Measure It, Monitor It: Tools for Monitoring Implementation of Text-to-Speech Software

Measure It, Monitor It: Tools for Monitoring Implementation of Text-to-Speech Software

Joan B. Hodapp (Area Education Agency 267, USA) and Cinda Rachow (Area Education Agency 13, USA)
DOI: 10.4018/978-1-61520-817-3.ch015
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Abstract

This chapter addresses the importance of systematic assessment using a variety of tools to evaluate implementation and monitor the outcomes of assistive technology innovations. A variety of the tools and strategies—developed to monitor implementation and change, gather perceptual data, and collect academic outcome data—are discussed. These tools and strategies were developed and tested in the 2005-2006 and 2006-2007 Iowa Text Reader Studies. Applications of the tools are featured for various stakeholders, such as teachers, administrators, and researchers. Multiple research designs to determine the impact of assistive technology, including the Time Sequence Concurrent Differential Model, are contrasted.
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Background

With the passage of the Education of All Handicapped Children Act (P.L.94-142) in 1975, the focus and mandate for improving academic achievement for students with special needs have increasingly narrowed and become high stakes concerns for school districts. Initially, concerns were focused on providing student access to the general education curriculum. Now, the emphasis has moved to student outcomes documenting closure of the achievement gap between students with special needs and their typical peers by providing this cognitive access to the general education curriculum (Abell, Bauder, & Simmons, 2005; Hitchcock, Meyer, Rose, & Jackson, 2007). The inclusion, for the first time ever, of special education student achievement within the accountability of the No Child Left Behind (NCLB) Act of 2001 raised the level of concern for student proficiency from the individual to the systems level.

Since the mandate of Individuals with Disabilities Education Act (IDEA) of 1994, and despite the requirement of NCLB to utilize research-based strategies, only limited research has been conducted in the fourteen years on the effectiveness of assistive technology (AT) to improve student achievement regardless of instructional area (Edyburn, 2003, 2007). DeRuyter (1994, 1997) attributed the paucity of research to lack of both subjective and objective measurement tools to support or deny the effectiveness of AT. Gersten and Edyburn (2007) attributed the overdependence of consumer satisfaction surveys to the lack of validated outcome measures. Numerous researchers have commented that more attention was paid to the device selection than implementation and outcome measurement (Bausch & Ault, 2008; Edyburn, 2008; Parette, Peterson-Karlan, Wojcik, & Bardi, 2007). Edyburn (2003) defined ten variables, such as change in function, change in participation, goal achievement and usage associated with AT use that could be indicators to help understand the outcomes. Indeed, it is only recently that the concept of an implementation plan including tools for measuring outcomes has been introduced into the literature (Bausch & Ault, 2008; Edyburn, Fennema-Jansen, Harihan, & Smith, 2005; Malouf & Hauser, 2005).

Key Terms in this Chapter

Progress Monitoring: Routine monitoring of assessment data used as formative data to make instructional decisions. It is most commonly associated with the use of curriculum-based measurement data with decision rules for instructional changes. Student performance improves significantly when used with graphing and decision rules.

Assistive Technology (AT): A category of technology used by persons with disabilities to provide access and help performing tasks in living, learning, and working as well as increase independence, and quality of life.

Time Sequence Differential Concurrent Model (TSCD): A research design that compares student performance of the same task with and without technology to measure the impact of assistive technology.

Implementation: Application of the innovation with strict compliance to the intervention schedule (i.e., fidelity (quality of application) and integrity (completely and as scheduled)).

Text-to-Speech Software: A category of software using scanned digitized text that can convert any written text into spoken word. It allows access to software and digital documents such as MS Word, web page, PDF files, and the Internet. Leading examples include Kurzweil 3000, Read and Write Gold, and Wynn Scan and Read Software.

Authentic Assessment: Assessment that uses direct measurement to test the students’ ability to demonstrate mastery of the outcome objectives of the targeted instructional indicators.

Outcome Measures: Technically adequate and sensitive measures of the effects of the technology on the targeted skill area. For example, if the target is improved reading skills, an appropriate outcome measure would include curriculum-based measurement data which has been proven to be reliable and valid.

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