Improving Reading within an Urban Elementary School: Computerized Intervention and Paraprofessional Factors
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| Title: | Improving Reading within an Urban Elementary School: Computerized Intervention and Paraprofessional Factors |
|---|---|
| Language: | English |
| Authors: | Council, Morris R., III, Gardner, Ralph, III, Cartledge, Gwendolyn, Telesman, Alana O. |
| Source: | Preventing School Failure. 2019 63(2):162-174. |
| Availability: | Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals |
| Peer Reviewed: | Y |
| Page Count: | 13 |
| Publication Date: | 2019 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Early Childhood Education Elementary Education Grade 2 Primary Education |
| Descriptors: | Reading Improvement, Reading Instruction, Urban Schools, Culturally Relevant Education, Computer Software, Intervention, Oral Reading, Reading Fluency, Computer Assisted Instruction, Repetition, Grade 2, Elementary School Students, At Risk Students, Reading Comprehension, Librarians, Paraprofessional School Personnel, School Libraries, Emergent Literacy, Reading Tests |
| Geographic Terms: | Ohio (Columbus) |
| Assessment and Survey Identifiers: | Dynamic Indicators of Basic Early Literacy Skills (DIBELS) |
| DOI: | 10.1080/1045988X.2018.1540392 |
| ISSN: | 1045-988X |
| Abstract: | Reading RACES--Relevant and Culturally Engaging Stories (RR) is a repeated reading intervention using culturally relevant literature that is delivered through computer software. This study extends previous research with RR intended to further evaluate the effects of RR on the fluency and comprehension growth of second-grade students with reading risk within an urban setting. A second focus was to determine the degree to which paraprofessional school personnel could successfully implement the intervention. Five second graders and the school librarian (paraprofessional) participated in this study. A multiple baseline probe across participants revealed a functional relation between RR and student participants' gains in oral reading fluency and comprehension. Procedural integrity data also revealed that participants (i.e., students and librarian) were able to use and monitor the program with integrity to the maximum extent enabled by the technology. These findings extend the research base for RR. Limitations and directions for future research are discussed. |
| Abstractor: | As Provided |
| Entry Date: | 2019 |
| Accession Number: | EJ1210677 |
| Database: | ERIC |
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| FullText | Links: – Type: pdflink Url: https://content.ebscohost.com/cds/retrieve?content=AQICAHj0k_4E0hTGH8RJwT4gCJyBsGNe_WN95AvKlDbXJGqwxwFfjqNtYd6RA1xScj4HYe6hAAAA4zCB4AYJKoZIhvcNAQcGoIHSMIHPAgEAMIHJBgkqhkiG9w0BBwEwHgYJYIZIAWUDBAEuMBEEDKoqnqyVVEYbFXfCjwIBEICBmyW9Hkddl08f23nCm4xKXVj-w7vWhPzuH4rdwo8ktjl_8Tp79ksD5FYTWCmNfJclKJZG4P-x3J6az7bxXfSK_Wavy6ADc27URdOoDnvd28CGHBkU5KqJlwiMQ0MqjoqhmMBMLbj30twdOvtIob8OkfZIELlVCQJf7lIbdsJrmwFtHmx5QaH37Mi5WFTvAlTtq0RBsQlzUKdVds4O Text: Availability: 1 Value: <anid>AN0135649624;psf01feb.19;2019Apr02.10:09;v2.2.500</anid> <title id="AN0135649624-1">Improving reading within an urban elementary school: computerized intervention and paraprofessional factors </title> <p>Reading RACES-Relevant and Culturally Engaging Stories (RR) is a repeated reading intervention using culturally relevant literature that is delivered through computer software. This study extends previous research with RR intended to further evaluate the effects of RR on the fluency and comprehension growth of second-grade students with reading risk within an urban setting. A second focus was to determine the degree to which paraprofessional school personnel could successfully implement the intervention. Five second graders and the school librarian (paraprofessional) participated in this study. A multiple baseline probe across participants revealed a functional relation between RR and student participants' gains in oral reading fluency and comprehension. Procedural integrity data also revealed that participants (i.e., students and librarian) were able to use and monitor the program with integrity to the maximum extent enabled by the technology. These findings extend the research base for RR. Limitations and directions for future research are discussed.</p> <p>Keywords: Computer-assisted technology; culturally relevant pedagogy; oral reading fluency; paraprofessional; urban education</p> <p>Young learners who attend high-poverty urban schools have been consistently identified as some of our nation's most academically marginalized citizens. Their educational outcomes are often the result of various social ills (Cunningham, Mars, &amp; Burns, 2012; Milner, 2013) influenced by policies and systems in our society that often lack sensitivity to their experiences. Although these learners are faced with unique challenges that can affect their achievement, their lives are fluid and are not predetermined by the conditions in which they live. Unfortunately, those tasked to support learners in high-poverty schools often struggle to see beyond the underachievement of their students, resulting in a deficit perspective of students (Gay, 2004; Ladson-Billings, 2014; Paris, 2012). Far too many teachers and researchers make the mistake of blaming the students and their families for poor academic performance (Ford, 2014), oftentimes overlooking institutional practices that have a significant impact on learning (Harry &amp; Klingner, 2007).</p> <p>The National Assessment of Educational Progress (NAEP, 2016) reported that in 2015 only 36% of fourth graders scored at or above proficiency in reading achievement, with 31% reading below basic. Basic is defined as "partial mastery of prerequisite knowledge and skills that are fundamental for proficient work at each grade" (NAEP, 2012, para. 4). Poor literacy rates are even more alarming for students attending urban schools. According to a recent National Report Card, students in urban public school districts performed 9% lower in literacy than the national average (National Center for Education Statistics [NCES], 2013). In the United States, traditionally marginalized groups (e.g., African Americans and Latinas/Latinos) disproportionately attend urban schools, which typically evidence inadequate resources and less experienced teachers (Cooper &amp; Jordan, 2003; O'Connor, Hill, &amp; Robinson, 2009), conditions that potentially undermine the academic performance of learners in these settings (Kourea, Cartledge, &amp; Musti-Rao, 2007; Lippman, Burns, &amp; McArthur, 1996). Fortunately, good research exists on viable methods for improving reading that are beneficial for learners from all backgrounds (Moats, 2007; Torgesen, 2004). These interventions are most beneficial when delivered during children's early elementary school years (Moats, 2007).</p> <p>An underlying principle that frames this study and discussion is that learning to read is a basic right and an essential competence. Reading failure is the greatest academic risk factor confronting young children from low-socioeconomic status urban areas. One critical component of beginning reading is oral reading fluency (ORF); however, it tends to be overlooked for explicit instruction, causing many children in literacy-impoverished environments to be permanently reading disadvantaged, if not disabled. The work of Samuels (LaBerge &amp; Samuels, 1974) on automaticity informs our theoretical and instructional model. Although fluency is validated in the empirical literature (e.g., Therrien, 2004), of particular importance within urban schools is efficient and effective instructional delivery within available but limited resources. Advances in instructional technology may provide opportunities to enhance available school resources and better use paraprofessional staff.</p> <hd id="AN0135649624-2">Reading fluency</hd> <p>Learners who read fluently are able to decode with automaticity (LaBerge &amp; Samuels, 1974; Stanovich, 2000), thus improving the likelihood that they draw relevant meaning from text. The ability to easily decode (i.e., connect appropriate sounds to letter combinations) enables learners to focus on extracting meaning, which results in improved comprehension (Veenendaal, Groen, &amp; Verhoeven, 2015; Wexler, Vaughn, Edmonds, &amp; Reutebuch, 2008). Fuchs, Fuchs, Hosp, and Jenkins (2001) argue that ORF is an indicator of overall reading competence due to the need to simultaneously execute complex component skills (i.e., phonological segmentation, decoding skills, and rapid word recognition). Fuchs et al. (2001) also determined that ORF was a better indicator of reading comprehension than question answering, passage recall, and cloze assessments.</p> <p>Despite research indicating the importance of ORF, far too many children are non-fluent readers. Non-fluent learners are less likely to engage in reading, which further increases the gap with their peers in reading achievement. Research suggests that primary school-aged students who struggle with fluency are at an increased risk for sustained reading difficulty (Moats, 2007; Speece &amp; Ritchey, 2005) and fluency should be nurtured during students' initial reading instruction with highly effective explicit techniques such as repeated reading (National Reading Panel [NRP], 2000).</p> <p>Many young children who show special education risk, especially students of color in urban schools, struggle with reading fluency and would benefit from explicit fluency training (Kourea et al., 2007). Researchers have identified repeated reading interventions as an effective method to improve reading achievement (Therrien, 2004; Therrien &amp; Kubina, 2006), but these procedures are not widely employed in urban schools. Repeated reading methodology is a labor-intensive but valued commodity in urban schools where personnel and other resources are limited. One possible alternative to deliver intervention is through technology, that is, computer assisted instruction (CAI). The consideration of these factors led the researchers of this study to question whether a repeated reading approach can be delivered effectively through voice recognition computer software.</p> <hd id="AN0135649624-3">Computer-delivered fluency training</hd> <p>Although many schools (particularly schools in low-income communities) face limitations in human resources, computer technology is becoming increasingly common in classrooms. According to the NCES, in 2009 97% of all teachers had one or multiple computers permanently located in their classrooms (Gray, Thomas, &amp; Lewis, 2010). This percentage was found consistent across both high- and low-poverty urban public schools. Gray et al. (2010) also found "83% of teachers in high poverty schools reported that their students used educational technology sometimes or often during the school day to learn or practice basic skills" (p. 3). As our society continues to advance technologically, CAI has become a viable means to address the resource challenges of many schools.</p> <p>CAI can simply be defined as instruction that is presented or delivered on a computer (e.g., desktop, laptop, tablet). This definition is critical to understand because "computers themselves are not capable of teaching content but simply the vehicle by which instruction is delivered" (Musti-Rao, Cartledge, Bennett, &amp; Council, 2015, p. 2). Although technology is rapidly advancing, making this the digital age, CAI has an extensive history of classroom effectiveness dating back to the 1960s (Cheung &amp; Slavin, 2012; Fletcher &amp; Atkinson, 1972; Kulik &amp; Kulik, 1991). This research, showing small to moderate effect sizes, has been conducted with a variety of populations, including students with reading disabilities (Regan, Berkeley, Hughes, &amp; Kirby, 2014; Saine, Lerkkanen, Ahonen, Tolvanen, &amp; Lyytinen, 2011; Torgesen, Wagner, Rashotte, Herron, &amp; Lindamood, 2010) and those from culturally and linguistically diverse backgrounds (Gibson, Cartledge, &amp; Keyes, 2011; Gibson, Cartledge, Keyes, &amp; Yawn, 2014; Leonard, Davis, &amp; Sidler, 2005).</p> <p>There are several potential benefits of CAI for struggling readers. Effective CAI programs typically produce high rates of response with correct responding required to progress through programs. CAI can deliver <emph>individualized and differentiated instruction</emph> to students, allowing students to receive appropriate instruction in a private learning environment. An additional benefit of CAI is c<emph>onsistent delivery of instruction</emph>, or systematic execution of the program with fidelity minimizing instructor error. CAI also has the potential to increase student <emph>motivation</emph> through the use of multimedia (e.g., sound and animation; Couse &amp; Chen, 2010; Moreno &amp; Mayer, 2007). Last, CAI can contribute to <emph>classroom management</emph> by increasing student learning and engagement (Council, Cartledge, Gardner, Barber, &amp; Green, 2016; Laffey, Espinosa, Moore, &amp; Lodree, 2003).</p> <p>Reading RACES-Relevant and Culturally Engaging Stories (RR) was created through a multidisciplinary development project that involved collaboration among faculty, staff, and students in special education and computer science engineering at The Ohio State University. The intervention was designed to provide repeated readings of culturally relevant passages through computer software. Several studies have been completed utilizing the RR software and have demonstrated a functional relation between the software intervention and increased oral reading fluency and reading comprehension for seven second graders showing reading risk (Bennett, Gardner, Cartledge, Ramnath, &amp; Council, 2017), for three first-grade English learners (Barber et al., 2018), and for three primary school-aged children who showed both academic and behavioral risk (Council et al., 2016). The inaugural study required students to (a) listen to a computer-delivered passage read by a model, (b) read with the model, (c) read independently up to three times with corrective feedback, (d) read for one-minute timing, and, if successful, (e) take a three-minute maze comprehension assessment. If not successful, the student repeated the one-minute timings for a maximum of two more trials or the goal was reduced until success was achieved. The student also read a generalization (novel, non-practiced) passage and a comprehension assessment (i.e., maze) to verify fluency progress. Substantial gains in fluency and comprehension resulted and persisted for six of the seven participants. Upgraded versions of the software were used with first-grade (Green, 2015) and English learning (Barber et al., 2018) students in urban schools. Students in these subsequent studies made comparable or better gains in fluency and comprehension, as did those in the Bennett et al. (2017) study. Although these studies consistently showed the beneficial effects of the RR intervention, they all required the presence of multiple researchers in distraction-reduced spaces (i.e., school nonacademic rooms), which raised questions about the viability of the program in a more typical school environment. This was especially the case in urban low-income schools where resources in terms of staff and equipment are sorely limited (Verstegen, Venegas, &amp; Knoeppel, 2006). The researchers noted that these schools typically employed paraprofessionals who served in various capacities in the school libraries. If appropriately prepared, these paraprofessionals could address the personnel resource shortage. Thus, a realistic, valid school application might be the computer-delivered intervention with paraprofessional supervision.</p> <hd id="AN0135649624-4">Paraprofessionals in the schools</hd> <p>Paraprofessionals have assumed many roles within schools (e.g., library aides) but traditionally have been most impactful in supplementing the instruction of teachers (Brock &amp; Carter, 2013a). They are used extensively in special education, particularly to relieve excessive burdens of instructing diverse students with disabilities or to assist students with disabilities placed in general education settings (Giangreco, Doyle, &amp; Suter, 2012). Although teachers typically welcome and respond positively to having paraprofessionals assigned as assistants, some of the early research questioned their effect on pupil performance and has led to an emphasis on paraprofessional training involving lectures, demonstrations, and feedback (Brown &amp; Stanton-Chapman, 2017). Lane, Fletcher, Carter, Dejud, and Delorenzo (2007) found a that paraprofessional-led reading intervention on primary-aged learners at risk for reading and behavior concerns resulted in substantial reading gains for treated students. This and other noted studies suggest that with adequate training, paraprofessionals are capable of effectively implementing and supervising supplementary interventions (Brock &amp; Carter, 2013b; Greenwood, 2009; Harn, Parisi, &amp; Stoolmiller, 2013), such as monitoring computer-assisted interventions. Giangreco, Doyle, and Suter (2012) also caution that in addition to being sufficiently trained, paraprofessionals need to be closely supervised and need to assume appropriate roles that will produce the best returns for students.</p> <p>Accordingly, the researchers of this study questioned the following: (a) Would school paraprofessional personnel be able to monitor the RR interventions with 100% fidelity based on a researcher-developed protocol? (b) Would participating second-grade students evidence a functional relationship between the RR intervention and reading fluency and comprehension gains when not exclusively supervised by trained researchers?</p> <hd id="AN0135649624-5">Method</hd> <p></p> <hd id="AN0135649624-6">Participants</hd> <p> <bold>Students.</bold> The researchers provided each second grader with a consent form. Researchers administered the Dynamic Indicators of Basic Literacy Skills-Next (DIBELS Next; Good &amp; Kaminski, 2011) individually to all students who returned a signed consent form (85% of all second graders). Grade-level teachers provided recommendations for participants on the basis of classroom observation and schoolwide reading assessment. Five second graders from two separate classrooms who showed reading risk were selected for this study. Scores from the researcher-administered DIBELS Next second-grade beginning of the year benchmark assessment were used as a screening measure for the study. The DIBELS Next's subtests provide three score levels: (<reflink idref="bib1" id="ref1">1</reflink>) <emph>at or above benchmark,</emph> (<reflink idref="bib2" id="ref2">2</reflink>) <emph>below benchmark</emph>, and (<reflink idref="bib3" id="ref3">3</reflink>) <emph>well below benchmark.</emph> Second-grade participants were required to score a minimum of 35 Correct Letter Sounds on the Nonsense Word Fluency (NWF) subtest along with an DIBELS Oral Reading Fluency (DORF) score of less than 51 correct words per minute (CWPM; i.e., <emph>well below benchmark</emph> or <emph>below benchmark</emph>). Each student participant was selected on the basis of his/her teacher's recommendations and the aforementioned screening criteria. See Table 1 for details of the student participants.</p> <p>Participant Information.</p> <p> <ephtml> &lt;table border="1" cellpadding="7"&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td align="left" rowspan="3"&gt;Name&lt;/td&gt;&lt;td align="center" rowspan="3"&gt;Age&lt;sup&gt;a&lt;/sup&gt;&lt;/td&gt;&lt;td align="center" rowspan="3"&gt;Gender&lt;/td&gt;&lt;td align="center" colspan="4"&gt;DIBELS Next Scores BOY&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="center" colspan="2"&gt;Nonsense Word Fluency&lt;/td&gt;&lt;td align="center" colspan="2"&gt;Oral Reading Fluency&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="center"&gt;Raw score&lt;/td&gt;&lt;td align="center"&gt;Score level&lt;/td&gt;&lt;td align="center"&gt;Medium score&lt;/td&gt;&lt;td align="center"&gt;Score level&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td align="left"&gt;Mike&lt;/td&gt;&lt;td align="char"&gt;7-7&lt;/td&gt;&lt;td&gt;M&lt;/td&gt;&lt;td align="char"&gt;48&lt;/td&gt;&lt;td&gt;BB&lt;/td&gt;&lt;td align="char"&gt;16&lt;/td&gt;&lt;td&gt;WBB&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Justice&lt;/td&gt;&lt;td align="char"&gt;7-8&lt;/td&gt;&lt;td&gt;F&lt;/td&gt;&lt;td align="char"&gt;32&lt;/td&gt;&lt;td&gt;WBB&lt;/td&gt;&lt;td align="char"&gt;32&lt;/td&gt;&lt;td&gt;WBB&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Roland&lt;/td&gt;&lt;td align="char"&gt;7-6&lt;/td&gt;&lt;td&gt;M&lt;/td&gt;&lt;td align="char"&gt;42&lt;/td&gt;&lt;td&gt;BB&lt;/td&gt;&lt;td align="char"&gt;33&lt;/td&gt;&lt;td&gt;WBB&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Calvin&lt;/td&gt;&lt;td align="char"&gt;7-2&lt;/td&gt;&lt;td&gt;M&lt;/td&gt;&lt;td align="char"&gt;38&lt;/td&gt;&lt;td&gt;BB&lt;/td&gt;&lt;td align="char"&gt;39&lt;/td&gt;&lt;td&gt;BB&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Simone&lt;/td&gt;&lt;td align="char"&gt;7-5&lt;/td&gt;&lt;td&gt;F&lt;/td&gt;&lt;td align="char"&gt;41&lt;/td&gt;&lt;td&gt;BB&lt;/td&gt;&lt;td align="char"&gt;32&lt;/td&gt;&lt;td&gt;WBB&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt; </ephtml> </p> <p>1 <emph>Note.</emph> DIBELS = Dynamic Indicators of Basic Literacy Skills; BB = below benchmark; WBB = well below benchmark.</p> <p>2 Age: refers to the age of each participant in years and months at the time DIBELS Next beginning of the year (BOY) subtests were administered.</p> <p> <bold>Librarian.</bold> The school's librarian was included as a participant in this study. Her task was to increasingly monitor student participants throughout the study. Her research responsibilities (e.g., providing praise and reviewing student performance) were phased into the study to accommodate her existing work duties. The librarian was required to sign a consent form before participating in the study. The librarian was a paraprofessional (i.e., not credentialed) with 16 years' experience. In addition to managing the library and encouraging students to read, she also instructed four special area classes (e.g., physical education or music) in the all-purpose room. In addition, the librarian assisted with other duties such as student breakfasts and school food drives. The librarian's schedule did not permit her to be present for all of the sessions of this study.</p> <hd id="AN0135649624-7">Settings</hd> <p> <bold>School.</bold> The school was located in an urban area of a large metropolitan city within the U.S. Midwest. The student population was 88.4% African American and 92.3% low-income. The school reported 24.8% chronic absenteeism (i.e., students missing 10% or more of the school year), compared to a 29.3% district rate. The school received a state grade of F on their K-3 Literacy Improvement indicators, with only 50% of third graders passing the state reading assessment compared to the state average of 81%. Study participants came from two second-grade classrooms, consisting of 29 and 27 students with 93% and 89%, respectively, reading below grade level (Fountas &amp; Pinnell, 2006). Reading instruction in both classrooms included whole-group activities and follow-up small-group independent work. According to the teachers, the classroom reading curriculum focused on comprehension strategies delivered through classwide and independent instructional opportunities.</p> <p> <bold>Library.</bold> All study conditions occurred in the school library, which had the available schedule, equipment, and space to accommodate this research project. The library provided a safe and relatively distraction-free environment. The library contained five small circular tables in the middle of the room as well as a larger round computer station in one corner of the room. The computer station had the outlets and space needed for setting up the four RR laptops.</p> <hd id="AN0135649624-8">Materials</hd> <p> <bold>Screening and intervention.</bold> Screening measures consisted of two subtests of the DIBELS Next: NWF and DORF. DIBELS Next is a formative assessment designed to measure basic early literacy skills during a one-minute time for children in kindergarten through third grade (Good &amp; Kaminski, 2011). Assessment procedures prescribed by the DIBELS Next authors were followed.</p> <p>Reliability for the second-grade NWF Correct Letter Sounds was reported as.90, and the NWF Whole Words read was reported as.99. Aggregate reliability for the second-grade DORF Words Correct was reported at.99 and DORF Accuracy was reported as.99. Reliability for DIBELS Next was calculated using alternative-form reliability with a two-week interval (Good et al., 2013, p. 84).</p> <p>RR materials consisted of 38 passages: 26 researcher-developed culturally relevant (CR) passages and corresponding comprehension assessment mazes and up to 12 non-culturally relevant (NCR) passages and mazes taken from AIMSweb (aimsweb.pearson.com).</p> <p> <bold>CR passages.</bold> As part of an ongoing larger study, a research team had created a novel set of CR passages designed to reflect the interests and background of the target population (i.e., young learners in urban communities who display reading and special education risk). The research team developed a total of 30 second-grade passages and corresponding mazes that were validated for readability and cultural relevance. Specific procedures for developing and equating these passages and mazes are detailed elsewhere in the research literature (see Cartledge, Keesey, Bennett, Gallant, &amp; Ramnath, 2015; Council et al., 2016). A total of 26 CR passages were used for this study.</p> <p> <bold>CR maze passages.</bold> Maze comprehension passages were created as part of the larger study to correspond to each of the 26 CR passages (25 CR intervention passages and 1 training passage). In other words, one CR passage was used, before beginning intervention, for the sole purpose of training participants to use the RR intervention. The mazes required students to fill in the missing word to assess the student's understanding of the previously read passage. A fill-in-the-bubble display format for the maze was used and the computer automatically randomized the answer choices and graded student performances.</p> <p> <bold>NCR passages.</bold> The NCR (i.e., generalization passages) were taken from AIMSweb, which is a curriculum-based management system that provides screening and progress monitoring of basic academic (e.g., reading) skills. The researchers viewed these passages as NCR because the narratives were not specific to urban settings or common themes, even though the passages did contain content of interest to this grade level. Passages and corresponding mazes were chosen based on grade-level difficulty (2.4-2.7) as measured by the Spache readability formula (<ulink href="http://www.readabilityformulas.com/free-spache-readability-test.php">http://www.readabilityformulas.com/free-spache-readability-test.php</ulink>). Second-grade AIMSweb passages that did not fall between the 2.4-2.7 range as measured by the Spache readability formula were not included in this study.</p> <p> <bold>Computer hardware.</bold> One Linksys Wireless Broadband Router was used to communicate participant data within the school building. Seven Dell laptop computers were used: One served as a server and the other six operated as stations to deliver both the CR and NCR passages and the intervention. CR and NCR passages and mazes were also presented on the computers. Logitech headsets with microphones were used so that participants could listen to the stories with limited distractions and to allow students' oral reading to be audio-recorded.</p> <p> <bold>RR software.</bold> RR is a computer-assisted intervention designed to deliver a repeated reading intervention to first and second graders. The software allowed students to listen to a human voice model and read along with that model and had the capacity to "listen" to students as they read independently (Bennett et al., 2017). The software package used a set of 25 CR passages and it provided reading remediation (e.g., if a student did not know a word the student could click on the word and the computer would "say" the word), along with pre-teaching and post-teaching features (i.e., presentation and review of non-decodable vocabulary words before student reading). The software also graphed each student's performance. Participants received intervention three to four times a week ranging from 25-30 minutes in duration.</p> <hd id="AN0135649624-9">Dependent variables</hd> <p>The oral reading dependent variable measured CWPM during cold read CR and AIMSweb passages read on the computer. A word was counted correct when a participant accurately pronounced it within three seconds of the previous word being read. A word was counted as incorrect if the participant omitted or mispronounced the word or failed to read it within three seconds. Additions (i.e., adding or repeating a word) and self-corrections were not counted as errors. Corrective feedback was not provided during the timed reading. All CWPM measures were calculated by the RR software and verified by the researcher via retroactive evaluation of permanent product voice recordings.</p> <p>Participant responses during the maze assessment (i.e., CR and AIMSweb) were counted correct only if the answer matched the answer key. The authors' protocol for the DIBELS Next was followed in determining the accuracy of participants' responses.</p> <hd id="AN0135649624-10">Experimental design and conditions</hd> <p>The experimental design was a multiple probe design across participants (Cooper, Heron, &amp; Heward, 2007). This design was implemented to analyze the effects of the RR on the participants' fluency and comprehension of CR and AIMSweb passages.</p> <p> <bold>Pre-baseline.</bold> The librarian was trained by the researchers to use the RR software implementing the same procedures as the researchers. The researchers modeled the appropriate procedures for the librarian as the researchers implemented the study. The librarian participated in one training and one coaching session conducted by the researchers on how to implement the intervention. Before the training session, the librarian was issued a training manual providing both technological and procedures information. The researchers used the training manual to model the intervention and procedures and answer questions proposed by the librarian. Following the training session, the librarian continued the study implementing the program independently under the supervision of the researchers, receiving immediate feedback and coaching. Important features of the training were to increase the librarian's skills (<reflink idref="bib1" id="ref4">1</reflink>) using instructional technology according to student needs and (<reflink idref="bib2" id="ref5">2</reflink>) facilitating reading fluency. Once the librarian reached 100% accuracy using the participant training checklist, she was deemed ready to monitor students using the RR computer software and was gradually phased into the study based on her established job duties. Working with the classroom teachers, the librarian set up a schedule for the participants.</p> <p> <bold>Baseline.</bold> Researchers conducted all baseline activities. Baseline consisted of a series of alternating "cold reads" (i.e., not previously read passages). There were a minimum of three AIMSweb passages and three CR passages delivered on the computer. Participants entered the intervention when they demonstrated a steady state of oral reading fluency during baseline or had descending oral reading fluency data. CR and AIMSweb passages were randomized using random.org. The participant with the lowest stabilized (i.e., steady state) scores entered into the intervention first.</p> <p> <bold>RR student software training.</bold> During the session immediately preceding the intervention, the researchers trained the participants to use the software. A training script was used to ensure procedural fidelity during the training. The researchers instructed each participant, using a model-lead-test instructional format. This instruction followed the same sequence that was expected during intervention. Participants needed to demonstrate 100% accuracy of the procedures including the correct sequence before beginning the study. The CR story (i.e., "When I Grow Up") was used only for training purposes. Training involved oral directions from the researcher and verbal directions preprogrammed in the software.</p> <p>The RR intervention software consisted of the follow sequence, which was employed in previously discussed studies (e.g., Council et al., 2016):</p> <p></p> <ulist> <item> Begin (i.e., the participant reads a novel passage).</item> <p></p> <item> Practice words pre-teaching activity.</item> <p></p> <item> Read to me (i.e., the computer reads the passage to the participant).</item> <p></p> <item> Read along (i.e., the participant reads with the computer).</item> <p></p> <item> Listen to me (i.e., the participant reads independently for up to three one-minute timings with computer assistance for unknown words).</item> <p></p> <item> Timed reading (i.e., one-minute fluency timing).</item> <p></p> <item> Maze comprehension passage.</item> </ulist> <hd id="AN0135649624-11">Social validity</hd> <p> <bold>Librarian and teachers</bold>. The librarian rated the usability of the RR user's manual and completed a post-intervention questionnaire to assess her perceptions of the effectiveness and utility of RR. The teachers completed a questionnaire on their perceptions of the program's value for students.</p> <p> <bold>Participant social validity</bold>. Each participant responded to a post-intervention assessment to determine whether the student liked RR and whether the student felt it helped him/her to become a better reader. A secondary researcher and the librarian orally administered the surveys at the study's conclusion.</p> <hd id="AN0135649624-12">Interobserver agreement (IOA)</hd> <p> <bold>Primary experimenter.</bold> The mean IOA calculations for the five student participants for each phase of intervention were as follows: During baseline the mean agreement was 99.5% (range: 95%-100%). Intervention sessions had a mean agreement of 99.72% (range: 98.14%-100%). For the treatment probes the mean agreement was 99.38% (range: 95%-100%). The generalization probes mean was 99.15% (range: 95.91%-100%), and the maintenance mean was 99.8% (range: 98%-100%).</p> <p>In addition to the primary experimenter, two graduate assistants (GAs) were trained to criterion during all phases of the project (i.e., pretest, baseline, training, treatment, generalization probes, maintenance, and social validity measures). One of the GAs was a first-year master's student and the other was a third-year doctoral candidate. The two GAs and the researcher randomly took turns as the first and second observers for each participant. A second observer was present for at least 70% during pretests, posttests, and experimental conditions for each participant. The breakdown was as follows: 91.7% of pretests and posttests, 83.3% of baseline AIMSweb and CR passages assessments, 72.8% of intervention sessions (i.e., timed readings), 81.2% of treatment probes (i.e., cold reads) and 86.9% of generalization probes. Exact agreement was used, which is agreements divided by the number of agreements plus disagreements and multiplied by 100.</p> <p> <bold>Librarian.</bold> The school librarian (paraprofessional) was trained to use the program and subsequently monitor students who independently (i.e., high procedural fidelity) used the program. The librarian participated in 49.2% of all student interventions with 100% treatment integrity.</p> <hd id="AN0135649624-13">Treatment integrity</hd> <p>Treatment integrity data during this study served three purposes: to verify the behavior integrity of the primary experimenter, the ability of student participants to independently use the software correctly, and the ability of the librarian to monitor the students correctly. In all instances, checklists were used to calculate a percentage of steps completed correctly. The researchers observed all three sets of behavior and completed a treatment integrity checklist for at least 33% of the sessions.</p> <p> <bold>Participants.</bold> The researchers evaluated the participants' ability to independently follow software procedures. During the RR intervention, a checklist was used to assess the students' treatment integrity across 98.1% of the sessions. A second observer was present during at least 33.3% of the sessions. The aggregated means according to the researchers revealed that participants followed 96.26% of the computer directions (individual participants' mean scores ranged from 90% to 100%). All participants consistently scored at or above 90% on the procedural integrity checklist, demonstrating that they operated the software with a high degree of procedural fidelity.</p> <hd id="AN0135649624-14">Results</hd> <p></p> <hd id="AN0135649624-15">Reading growth measures</hd> <p> <bold>DIBELS Next.</bold> Table 2 presents the DIBELS Next benchmark assessments taken three times (beginning, middle, and end) of the school year for all the participants. Except for Mike, these data reveal steady progress, although none of the participants were able to improve their end-of-year level of risk. In addition, the students averaged 10 more CWPM during maintenance compared to intervention and more than 4 correct maze responses in intervention over baseline.</p> <p>DIBELS Next scores on oral reading fluency for beginning (BOY), middle (MOY), and end of the year (EOY).</p> <p> <ephtml> &lt;table border="1" cellpadding="9"&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td rowspan="2"&gt;Name&lt;/td&gt;&lt;td align="center" colspan="2"&gt;BOY&lt;/td&gt;&lt;td align="center" colspan="2"&gt;MOY&lt;/td&gt;&lt;td align="center" rowspan="2"&gt;(Percentage growth from BOY)&lt;/td&gt;&lt;td align="center" colspan="2"&gt;EOY&lt;/td&gt;&lt;td align="center" rowspan="2"&gt;(Percentage growth from BOY)&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td&gt;Raw median score&lt;/td&gt;&lt;td&gt;Risk level&lt;/td&gt;&lt;td&gt;Raw median score&lt;/td&gt;&lt;td&gt;Risk level&lt;/td&gt;&lt;td&gt;Raw median score&lt;/td&gt;&lt;td&gt;Risk level&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td align="left"&gt;Mike&lt;/td&gt;&lt;td align="char"&gt;16&lt;/td&gt;&lt;td&gt;WBB&lt;/td&gt;&lt;td align="char"&gt;47&lt;/td&gt;&lt;td&gt;WBB&lt;/td&gt;&lt;td align="char"&gt;193.8%&lt;/td&gt;&lt;td align="char"&gt;37&lt;/td&gt;&lt;td&gt;WBB&lt;/td&gt;&lt;td align="char"&gt;131.3%&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Justice&lt;/td&gt;&lt;td align="char"&gt;32&lt;/td&gt;&lt;td&gt;WBB&lt;/td&gt;&lt;td align="char"&gt;39&lt;/td&gt;&lt;td&gt;WBB&lt;/td&gt;&lt;td align="char"&gt;21.9%&lt;/td&gt;&lt;td align="char"&gt;44&lt;/td&gt;&lt;td&gt;WBB&lt;/td&gt;&lt;td align="char"&gt;37.5%&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Roland&lt;/td&gt;&lt;td align="char"&gt;33&lt;/td&gt;&lt;td&gt;WBB&lt;/td&gt;&lt;td align="char"&gt;44&lt;/td&gt;&lt;td&gt;WBB&lt;/td&gt;&lt;td align="char"&gt;33.3%&lt;/td&gt;&lt;td align="char"&gt;47&lt;/td&gt;&lt;td&gt;WBB&lt;/td&gt;&lt;td align="char"&gt;42.4%&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Calvin&lt;/td&gt;&lt;td align="char"&gt;39&lt;/td&gt;&lt;td&gt;BB&lt;/td&gt;&lt;td align="char"&gt;43&lt;/td&gt;&lt;td&gt;WBB&lt;/td&gt;&lt;td align="char"&gt;10.3%&lt;/td&gt;&lt;td align="char"&gt;60&lt;/td&gt;&lt;td&gt;WBB&lt;/td&gt;&lt;td align="char"&gt;53.8%&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Simone&lt;/td&gt;&lt;td align="char"&gt;32&lt;/td&gt;&lt;td&gt;WBB&lt;/td&gt;&lt;td align="char"&gt;39&lt;/td&gt;&lt;td&gt;WBB&lt;/td&gt;&lt;td align="char"&gt;30.3%&lt;/td&gt;&lt;td align="char"&gt;64&lt;/td&gt;&lt;td&gt;WBB&lt;/td&gt;&lt;td align="center"&gt;100%&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt; </ephtml> </p> <p>3 <emph>Note.</emph> DIBELS = Dynamic Indicators of Basic Literacy Skills; WBB = well below benchmark; BB = below benchmark.</p> <p> <bold>Tau-<emph>U</emph>.</bold> Tau-<emph>U</emph> was used to calculate effect size for each participant. Tau-<emph>U</emph> is an estimate of the percentage of data that shows improvement between phases (Parker, Vannest, Davis, &amp; Sauber, 2011; Rakap, 2015). For multiple probe designs, Tau-<emph>U</emph> is calculated for each participant's baseline and intervention phase to get an individual Tau-<emph>U</emph> value. The effect size across all participants is calculated by averaging the individual Tau-<emph>U</emph> scores (Rakap, 2015). Tau-<emph>U</emph> effect size values can be interpreted as follows: 65% or lower, small effect; between 66% and 92%, medium effect; and 93% or higher, large effect (Parker &amp; Vannest, 2009). Table 3 shows that each participant demonstrated medium to large effect sizes for reading fluency and comprehension with the exception of Mike's CR Maze, Justice's AIMSweb Maze, and Roland's CR Passages. Individual participant results on other measures are discussed below.</p> <p>Tau-U effect size for reading fluency and comprehension.</p> <p> <ephtml> &lt;table border="1" cellpadding="5"&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td align="left"&gt;Student&lt;/td&gt;&lt;td align="center"&gt;Tau-&lt;italic&gt;U&lt;/italic&gt; CR passages&lt;/td&gt;&lt;td align="center"&gt;Tau-&lt;italic&gt;U&lt;/italic&gt; CR mazes&lt;/td&gt;&lt;td align="center"&gt;Tau-&lt;italic&gt;U&lt;/italic&gt; AIMSweb passages&lt;/td&gt;&lt;td align="center"&gt;Tau-&lt;italic&gt;U&lt;/italic&gt; AIMSweb mazes&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td align="left"&gt;Mike&lt;/td&gt;&lt;td align="center"&gt;1.0&lt;/td&gt;&lt;td align="center"&gt;.49&lt;/td&gt;&lt;td align="center"&gt;.90&lt;/td&gt;&lt;td align="center"&gt;.90&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left" /&gt;&lt;td align="center"&gt;Large&lt;/td&gt;&lt;td align="center"&gt;Small&lt;/td&gt;&lt;td align="center"&gt;Medium&lt;/td&gt;&lt;td align="center"&gt;Medium&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Justice&lt;/td&gt;&lt;td align="center"&gt;.80&lt;/td&gt;&lt;td align="center"&gt;.90&lt;/td&gt;&lt;td align="center"&gt;1.0&lt;/td&gt;&lt;td align="center"&gt;0&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left" /&gt;&lt;td align="center"&gt;Medium&lt;/td&gt;&lt;td align="center"&gt;Medium&lt;/td&gt;&lt;td align="center"&gt;Large&lt;/td&gt;&lt;td align="center"&gt;Small&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Roland&lt;/td&gt;&lt;td align="center"&gt;.57&lt;/td&gt;&lt;td align="center"&gt;1.0&lt;/td&gt;&lt;td align="center"&gt;.74&lt;/td&gt;&lt;td align="center"&gt;.67&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left" /&gt;&lt;td align="center"&gt;Small&lt;/td&gt;&lt;td align="center"&gt;Large&lt;/td&gt;&lt;td align="center"&gt;Medium&lt;/td&gt;&lt;td align="center"&gt;Medium&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Simone&lt;/td&gt;&lt;td align="center"&gt;1.0&lt;/td&gt;&lt;td align="center"&gt;.96&lt;/td&gt;&lt;td align="center"&gt;.75&lt;/td&gt;&lt;td align="center"&gt;.67&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left" /&gt;&lt;td align="center"&gt;Large&lt;/td&gt;&lt;td align="center"&gt;Large&lt;/td&gt;&lt;td align="center"&gt;Medium&lt;/td&gt;&lt;td align="center"&gt;Medium&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Calvin&lt;/td&gt;&lt;td align="center"&gt;.96&lt;/td&gt;&lt;td align="center"&gt;1.0&lt;/td&gt;&lt;td align="center"&gt;.78&lt;/td&gt;&lt;td align="center"&gt;1.0&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left" /&gt;&lt;td align="center"&gt;Large&lt;/td&gt;&lt;td align="center"&gt;Large&lt;/td&gt;&lt;td align="center"&gt;Medium&lt;/td&gt;&lt;td align="center"&gt;Large&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Weighted average&lt;/td&gt;&lt;td align="center"&gt;.86&lt;/td&gt;&lt;td align="center"&gt;.88&lt;/td&gt;&lt;td align="center"&gt;.84&lt;/td&gt;&lt;td align="center"&gt;.66&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left" /&gt;&lt;td align="center"&gt;Medium&lt;/td&gt;&lt;td align="center"&gt;Medium&lt;/td&gt;&lt;td align="center"&gt;Medium&lt;/td&gt;&lt;td align="center"&gt;Medium&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt; </ephtml> </p> <p>4 <emph>Note</emph>. Small effect =.65 and lower; medium effect =.66-.92; large effect =.93 and higher.</p> <hd id="AN0135649624-16">Mike</hd> <p>During baseline Mike obtained a mean fluency score of 17.5 (range: 16-19) for CR passages and increased his fluency mean to 40.9 CWPM (range: 26-62) in the intervention, which was 133% over baseline. Similarly, on the AIMSweb generalization passages, Mike averaged 22.7 (range: 18-26) CWPM during baseline but increased by 74.3% to a mean of 39.4 (range: 28-55) during the intervention (see Figure 1). Mike showed comparable progress on his maze comprehension scores, moving from a baseline mean of 1.0 (range: 0-2) to an intervention mean of 11.8 (range: 9-16) for CR passages. Likewise, on the generalization AIMSweb passages Mike improved 170% from a baseline mean of 2.7 (range: 1-4) to an intervention mean of 7.2 (range: 4-10). Mike's maintenance generalization means for both fluency (<reflink idref="bib49" id="ref6">49</reflink>) and comprehension (<reflink idref="bib10" id="ref7">10</reflink>) exceeded baseline and intervention averages (see Figures 1 and 2).</p> <p>PHOTO (COLOR): Figure 1. Correct words per minute per session.</p> <p>PHOTO (COLOR): Figure 2. Correct responses to maze comprehension per session.</p> <hd id="AN0135649624-17">Justice</hd> <p>During baseline, Justice averaged 25 (range: 14-34) CWPM and improved that average to 44.7 CWPM (range: 19-65) during the intervention, for a 78.8% increase. For fluency on the AIMSweb generalization passages, Justice had a baseline average of 25 CWPM (range: 15-32) that increased 72% during intervention to 43 (range: 35-48). Justice's two AIMSweb fluency maintenance probes were 59 and 58, which were higher than her baseline and intervention averages (see Figure 1). For the comprehension mazes, Justice averaged 4.2 correct responses (range: 1-6) during baseline, which increased to an intervention mean of 12.04 (range: 5-19). The AIMSweb maintenance comprehension maze showed little change, with an average of eight correct responses for baseline, intervention, and maintenance (see Figure 2).</p> <hd id="AN0135649624-18">Roland</hd> <p>Roland went from a mean baseline fluency score of 39 (range: 37-43) to a mean intervention score of 52.7 CWPM (range: 23-71), for a 35.1% increase over baseline. Similar gains occurred for the AIMSweb generalization measures, averaging at baseline 34 CWPM (range: 27-37) and making a 27.1% increase to average 43.2 (range: 32-54) during intervention. Roland obtained even higher maintenance scores of 54 and 78 CWPM (see Figure 1). For the comprehension maze, Roland averaged 8.7 correct responses (range: 8-9) at baseline and improved to an average of 15.8 (range: 11-21) during the intervention. The generalization AIMSweb mazes showed similar improvements, moving from a baseline average of 8 correct responses (range: 3-13), increasing by 53.8% to a mean of 12.3 (range: 10-14) during intervention, and showing maintenance scores of 16 and 15 correct (see Figure 2).</p> <hd id="AN0135649624-19">Simone</hd> <p>During baseline, Simone had a mean fluency score of 36 CWPM (range: 26-36) that increased to a mean intervention score of 62.6 CWPM (range: 49-85), showing 73.9% growth over baseline. The AIMSweb generalization passages showed similar growth, moving from a baseline mean of 36.8 (range: 29-42) to an intervention mean of 57 (range: 46-65), for a 54.9% increase over baseline. Fluency scores of 78 and 71 were recorded for maintenance (see Figure 1). Simone's data for CR maze comprehension show a baseline mean of 3.3 correct responses (range: 1-5), which improved to 11.3 (range: 9-15) in the intervention. Simone's AIMSweb comprehension generalization data paralleled the CR maze passages beginning with a baseline mean of 5 correct responses (range: 2-8) and improving to an intervention mean of 11.3 (range: 9-15), for a 126% increase. For maintenance probes, Simone scored 17 and 7 correct responses, respectively (see Figure 2).</p> <hd id="AN0135649624-20">Calvin</hd> <p>Calvin scored 32.3 CWPM (range: 22-43) at baseline. His mean score increased in the intervention to 61.6 CWPM (range: 33-80), for a 90.7% growth over baseline. Calvin's data on AIMSweb generalization showed a baseline mean of 43.8 (range: 37-50) and an intervention mean of 56.3 (range: 44-64), for a 74.3% increase. Maintenance probe scores were 48 and 74 CWPM. The maze comprehension scores showed a baseline mean of 2.7 (range: 2-3) that improved to an intervention mean of 12.8 (range: 8-20). The AIMSweb generalization revealed baseline mean scores of 2.7 (range: 1-4), which increased to a mean of 7.2 (range: 4-10) during intervention for a 28.5% growth. For maintenance probes, Calvin scored 9 and 18 correct responses, respectively (see Figure 2).</p> <hd id="AN0135649624-21">Discussion</hd> <p></p> <hd id="AN0135649624-22">Student reading achievement</hd> <p>Each participant was assessed using DIBELS' beginning of the year (BOY) through end of the year (EOY) assessment. All of the participants with the exception of Mike (slight decline MOY to EOY) made steady gains on their DORF assessments from the BOY through the EOY (see Table 2). Although none of the participants moved out of the "well below benchmark" category, it is noteworthy that the second-grade students began the study assessed at early first-grade reading levels and completed the study indicating ending first-grade or early second-grade levels. This suggests approximately one-half to one-year fluency growth. This is particularly noteworthy for Simone and Calvin, who received considerably less treatment but made much greater and more pronounced improvement than their lower-performing peers. This is evident in Figure 1, which shows that the fluency data for Simone and Calvin quickly and steadily accelerated once the intervention began. Simone's data, with no overlapping baseline-intervention points, are especially impressive. Further, a review of the scores in Table 2 show alignment and thus comparable performance for the AIMSweb, CR, and DORF scores.</p> <p>Despite their obvious gains, none of the students made two years' progress to reach EOY second-grade goals (e.g., 90 to 120 CWPM). These findings reflect the work of Wanzek, Al Otaiba, and Petscher (2014), who compared the oral reading fluency growth of students in general education to those with specific learning disabilities (SLD) and with emotional behavioral disorders (EBD). One important finding was that students with disabilities made progress in reading, but the amount of progress was not commensurate with their general education peers. That is, despite gains, they continued to perform at the "deficit" level—where they make progress but never catch up. Although the students with disabilities in this study were compared to their non-disabled peers, the dismal prognosis of Wanzek et al. (2014) probably will be realized if interventions are terminated. This is especially the case for the lower-performing students (i.e., Justice, Roland, and Mike). Indicated in this study is the need for highly intensive and extensive interventions to attain desired goals for children with significant reading risk. For some students, interventions may need to take place in earlier grades (e.g., kindergarten) and to be protracted, occurring over several years or throughout their schooling to help them become proficient readers. On the other hand, students such as Simone and Calvin with higher response rates may only need periodic boosters once desired levels of responding are achieved.</p> <p>In addition to systematic, intensive instruction, we found that some students needed more external incentives to maintain academic engagement. Simone, for example, started a downward trend of responding, but when the researchers tied her performance to rewards such as additional stickers, there was an immediate improvement in her scores (see third AIMSweb probe in Figure 1). Although cause and effect can only be speculated, the improved scores continued along with the reinforcement contingencies.</p> <p>All student participants were able to maintain their fluency growth as assessed with the two-week and one-month AIMSweb maintenance check. The only exception was Calvin, who seemed extremely anxious during his two-week maintenance probe. He expressed excitement to the researcher, stating that he wanted to set his goal at 105 CWPM, but he lost his place multiple times while reading and rereading sentences that he had already read correctly. Anxiety also may have been a factor in the variability in his novel CR generalization probes early during intervention.</p> <p>The maze comprehension measures indicated that all five students made steady gains in their abilities to comprehend read materials. One exception was Roland, who began a downward trend midway through the intervention but then recovered to show substantial improvements over baseline levels for both AIMSweb and CR assessments. Another exception was Justice, whose variable maze scores showed no gains on the AIMSweb measures. Roland and Justice initially employed a fast guessing strategy that would enable them to complete more items and get a higher score. This was evidenced by their testimony when probed by the researcher. As their fluency improved, they were less inclined to guess and spent more time reading before responding. Although their scores appeared to decline when they were responding purposefully, the latter scores more accurately reflected their comprehension. Such strategies for maze completion are not uncommon, leading some researchers to recommend multiple assessments to determine more accurately students' ability to comprehend (January &amp; Ardoin, 2012). The comprehension gains obtained in this fluency study are consistent with those found elsewhere in the fluency training research literature (e.g., Strickland et al, 2013; Therrien, 2004). Despite the previously noted variability and below-benchmark findings, overall, the mostly median to large effect sizes calculated with the Tau-<emph>U</emph> indicate the benefit of this intervention on the fluency and comprehension of these students.</p> <hd id="AN0135649624-23">Librarian</hd> <p>The librarian responded positively to the project and although her other duties limited her ability to monitor the majority of the interventions, the evidence showed that she was both capable and proficient in using RR to benefit the students. As noted, the librarian executed all steps of the treatment with integrity, but because other duties prevented her from independently carrying out the interventions, her impact on pupil outcomes is inconclusive. Our findings, however, do support other researchers' position that trained personnel are more likely to execute empirically validated procedures with a high degree of fidelity (Greenwood, 2009; Harn et al., 2013; Kaderavek &amp; Justice, 2010).</p> <hd id="AN0135649624-24">Social validity</hd> <p> <bold>Students</bold>. The students indicated that they enjoyed using RR and felt that their classmates also would enjoy the program. They specified that they liked seeing their scores improve and that they became more confident, better readers. The male participants expressed heightened interest in the program because of the computer technology.</p> <p> <bold>Librarian.</bold> The librarian responded favorably to the RR questionnaire because she felt it was user-friendly and engaging for the students and enabled students to improve in reading fluency.</p> <p> <bold>Teachers.</bold> On their questionnaires, the two classroom teachers indicated that they felt all of their participants improved in reading throughout the intervention and enjoyed using RR. They further stated that they felt that RR made a positive impact on their students' reading and would recommend continuing the program.</p> <hd id="AN0135649624-25">Limitations</hd> <p>The goal of this intervention was not to completely eliminate adult supervision but to reduce the need so that school personnel could use RR without creating a vastly increased teacher workload. In this study, humans (i.e., researchers and the librarian) were necessary to support the program with error correction (e.g., missed words and omissions) and minor glitches in the software (i.e., errors with the human-generated recordings or highlighting), limiting how and where the software can be used in a school setting. Although the computer evidenced reliability in all procedural components of the software (i.e., accurate timings, responses to appropriate actions), the ability to provide immediate error corrections remains an essential innovation to move RR to a position for more independent use.</p> <p>An additional limitation of the study was the sensitivity of the procedural integrity checklist for the participants. All participants (i.e., students and librarian) were able to execute the procedures of the study with a high degree of fidelity (i.e., 90% or higher), but checklists were limited in how they assessed verbal, physical, temporal, and special parameters (Lane et al., 2004). Examining additional features of participant interactions with the intervention could provide invaluable insight to improve future iterations of the program.</p> <p>It is also critical to acknowledge that not all students will be able to use the program independently regardless of the technological innovation. Students who are more prone to off-task behavior will require adult supervision to ensure that they execute the program with procedural integrity. Although research suggests that CAI increases motivation for learners (Musti-Rao et al., 2015), some students will require additional reinforcement in the form of human attention and praise to give their maximum effort. Data also revealed that certain students could benefit from extended participation in the program, but RR is currently only designed to deliver 25 CR intervention stories. Future studies should expand CR content and evaluate the effects of extended intervention for students.</p> <p>Limitations relative to the construction of the intervention need to be noted. For some students, the use of mazes (which were vulnerable to guessing/fatigue), at least initially, may have skewed the findings for the comprehension assessments. Another observation was that repeated reading interventions provide multiple exposures to a text, thus increasing the likelihood that learners' sight word vocabulary will improve through those extra encounters with vocabulary (Roberts, Torgesen, Boardman, &amp; Scammacca, 2008). Unfortunately, there is limited research to support the vocabulary transfer of untrained words (Thaler, Ebner, Wimmer, &amp; Landerl, 2004). The current study focused on the cultural sensitivity of the text but gave little attention to the vocabulary and frequency of word overlap across passages.</p> <p>Last, despite the positive participant and teacher feedback, the researchers need to take into consideration the possible influence of rewards such as stickers for children and positive relationships the school personnel/students had with the researchers.</p> <hd id="AN0135649624-26">Conclusion</hd> <p>The findings of this study support previous research evaluating the positive effects of RR on the reading fluency and comprehension of second-grade students with reading risk within an urban school (Bennett et al., 2017). The data on student achievement measures (i.e., ORF and comprehension) demonstrated a functional relation between RR and their reading outcomes. Procedural integrity data provided support for the utility and benefits of RR for both school personnel and students with reading needs. Student participants demonstrated the ability to navigate the software with little assistance. The students responded favorably to the RR one-to-one instruction and the immediate feedback of improved performance. RR used an evidence-based strategy (i.e., repeated readings) paired with culturally relevant pedagogy to deliver a tier-two individualized reading intervention. This software can serve as an instructional resource for students who attend schools with limited resources. The question remains whether the RR technology can be advanced further to greatly minimize school personnel supervision with reading benefits for students. More development and study are warranted.</p> <hd id="AN0135649624-27">Notes on contributors</hd> <p> <emph>Morris R. Council, III</emph> is an assistant professor at the University of West Georgia in the Department of Literacy and Special Education. His research interests are instructional interventions for improving academic outcomes culturally and linguistically diverse individuals who are at risk for school failure and individuals with diagnosed high-incidence disabilities.</p> <p> <emph>Ralph Gardner, III</emph>, Ph.D. is an Emeritus Professor of Special Education/Applied Behavior Analysis at The Ohio State University in the Department of Educational Studies. Dr. Gardner's research focuses on instructional interventions for improving academic outcomes for urban children who are at risk for school failure and children with mild/moderate disabilities. Dr. Gardner's research has appeared in some of the field's leading peer-reviewed journals. Dr. Gardner has received several awards for teaching excellence from The Ohio State University, including the Alumni Distinguished Teaching Award (highest teaching award at the university). He has been invited to present at U.S. and international universities on academic instructional practices, special education, and multicultural issues.</p> <p> <emph>Gwendolyn Cartledge</emph> is professor emeritus at The Ohio State University, College of Education and Human Ecology, Department of Educational Studies. She documents an extensive teaching career in both the public schools and higher education. A faculty member at OSU since 1986, her professional research and writings have centered on the social and academic skills of children with and without disabilities including those from culturally/linguistically diverse backgrounds. Her writings have included over 70 journal articles, 4 books, over 27 chapters and monographs, over 150 national/international presentations, and 2 curricula. She also has served as principal investigator on several nationally and locally funded grants researching these topics.</p> <p> <emph>Alana O. Telesman</emph>, M.A. has taught students with wide ranges of high incidence disabilities as well as consulted with various school districts to improve reading instruction for students with reading challenges. She is currently pursuing her doctorate at The Ohio State University with a dual degree in Applied Behavior Analysis and Special Education. Alana has conducted various research studies in high poverty schools to provide early reading intervention for struggling learners.</p> <ref id="AN0135649624-28"> <title> References </title> <blist> <bibl id="bib1" idref="ref1" type="bt">1</bibl> <bibtext> Barber, M., Cartledge, G., Council, M., Konrad, M., Gardner, R., &amp; Telesman, A. O. ( 2018 ). The effects of computer-assisted culturally relevant repeated readings on English learners. 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| Items | – Name: Title Label: Title Group: Ti Data: Improving Reading within an Urban Elementary School: Computerized Intervention and Paraprofessional Factors – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Council%2C+Morris+R%2E%2C+III%22">Council, Morris R., III</searchLink><br /><searchLink fieldCode="AR" term="%22Gardner%2C+Ralph%2C+III%22">Gardner, Ralph, III</searchLink><br /><searchLink fieldCode="AR" term="%22Cartledge%2C+Gwendolyn%22">Cartledge, Gwendolyn</searchLink><br /><searchLink fieldCode="AR" term="%22Telesman%2C+Alana+O%2E%22">Telesman, Alana O.</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="SO" term="%22Preventing+School+Failure%22"><i>Preventing School Failure</i></searchLink>. 2019 63(2):162-174. – Name: Avail Label: Availability Group: Avail Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals – Name: PeerReviewed Label: Peer Reviewed Group: SrcInfo Data: Y – Name: Pages Label: Page Count Group: Src Data: 13 – Name: DatePubCY Label: Publication Date Group: Date Data: 2019 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Journal Articles<br />Reports - Research – Name: Audience Label: Education Level Group: Audnce Data: <searchLink fieldCode="EL" term="%22Early+Childhood+Education%22">Early Childhood Education</searchLink><br /><searchLink fieldCode="EL" term="%22Elementary+Education%22">Elementary Education</searchLink><br /><searchLink fieldCode="EL" term="%22Grade+2%22">Grade 2</searchLink><br /><searchLink fieldCode="EL" term="%22Primary+Education%22">Primary Education</searchLink> – Name: Subject Label: Descriptors Group: Su Data: <searchLink fieldCode="DE" term="%22Reading+Improvement%22">Reading Improvement</searchLink><br /><searchLink fieldCode="DE" term="%22Reading+Instruction%22">Reading Instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Urban+Schools%22">Urban Schools</searchLink><br /><searchLink fieldCode="DE" term="%22Culturally+Relevant+Education%22">Culturally Relevant Education</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Software%22">Computer Software</searchLink><br /><searchLink fieldCode="DE" term="%22Intervention%22">Intervention</searchLink><br /><searchLink fieldCode="DE" term="%22Oral+Reading%22">Oral Reading</searchLink><br /><searchLink fieldCode="DE" term="%22Reading+Fluency%22">Reading Fluency</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Assisted+Instruction%22">Computer Assisted Instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Repetition%22">Repetition</searchLink><br /><searchLink fieldCode="DE" term="%22Grade+2%22">Grade 2</searchLink><br /><searchLink fieldCode="DE" term="%22Elementary+School+Students%22">Elementary School Students</searchLink><br /><searchLink fieldCode="DE" term="%22At+Risk+Students%22">At Risk Students</searchLink><br /><searchLink fieldCode="DE" term="%22Reading+Comprehension%22">Reading Comprehension</searchLink><br /><searchLink fieldCode="DE" term="%22Librarians%22">Librarians</searchLink><br /><searchLink fieldCode="DE" term="%22Paraprofessional+School+Personnel%22">Paraprofessional School Personnel</searchLink><br /><searchLink fieldCode="DE" term="%22School+Libraries%22">School Libraries</searchLink><br /><searchLink fieldCode="DE" term="%22Emergent+Literacy%22">Emergent Literacy</searchLink><br /><searchLink fieldCode="DE" term="%22Reading+Tests%22">Reading Tests</searchLink> – Name: Subject Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Ohio+%28Columbus%29%22">Ohio (Columbus)</searchLink> – Name: SubjectThesaurus Label: Assessment and Survey Identifiers Group: Su Data: <searchLink fieldCode="SU" term="%22Dynamic+Indicators+of+Basic+Early+Literacy+Skills+%28DIBELS%29%22">Dynamic Indicators of Basic Early Literacy Skills (DIBELS)</searchLink> – Name: DOI Label: DOI Group: ID Data: 10.1080/1045988X.2018.1540392 – Name: ISSN Label: ISSN Group: ISSN Data: 1045-988X – Name: Abstract Label: Abstract Group: Ab Data: Reading RACES--Relevant and Culturally Engaging Stories (RR) is a repeated reading intervention using culturally relevant literature that is delivered through computer software. This study extends previous research with RR intended to further evaluate the effects of RR on the fluency and comprehension growth of second-grade students with reading risk within an urban setting. A second focus was to determine the degree to which paraprofessional school personnel could successfully implement the intervention. Five second graders and the school librarian (paraprofessional) participated in this study. A multiple baseline probe across participants revealed a functional relation between RR and student participants' gains in oral reading fluency and comprehension. Procedural integrity data also revealed that participants (i.e., students and librarian) were able to use and monitor the program with integrity to the maximum extent enabled by the technology. These findings extend the research base for RR. Limitations and directions for future research are discussed. – Name: AbstractInfo Label: Abstractor Group: Ab Data: As Provided – Name: DateEntry Label: Entry Date Group: Date Data: 2019 – Name: AN Label: Accession Number Group: ID Data: EJ1210677 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/1045988X.2018.1540392 Languages: – Text: English PhysicalDescription: Pagination: PageCount: 13 StartPage: 162 Subjects: – SubjectFull: Reading Improvement Type: general – SubjectFull: Reading Instruction Type: general – SubjectFull: Urban Schools Type: general – SubjectFull: Culturally Relevant Education Type: general – SubjectFull: Computer Software Type: general – SubjectFull: Intervention Type: general – SubjectFull: Oral Reading Type: general – SubjectFull: Reading Fluency Type: general – SubjectFull: Computer Assisted Instruction Type: general – SubjectFull: Repetition Type: general – SubjectFull: Grade 2 Type: general – SubjectFull: Elementary School Students Type: general – SubjectFull: At Risk Students Type: general – SubjectFull: Reading Comprehension Type: general – SubjectFull: Librarians Type: general – SubjectFull: Paraprofessional School Personnel Type: general – SubjectFull: School Libraries Type: general – SubjectFull: Emergent Literacy Type: general – SubjectFull: Reading Tests Type: general – SubjectFull: Ohio (Columbus) Type: general – SubjectFull: Dynamic Indicators of Basic Early Literacy Skills (DIBELS) Type: general Titles: – TitleFull: Improving Reading within an Urban Elementary School: Computerized Intervention and Paraprofessional Factors Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Council, Morris R., III – PersonEntity: Name: NameFull: Gardner, Ralph, III – PersonEntity: Name: NameFull: Cartledge, Gwendolyn – PersonEntity: Name: NameFull: Telesman, Alana O. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2019 Identifiers: – Type: issn-print Value: 1045-988X Numbering: – Type: volume Value: 63 – Type: issue Value: 2 Titles: – TitleFull: Preventing School Failure Type: main |
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