Using Comprehensive Observational Data to Improve Reading Instruction: Case Studies of DHH Student Readers

Using Comprehensive Observational Data to Improve Reading Instruction: Case Studies of DHH Student Readers

Copyright: © 2023 |Pages: 44
DOI: 10.4018/978-1-6684-5834-1.ch005
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Abstract

Reading assessment of deaf and hard-of-hearing students is difficult in that many typical curriculum-based and standardized assessments presume spoken English fluency. This affects not only the test items but also the numerical scores that can result in instructional decisions that are unfairly penalizing. In contract, miscue analysis provides a systematic analysis of an individual's reading performance that is flexible across languages and dialects in identifying skills and needs across the range of skilled and struggling readers. This chapter presents two DHH students' miscue scores, representing communication preferences for listening and spoken English, and American Sign Language. Readers will analyze these data through guided questions to develop insights and understandings about each reader's reading strengths and needs. This highly accurate and detailed analysis is the type that can lead teachers and researchers to better identify the nature of DHH students' reading challenges and provide the instruction that appropriately addresses their needs.
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Introduction: The Challenge Of Reading Assessment

Reading remains a fundamental instructional challenge for deaf and hard-of-hearing (DHH) students and their teachers. The extent of this challenge is seen in reading comprehension scores that have changed little in nearly five decades (Ewoldt, 1981; Luetke-Stahlman, 1998; Qi & Mitchell, 2012; Traxler, 2000). Accurate assessment is essential to addressing this challenge: It provides teachers with the data they need to identify students’ reading skills and needs, and to monitor the results of instruction. It also allows researchers to accurately identify the nature and extent of these reading difficulties, develop, and test effective strategies that address these issues.

However, most standardized and curriculum-based reading assessments used with DHH students do not accommodate their frequent lack of spoken language fluency. Such tests are rarely normed on DHH individuals and do not address potentially biased test items (Cawthon, 2015; Lewis, 2003; Miller, et al., 2015). Without accurate and valid measures of reading skills, neither teachers nor researchers are able to develop appropriate instruction and programs that address DHH students’ literacy needs. The long-term nature of their reading deficits (Ewoldt, 1981; Luetke-Stahlman, 1998; Qi & Mitchell, 2012; Traxler, 2000) suggest that causative elements remain largely unknown. It appears that these widely utilized testing practices have done little to illuminate the primary causative factors of DHH students’ ongoing reading deficits.

Miscue analysis provides an alternative form of assessment, using a meticulous, individualized, and systematic form of evaluation. This process also is flexible enough to examine a range of successful and struggling, monolingual, bilingual, and diverse hearing readers resulting in discovering distinctive skill patterns and reading processes used by each reader. Miscue analysis is additionally unique in that it provides an untimed and authentic reading experience. Its diagnostic observational procedures identify and evaluate each reader’s meaning-making processes allowing for greater insight into each reader’ approaches.

The foundational miscue processes are incorporated into oral miscue analyses used in many individual reading assessments (Burns & Roe, 2002; McKenna & Picard, 2006; Nilsson, 2008) and with running records (Clay, 2000; Nilsson, 2008). However, the full miscue procedure provides a more thorough and detailed examination than these other assessments provide, to include lspecific behavioral patterns that can be used to guide instructional decision-making (Blaiklock, 2004; Fawson et al., 2006). Its use has led to unique insights regarding the reading processes and otherwise unrecognized capabilities of DHH students across the continuum of communication preferences (Luft, 2018, 2020). Importantly, its direct observational documentation of reading behaviors contrasts with typical paper/pencil assessments that calculate reading scores across skill categories and procedures developed from assumptions of fluent spoken English.

This chapter begins with a description of procedures for conducting a miscue analysis. This includes examples and explanations of coding and scoring for DHH students who use Listening and Spoken Language (English) and American Sign Language (ASL). The next section presents two case studies of DHH students, one using Listening and Spoken Language (Brandon) and the other using ASL (Kalena). Each case study presents a portion of a reading text with miscues highlighted, a coded and scored spreadsheet of miscues from this portion of text, and guided questions to facilitate the reader’s analysis of these data. Appendices A and B provide an analysis of each student’s reading for the reader to compare with his or her own. The chapter concludes with a summary of what can be learned from each case study miscue, and how this can be applied to other DHH students.

Key Terms in this Chapter

Semantic: The result of examining a miscue for its effects on the meaning of the text. These can be minor miscues (“same” for “similar”) and scored as – ½ or a major miscue (“different” for “similar”) which is scored as -1.

Miscue Analysis: An individualized, systematic examination of a readers sociopsycholinguistic reading processes accomplished by noting all of the mismatches with the written text during an oral or signed read-aloud. These are then analyzed across and within miscue categories to identify the reader’s cognitive meaning-making processes.

Graphophonic: A type of miscue that occurs when a similarly spelled word is spoken or signed by a reader. Specific differences are categorized as occurring at the beginning (“say” for “day”), middle (“simple” for “single”), or ends or words (“engine” for “engineer”).

Syntactic: The result of examining a miscue for its effects on the intended grammar of the text. These can be minor miscues (“same” for “similar”) and scored as – ½ (0.5 on the spreadsheet) or a major miscue (“simpler” for “similar”) which is scored as -1.

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