Effective technologies that support inclusive science instruction
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Effective Technologies that Support Inclusive Science Instruction. Dr. Matthew T. Marino Washington State University Spring 2008 matthewmarino@wsu.edu http://www.wsu.edu/~matthewmarino/index.html. Universal Design: A Theoretical Framework for Improving Access to Learning Materials.

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Effective Technologies that Support Inclusive Science Instruction

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Effective technologies that support inclusive science instruction

Effective Technologies that Support Inclusive Science Instruction

Dr. Matthew T. Marino

Washington State University

Spring 2008



Universal design a theoretical framework for improving access to learning materials

Universal Design: A Theoretical Framework for Improving Access to Learning Materials

  • Developed from architecture in the early 1970’s at North Carolina State University

  • Based on the idea that all products should be usable to the greatest extent possible by everyone, regardless of their age, ability, or status in life.

  • Examples of Universal Design include curb cuts, TV captioning, & pictorial representation on restroom doors.

Universal design for learning udl

Universal Design for Learning (UDL)

  • An educational application of the original architecture-based UD construct

  • Developed at the Center for Applied Special Technology (CAST) for K-12 students

  • UDL is designed to improve access, participation, and progress in the general education curriculum

  • UDL challenges teachers to anticipate, reduce, and/or eliminate barriers by creating flexible curricula

Premise for udl

Premise for UDL

  • Barriers occur as diverse learners interact with curriculum (e.g., nonreaders working with text)

  • The curriculum and instruction are the problem, NOT the students

  • Curricula should consider student differences at the outset… as opposed to retrofitting existing instructional plans (Meyer & Rose, 2005)

Barriers to student learning

Barriers to Student Learning

  • Prior knowledge about the concept

  • Seeing, decoding, or fluently reading text

  • Filtering extraneous sensory information

  • Keeping track of information (e.g., organization)

  • Lack of interest with the topic

  • Ability to maintain focus for an appropriate period of time

Struggling readers face significant barriers

Struggling Readers Face Significant Barriers

  • 12.4 million students will experience significant difficulties learning to read(NCES, 2003)

  • Students with reading difficulties (RD) possess unique neural systems that affect metacognition(Mastropieri & Scruggs, 2004; Shaywitz & Shaywitz, 2004)

  • Poor readers have difficulty with: knowledge of print conventions, print awareness, attention, planning, concentration, and organization abilities(Fletcher et al., 1994; Stanovich and Siegel, 1994; Velutino, Scanlon, & Lyon, 2000)

  • Students with LD in reading and poor readers possess virtually indistinguishable reading growth curves in grades 1 through 12(Lyon et al., 2001)

Struggling readers expository texts

Often lack prior knowledge (Gersten et al., 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)

Struggling Readers & Expository Texts

This leads to

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)

How can we help these students?

Technology can provide

Technology Can Provide

  • Representational illustrations of concepts (Mastropieri et al., 1996)

  • Spatial / graphic organizers (Mastropieri et al, 2003)

  • Access to background information on demand (McKenna, Reinking, Labbo, & Kieffer, 1999)

  • Translational resources (e.g., text-to-speech) (Horney & Anderson-Inman, 1999)

  • Supplemental resources (e.g., screen reading, note taking, reference tools) (Pucket, 2004)

  • Embedded assessments(Liu & Bera, 2005)

Udl technology instruction learning

UDL +Technology + Instruction = Learning

  • 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; Marino, 2006, Williams & Peterson, 2004)

  • Additional technology and content area training for teachers(Sharpe & Hawes, 2003)

  • Increased collaboration between special education and regular education teachers(Moore & Keefe, 2001)

  • Improved instructional strategies (Washburn-Moses, 2005)

Teachers technology challenges

Teachers’ Technology Challenges

  • There has been a flood of e-learning (online, multimedia, and software) material to the market

  • Purchasing decisions are based on marketing rather than unbiased assessment

  • Where can you go for reliable peer reviewed data about technology-based learning materials?


Purchase technology that

Purchase Technology That…

  • Includes an electronic pre/posttest design and/or curriculum-based measures (CBM) that allows teachers to monitor student learning

  • Meets the teachers’ levels of technological proficiency

  • Acts as assistive technology by including tools that support students with reading difficulties (e.g., text-to-speech)

  • Provides instructional strategies for effectively teaching students to use the technology

  • Offers customer support services and free training

Washington state university technology resource database

Washington State University Technology Resource Database

The goal of the Washington State University Technology Resource Database is to develop an internet-based e-learning resource for K-12 teachers, administrators, and researchers that will provide unbiased, peer-reviewed information about the types of e-learning products that are most efficacious for student learning.

The database is composed of three linked interfaces: 1) an online e-learning assessment survey that teachers complete after using e-learning products with their students, 2) a database comprised of the results of the survey responses, and 3) a search engine that allows teachers and researchers to access pertinent information in the database quickly and efficiently.

E learning survey domains






Student Information

Technical Aspects

Manufacturer information

E-learning Survey Domains

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