S.: Civil Rights for People with Access Needs: Section 504-Rehabilitation Act of 1973,as amended, 29 U.S.C. Section 794 2. More than 30 years U.S. public education - inclusion P.L.94-142 (1975) 3. IDEA 2004: Accessibility/Universal Design [for Learning] now the Law pre-K-12 -- IDEA 2004, P.L.108-446 Sec. 601; Federal Regulations: Sec. 300 et seq. -- IDEA-Mo Child Left Behind (NCLB) Alignment (http://idea.ed.gov http://www.ed.gov/nclb/ ) -- Texas Education Code, Ch. 89 (http://www.tea.state.tx.us/rules/tac/chapter089) -- Universal Design for Learning(IDEA Secs. 612, 674; Federal Regulations Section 300.160) -- Accessible instructional materials-NIMAS (Regulations Section 300.172 ) -- Assistive Technology provision (IDEA P.L. 108-446 Sec. 602) [slide 9] Graphic displays the equation: (Universal Design and Universal Design for Learning) added to Assistive Technology equals Accessibility. [slide 10] Literature Review (continued) Graph depicting increasing population and enrollment prevalence of students served under U.S. IDEA, 1976-2006, nationally and in Texas (U.S. Department of Education, Office for Special Education Programs [OSEP], 2007a) [slide 11] Literature Review (continued) Percentage of ages 6-21 served under IDEA rising (excerpted. and category labels modified, U.S. Department of Education OSEP, 2007b, page 66): Chart: percent of U.S. Population, Ages 6-21-All Access Needs 2001: 8.8 percent 2002 8.93 percent 2003: 9.05 percent 2004: 9.14 percent 2005: 9.15 percent percent of U.S. Population, Ages 6-21-Autism Spectrum 2001: 0.15 percent 2002 0.18 percent 2003: 0.21 percent 2004: 0.25 percent 2005: 0.29 percent percent of U.S. Population, Ages 6-21-Traumatic Brain Injury 2001: 0.03 percent 2002 0.03 percent 2003: 0.03 percent 2004: 0.03 percent 2005: 0.04 percent percent of U.S. Population, Ages 6-21-Developmental issues, ages 3 to 9: 2001: 0.07 percent 2002 0.09 percent 2003: 0.10 percent 2004: 0.11 percent 2005: 0.12 percent percent of U.S. Population, Ages 6-21-Other Health issues, including AD/HD: 2001: 0.52 percent 2002 0.59 percent 2003: 0.68 percent 2004: 0.77 percent 2005: 0.85 percent 2. Students served under IDEA also are high school graduates who become college applicants and enrollees: about 225,000 high school graduates under IDEA (2005/2006 data) (U.S. Department of Education Office for Special Education Programs [OSEP, 2007c) 3. Between 2006 and 2016, there will be an estimated 15 percent growth in the need for special education teachers (U.S. Department of Labor, 2007) [slide 12] Literature Review (continued) Access Issues/Special Education are Lifelong: Children Become Adults 1. There is a rising proportion of U.S. college students with access needs: From 1999 to 2003: For Undergraduates: An increase from 9 percent to 11 percent; For Graduate Students: An increase from 6.1 percent to 6.7 percent (Foss, 2002; Lewis and Farris, 1999; U.S. Department of Education, 2003; 2008). 2. An increasing number of older students are attending college (Gregg, Coleman, Davis, Lindstrom, and Hartwig, 2006; Kressley and Huebschmann, 2002; Silverstein, Choi, and Bulot, 2001) 3. An increasing U.S. population of older adults age 65 or older Graph from U.S. Department of Health and Human Services. Administration on Aging, 2008: showing rise in older adult age 65 or older U.S. population from 1900, projected to 2030. Just wait: that's all of us! Note: P.S. Aging changes and increases access needs (U.S. Centers for Disease Control and Prevention, 2003). [slide 13] Access Issues Universal Everyone Everywhere 4. People with access needs are 18 percent to 20 percent of the U.S. population and 10% of the World population (U.S. Census Bureau, 2006; United Nations, 2008) 5. Global aging, climate change, war/terrorism (Atchley, 2001; Bilmes and Stiglitz, 2006 ; Boyle and Cordero, 2005; Gawande, 2004; Gore, 2006; Tanielan and Jaycox, 2008; U.S. Defense and Veterans Brain Injury Center, 2008; U.S. Department of Defense, 2008a, 2008b; U.S. Department of Health and Human Services, Administration on Aging, 2008; World Health Organization, 2002) 6. Virtually everyone joins the class (Shapiro, 1994) 7. Accessibility is a boundary-free universal diversity issue, affecting all people throughout the world across all categories of diversity: age, gender, sexual orientation, ethnicity, class 8. September 11th, Katrina, Tsunami, Earthquakes, Darfur, famine, HIV/AIDS, violence, accidents, Afghanistan/Iraq ... [slide 14] Literature Review (continued) Accessibility in U.S. Higher Education Policies 1. "In September 2006, [U.S. Department of Education] Secretary Spellings announced her action plan to make higher education in the U.S. more accessible, affordable, and accountable." http://www.ed.gov/about/bdscomm/list/hiedfuture/plan/index.html 2. Secretary Spellings' Action Plan = September 2006 Final Report of the Spellings Commission on the Future of Higher Education http://www.ed.gov/about/bdscomm/list/hiedfuture/reports/final-report.pdf 3. Institutional Effectiveness, Accountability … Accreditation, Spellings Report sound familiar? See TWU website:http://www.twu.edu/iep/sacs/ 4. Texas Web Accessibility Policy: http://www.twu.edu/accessibility.asp 5. Pre-K-12(21) NCLB/IDEA now in Higher Education. [slide 15] Methodology: Institutional Review Board [IRB] / Participants 1. TWU Institutional Review Board [IRB]-approved studies 2. Informed consent to participate in research, to audiotape: age 18 or older, faculty member in discipline 3. Accessibility of research process: - Consent forms: standard, large print (IRB requires signature); alternative formats-read only - Other research documents: alt. formats available 4. Purposive samples, primarily U.S. higher education faculty - 2006-2007: Health Education/Public Health faculty (n=30) - 2007-present: Education/Library and Information Science (as of April 23, 2008: n=14) [slide 16] Participants: Recruitment 1. Recruitment: invitation via IRB-approved U.S.-based discussion lists and conferences frequented by higher education faculty in particular discipline 2. Participants respond, indicate requests, if any, for alternative formats, send consent, survey, postage-paid envelope to return documents 3. Participants insert signed consent separate envelope, return form[s], survey to investigator 4. Investigator receives; stores consent separately 5. Variable: IRB Informed Consent Document-Standard Print: 5 pages; Large Print: 20 pages [slide 17] Participants: Why these faculties? 1. Health Education: Accessibility priority in Healthy People, Health Literacy (U.S. Department of Health and Human Services, 2000), Professional Areas of Responsibility (National Commission for Health Education Credentialing, 2008); Priority population for eliminating [major] health disparities (U.S. Agency for Healthcare Research and Quality [AHRQ], 2008) 2. Education: Accessibility, Universal Design for Learning mandated: U.S. federal legislation for pre-K-12 public education (NCLB, 2002; IDEA 2004). 3. Library and Information Science: a. School librarians are teachers (Texas: 2 years teaching experience required for school librarian certification: State of Texas. Texas Administrative Code, 2001) b. Equity of Access: Key Action Area for profession (American Library Association, 2008) [slide 18] Methodology: Instruments 1. Anonymous, demographic-free surveys: except for references to discipline, two surveys identical. 2. 15 randomly ordered question items: participant selects/circles one of five responses for each question. 3. Ordinal scale: Least positive (1) to Most positive (5) 4. "I Don't Know"(3) can be valid response. 5. Simple process accommodates busy faculty. 6. Common faculty concerns addressed: student with access needs 'disrupting' classes, seeking undeserved assistance; ability to pass classes, complete program, enter profession. 7. Optional Comments: responses analyzed qualitatively. [slide 19] A. Original classification-15 question items into 5 groups: 1. Experience/Knowledge: Experience with [people with] access needs; assistive technology, UD[L] knowledge. Items 1, 3, 13 2. Negative Experience with students with access needs disrupting classes, receiving undeserved treatment. Items 8, 9 3. Comfort: Comfort level in teaching and interacting with people/students with access needs. Items 2, 4, 5, 6, 7 4. Confidence in students with access needs' academic success in class, department program, entering profession. Items 10, 11, 12 5. Interest: Participant interest in learning [more] about accessibility, assistive technology, Universal Design [for Learning]. Items 14, 15 B. Design phase: Reliability Analysis of Classification Scheme: 1. Experts' Review; 2. Internal Consistency: Cronbach's Alpha [slide 20] Internal Consistency Reliability: Cronbach’s Alpha (PROC CORR in SAS): Experience/Knowledge: Items 1, 3, 13: Standardized Value r = 0.797913 - HIGH Negative Experience : Items 8, 9: Standardized Value r = 0.294803 - LOW Experience/Knowledge + Negative Experience: Items 1, 3, 8, 9, 13: Standardized Value r = 0.277185 - LOW Comfort: Items 2, 4, 5, 6, 7 : Standardized Value r = 0.855175 - HIGH Comfort + Negative Experience = Comfort* : Items 2, 4, 5, 6, 7, 8, 9: Standardized Value r = 0.729115 - HIGH Confidence : Items 10, 11, 12: Standardized Value r = 0.491675 MODERATE Interest : Items 14, 15: Standardized Value r = 0.893705 - HIGH [slide 21] Data Analysis: Adjusting Groups Effect of reliability analysis: Group variables of interest reduced from five categories to four categories, with Negative Experience subsumed within the Comfort category: new variable = Comfort* 1. Experience/Knowledge: Items 1, 3, 13 2. Comfort* : Items 2, 4, 5, 6, 7, 8, 9 3. Confidence : Items 10, 11, 12 4. Interest : Items 14, 15 [slide 22] Caption for Graphic showing areas of inquiry: Survey's 15 ordinal variables coded into 4 groups or categories that affect faculty attitudes: 1) Experience/Knowledge, 2) Comfort* [Comfort + Negative Experience], 3) Confidence, and 4) Interest. [slide 23] [In parentheses: SAS Commands] 1. Compare responses by academic discipline (BY AREA) 2. Frequencies (Mode), 5 point summary: Quartile 1 Median Quartile 3, Minimum Maximum 3. Nonparametric tests: independent samples: non-random purposive sampling, small sample sizes (n=30; n=14): parametric assumptions not met. (PROC NPAR1WAY) 4. Ordinal data: Wilcoxon Rank Sum (n less or equal to 30) [Mann-Whitney U (n greater than 30] (EXACT WILCOXON) [Kruskal-Wallis: 3 samples]. Test null: Do samples come from same population? (Portney and Watkins, 1993, page 421) 5. Spearman Rank Correlation Coefficient: nonparametric Chi-Square test (PROC CORR SPEARMAN) 6. Representations: Plots (PROC PLOT, PROC G3D) [slide 24] 1. Results by Academic Discipline (as of 23 April 2008) 1. Data: Study 1: Health Education Health Education Faculty: n = 30 2. Data: Study 2 (ongoing): Education and Library and Information Science [LIS] Faculty - As of April 23, 2008: LIS Faculty only: n = 14 3. Current recruitment of LIS and Education Faculty participants … Please refer to IRB-approved "Invitation to Participate in Research" handout. [slide 25] 2. Caption for chart: Frequency Results show high number of "I Don't Know" responses in Comfort-Online classes and Confidence item questions [slide 26] 2. Caption for Chart: Frequency Results: Five-Point Summary: Notice LIS Faculty have higher level of reported Experience/Knowledge about access issues. [slide 27] 3-4. Results: Nonparametric Wilcoxon Rank Sum Test: Testing null hypothesis whether two samples come from same population Caption for chart: Wilcoxon measures difference in category responses between Health Education, n=30 and Library and Information Science [LIS], n=14 disciplines. At alpha = .05, significant difference only occurs in Experience/Knowledge category. Category [Group variable]: Experience/Knowledge: Items 1, 3, 13 : Significant at .05: F value falls in rejection region: Reject Null: F /p values: F = 6.2436 p = 0.0165 Category [Group variable]: Comfort* Items 2, 4, 5, 6, 7, 8, 9 Fail to reject null hypothesis: F /p values: F = 0.2393 p = 0.6273 Category [Group variable]: Confidence - Items 10, 11, 12 Fail to reject null hypothesis: F /p values: F = 0.1027 p = 0.7502 Category [Group variable]: Interest - Items 14, 15 Fail to reject null hypothesis: F = 0.3681 p = 0.5473 [slide 28] 5. Results: Spearman Correlations (A) SAS output for 4 group variables Caption: Key: Health Ed. = Health Education Faculty LIS = Library and Info. Science Faculty For each cell: Correlations (r ) = UPPER values Significance levels = LOWER values Correlation Values: 0 -.39=weak .4 -.69 =moderate .7–1.0 = strong Chart of values - key findings enumerated on next slide [slide 29] 5. Selected Results: Spearman Correlations (A) Selected Results from correlations calculated with 4 group variables, merged Comfort-Negative Experience, herein the Comfort* variable (question items 2, 4, 5, 6, 7, 8, 9): 1. Moderate positive correlation (r = 0.48929) between Comfort* and Interest categories at alpha = .10 (p = 0.0758) for LIS sample (n=14) 2. Moderate positive correlation (r = 39.957), but not significant at alpha = .05 or alpha = .10 (p = 0.1569) between Comfort* and Confidence categories for LIS sample (n=14) 3. Weak inverse, non-significant correlation (r = -23724. p = 0.2068) between Confidence and Interest categories in Health Education sample (n=30) [slide 30] 6. Results: Scatterplot (PROC GPLOT-SAS) Caption for Scatterplot: Overlay scatterplot: moderate positive correlation shown Comfort* and Interest categories, Health Education (red stars) Library and Information Science [LIS] (blue dots), significant for LIS at alpha = .10 (r = 0.48929; p = 0.0758) SAS CODE for Overlay Scatterplot goptions reset=global gunit=pct border cback=white colors=(black blue green red) ftitle=swissb ftext=swiss htitle=4 htext=4; axis1 label=(angle=90); symbol1 i=none c=red v=star h=6 w=6; symbol2 i=none c=blue v=dot h=3 w=4; proc gplot data=access_heaccess uniform; plot COMFORTN*INTEREST=AREA / vaxis = axis1 haxis=1 to 5.9 by 1 vaxis=1 to 5.9 by 1 overlay; title 'Comfort+ - Interest Level'; run; quit; [slide 31] 5. Results: Spearman Correlations (B) SAS output for 4 group variables Caption: Key: Health Ed. = Health Education Faculty LIS = Library and Info. Science Faculty For each cell: Correlations (r ) = UPPER values Significance levels = LOWER values Correlation Values: 0 -.39=weak .4 -.69 =moderate .7–1.0 = strong Chart of values - key findings enumerated on next slide [slide 32] Correlations calculated - 5 group variables: Negative Experience (question items 8, 9) separate from Comfort (items 2, 4, 5, 6, 7): 1. Moderate negative correlation (r = -0.43082) between Experience/Knowledge and Negative Experience categories, significant at alpha = .05 (p =0.0175) for the Health Education sample (n=30). 2. Weak-moderate positive correlation (r=.36), significant at alpha = .05 (p = .0491) between Negative Experience - Interest categories for the Health Education sample (n=30). 3. Moderate positive correlation (r = 39.909), but not significant at alpha = .05 or alpha = .10 (p = 0.1575) between Negative Experience-Interest categories for the Library and Information Science sample (n=14). 4. Weak inverse, non-significant correlation (r = -23724. p = 0.2068): Confidence and Interest categories in Health Education sample (n=30) [slide 33] 6. Results: Scatterplot (PROC GPLOT-SAS) Caption for Scatterplot: Overlay Scatterplot depicts inverse correlation: between Experience/Knowledge and Negative Experience, more so, Health Education, n=30-red stars (r = -0.43082, p =0.0175, significant at alpha = .05 ) than Library/Information Science n=14 (blue dots) SAS CODE for Overlay Scatterplot goptions reset=global gunit=pct border cback=white colors=(black blue green red) ftitle=swissb ftext=swiss htitle=5 htext=4; axis1 label=(angle=90); symbol1 i=none c=red v=star h=6 w=6; symbol2 i=none c=blue v=dot h=3 w=4; proc gplot data=access_heaccess uniform; plot EXPEKNOW*EXPENNEG=AREA / vaxis = axis1 haxis=1 to 5.9 by 1 vaxis=1 to 5.9 by 1 overlay; title 'Experience/Knowledge-Negative Experience'; run; quit; [slide 34] 6. Results: 3-Dimensional Scatterplots (SAS-PROC G3D) Experience/Comfort+/Confidence Caption: 3-dimensional scatterplots of Experience/Comfort+/Confidence group data by discipline (Left plot: Health Education, Right plot: Library/Info Science [LIS]). Generally, but moreso in LIS, both plots show that more experience/ knowledge and comfort+ tend to foster in higher confidence. SAS CODE for 3-Dimensional Scatterplots by Discipline goptions reset=global gunit=pct border cback=white colors=(black blue green red) ftitle=swissb ftext=swiss htitle=4 htext=4; proc g3d data=access_heaccess; scatter EXPEKNOW*COMFORTN=CONFIDNC / caxis='black' color='red' shape='balloon' grid size=2 noneedle zmin=1 zmax=5; *color=‘blue’ by area; title 'Discipline: Health Education'; run; [slide 35] Preliminary Conclusions Recalling the research questions and hypotheses: Regarding differences toward access issues based on faculty discipline: a. Differences between health education and Library/Information Science [LIS] do not appear to be significant (small sample size factor considered); LIS Faculty have somewhat more reported experience and knowledge (significant Wilcoxon test score) b. With further recruitment of Education and other disciplines, may differences appear? 2. Correlations between group variables: a. Experience/Knowledge and Negative Experience appear to have inverse correlation (significantly for Health Education): increased knowledge appears to reduce negative attitudes b. Experience/Knowledge and Comfort: Moderate positive correlation (although not significant) c. Negative Experience and Confidence: Inversely correlation apparent, although not significant d. Interest and Negative Experience: apparent positive weak/moderate correlation (significantly for Health Eduaction n=30 at the alpha = .10 level) 3. Both disciplines (Health Education and Library and Information Science) interested in positive interaction with class members, learning more about access issues, although lack full confidence in students with access needs' academic and career success. [slide 36] 1. Continued participant recruitment: current study (especially need Education Faculty) so can expand analysis 2. Feature positive effect: positive framing of access issues yields more positive attitudes? (Zhao and Pechmann, 2006) 3. Replication of research in more disciplines 4. Convergence in U.S. of access support: pre-K-12 through higher education 5. Impact: institutional effectiveness initiatives 6. Wasting no time: Higher Education: Adopt UDL! a. Universal Design for Learning [UDL] evidence-based (CAST, 2008) b. Do right the first time: fiscal accountability/institutional effectiveness: saves money, time, effort c. Mutually beneficial: increasingly diverse student community, distance and lifelong learning initiatives, very busy, dedicated faculty [slide 37] Thank you! Presenter Contact Information Ellen Perlow, Ph.D. CHES eperlow@hotmail.com Presentation materials located at: http://www.a4access.org/twu2008.html Alternative formats are available upon request. copyright 2008 [slide 38] UDL/Assistive Tech in Action Oh my. I forgot to introduce myself. My name is Kurzweil 3000, developed by my namesake, Raymond Kurzweil, the inventor over 30 years ago of the original text to speech Kurzweil Machine, (see http://www.kurzweiledu.com). I am universally designed assistive technology that makes everyone's life easier. As you have noticed, I simultaneously voice and I visually read aloud text, guiding the reading by highlighting words, phrases, and sentences. I can be personalized in many ways with different voices, pitch, volume, reading speed, and various highlighter color combinations. Text font size and style, and pronunciation of words are adjustable. I navigate by keystroke or mouse and import/export documents. I have word prediction spell-check dictionary and thesaurus. My multimodality supports diverse learning styles and promotes everyone's literacy skills. Both professors and students find me very helpful, especially upon losing their voice or when needing to rehearse presentations as not to speak past their allotted time. With that subtle reminder, before opening the floor to questions … [slide 39] Acknowledgments Thank you to our interpreter Jennifer Borgman. Deepest gratitude is extended to three distinguished "Simply the Best" Texas Woman's University Professors who have made this research both possible and accessible: William Cissell, Ph.D. – Cornaro Professor and Faculty Advisor, Health Studies (retired) Michael Wiebe, Ph.D. - Professor and Faculty Advisor, Teacher Education/Special Education, and Mark Hamner, Ph.D., Statistics Professor Extraordinaire, recipient, Texas Woman's University's prestigious Mary Mason Lyon Faculty Award for 2008. Congratulations, Dr. Hamner ! [End of Presentation copyright Ellen Perlow, Ph.D. CHES April 2008]