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Testing Variations in Sublexical Units to Improve Word Reading for Students with Word Reading Disabilities

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Title: Testing Variations in Sublexical Units to Improve Word Reading for Students with Word Reading Disabilities
Language: English
Authors: Alexis N. Boucher (ORCID 0000-0001-8719-4415), Nathan H. Clemens (ORCID 0000-0002-8361-1303), Sharon Vaughn (ORCID 0000-0001-8305-5549), Greg Roberts (ORCID 0000-0002-7680-8757), Marcia A. Barnes (ORCID 0000-0002-9446-3000)
Source: Annals of Dyslexia. 2025 75(2):199-224.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 26
Publication Date: 2025
Sponsoring Agency: Institute of Education Sciences (ED)
Contract Number: R324A200209
Document Type: Journal Articles
Reports - Research
Education Level: Elementary Education
Early Childhood Education
Grade 3
Primary Education
Grade 2
Grade 4
Intermediate Grades
Descriptors: Reading Difficulties, Reading Instruction, Students with Disabilities, Elementary School Students, Grade 3, Grade 2, Grade 4, Instructional Effectiveness, Vocabulary
DOI: 10.1007/s11881-025-00332-3
ISSN: 0736-9387
1934-7243
Abstract: Word reading disabilities (WRD) represent the most common disability in reading; however, questions remain regarding how to design instruction that results in significant, long-lasting effects on word reading outcomes for individuals who experience considerable difficulties that persist within and beyond primary grades. Two related studies examined effects of variations in targeted sublexical content on word reading efficiency of students in grades 2-4 with WRD. Study 1 addressed effects of instruction and practice targeting complex vs. simple letter units. Study 2 addressed effects of instruction and practice targeting multiple pronunciations of a letter unit vs. standard pronunciations alone. In Study 1, statistically significant differences at posttest on taught ([beta]=9.43, t(56)=2.32, p=0.02; g=0.17, 95\% CI[0.01,0.33]) words included in Aligned Word Lists favored the complex letter unit condition. In Study 2, statistically significant differences at posttest on taught words included in Aligned Word Lists favored the standard pronunciations condition ([beta]=-4.15, t(60)=-2.04, p=0.045; g=-0.18, 95\% CI[-0.35,0.004]) and group differences in average student performance were non-significant on untaught words ([beta]=-0.22, t(60)=-0.06, p=0.96; g=-0.01, 95\% CI-0.17,0.17]). Given the modest sample sizes (N = 64) and amount of instruction provided in each study (i.e., 6 lessons), further research is warranted to better understand the impact of variations in targeted sublexical content on word reading outcomes for students with WRD in grades 2-4.
Abstractor: As Provided
IES Funded: Yes
Entry Date: 2025
Accession Number: EJ1476426
Database: ERIC
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  Value: <anid>AN0186465936;bm501jul.25;2025Jul10.06:08;v2.2.500</anid> <title id="AN0186465936-1">Testing variations in sublexical units to improve word reading for students with word reading disabilities </title> <p>Word reading disabilities (WRD) represent the most common disability in reading; however, questions remain regarding how to design instruction that results in significant, long-lasting effects on word reading outcomes for individuals who experience considerable difficulties that persist within and beyond primary grades. Two related studies examined effects of variations in targeted sublexical content on word reading efficiency of students in grades 2–4 with WRD. Study 1 addressed effects of instruction and practice targeting complex vs. simple letter units. Study 2 addressed effects of instruction and practice targeting multiple pronunciations of a letter unit vs. standard pronunciations alone. In Study 1, statistically significant differences at posttest on taught ( β = 9.43 , t 56 = 2.32 , p = 0.02 ; g = 0.17 , 95 \% CI [ 0.01 , 0.33 ]) and untaught β = 8.44 , t 56 = 2.09 , p = 0.04 ; g = 0.15 , 95 \% CI [ - 0.01 , 0.31 ] words included in Aligned Word Lists favored the complex letter unit condition. In Study 2, statistically significant differences at posttest on taught words included in Aligned Word Lists favored the standard pronunciations condition (β = - 4.15 , t 60 = - 2.04 , p = 0.045 ; g = - 0.18 , 95 \% CI [ - 0.35 , 0.004 ]) and group differences in average student performance were non-significant on untaught words β = - 0.22 , t 60 = - 0.06 , p = 0.96 ; g = - 0.01 , 95 \% CI - 0.17 , 0.17. Given the modest sample sizes (N = 64) and amount of instruction provided in each study (i.e., 6 lessons), further research is warranted to better understand the impact of variations in targeted sublexical content on word reading outcomes for students with WRD in grades 2–4.</p> <p>Keywords: Dyslexia; Elementary; Intervention; Word reading</p> <p>Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s11881-025-00332-3.</p> <p>Difficulties reading words accurately and efficiently are primary challenges of learning to read and the defining characteristic of word reading disability (WRD), the most prevalent form of disability in the school-age population (Xia et al., [<reflink idref="bib104" id="ref1">104</reflink>]; Yang et al., [<reflink idref="bib105" id="ref2">105</reflink>]). Persistent word reading difficulties are a primary reason for problems in reading comprehension (Shankweiler et al., [<reflink idref="bib77" id="ref3">77</reflink>]) and are associated with long-term avoidance of reading and low academic achievement (Cunningham & Stanovich, [<reflink idref="bib17" id="ref4">17</reflink>]).</p> <p>Research from the last several decades points to intervention elements associated with improved reading skills for students with WRD. For example, evidence supports the use of explicit phonics instruction that teaches students the links between letter(s) and pronunciations (i.e., grapheme-phoneme correspondences) and how to use that information to read words (i.e., decoding), integrating spelling (i.e., encoding) activities, and extensive opportunities to read words and text (Al Otaiba et al., [<reflink idref="bib1" id="ref5">1</reflink>]; Foorman et al., [<reflink idref="bib30" id="ref6">30</reflink>]; Gersten et al., [<reflink idref="bib37" id="ref7">37</reflink>]; Hall et al., [<reflink idref="bib39" id="ref8">39</reflink>]; Vaughn et al., [<reflink idref="bib95" id="ref9">95</reflink>]). However, scholars have also pointed out that many existing intervention approaches targeting students with WRD have been only partly successful in improving reading outcomes, as many have been more successful in improving students' ability to read individual words and pseudowords and less impactful in promoting fluent and generalized word and text reading skills (Boucher et al., [<reflink idref="bib9" id="ref10">9</reflink>]; Compton et al., [<reflink idref="bib15" id="ref11">15</reflink>]; Flynn et al., [<reflink idref="bib28" id="ref12">28</reflink>]; Stevens et al., [<reflink idref="bib85" id="ref13">85</reflink>]). It is possible that the way interventions have been traditionally structured, with an emphasis on teaching sound-by-sound decoding and regularity in spelling-sound correspondences, may not be sufficient for moving students beyond accuracy with phonetically regular words toward efficient word recognition that is a hallmark of skilled reading.</p> <p>One particular intervention, Phonological + Strategy Training (PHAST; Lovett et al., [<reflink idref="bib52" id="ref14">52</reflink>]), which includes instruction in phonics and word identification strategies (i.e., phonological letter-sound decoding, word identification-by-analogy, separation of affixes in multisyllabic words, identification of familiar parts in unknown words, and navigating vowels with variable pronunciations), was successful in advancing real word reading and text reading outcomes for students with WRD; however, given the multicomponent approach to this program, which instructional components led to improvements is unclear. The present research examined two unique aspects of word reading instruction that may promote meaningful gains for the target population—variations in the size of the letter unit and the number of taught pronunciations for a letter unit.</p> <hd id="AN0186465936-2">Two potential areas of intervention advancement</hd> <p></p> <hd id="AN0186465936-3">Variation in size of letter unit</hd> <p>Students with WRD may benefit from explicit instruction and practice in word reading that varies in size of letter units taught and prompted for use in decoding (e.g., tr-ail vs. t-r-ai-l; Ziegler & Goswami, [<reflink idref="bib105" id="ref15">105</reflink>]), as evidenced by theory (Ehri, [<reflink idref="bib22" id="ref16">22</reflink>]; Perfetti & Stafura, [<reflink idref="bib63" id="ref17">63</reflink>]) and intervention research (Lovett et al., [<reflink idref="bib52" id="ref18">52</reflink>]; Steacy et al., [<reflink idref="bib84" id="ref19">84</reflink>]). The quasi-regular quality of English, or the idea that letters/letter clusters can represent more than one sound, makes it challenging to establish print-to-speech connections (Seymour et al., [<reflink idref="bib74" id="ref20">74</reflink>]). Instruction targeting primarily smaller letter units (i.e., 1–2 letters) as opposed to larger letter units (i.e., more than 2 letters) is more reflective of phonics instruction typically provided in schools; however, overreliance on smaller letter units is characteristic of less skilled readers (Brown & Deavers, [<reflink idref="bib10" id="ref21">10</reflink>]). In particular, instruction focused primarily on targeting simple (i.e., one- or two-letter) sublexical units, a hallmark of existing reading interventions (e.g., Foorman et al., [<reflink idref="bib29" id="ref22">29</reflink>]; McCandliss et al., [<reflink idref="bib56" id="ref23">56</reflink>]; Olson et al., [<reflink idref="bib60" id="ref24">60</reflink>]; Torgesen et al., [<reflink idref="bib87" id="ref25">87</reflink>]), may have the unintended effect of fostering dependence on smaller sublexical units at the expense of acquiring broader lexical knowledge (Barca et al., [<reflink idref="bib5" id="ref26">5</reflink>]; Coltheart et al., [<reflink idref="bib14" id="ref27">14</reflink>]). It is possible that instruction emphasizing sound-by-sound decoding is appropriate for beginning readers, but not necessarily for older students with WRD for whom larger letter units might promote unitization needed to read larger words with ease. Complex (i.e., 3- or 4-letter) sublexical units are difficult to acquire (e.g., Larsen et al., [<reflink idref="bib48" id="ref28">48</reflink>]) but may be more conducive to the acquisition of context-sensitive connections between print and speech (Treiman et al., [<reflink idref="bib90" id="ref29">90</reflink>], [<reflink idref="bib91" id="ref30">91</reflink>]; Ziegler & Goswami, [<reflink idref="bib105" id="ref31">105</reflink>]). Previous research examining the effects of variation in the size of sublexical units has shown varied results and been limited to younger students (Vadasy & Sanders, [<reflink idref="bib92" id="ref32">92</reflink>]) or instruction in languages other than English (Huemer et al., [<reflink idref="bib44" id="ref33">44</reflink>]; Marinus et al., [<reflink idref="bib54" id="ref34">54</reflink>]). Notably, English-speaking kindergarteners who received instruction targeting sublexical units that varied in size (i.e., one- and two-letter-sound correspondences) outperformed individuals assigned to instruction targeting <emph>only</emph> single-letter-sound correspondences on a researcher-developed decoding measure. Alternatively, instruction of larger letter units did not yield impactful gains on generalized word reading for struggling readers in grade 2 who speak Dutch (Marinus et al., [<reflink idref="bib54" id="ref35">54</reflink>]) or grades 4–6 who speak Finnish (Huemer et al., [<reflink idref="bib44" id="ref36">44</reflink>]).</p> <hd id="AN0186465936-4">Variation in targeted sounds for a letter unit</hd> <p>Students with WRD may also benefit from explicit instruction and practice in multiple pronunciations for a given letter/letter unit (e.g., "ost" says /ohst/ as in m<uline>ost</uline> or /awst/ as in l<uline>ost</uline>; Compton et al., [<reflink idref="bib15" id="ref37">15</reflink>]; Ehri, [<reflink idref="bib22" id="ref38">22</reflink>]; Huang et al., [<reflink idref="bib43" id="ref39">43</reflink>]; Lovett et al., [<reflink idref="bib52" id="ref40">52</reflink>]; Perfetti & Stafura, [<reflink idref="bib63" id="ref41">63</reflink>]; Siegel & Faux, [<reflink idref="bib80" id="ref42">80</reflink>]; Steacy et al., [<reflink idref="bib84" id="ref43">84</reflink>]; Ziegler & Goswami, [<reflink idref="bib105" id="ref44">105</reflink>]). More specifically, Compton and colleagues ([<reflink idref="bib15" id="ref45">15</reflink>]) have called for research that examines whether utility (i.e., the most common pronunciation) or flexibility (i.e., multiple pronunciations) should drive the number of pronunciations targeted in instruction and practice for a given letter/letter unit. Inconsistent letter-sound correspondences (i.e., letters/letter units representing variable pronunciations) are especially challenging to learn (Huang et al., [<reflink idref="bib43" id="ref46">43</reflink>]; Larsen et al., [<reflink idref="bib48" id="ref47">48</reflink>]; Siegel & Faux, [<reflink idref="bib80" id="ref48">80</reflink>]). Knowledge of multiple pronunciations for a given letter/letter unit is anticipated to be more supportive in improving word reading performance for individuals with WRD than standard pronunciations alone due to the quasi-regular quality of the English language, which contains variation in the number of letters that contribute to a given sound and the number of sounds that can be represented by a given letter/letter unit (Ehri, [<reflink idref="bib22" id="ref49">22</reflink>]; Perfetti & Stafura, [<reflink idref="bib63" id="ref50">63</reflink>]). Knowledge of multiple pronunciations for a given letter/letter unit contributes to the development of rich sublexical knowledge, which affords beginning and struggling readers increased success in accurately decoding unfamiliar words encountered in text (Perfetti, [<reflink idref="bib62" id="ref51">62</reflink>]). Accurate decoding attempts increase the likelihood that students will decode the same word accurately in future encounters, ultimately increasing word-level entries in a reader's sight word bank (Share, [<reflink idref="bib79" id="ref52">79</reflink>]). An extensive sight word bank is supportive of efficient word reading needed for text comprehension. In particular, beginning and struggling readers have demonstrated difficulty in developing accurate recognition of vowels (Ehri & Saltmarsh, [<reflink idref="bib23" id="ref53">23</reflink>]; Shankweiler & Liberman, [<reflink idref="bib76" id="ref54">76</reflink>]); however, interventions targeting flexible approaches to the identification of vowels have demonstrated promise (Colenbrander et al., [<reflink idref="bib13" id="ref55">13</reflink>]; Dyson et al., [<reflink idref="bib21" id="ref56">21</reflink>]; Lovett et al., [<reflink idref="bib52" id="ref57">52</reflink>], [<reflink idref="bib53" id="ref58">53</reflink>]; Savage et al., [<reflink idref="bib73" id="ref59">73</reflink>]; Steacy et al., [<reflink idref="bib84" id="ref60">84</reflink>]).</p> <hd id="AN0186465936-5">Purpose and research questions</hd> <p>Most reading difficulties result from challenges in word reading. Research is needed to investigate variations in sublexical units targeted in word reading instruction and practice, such as letter unit size and number of taught pronunciations for a letter/letter unit, to test theoretical frameworks that suggest co-development of sublexical and lexical knowledge and unitization of letter-sound correspondences are key to word reading efficiency (e.g., Ehri, [<reflink idref="bib24" id="ref61">24</reflink>]; Perfetti, [<reflink idref="bib64" id="ref62">64</reflink>]). The present studies served as pilot studies for a larger-scale project funded by the Institute of Education Sciences in which the overall goal is to develop an intervention for improving word and text reading efficiency for individuals with WRD in middle elementary grades (i.e., when identification of WRD is most prevalent; Fletcher et al., [<reflink idref="bib27" id="ref63">27</reflink>]). The aims of the present research were to examine two instructional elements: variation in letter unit size and number of unique pronunciations taught for a given letter unit, in two short-term studies. In both studies, students received explicit instruction in sublexical knowledge coupled with opportunities to develop lexical knowledge through reading words that contained: (a) targeted sublexical units and (b) variation in non-targeted letters contributing to taught words. Study 1 investigated: What are the effects of instruction and practice in complex (i.e., three- or four-letter) letter units compared to simple (i.e., two-letter) letter units on word reading performance? Study 2 investigated: What are the effects of instruction and practice targeting multiple pronunciations (i.e., most common pronunciation plus an alternate, variable pronunciation) of a letter unit vs. standard (i.e., most common) pronunciation of a letter unit on word reading performance?</p> <hd id="AN0186465936-6">Study 1</hd> <p></p> <hd id="AN0186465936-7">Method</hd> <p></p> <hd id="AN0186465936-8">Participants</hd> <p>Participants from grades 2, 3, and 4 were recruited from schools in the Southwestern USA. Teachers were asked to nominate students with identified WRD or students they perceived to be at risk for WRD. Students who provided parental consent and assent to participate were administered the Sight Word Efficiency subtest from the Second Edition of the Test of Word Reading Efficiency (TOWRE-2 SWE; Torgesen et al., [<reflink idref="bib88" id="ref64">88</reflink>]), which was used to create matched pairs for random assignment to condition. The final <emph>analytic</emph> sample (<emph>N</emph> = 61) had a mean standard score (SS) of 79.25 (<emph>SD</emph> = 14.69); thus, average student word reading performance was more than 1 SD below the mean and reflects below-average performance (Flanagan et al., [<reflink idref="bib26" id="ref65">26</reflink>]). Hispanic students are overrepresented in this sample (85%), which is characteristic of the demographics for the school district from which we sampled (77.6%). The majority (90.3%) of students speak English only at home, and 34.2% of students live below the poverty line. Table 1 contains additional student demographics.</p> <p>Table 1 Student demographics</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="3"><p>Demographic variable</p></th><th align="left" colspan="6"><p>Study 1</p></th><th align="left" colspan="6"><p>Study 2</p></th></tr><tr><th align="left" colspan="2"><p>SLU (<italic>n</italic> = 32)</p></th><th align="left" colspan="2"><p>CLU (<italic>n</italic> = 29)</p></th><th align="left" colspan="2"><p>Overall sample (<italic>n</italic> = 61)</p></th><th align="left" colspan="2"><p>SP (<italic>n</italic> = 29)</p></th><th align="left" colspan="2"><p>MP (<italic>n</italic> = 35)</p></th><th align="left" colspan="2"><p>Overall sample (<italic>n</italic> = 64)</p></th></tr><tr><th align="left"><p><italic>n</italic></p></th><th align="left"><p>%</p></th><th align="left"><p><italic>n</italic></p></th><th align="left"><p>%</p></th><th align="left"><p><italic>n</italic></p></th><th align="left"><p><italic>%</italic></p></th><th align="left"><p><italic>n</italic></p></th><th align="left"><p>%</p></th><th align="left"><p><italic>n</italic></p></th><th align="left"><p>%</p></th><th align="left"><p><italic>n</italic></p></th><th align="left"><p>%</p></th></tr></thead><tbody><tr><td align="left" colspan="13"><p>Gender</p></td></tr><tr><td align="left"><p>Male</p></td><td align="left"><p>11</p></td><td align="left"><p>34</p></td><td align="left"><p>17</p></td><td align="left"><p>59</p></td><td align="left"><p>28</p></td><td align="left"><p>46</p></td><td align="left"><p>13</p></td><td align="left"><p>45</p></td><td align="left"><p>17</p></td><td align="left"><p>49</p></td><td align="left"><p>30</p></td><td align="left"><p>47</p></td></tr><tr><td align="left"><p>Female</p></td><td align="left"><p>21</p></td><td align="left"><p>66</p></td><td align="left"><p>12</p></td><td align="left"><p>41</p></td><td align="left"><p>33</p></td><td align="left"><p>54</p></td><td align="left"><p>16</p></td><td align="left"><p>55</p></td><td align="left"><p>18</p></td><td align="left"><p>51</p></td><td align="left"><p>34</p></td><td align="left"><p>53</p></td></tr><tr><td align="left" colspan="13"><p>Grade</p></td></tr><tr><td align="left"><p>2</p></td><td align="left"><p>12</p></td><td align="left"><p>37</p></td><td align="left"><p>11</p></td><td align="left"><p>38</p></td><td align="left"><p>23</p></td><td align="left"><p>38</p></td><td align="left"><p>10</p></td><td align="left"><p>35</p></td><td align="left"><p>16</p></td><td align="left"><p>46</p></td><td align="left"><p>26</p></td><td align="left"><p>41</p></td></tr><tr><td align="left"><p>3</p></td><td align="left"><p>13</p></td><td align="left"><p>41</p></td><td align="left"><p>10</p></td><td align="left"><p>34</p></td><td align="left"><p>23</p></td><td align="left"><p>38</p></td><td align="left"><p>12</p></td><td align="left"><p>41</p></td><td align="left"><p>10</p></td><td align="left"><p>28</p></td><td align="left"><p>22</p></td><td align="left"><p>34</p></td></tr><tr><td align="left"><p>4</p></td><td align="left"><p>7</p></td><td align="left"><p>22</p></td><td align="left"><p>8</p></td><td align="left"><p>28</p></td><td align="left"><p>15</p></td><td align="left"><p>24</p></td><td align="left"><p>7</p></td><td align="left"><p>24</p></td><td align="left"><p>9</p></td><td align="left"><p>26</p></td><td align="left"><p>16</p></td><td align="left"><p>25</p></td></tr><tr><td align="left" colspan="13"><p>Ethnicity/race</p></td></tr><tr><td align="left"><p>Hispanic</p></td><td align="left"><p>26</p></td><td align="left"><p>81</p></td><td align="left"><p>26</p></td><td align="left"><p>90</p></td><td align="left"><p>52</p></td><td align="left"><p>85</p></td><td align="left"><p>22</p></td><td align="left"><p>76</p></td><td align="left"><p>32</p></td><td align="left"><p>91</p></td><td align="left"><p>54</p></td><td align="left"><p>84</p></td></tr><tr><td align="left"><p>White</p></td><td align="left"><p>4</p></td><td align="left"><p>13</p></td><td align="left"><p>3</p></td><td align="left"><p>10</p></td><td align="left"><p>7</p></td><td align="left"><p>12</p></td><td align="left"><p>6</p></td><td align="left"><p>21</p></td><td align="left"><p>2</p></td><td align="left"><p>6</p></td><td align="left"><p>8</p></td><td align="left"><p>13</p></td></tr><tr><td align="left"><p>Other</p></td><td align="left"><p>2</p></td><td align="left"><p>6</p></td><td align="left" /><td align="left" /><td align="left"><p>2</p></td><td align="left"><p>3</p></td><td align="left"><p>1</p></td><td align="left"><p>3</p></td><td align="left"><p>1</p></td><td align="left"><p>3</p></td><td align="left"><p>2</p></td><td align="left"><p>3</p></td></tr><tr><td align="left"><p>Disability</p></td><td align="left"><p>16</p></td><td align="left"><p>50</p></td><td align="left"><p>11</p></td><td align="left"><p>38</p></td><td align="left"><p>27</p></td><td align="left"><p>44</p></td><td align="left"><p>13</p></td><td align="left"><p>45</p></td><td align="left"><p>15</p></td><td align="left"><p>43</p></td><td align="left"><p>28</p></td><td align="left"><p>44</p></td></tr><tr><td align="left"><p>ADHD</p></td><td align="left"><p>2</p></td><td align="left"><p>6</p></td><td align="left"><p>2</p></td><td align="left"><p>7</p></td><td align="left"><p>4</p></td><td align="left"><p>7</p></td><td align="left"><p>2</p></td><td align="left"><p>7</p></td><td align="left"><p>2</p></td><td align="left"><p>6</p></td><td align="left"><p>4</p></td><td align="left"><p>6</p></td></tr><tr><td align="left"><p>Dyslexia</p></td><td align="left"><p>6</p></td><td align="left"><p>19</p></td><td align="left"><p>4</p></td><td align="left"><p>14</p></td><td align="left"><p>10</p></td><td align="left"><p>16</p></td><td align="left"><p>5</p></td><td align="left"><p>18</p></td><td align="left"><p>5</p></td><td align="left"><p>14</p></td><td align="left"><p>10</p></td><td align="left"><p>16</p></td></tr><tr><td align="left"><p>Learning disability</p></td><td align="left"><p>3</p></td><td align="left"><p>9</p></td><td align="left"><p>2</p></td><td align="left"><p>7</p></td><td align="left"><p>5</p></td><td align="left"><p>8</p></td><td align="left"><p>4</p></td><td align="left"><p>14</p></td><td align="left"><p>1</p></td><td align="left"><p>3</p></td><td align="left"><p>5</p></td><td align="left"><p>8</p></td></tr><tr><td align="left"><p>Speech impairment</p></td><td align="left"><p>1</p></td><td align="left"><p>3</p></td><td align="left"><p>1</p></td><td align="left"><p>3</p></td><td align="left"><p>2</p></td><td align="left"><p>3</p></td><td align="left"><p>1</p></td><td align="left"><p>3</p></td><td align="left"><p>2</p></td><td align="left"><p>6</p></td><td align="left"><p>3</p></td><td align="left"><p>5</p></td></tr><tr><td align="left"><p>Multiple</p></td><td align="left"><p>4</p></td><td align="left"><p>13</p></td><td align="left"><p>2</p></td><td align="left"><p>7</p></td><td align="left"><p>6</p></td><td align="left"><p>10</p></td><td align="left"><p>1</p></td><td align="left"><p>3</p></td><td align="left"><p>5</p></td><td align="left"><p>14</p></td><td align="left"><p>6</p></td><td align="left"><p>9</p></td></tr></tbody></table> </ephtml> </p> <p>Note. <emph>CLU</emph>, complex letter units; <emph>MP</emph>, multiple pronunciations; <emph>SLU</emph>, simple letter units; <emph>SP</emph>, standard pronunciation</p> <p>Within matched pairs based on their TOWRE-2 SWE scores, individuals were randomly assigned to one of two instructional conditions (i.e., simple or complex letter units). Baseline equivalence (i.e., pre-treatment performance and demographic variables) was investigated using chi-square analyses (i.e., disability and gender), Fisher's test (i.e., ethnicity/race) for categorical variables, and Welch's two sample <emph>t</emph>-tests for continuous variables (i.e., pretest performance on Aligned Word Lists and TOWRE-2 SWE). Additionally, percentages of total and differential attrition were calculated to determine if integrity of the findings was compromised (What Works Clearinghouse [WWC], [<reflink idref="bib95" id="ref66">95</reflink>]). In all, 3 (out of 67) students attrited from Study 1. One student's teacher withdrew him due to a mismatch between instructional focus of the treatment and the student's needs; pretest performance on Aligned Word Lists was not available for this student due to a clerical error. Parents withdrew the other two students who were siblings. Overall attrition was 4% and differential attrition between conditions was 2%, which meets WWC Group Design Standards Without Reservations (WWC, [<reflink idref="bib95" id="ref67">95</reflink>]). All non-attrited student data were included in the analyses, based on an intent-to-treat approach. At randomization, average student performance on TOWRE-2 SWE and Aligned Word Lists was non-different across groups (<emph>N</emph> = 67; <emph>t</emph> (<reflink idref="bib64" id="ref68">64</reflink>) = 0.64, <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>p</mi></math> </ephtml> > 0.05; <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>N</mi><mo>=</mo><mn>67</mn><mo>;</mo><mi>t</mi><mo stretchy="false">(</mo><mn>63</mn><mo stretchy="false">)</mo><mo>=</mo><mn>1.02</mn><mo>,</mo><mi>p</mi><mo>></mo><mn>0.05</mn></mrow></math> </ephtml> ). Performance on TOWRE-2 was also non-different for (a) the three students who attrited and for those who remained in the study <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mfenced close=")" open="("><mi>N</mi><mo>=</mo><mn>64</mn><mo>;</mo><mi>t</mi><mfenced close=")" open="("><mn>2</mn></mfenced><mo>=</mo><mn>1.26</mn><mo>,</mo><mi>p</mi><mo>></mo><mn>0.05</mn></mfenced></math> </ephtml> and (b) for the final analytic sample (after the removal of three outlier data points due to observed discrepancy and influence—i.e., all extremely large residuals indicative of observed values beyond what was predicted <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mo stretchy="false">(</mo><mi>N</mi><mo>=</mo><mn>61</mn><mo>;</mo><mi>t</mi><mo stretchy="false">(</mo><mn>58</mn><mo stretchy="false">)</mo><mo>=</mo><mn>0.84</mn><mo>,</mo><mi>p</mi><mo>></mo><mn>0.05</mn><mo stretchy="false">)</mo></mrow></math> </ephtml> ). There was a statistically significant difference in average pretest performance on Aligned Word Lists for the two attrited students for whom data was available versus students who remained in the study <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mo stretchy="false">(</mo><mi>N</mi><mo>=</mo><mn>64</mn><mo>;</mo><mi>t</mi><mo stretchy="false">(</mo><mn>5</mn><mo stretchy="false">)</mo><mo>=</mo><mn>5.11</mn><mo>,</mo><mi>p</mi><mo><</mo><mn>0.05</mn><mo stretchy="false">)</mo></mrow></math> </ephtml> ; however, after removing three outlier data points, average pretest performance on Aligned Word Lists was non-different between groups <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mo stretchy="false">(</mo><mi>N</mi><mo>=</mo><mn>61</mn><mo>;</mo><mi>t</mi><mo stretchy="false">(</mo><mn>58</mn><mo stretchy="false">)</mo><mo>=</mo><mn>1.14</mn><mo>,</mo><mi>p</mi><mo>></mo><mn>0.05</mn><mo stretchy="false">)</mo></mrow></math> </ephtml> . At randomization and after attrition, treatment groups were non-different on disability status <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mo stretchy="false">(</mo><msup><mrow><mi>χ</mi></mrow><mn>2</mn></msup><mrow><mo stretchy="false">(</mo><mn>1</mn><mo>,</mo><mi>N</mi><mo>=</mo><mn>67</mn><mo stretchy="false">)</mo></mrow><mo>=</mo><mn>0.71</mn><mo>,</mo><mi>p</mi><mo>></mo><mn>0.05</mn><mo>;</mo><msup><mrow><mi>χ</mi></mrow><mn>2</mn></msup><mrow><mo stretchy="false">(</mo><mn>1</mn><mo>,</mo><mi>N</mi><mo>=</mo><mn>64</mn><mo stretchy="false">)</mo></mrow><mo>=</mo><mn>0.71</mn><mo>,</mo><mi>p</mi><mo>></mo><mn>0.05</mn><mo stretchy="false">)</mo><mo stretchy="false">)</mo></mrow></math> </ephtml> and ethnicity/race ( <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>p</mi></math> </ephtml> > 0.05; <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>p</mi></math> </ephtml> > 0.05), but there were statistically significant differences for proportions of gender contributing to the sample across groups <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mo stretchy="false">(</mo><msup><mrow><mi>χ</mi></mrow><mn>2</mn></msup><mrow><mo stretchy="false">(</mo><mn>1</mn><mo>,</mo><mi>N</mi><mo>=</mo><mn>67</mn><mo stretchy="false">)</mo></mrow><mo>=</mo><mn>4.23</mn><mo>,</mo><mi>p</mi><mo><</mo><mn>0.05</mn><mo stretchy="false">)</mo></mrow></math> </ephtml> . At randomization, the simple letter unit condition had more females (<emph>n</emph> = 23) than the complex letter unit condition (<emph>n</emph> = 12) and the simple letter unit condition had less males (<emph>n</emph> = 13) than the complex letter unit condition (<emph>n</emph> = 19). After attrition, treatment groups still differed on proportions of gender <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mo stretchy="false">(</mo><msup><mrow><mi>χ</mi></mrow><mn>2</mn></msup><mrow><mo stretchy="false">(</mo><mn>1</mn><mo>,</mo><mi>N</mi><mo>=</mo><mn>64</mn><mo stretchy="false">)</mo></mrow><mo>=</mo><mn>4.92</mn><mo>,</mo><mi>p</mi><mo><</mo><mn>0.05</mn><mo stretchy="false">)</mo></mrow></math> </ephtml> ; the simple letter unit condition had more females (<emph>n</emph> = 23) than the complex letter unit condition (<emph>n</emph> = 12) and the simple letter unit condition had less males (<emph>n</emph> = 11) than the complex letter unit condition (<emph>n</emph> = 18). In the final analytic sample, excluding outlier data points, treatment groups were non-different on all demographic variables, including gender <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mo stretchy="false">(</mo><msup><mrow><mi>χ</mi></mrow><mn>2</mn></msup><mrow><mo stretchy="false">(</mo><mn>1</mn><mo>,</mo><mi>N</mi><mo>=</mo><mn>61</mn><mo stretchy="false">)</mo></mrow><mo>=</mo><mn>3.60</mn><mo>,</mo><mi>p</mi><mo>></mo><mn>0.05</mn><mo stretchy="false">)</mo></mrow></math> </ephtml> , disability status <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mo stretchy="false">(</mo><msup><mrow><mi>χ</mi></mrow><mn>2</mn></msup><mrow><mo stretchy="false">(</mo><mn>1</mn><mo>,</mo><mi>N</mi><mo>=</mo><mn>61</mn><mo stretchy="false">)</mo></mrow><mo>=</mo><mn>0.90</mn><mo>,</mo><mi>p</mi><mo>></mo><mn>0.05</mn><mo stretchy="false">)</mo></mrow></math> </ephtml> , and ethnicity/race ( <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>p</mi></math> </ephtml> > 0.05).</p> <hd id="AN0186465936-9">Measurement</hd> <p>The dependent variable in the present study was student performance on Aligned Word Lists, a researcher-developed measure of word reading efficiency, which was administered at pretest to evaluate baseline equivalence across conditions and at posttest to determine treatment effects. Word types contributing to the 120 words included in Aligned Word Lists consisted of (a) 50% taught words and (b) 50% untaught words that contained targeted letter units.</p> <p>To avoid any potential bias, participants were posttested by a tutor other than the one that served as their instructor in the study. Words were arranged in vertical lists and displayed on the screen in sets of five words per slide. Students were asked to read the words aloud when each set appeared on the screen. Responses were scored in the following manner: (a) an incorrect response or no response earned 0 points, (b) an incorrect response with correct pronunciation of the targeted letter unit earned 1 point, (c) a correct but tentative (i.e., more than 1 s) or self-corrected response earned 2 points, and (d) a correct and automatic (i.e., within 1 s) response earned 3 points. The scoring system used was designed to award higher value to efficient word reading, with the option to examine accurate reading of (a) words and (b) targeted letter units. Tutors responsible for administering a given posttest were also responsible for initial data entry and scoring. All data were double-entered and scored by a doctoral student with expertise in reading research, and any discrepancies between entry and scores were resolved by the first author of this manuscript.</p> <hd id="AN0186465936-10">Procedures</hd> <p></p> <hd id="AN0186465936-11">Intervention</hd> <p>There were two treatments: (a) instruction reflective of existing reading interventions (Foorman et al., [<reflink idref="bib29" id="ref69">29</reflink>]; McCandliss et al., [<reflink idref="bib56" id="ref70">56</reflink>]; Olson et al., [<reflink idref="bib60" id="ref71">60</reflink>]; Torgesen et al., [<reflink idref="bib87" id="ref72">87</reflink>]; i.e., simple letter units) and (b) instruction reflective of reading development theory and mechanisms used by skilled readers (Compton et al., [<reflink idref="bib15" id="ref73">15</reflink>]; Perfetti, [<reflink idref="bib64" id="ref74">64</reflink>]; i.e., complex letter units). Research-hired tutors, who all had experience working with elementary students, provided participants with one of two conditions—simple letter units or complex letter units. In the simple letter unit condition, instruction and practice targeted simple sublexical units, reflective of typical word reading intervention (e.g., McCandliss et al., [<reflink idref="bib56" id="ref75">56</reflink>]; Torgesen et al., [<reflink idref="bib87" id="ref76">87</reflink>]). The complex letter unit condition provided instruction and practice targeting simple letter units but also explicit instruction of complex letter units, or frequently co-occurring letters. Thus, the present study investigated: What are the effects of instruction and practice in complex (i.e., three- or four-letter) letter units compared to simple (i.e., two-letter) letter units on word reading performance?</p> <p>This study was conducted during the height of the COVID-19 pandemic (i.e., early 2021) when only virtual delivery of researcher-provided intervention was permitted by participating schools. For each session, tutors met with students individually via video conference and provided instruction using scripted lesson plans. Students used school-provided laptop or tablet computers. Instructional content was displayed using Microsoft PowerPoint slides. Students received six 15-min lessons, which were delivered daily on consecutive days to the greatest extent possible (i.e., adjusting for student absences and weekends). Treatments targeted word reading through explicit instruction of letter units and practice reading words that contained targeted letter units. Both conditions were comprised of the following instructional components: (a) explicit instruction of a targeted letter unit and its corresponding pronunciation; (b) practice reading targeted letter units and their corresponding pronunciation; (c) explicit decoding instruction using a word containing the targeted letter unit and its corresponding pronunciation; and (d) practice reading words that contained the targeted letter unit and its corresponding pronunciation. Students reread word lists as needed until they demonstrated accurate and fluent reading of all words, to the greatest extent possible within the time allotted for a given lesson. Once students demonstrated mastery (i.e., correct and automatic recognition of words within 1 s) of word lists, if time allowed, interventionists read aloud articles from Newsela. Articles selected were above students' reading level and reflected their interests. Key vocabulary was briefly defined prior to reading the article, and higher-order thinking questions were asked after the article was read. Because the read aloud was a supplementary instructional practice not all students received, students had access to an image that accompanied the article as opposed to the article itself to ensure the read aloud component of the lesson was not associated with improvements in word reading. If students did not demonstrate mastery in reading the targeted words, the lesson concluded after 15 min, and no supplementary instruction occurred. All conditions included affirmative and corrective teacher feedback (Hughes et al., [<reflink idref="bib45" id="ref77">45</reflink>]; Schrauben & Witmer, [<reflink idref="bib75" id="ref78">75</reflink>]; Warren et al., [<reflink idref="bib95" id="ref79">95</reflink>]). Examples of lesson plans and student-facing materials from Study 1 conditions are available as supplemental materials.</p> <p>Letter units targeted in Study 1 were selected based upon utility (i.e., letter units frequently represented in written English and contributing to many words; Fry, [<reflink idref="bib34" id="ref80">34</reflink>]; Wylie & Durrell, [<reflink idref="bib95" id="ref81">95</reflink>]). In both conditions, participants received instruction in vowel combinations (e.g., <emph>ai</emph>; see Fig. 2), which represent a known challenge for the target population (Frederiksen & Kroll, [<reflink idref="bib31" id="ref82">31</reflink>]; Gilbert et al., [<reflink idref="bib38" id="ref83">38</reflink>]; Olson et al., [<reflink idref="bib61" id="ref84">61</reflink>]). In the complex letter unit condition, vowel combinations <emph>and</emph> co-occurring final consonants (e.g., <emph>ai– ait</emph>, <emph>ain</emph>, <emph>aid</emph>; see Fig. 2) were targeted in instruction; sublexical content targeted in this condition is especially difficult for readers with WRD to acquire (Ehri & Saltmarsh, [<reflink idref="bib23" id="ref85">23</reflink>]; Shankweiler & Liberman, [<reflink idref="bib76" id="ref86">76</reflink>]) and aligned with promising results reported in initial investigations (Apfelbaum et al., [<reflink idref="bib3" id="ref87">3</reflink>]). For students assigned to the complex letter unit condition, instruction and practice emphasized the use of the targeted complex letter unit to support the decoding of words (e.g., <emph>c-oast</emph>); however, students assigned to the complex letter unit condition also received some prompting to use simple letter units to support accurate decoding of non-targeted letter-sound correspondences in words, as needed (e.g., <emph>b-l-oom</emph> vs. <emph>sh-out).</emph> The corpus of words containing the targeted sublexical units was curated from a list of commonly occurring words in printed English to ensure the lexical knowledge gained from the study was highly useful to reading (e.g., Norvig's list (https://norvig.com/ngrams/); Phinder (https://devinkearns.com/phinder/)). Word lists used for instruction and practice opportunities were consistent across instructional conditions; these lists were comprised of ten 1- and 2-syllable words, resulting in 60 words total.</p> <hd id="AN0186465936-12">Fidelity</hd> <p>Tutors received 6 h of training, which included (a) an overview and timeline, (b) modeling of each instructional condition, (c) opportunities to practice teaching each instructional condition, (d) protocol for administration of Aligned Word Lists (i.e., dependent variables), and (e) fidelity checks for all four instructional conditions and administration of Aligned Word Lists. Prior to treatment delivery, additional training was provided to any tutor that did not demonstrate a minimum score of 95% fidelity in the implementation of instructional conditions or administration of Aligned Word Lists.</p> <p>Tutors were observed teaching each assigned instructional condition. Adherence was evaluated using a checklist of instructional components and tutor-demonstrated behaviors specific to each condition. Each item on the checklist was rated as fully observed, partially observed, or not observed; these ratings earned a score of 2, 1, or 0, respectively. Additionally, the quality of instruction was evaluated based on a scale of 1–7, which reflected a range of quality from less than adequate instruction to the highest quality instruction. The dose delivered (Dusenbury et al., [<reflink idref="bib20" id="ref88">20</reflink>]) was measured using tutors' attendance records; the maximum possible dose was six lessons.</p> <hd id="AN0186465936-13">Results</hd> <p></p> <hd id="AN0186465936-14">Preliminary analyses</hd> <p>Descriptive features of the data were examined prior to analysis. Data were plotted using the ggplot2 package in R (v3.3.3; Wickham, [<reflink idref="bib95" id="ref89">95</reflink>]). Residuals for Study 1 data were non-normal based on visual inspection and on the Shapiro–Wilk normality test (Shapiro & Wilk, [<reflink idref="bib78" id="ref90">78</reflink>]), presumably due to three outlying cases, all of which exceeded two standard errors from the regression line and a Cook's distance of 0.07. The cases were omitted, yielding a "normal" distribution based on the pattern residuals and related metrics.</p> <hd id="AN0186465936-15">Multilevel modeling</hd> <p>Due to the nested structure of the data (i.e., students nested within teachers and schools), intraclass correlations (ICCs) were calculated to determine whether multilevel modeling was necessary for estimating study-level effects (Hox, [<reflink idref="bib42" id="ref91">42</reflink>]; Raudenbush & Bryk, [<reflink idref="bib66" id="ref92">66</reflink>]). Shared commonalities among students—such as having the same teacher, interventionist, or school—can violate the assumption of independence in statistical analyses. The ICC served as an estimate of this non-independence across level-1 units, with values exceeding 0.05 indicating the need for multilevel modeling (Hayes, [<reflink idref="bib40" id="ref93">40</reflink>]). As a first step, unconditional models were fit to estimate ICCs. For contrasts with ICC values above 0.05, fully conditional multilevel regression models were estimated to account for data dependencies by partitioning variance into level-specific components and estimating residuals at each level. This approach helps correct for artificially small standard errors and reduces the risk of inflated type I error rates—i.e., falsely identifying significant effects.</p> <p>Groups were contrasted using regression techniques, including multilevel regression when clustering was detected. For all multilevel models, main treatment effects were calculated as average treatment effects (ATEs), and effect sizes were computed as Hedges' g (Hedges, [<reflink idref="bib41" id="ref94">41</reflink>]). Beta coefficients from fitted multilevel models were converted to Hedges' g using the <emph>lmeInfo</emph> package in R (J. Pustejovsky, personal communication, January 24, 2022). To support the interpretation of the results, pretest values were grand-mean centered (Enders & Tofighi, [<reflink idref="bib25" id="ref95">25</reflink>]; Raudenbush & Bryk, [<reflink idref="bib66" id="ref96">66</reflink>]).</p> <p>There were 61 students at level 1, 12 teachers and 10 interventionists at level 2, and 3 schools at level 3. An unconditional model containing both level-2 variables, teacher and interventionist, revealed that data were not cross-classified, and that significant variance was explained by teachers only (0.27). A two-level model investigating the variance explained by teachers only revealed an ICC of 0.27, indicating a need for multilevel modeling. A three-level model was run to estimate the variance explained by teachers and schools (i.e., level-3 variable). Significant variance at the teacher-level (0.22) and school-level (0.08) indicated it may be appropriate to use a three-level model to estimate treatment effects. Initially, the effects of instructional condition were contrasted in a multilevel context that accounted for clustering of data at the teacher and school levels, while controlling for non-significant treatment group differences in pretest performance on Aligned Word Lists; however, ICCs estimated from this conditional model indicated that variance was explained at the school level only. As a result, an unconditional two-level model was run to determine the amount of school-level variance. An ICC of 0.09 indicated significant variance at the school level; thus, instructional conditions were contrasted in a two-level model that accounted for (a) clustering of data at the school level and (b) non-significant group differences in pretest performance on Aligned Word Lists. Specifically, fixed effects were estimated for instructional condition and pretest performance on Aligned Word Lists.</p> <hd id="AN0186465936-16">Main treatment effects</hd> <p>Descriptive statistics are reported in Table 2. Group differences in posttest performance on Aligned Word Lists, controlling for non-significant differences in pretest performance on Aligned Word Lists and significant school-level variance, were statistically significant in favor of the complex letter unit condition (see Table 3; <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>β</mi><mo>=</mo><mn>17.84</mn><mo>,</mo><mi>t</mi><mfenced close=")" open="("><mn>56</mn></mfenced><mrow><mo>=</mo><mn>2.33</mn><mo>,</mo><mi>p</mi><mo>=</mo><mn>0.02</mn><mo>;</mo><mi>g</mi><mo>=</mo><mn>0.16</mn><mo>,</mo><mn>95</mn><mtext>\% CI</mtext><mspace width="0.333333em" /><mrow><mo stretchy="false">[</mo><mn>0.01</mn><mo>,</mo><mn>0.31</mn><mo stretchy="false">]</mo></mrow><mo stretchy="false">)</mo><mo>.</mo></mrow></mrow></math> </ephtml></p> <p>Table 2 Study 1 pre- and posttest descriptive statistics for Aligned Word Lists</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="2"><p>Measure</p></th><th align="left"><p>Simple letter units (<italic>n</italic> = 32)</p></th><th align="left"><p>Complex letter units (<italic>n</italic> = 29)</p></th></tr><tr><th align="left"><p><italic>M (SD)</italic></p></th><th align="left"><p><italic>M (SD)</italic></p></th></tr></thead><tbody><tr><td align="left" colspan="3"><p>Aligned Word Lists</p></td></tr><tr><td align="left"><p>Pretest</p></td><td align="left"><p>188.84 (107.63)</p></td><td align="left"><p>157.66 (105.57)</p></td></tr><tr><td align="left"><p>Posttest</p></td><td align="left"><p>211.91 (103.8)</p></td><td align="left"><p>200.38 (110.68)</p></td></tr></tbody></table> </ephtml> </p> <p>Note. Results reported reflect all items administered (i.e., taught words and untaught words)</p> <p>Table 3 Study 1 results for Aligned Word Lists</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="2"><p>Effect</p></th><th align="left" rowspan="2"><p><math xmlns="http://www.w3.org/1998/Math/MathML"><mi xmlns="">β</mi></math><inline-graphic mime-subtype="GIF" href="11881_2025_332_Article_IEq36.gif" /></p></th><th align="left" rowspan="2"><p><italic>SE</italic></p></th><th align="left" rowspan="2"><p><italic>t</italic></p></th><th align="left" rowspan="2"><p><italic>p</italic></p></th><th align="left" rowspan="2"><p><italic>g</italic></p></th><th align="left" colspan="2"><p>95% CI</p></th><th align="left" rowspan="2"><p>Variance</p></th><th align="left" rowspan="2"><p><italic>SD</italic></p></th></tr><tr><th align="left"><p><italic>LL</italic></p></th><th align="left"><p><italic>UL</italic></p></th></tr></thead><tbody><tr><td align="left" colspan="10"><p>Fixed effects</p></td></tr><tr><td align="left"><p>Intercept</p></td><td char="." align="char"><p>194.36</p></td><td char="." align="char"><p>7.79</p></td><td char="." align="char"><p>24.97</p></td><td align="left"><p> < 0.001</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p>Pretest</p></td><td char="." align="char"><p>0.95</p></td><td char="." align="char"><p>0.04</p></td><td char="." align="char"><p>25.55</p></td><td align="left"><p> < 0.001</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p>CLU vs. SLU</p></td><td char="." align="char"><p>17.84</p></td><td char="." align="char"><p>7.66</p></td><td char="." align="char"><p>2.33</p></td><td align="left"><p>0.0234</p></td><td char="." align="char"><p>0.16</p></td><td char="." align="char"><p>0.01</p></td><td char="." align="char"><p>0.31</p></td><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left" colspan="10"><p>Random effects</p></td></tr><tr><td align="left"><p>Between school</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td align="left" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char"><p>85.36</p></td><td char="." align="char"><p>9.24</p></td></tr><tr><td align="left"><p>Residual</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td align="left" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char"><p>870.59</p></td><td char="." align="char"><p>29.51</p></td></tr></tbody></table> </ephtml> </p> <p>Note. Results reported reflect all items administered (i.e., taught words and untaught words). Abbreviations: <emph>CI</emph>, confidence interval; <emph>LL</emph>, lower limit; <emph>UL</emph>, upper limit; <emph>CLU</emph>, complex letter units; <emph>SLU</emph>, simple letter units</p> <hd id="AN0186465936-17">Subset analyses</hd> <p>Subset analyses with Aligned Word Lists were conducted to estimate treatment effects on taught vs. untaught words. The group difference in average student performance on taught words was statistically significant and in favor of the complex letter unit condition ( <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>β</mi><mo>=</mo><mn>9.43</mn><mo>,</mo><mi>t</mi><mfenced close=")" open="("><mn>56</mn></mfenced><mrow><mo>=</mo><mn>2.32</mn><mo>,</mo><mi>p</mi><mo>=</mo><mn>0.02</mn><mo>;</mo><mi>g</mi><mo>=</mo><mn>0.17</mn><mo>,</mo><mn>95</mn><mtext>\% CI</mtext><mspace width="0.333333em" /><mrow><mo stretchy="false">[</mo><mn>0.01</mn><mo>,</mo><mn>0.33</mn><mo stretchy="false">]</mo></mrow><mo stretchy="false">)</mo><mo>.</mo></mrow></mrow></math> </ephtml> The group difference in average student performance on untaught words was statistically significant when reported as an unstandardized beta coefficient in favor of the complex letter unit condition <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mo stretchy="false">(</mo><mi>β</mi><mo>=</mo><mn>8.44</mn><mo>,</mo><mi>t</mi><mfenced close=")" open="("><mn>56</mn></mfenced><mo>=</mo><mn>2.09</mn><mo>,</mo><mi>p</mi><mo>=</mo><mn>0.04</mn><mo>;</mo><mi>g</mi><mo>=</mo><mn>0.15</mn><mo>,</mo><mn>95</mn><mtext>\% CI</mtext><mspace width="0.333333em" /><mrow><mo stretchy="false">[</mo><mo>-</mo><mn>0.01</mn><mo>,</mo><mn>0.31</mn><mo stretchy="false">]</mo></mrow><mo stretchy="false">)</mo><mo>.</mo></mrow></math> </ephtml></p> <hd id="AN0186465936-18">Fidelity</hd> <p>Overall scores of adherence were estimated for the simple letter unit condition (<emph>M</emph> = 1.95 (<emph>SD</emph> = 0.21)) and complex letter unit condition (<emph>M</emph> = 1.95 (<emph>SD</emph> = 0.24)). Overall scores for the quality of instructional delivery were calculated for the simple letter unit condition (<emph>M</emph> = 6.5 (<emph>SD</emph> = 0.76)) and complex letter unit condition (<emph>M</emph> = 6.36 (<emph>SD</emph> = 0.67)). An average dose was calculated for the simple letter unit condition (<emph>M</emph> = 5.25 (<emph>SD</emph> = 1.08)) and complex letter unit condition (<emph>M</emph> = 5.1 (<emph>SD</emph> = 1.47)).</p> <hd id="AN0186465936-19">Discussion</hd> <p>Students assigned to instruction targeting complex letter units significantly outperformed students assigned to instruction targeting simple letter units for both retrieval of taught words and transfer to untaught words. Findings suggest that students may benefit from additional context afforded by larger letter units than are typically taught in most word reading programs.</p> <p>For individuals with WRD, instruction and practice in larger letter units may support the consolidation of letter units and their associated sounds; notably, orthographic mapping of increasingly larger letter strings is reflective of more advanced word reading (Ehri, [<reflink idref="bib24" id="ref97">24</reflink>]). In particular, efficiency is evident in the process of segmenting and blending involved in decoding. For example, individuals assigned to the complex letter unit condition were prompted to decode the word <emph>coast</emph> as <emph>c-oast</emph>, whereas individuals assigned to the simple letter unit condition were prompted to decode it as <emph>c-oa-s-t</emph>. Consequently, cognitive load is reduced for individuals assigned to the complex letter unit condition as their task involves fewer unique units. Limiting the cognition required to read words allows students to redirect their attention to text understanding (LaBerge & Samuels, [<reflink idref="bib47" id="ref98">47</reflink>]).</p> <p>It is also possible that when targeting larger letter units, individuals may experience more success in decoding; when practice opportunities extend to mastery, they are afforded the opportunity to establish high-quality lexical representations (Perfetti, [<reflink idref="bib64" id="ref99">64</reflink>]; Ritchey & Speece, [<reflink idref="bib70" id="ref100">70</reflink>]). Theorists posit that sublexical quality contributes to successful phonological recoding attempts (Perfetti, [<reflink idref="bib64" id="ref101">64</reflink>]; Ritchey & Speece, [<reflink idref="bib70" id="ref102">70</reflink>]; Wolf & Katzir-Cohen, [<reflink idref="bib95" id="ref103">95</reflink>]). Larger sublexical units provide more context, which is critically important given the inconsistencies between print and speech evident in English and the influence of surrounding letters on the pronunciation of letters. The notion that instruction and practice targeting complex letter units yielded stronger transfer of taught sublexical content to new word-level contexts may reflect the development of high-quality sublexical representations.</p> <p>In summary, instruction and practice opportunities provided in the complex letter unit condition may support symmetrical development of lexical and sublexical knowledge, as evidenced by growth on taught and untaught words. Notably, theorists suggest simultaneous development of lexical and sublexical knowledge yields proficient word reading (Perfetti, [<reflink idref="bib64" id="ref104">64</reflink>]).</p> <hd id="AN0186465936-20">Limitations</hd> <p>During Study 1, a record-breaking freeze caused a week-long disruption of instruction due to a state-wide power failure. Although the events were indeed disruptive, there is no reason to believe treatment groups were differentially impacted.</p> <hd id="AN0186465936-21">Study 2</hd> <p></p> <hd id="AN0186465936-22">Method</hd> <p></p> <hd id="AN0186465936-23">Participants</hd> <p>Using matched pairs created prior to Study 1, students were re-randomized to condition within their matched pairs to one of two conditions (i.e., standard or multiple pronunciations). For Study 2, the final <emph>analytic</emph> sample (<emph>N</emph> = 64) had a mean SS of 80.19 (<emph>SD</emph> = 15.01) on the TOWRE-2; thus, average student word reading performance was more than 1 SD below the mean and reflects below-average performance (Flanagan et al., [<reflink idref="bib26" id="ref105">26</reflink>]). Table 1 contains additional student demographics. In Study 2, no attrition was observed. As in Study 1, all student data were included in the analyses, reflecting an intent-to-treat approach. At randomization and in the final analytic sample, average student performance was non-different across treatment groups on TOWRE-2 SWE <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mo stretchy="false">(</mo><mi>N</mi><mo>=</mo><mn>64</mn><mo>;</mo><mi>t</mi><mo stretchy="false">(</mo><mn>61</mn><mo stretchy="false">)</mo><mo>=</mo><mo>-</mo><mn>0.74</mn><mo>,</mo><mi>p</mi><mo>></mo><mn>0.05</mn><mo stretchy="false">)</mo></mrow></math> </ephtml> and Aligned Word Lists at pretest <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mo stretchy="false">(</mo><mi>N</mi><mo>=</mo><mn>64</mn><mo>;</mo><mi>t</mi><mo stretchy="false">(</mo><mn>60</mn><mo stretchy="false">)</mo><mo>=</mo><mo>-</mo><mn>0.44</mn><mo>,</mo><mi>p</mi><mo>></mo><mn>0.05</mn></mrow></math> </ephtml> ). Additionally, treatment groups were non-different on demographic variables including gender <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mo stretchy="false">(</mo><msub><mi>χ</mi><mn>2</mn></msub><mrow><mo stretchy="false">(</mo><mn>1</mn><mo>,</mo><mi>N</mi><mo>=</mo><mn>64</mn><mo stretchy="false">)</mo></mrow><mo>=</mo><mn>0.09</mn><mo>,</mo><mi>p</mi><mo>></mo><mn>0.05</mn><mo stretchy="false">)</mo></mrow></math> </ephtml> , disability status <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mo stretchy="false">(</mo><msub><mi>χ</mi><mn>2</mn></msub><mrow><mo stretchy="false">(</mo><mn>1</mn><mo>,</mo><mi>N</mi><mo>=</mo><mn>64</mn><mo stretchy="false">)</mo></mrow><mo>=</mo><mn>0.03</mn><mo>,</mo><mi>p</mi><mo>></mo><mn>0.05</mn><mo stretchy="false">)</mo></mrow></math> </ephtml> , and ethnicity/race ( <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>p</mi></math> </ephtml> > 0.05). Notably, students were re-randomized within matched pairs to conditions prior to the start of Study 2 <emph>and</emph> measures used were study-specific, which means the sample and student performance were unique to each study.</p> <hd id="AN0186465936-24">Measurement</hd> <p>As in Study 1, the dependent variable in the present research was student performance on Aligned Word Lists, researcher-developed measures of word reading efficiency, which were administered at pretest to evaluate baseline equivalence across conditions and at posttest to determine treatment effects. The 120 words contributing to the Aligned Word Lists included the following word types: 25% taught words reflecting standard pronunciation of targeted letter units, 25% taught words reflecting a variable pronunciation of targeted letter units, 25% untaught words reflecting standard pronunciation of targeted letter units, and 25% untaught words reflecting a variable pronunciation of targeted letter units. Students randomly assigned to the standard pronunciation condition were not exposed to the taught variable pronunciation words; consequently, this subset of words was not included in any analyses. Administration and scoring of the dependent variable were conducted in the same manner as Study 1.</p> <hd id="AN0186465936-25">Procedures</hd> <p></p> <hd id="AN0186465936-26">Intervention</hd> <p>As was the case in Study 1, Study 2 included two treatment groups: (a) instruction reflective of existing reading interventions (Foorman et al., [<reflink idref="bib29" id="ref106">29</reflink>]; McCandliss et al., [<reflink idref="bib56" id="ref107">56</reflink>]; Olson et al., [<reflink idref="bib60" id="ref108">60</reflink>]; Torgesen et al., [<reflink idref="bib87" id="ref109">87</reflink>]; i.e., standard pronunciations of letter units) and (b) instruction reflective of reading development theory and mechanisms used by skilled readers (Compton et al., [<reflink idref="bib15" id="ref110">15</reflink>]; Perfetti, [<reflink idref="bib64" id="ref111">64</reflink>]; i.e., multiple pronunciations of letter units). Additionally, Study 2 consisted of a similar dose, delivered over a similar timespan, and in a similar fashion as Study 1. Study 1 and Study 2 occurred consecutively over the course of a 2-month time period, which accounts for time attributed to teacher nomination and collection of parent consent prior to Study 1, as well as study-specific procedures, all of which are documented in Fig. 1.</p> <p>Graph: Fig. 1 Research design</p> <p>Examples of lesson plans and student-facing materials from Study 2 conditions are available as supplemental materials. Notably, unique to Study 2 was the variation in pronunciations of a given letter unit targeted via treatments—in the standard pronunciation condition, instruction and practice targeted standard (i.e., most common) pronunciation of a letter unit (e.g., <emph>or</emph> most often says <emph>/ore/</emph> like in <emph>fort</emph>), reflective of instructional practices used in existing word reading interventions (see Compton et al., [<reflink idref="bib15" id="ref112">15</reflink>]). More specifically, in the standard pronunciation condition, ten words containing standard pronunciations of the targeted letter unit contributed to a list of words used during word reading practice opportunities in each lesson. In the multiple pronunciations condition, instruction and practice targeted standard pronunciations of a given letter unit plus an alternate, variable pronunciation of that same letter unit (e.g., <emph>or</emph> most often says <emph>/ore/</emph> like in <emph>fort</emph>, but sometimes <emph>or</emph> says <emph>/er/</emph> like in <emph>work</emph>). In particular, five words reflecting the standard pronunciation and five words reflecting a variable pronunciation of the same targeted letter unit contributed to a list of ten words used during word reading practice opportunities in each lesson. Thus, the present study investigated: What are the effects of instruction and practice targeting multiple pronunciations (i.e., most common pronunciation plus an alternate, variable pronunciation) of a letter unit vs. standard (i.e., most common) pronunciation only on word reading performance?</p> <p>The targeted letter units were selected based upon frequency in printed language and variability in pronunciation (Fry, [<reflink idref="bib34" id="ref113">34</reflink>]; Wylie & Durrell, [<reflink idref="bib95" id="ref114">95</reflink>]); these sublexical units also represent known challenges for the target population—vowels (e.g., Rayner et al., [<reflink idref="bib67" id="ref115">67</reflink>]) and multi-letter units (Frederiksen & Kroll, [<reflink idref="bib31" id="ref116">31</reflink>]; Olson et al., [<reflink idref="bib61" id="ref117">61</reflink>]). Standard (i.e., most common) pronunciation for a given letter unit was verified using data collected by Fry ([<reflink idref="bib32" id="ref118">32</reflink>]) in combination with Wilson Fundations® instructional scope and sequence. As in Study 1, the corpus of words containing the targeted sublexical units used in Study 2 were curated from a list of commonly occurring words in printed English to ensure the lexical knowledge gained from the study was highly useful to reading (e.g., Dolch, [<reflink idref="bib18" id="ref119">18</reflink>]; Fry, [<reflink idref="bib35" id="ref120">35</reflink>]; Fry & Kress, [<reflink idref="bib33" id="ref121">33</reflink>]; Lexile® word lists for Grades 2 and 3; Norvig's list [https://norvig.com/ngrams/]; Phinder [https://devinkearns.com/phinder/]). Target words were those in which the target letter unit comprised 25% or more of the letters contributing to the word. For example, in a two-letter unit like <emph>oa</emph>, the words were limited to eight letters or less in length; the research team made this decision to increase the likelihood that instruction in the targeted letter unit might result in accurate decoding of the word. Ten words were introduced in each lesson, resulting in 60 taught words total.</p> <hd id="AN0186465936-27">Fidelity</hd> <p>Prior to and during Study 2, fidelity training, observations, and ratings were conducted; these were conducted in a similar manner as Study 1.</p> <hd id="AN0186465936-28">Results</hd> <p></p> <hd id="AN0186465936-29">Preliminary analyses</hd> <p>A similar approach to preliminary analyses conducted in Study 1 occurred in Study 2. In Study 2, two data points exceeded two standard errors from the regression line and a Cook's distance of 0.07, suggesting possible discrepancy and undue influence. However, because the removal of these outliers prevented the estimation of treatment effects adjusted for significant teacher-level variance, they remained in the analytic data set.</p> <hd id="AN0186465936-30">Multilevel modeling</hd> <p>As in Study 1, Study 2 groups were contrasted using regression, including multilevel regression when data were clustered. For Study 2, there were 64 students at level 1, 12 teachers and 10 interventionists at level 2, and 3 schools at level 3. An unconditional model containing both level-2 variables, teacher and interventionist, revealed that data were not cross-classified, and significant variance was explained by teachers (0.25). A two-level model investigating the variance explained by teachers alone revealed an ICC of 0.25, indicating a need for multilevel modeling. A three-level model was run to estimate the variance explained by teachers and schools (i.e., level-3 variable). In this model, significant variance was explained at the teacher-level only (0.23; school-level variance was 0.03), indicating a two-level model was appropriate for use in estimating treatment effects. Thus, instructional conditions were ultimately contrasted in a two-level model that accounted for significant variance at the teacher-level and non-significant group differences in student pretest performance on Aligned Word Lists. Specifically, fixed effects were estimated for instructional condition and pretest performance on Aligned Word Lists.</p> <hd id="AN0186465936-31">Main treatment effects</hd> <p>Descriptive statistics are reported in Table 4. There were no significant group differences in average student performance in posttest performance on Aligned Word Lists when controlling for non-significant differences in pretest performance on Aligned Word Lists and significant teacher-level variance (see Table 5; <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>β</mi><mo>=</mo><mo>-</mo><mn>4.34</mn><mo>,</mo><mi>t</mi><mfenced close=")" open="("><mn>60</mn></mfenced><mo>=</mo><mo>-</mo><mn>0.82</mn><mo>,</mo><mi>p</mi><mo>=</mo><mn>0.41</mn><mo>;</mo><mi>g</mi><mo>=</mo><mo>-</mo><mn>0.06</mn><mo>,</mo><mn>95</mn><mtext>\% CI</mtext><mspace width="0.333333em" /><mrow><mo stretchy="false">[</mo><mo>-</mo><mn>0.22</mn><mo>,</mo><mn>0.09</mn><mo stretchy="false">]</mo></mrow></mrow></math> </ephtml> ).</p> <p>Table 4 Study 2 pre- and posttest descriptive statistics for Aligned Word Lists</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="2"><p>Measure</p></th><th align="left"><p>Standard pronunciation (<italic>n</italic> = 29)</p></th><th align="left"><p>Multiple pronunciations (<italic>n</italic> = 35)</p></th></tr><tr><th align="left"><p><italic>M (SD)</italic></p></th><th align="left"><p><italic>M (SD)</italic></p></th></tr></thead><tbody><tr><td align="left" colspan="3"><p>Aligned Word Lists</p></td></tr><tr><td align="left"><p>Pretest</p></td><td align="left"><p>131.45 (68.67)</p></td><td align="left"><p>139.26 (72.40)</p></td></tr><tr><td align="left"><p>Posttest</p></td><td align="left"><p>151.38 (67.17)</p></td><td align="left"><p>154.14 (70.50)</p></td></tr></tbody></table> </ephtml> </p> <p>Note. Results reported reflect all items administered (i.e., taught words and untaught words)</p> <p>Table 5 Study 2 results for Aligned Word Lists</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="2"><p>Effects</p></th><th align="left" rowspan="2"><p><math xmlns="http://www.w3.org/1998/Math/MathML"><mi xmlns="">β</mi></math><inline-graphic mime-subtype="GIF" href="11881_2025_332_Article_IEq36.gif" /></p></th><th align="left" rowspan="2"><p><italic>SE</italic></p></th><th align="left" rowspan="2"><p><italic>t</italic></p></th><th align="left" rowspan="2"><p><italic>p</italic></p></th><th align="left" rowspan="2"><p><italic>g</italic></p></th><th align="left" colspan="2"><p>95% CI</p></th><th align="left" rowspan="2"><p>Variance</p></th><th align="left" rowspan="2"><p><italic>SD</italic></p></th></tr><tr><th align="left"><p><italic>LL</italic></p></th><th align="left"><p><italic>UL</italic></p></th></tr></thead><tbody><tr><td align="left" colspan="10"><p>Fixed effects</p></td></tr><tr><td align="left"><p>Intercept</p></td><td char="." align="char"><p>155.19</p></td><td char="." align="char"><p>4.04</p></td><td char="." align="char"><p>38.46</p></td><td align="left"><p> < 0.01</p></td><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left"><p>Pretest</p></td><td char="." align="char"><p>0.93</p></td><td char="." align="char"><p>0.04</p></td><td char="." align="char"><p>24.13</p></td><td align="left"><p> < 0.01</p></td><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left"><p>MP vs. SP</p></td><td char="." align="char"><p> − 4.34</p></td><td char="." align="char"><p>5.28</p></td><td char="." align="char"><p> − 0.82</p></td><td align="left"><p>0.41</p></td><td align="left"><p> − 0.06</p></td><td align="left"><p> − 0.22</p></td><td align="left"><p>0.09</p></td><td align="left" /><td align="left" /></tr><tr><td align="left" colspan="10"><p>Random effects</p></td></tr><tr><td align="left"><p>Between teacher</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left"><p>14.85</p></td><td align="left"><p>3.85</p></td></tr><tr><td align="left"><p>Residual</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left"><p>431.16</p></td><td align="left"><p>20.76</p></td></tr></tbody></table> </ephtml> </p> <p>Note. Results reported reflect all items administered (i.e., taught words and untaught words). Abbreviations: <emph>CI</emph>, confidence interval; <emph>LL</emph>, lower limit; <emph>UL</emph>, upper limit; <emph>MP</emph>, multiple pronunciations; <emph>SP</emph>, standard pronunciation</p> <hd id="AN0186465936-32">Subset analyses</hd> <p>The group difference in average student performance on taught words was statistically significant when reported as an unstandardized beta coefficient and in favor of the standard pronunciation condition <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mo stretchy="false">(</mo><mi>β</mi><mo>=</mo><mo>-</mo><mn>4.15</mn><mo>,</mo><mi>t</mi><mfenced close=")" open="("><mn>60</mn></mfenced><mo>=</mo><mo>-</mo><mn>2.04</mn><mo>,</mo><mi>p</mi><mo>=</mo><mn>0.045</mn><mo>;</mo><mi>g</mi><mo>=</mo><mo>-</mo><mn>0.18</mn><mo>,</mo><mn>95</mn><mtext>\% CI</mtext><mspace width="0.333333em" /><mrow><mo stretchy="false">[</mo><mo>-</mo><mn>0.35</mn><mo>,</mo><mn>0.004</mn><mo stretchy="false">]</mo></mrow><mo stretchy="false">)</mo></mrow></math> </ephtml> . The group difference in average student performance was non-significant on untaught words <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mo stretchy="false">(</mo><mi>β</mi><mo>=</mo><mo>-</mo><mn>0.22</mn><mo>,</mo><mi>t</mi><mfenced close=")" open="("><mn>60</mn></mfenced><mo>=</mo><mo>-</mo><mn>0.06</mn><mo>,</mo><mi>p</mi><mo>=</mo><mn>0.96</mn><mo>;</mo><mi>g</mi><mo>=</mo><mo>-</mo><mn>0.01</mn><mo>,</mo><mn>95</mn><mtext>\% CI</mtext><mspace width="0.333333em" /><mrow><mo stretchy="false">[</mo><mo>-</mo><mn>0.17</mn><mo>,</mo><mn>0.17</mn><mo stretchy="false">]</mo></mrow><mo stretchy="false">)</mo></mrow></math> </ephtml> .</p> <hd id="AN0186465936-33">Fidelity</hd> <p>Overall scores of adherence were estimated for the standard pronunciation condition (<emph>M</emph> = 1.94 (<emph>SD</emph> = 0.27)) and multiple pronunciations condition (<emph>M</emph> = 1.97 (<emph>SD</emph> = 0.18)). Overall scores for the quality of instructional delivery were calculated for the standard pronunciation condition (<emph>M</emph> = 6.67 (<emph>SD</emph> = 0.5)) and multiple pronunciations condition (<emph>M</emph> = 6.56 (<emph>SD</emph> = 0.73)). Average dose was calculated for the standard pronunciation condition (<emph>M</emph> = 5.07 (<emph>SD</emph> = 1.13)) and multiple pronunciations condition (<emph>M</emph> = 4.74 (<emph>SD</emph> = 1.44)). Data suggest fidelity did not vary significantly between conditions.</p> <hd id="AN0186465936-34">Evaluation of threats to internal validity</hd> <p></p> <hd id="AN0186465936-35">Carryover effects</hd> <p>Use of the same sample for Study 1 and Study 2 introduces a threat of carryover effects, or the possibility that residual effects from Study 1 influenced student performance in Study 2 (Cook et al., [<reflink idref="bib16" id="ref122">16</reflink>]). The design of the present research somewhat controls for this risk. That is, randomization within matched pairs to instructional condition prior to Study 1 and Study 2 suggests that students had equal chances of receiving either instructional condition in both studies. Carryover effects were tested using a multiple regression in a multilevel context that investigated whether Study 2 groups were equivalent on Study 1 posttest performance on Aligned Word Lists while controlling for Study 1 non-significant group differences on Aligned Word Lists at pretest and significant variance explained by school in Study 1. Results indicated no statistically significant carryover effects ( <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>β</mi><mo>=</mo></mrow></math> </ephtml> −6.79 <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mo>,</mo><mi>t</mi><mfenced close=")" open="("><mn>56</mn></mfenced><mo>=</mo><mo>-</mo></mrow></math> </ephtml> 0.82 <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mo>,</mo><mi>p</mi><mo>=</mo><mn>0.41</mn></mrow></math> </ephtml> ).</p> <hd id="AN0186465936-36">Interaction of condition assignment across studies</hd> <p>Another way to evaluate threats to internal validity based on use of the same sample for two studies is to test whether there were differences between student posttest performance on Aligned Word Lists in Study 2 based on assigned conditions across the two studies. More specifically, a multiple regression in the context of a multilevel model was conducted to examine whether there was an interaction between assigned conditions across Study 1 and Study 2; this model accounted for Study 2 non-significant group differences in pretest performance on Aligned Word Lists and significant variance explained by teachers in Study 2. Results indicated no statistically significant group differences in Study 2 posttest performance on Aligned Word Lists based on treatment assignment across the two studies ( <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>β</mi><mo>=</mo></mrow></math> </ephtml> −11.60 <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mo>,</mo><mi>t</mi><mfenced close=")" open="("><mn>48</mn></mfenced><mo>=</mo><mo>-</mo></mrow></math> </ephtml> 1.16 <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mo>,</mo><mi>p</mi><mo>=</mo><mn>0.25</mn></mrow></math> </ephtml> ).</p> <hd id="AN0186465936-37">Discussion</hd> <p>Treatment group differences in average posttest performance on taught words included in Aligned Word Lists were statistically significant in favor of those participants randomly assigned to the standard pronunciation condition. Specifically, recall of taught words was more strongly associated with the standard pronunciation condition. In the limited duration of the present context, instruction and practice targeting one pronunciation may have supported higher-quality lexical representations, at least for individuals with WRD who often struggle to establish print-speech connections. Desirable difficulties afforded by instruction and practice of two pronunciations in the multiple pronunciation condition may not have yielded short-term benefits; however, if examined in a context of extended duration, variability in sublexical content may result in stronger long-term retention and generalization (see Bjork & Bjork, [<reflink idref="bib7" id="ref123">7</reflink>]).</p> <p>The treatment group difference in average posttest performance on untaught words included in Aligned Word Lists was not statistically significant, which may indicate that neither approach resulted in the generalization of newly acquired sublexical content or that the treatments impacted student performance to a similar extent—perhaps, different pathways exist to the same outcome (Morris et al., [<reflink idref="bib57" id="ref124">57</reflink>]) or there is not "one best approach" (Mathes et al., [<reflink idref="bib55" id="ref125">55</reflink>]) to phonics instruction. In the present research, time was held constant across both conditions; thus, individuals assigned to the multiple pronunciations condition were expected to learn two pronunciations of a letter unit in the same amount of time that students assigned to the standard pronunciation condition were expected to learn just one pronunciation. Notably, the introduction of multiple pronunciations for a given letter unit in the context of one lesson is reflective of the aims of the present research. That is, access to knowledge of multiple pronunciations for a given letter unit must be accessible in real time to address inconsistencies between printed and spoken English. However, in order to observe generalized benefits, students with WRD likely require increased opportunities for practice with immediate, targeted feedback from a skilled reader (Ehri & Saltmarsh, [<reflink idref="bib23" id="ref126">23</reflink>]; Hughes et al., [<reflink idref="bib45" id="ref127">45</reflink>]; Kulik & Kulik, [<reflink idref="bib46" id="ref128">46</reflink>]; Reitsma, [<reflink idref="bib68" id="ref129">68</reflink>]; Spear-Swerling, [<reflink idref="bib82" id="ref130">82</reflink>]; Wisniewski et al., [<reflink idref="bib95" id="ref131">95</reflink>]). Future research examining the efficacy of a full-scale intervention over a longer duration of time may offer more insight regarding whether there are differential effects resulting from the number of pronunciations targeted in instruction.</p> <hd id="AN0186465936-38">Limitations</hd> <p>No limitations unique to Study 2 were noted.</p> <hd id="AN0186465936-39">General discussion</hd> <p>Individuals with WRD access less print over time, which reduces opportunities to engage in phonological recoding, a means for acquiring word-level representations that contribute to skilled reading (Wang et al., [<reflink idref="bib95" id="ref132">95</reflink>]). Limited access to print is especially problematic when considering the multiple encounters with words individuals with WRD need to demonstrate efficiency in reading them (Catts, [<reflink idref="bib11" id="ref133">11</reflink>]; Reitsma, [<reflink idref="bib69" id="ref134">69</reflink>]). For example, Ehri and Saltmarsh ([<reflink idref="bib23" id="ref135">23</reflink>]) revealed that more skilled readers demonstrated mastery of nonwords after 4.3 exposures, whereas 9.3 exposures to a word were needed for less skilled readers to demonstrate mastery of nonwords. Over time, the need for individuals with WRD to experience multiple encounters with words to achieve what typically achieving readers can do in less encounters widens the achievement gap between less skilled and more skilled readers (Stanovich, [<reflink idref="bib83" id="ref136">83</reflink>]; Wang et al., [<reflink idref="bib95" id="ref137">95</reflink>]). More specifically, access to print is correlated with improved vocabulary and content knowledge, which in turn support text comprehension; this phenomenon is referred to as the Matthew effect (Stanovich, [<reflink idref="bib83" id="ref138">83</reflink>]). Thus, without the ability to effectively translate print to speech, individuals are unable to access the meaning of text, the ultimate goal of reading.</p> <p>Reading theory suggests symmetrical growth in lexical and sublexical knowledge is needed to facilitate word reading efficiency for students with WRD (Ehri, [<reflink idref="bib22" id="ref139">22</reflink>]; Perfetti, [<reflink idref="bib64" id="ref140">64</reflink>]). Acquisition of grapheme–phoneme correspondences, sublexical units used to read, is especially challenging for individuals with WRD (Thompson et al., [<reflink idref="bib86" id="ref141">86</reflink>]; Torppa et al., [<reflink idref="bib89" id="ref142">89</reflink>]), but adequate sublexical knowledge contributes to efficient and effective phonological recoding useful for developing automaticity in word reading (Ritchey & Speece, [<reflink idref="bib70" id="ref143">70</reflink>]; Wolf & Katzir-Cohen, [<reflink idref="bib101" id="ref144">101</reflink>]). Specifically, research suggests multiple-letter (i.e., complex) grapheme–phoneme correspondences are more challenging for individuals to read than single-letter (i.e., simple) grapheme–phoneme correspondences (Frederiksen & Kroll, [<reflink idref="bib31" id="ref145">31</reflink>]; Olson et al., [<reflink idref="bib61" id="ref146">61</reflink>]). Additionally, vowels represent most irregularities in the English language (Rayner et al., [<reflink idref="bib67" id="ref147">67</reflink>]), which makes instruction and practice targeting spelling–sound relations of vowels an optimal choice. In particular, instruction that offers variability in non-targeted letters surrounding the targeted vowel has resulted in successful acquisition of targeted sublexical units and words that contain targeted sublexical units (Apfelbaum et al., [<reflink idref="bib3" id="ref148">3</reflink>]). Ultimately, transfer of taught sublexical units to word-level contexts is necessary for consolidation of learning to occur (Chen & Savage, [<reflink idref="bib12" id="ref149">12</reflink>]), a process referred to as direct mapping (Savage et al., [<reflink idref="bib73" id="ref150">73</reflink>]). For example, individuals with WRD and a mean age of 9.6 years demonstrated improved performance on both real word and nonword measures of regular-spelled words when instruction targeted letter–sound relations and words that contained taught letter–sound relations (Lovett et al., [<reflink idref="bib51" id="ref151">51</reflink>]). Thus, it may be beneficial to provide orthographic code learning in which individuals are exposed to conditional (i.e., context-sensitive) pronunciations and given opportunities to practice reading words that contain conditional pronunciations until individuals demonstrate efficiency (Compton et al., [<reflink idref="bib15" id="ref152">15</reflink>]; Wolf & Katzir-Cohen, [<reflink idref="bib95" id="ref153">95</reflink>]).</p> <hd id="AN0186465936-40">Limitations</hd> <p>The present research occurred during the COVID-19 pandemic before widespread vaccine access. Given limited school access, the present research was conducted virtually via Zoom. Despite consistent use of a virtual platform, students logged on from school or home based on COVID-19 symptoms. Barriers encountered in the virtual delivery of instruction included audio issues, weak internet connections, and drained batteries in devices used to access treatment. Also, given participant age, participants were often reliant on their teachers or parents to remember to log them onto Zoom, which was made more challenging because of participants' ever-changing status of remote vs. in-person learning. Nevertheless, the improved performance demonstrated across studies and conditions suggests that positive effects of word reading interventions can occur during virtual learning despite these challenges.</p> <p>Moreover, differences in exposure to words resulting from the varied extent of practice individual students required for mastery are a limitation of this study. For example, some students acquired mastery (i.e., accurate identification of word within 1 s) faster than others, and some students were unable to demonstrate mastery of word sets in the timespan of the lesson. Future research in which practice opportunities are more tightly controlled warrants further attention.</p> <p>The present analyses were conducted using an intent-to-treat approach, suggesting a potential influence of variation in dosage (i.e., number of lessons) received by participants; however, this decision also reflects the realities of real-world effectiveness. An a priori power analysis was not conducted, and the intent of these studies was exploratory; accordingly, the analyses and findings may be underpowered. Additionally, the present research included moderate sample sizes of 61 and 64 for Studies 1 and 2, respectively; further research using larger samples could offer more reliable findings (Fig. 2).</p> <p>Graph: Fig. 2 Scope and sequence for Study 1 and Study 2</p> <hd id="AN0186465936-41">Implications for practice</hd> <p></p> <hd id="AN0186465936-42">Delivery</hd> <p>The present research supports the use of explicit phonics instruction for students in elementary grades with WRD (e.g., Anderson et al., [<reflink idref="bib2" id="ref154">2</reflink>]; Bond & Dykstra, [<reflink idref="bib8" id="ref155">8</reflink>]; National Early Literacy Panel, [<reflink idref="bib58" id="ref156">58</reflink>]; National Reading Panel, [<reflink idref="bib59" id="ref157">59</reflink>]; Prochnow et al., [<reflink idref="bib65" id="ref158">65</reflink>]; Snow et al., [<reflink idref="bib81" id="ref159">81</reflink>]). Specifically, students may benefit from modeling, guided practice, and independent practice with immediate and specific feedback. Findings from these studies also support instructional opportunities in which taught sublexical units can be applied and practiced in a wide variety of word-level contexts (e.g., Lovett et al., [<reflink idref="bib51" id="ref160">51</reflink>]), with word reading practice opportunities that promote fluency, not just accuracy in the application of concepts and skills (Compton et al., [<reflink idref="bib15" id="ref161">15</reflink>]; Lemoine et al., [<reflink idref="bib49" id="ref162">49</reflink>]; Levy & Lysynchuk, [<reflink idref="bib50" id="ref163">50</reflink>]). Furthermore, the present studies contribute to existing research in favor of opportunities for struggling readers to demonstrate flexibility in the application of skills and concepts, such as variable vowel sounds (Lovett et al., [<reflink idref="bib52" id="ref164">52</reflink>], [<reflink idref="bib53" id="ref165">53</reflink>]; Savage & Stuart, [<reflink idref="bib71" id="ref166">71</reflink>], [<reflink idref="bib72" id="ref167">72</reflink>]; Steacy et al., [<reflink idref="bib84" id="ref168">84</reflink>]).</p> <p>Prior to COVID-19, research examining the effects of virtual academic intervention for students in elementary grades who experience academic difficulties was scarce (e.g., Barbour, [<reflink idref="bib4" id="ref169">4</reflink>]; Vasquez & Straub, [<reflink idref="bib93" id="ref170">93</reflink>]). Existing research supports one-to-one virtual reading interventions (e.g., Beach et al., [<reflink idref="bib6" id="ref171">6</reflink>]; Vasquez et al., [<reflink idref="bib94" id="ref172">94</reflink>]); the present research adds to this literature base. Despite challenges in the virtual delivery of instruction identified in the present research, growth in average word reading performance, evident across conditions and studies, supports its use in improving word reading skills of students in grades 2–4 with WRD.</p> <hd id="AN0186465936-43">Content focus</hd> <p>As supported by findings from Study 1, for students in grades 2–4 with WRD who have likely been exposed to beginning reading instruction in single letters, phonics instruction targeting complex letter units (e.g., vowel combinations with co-occurring consonants: <emph>ai– ail</emph>, <emph>aid</emph>, <emph>ait</emph>, <emph>aim</emph>, <emph>ain</emph>) may improve unitization needed to facilitate efficient word reading. Furthermore, emphasizing variability in vowel pronunciation may also improve the effectiveness of phonics instruction for poor readers (e.g., Lovett et al., [<reflink idref="bib53" id="ref173">53</reflink>]; Savage & Stuart, [<reflink idref="bib71" id="ref174">71</reflink>], [<reflink idref="bib72" id="ref175">72</reflink>]), which has been successful in existing research (e.g., Lovett et al., [<reflink idref="bib52" id="ref176">52</reflink>]; Steacy et al., [<reflink idref="bib84" id="ref177">84</reflink>]).</p> <p>Study 2 findings suggest students may benefit from instruction and practice targeting standard pronunciations of a given letter unit, as well as instruction simultaneously targeting an alternate, variable pronunciation of that same letter unit; however, for students with WRD, it may be more advantageous to hold off on introducing multiple pronunciations until knowledge of the standard pronunciation is more secure or to provide more substantial practice opportunities with immediate, targeted feedback from a skilled reader (Ehri & Saltmarsh, [<reflink idref="bib23" id="ref178">23</reflink>]; Hughes et al., [<reflink idref="bib45" id="ref179">45</reflink>]; Kulik & Kulik, [<reflink idref="bib46" id="ref180">46</reflink>]; Reitsma, [<reflink idref="bib68" id="ref181">68</reflink>]; Spear-Swerling, [<reflink idref="bib82" id="ref182">82</reflink>]; Wisniewski et al., [<reflink idref="bib95" id="ref183">95</reflink>]).</p> <hd id="AN0186465936-44">Future directions for research</hd> <p></p> <hd id="AN0186465936-45">Data collection</hd> <p>Data regarding prior participation in reading intervention for the current sample is unavailable. Notably, it is possible that conditions aligned with a more traditional approach offered in Study 1 and Study 2 may be redundant for students with a history of participation in reading intervention. Future efforts to examine intervention effects for the present population would benefit from the collection of these data. Moreover, follow-up measures might be administered to better understand how these effects maintain over time, especially considering the need for intervention resulting in long-lasting gains (e.g., Compton et al., [<reflink idref="bib15" id="ref184">15</reflink>]; Olson et al., [<reflink idref="bib60" id="ref185">60</reflink>]).</p> <hd id="AN0186465936-46">Delivery</hd> <p>Research supports the inclusion of review in remediation efforts (e.g., Dunlosky et al., [<reflink idref="bib19" id="ref186">19</reflink>]; Gerbier & Toppino, [<reflink idref="bib36" id="ref187">36</reflink>]). Review of previously taught content was not included in the present study; however, intentionally incorporating distributed practice may be useful in future iterations of this research.</p> <hd id="AN0186465936-47">Content focus</hd> <p>Findings from Study 2 suggest further research is needed to better understand the impact of teaching standard vs. multiple pronunciations for letter units. To evaluate the added benefit of learning multiple pronunciations for a given letter unit, it may be necessary to remove the constraint of controlling for time across conditions. Allowing time to vary between conditions in Study 2 may provide participants adequate time to develop high-quality representations of targeted sublexical content supportive of proficient word reading (Perfetti, [<reflink idref="bib64" id="ref188">64</reflink>]; Ritchey & Speece, [<reflink idref="bib70" id="ref189">70</reflink>]; Wolf & Katzir-Cohen, [<reflink idref="bib95" id="ref190">95</reflink>]). A modified approach to teaching multiple pronunciations of a letter unit might involve restructuring the instructional sequence within the context of a lesson. In the present research, unique pronunciations of a letter unit were introduced consecutively before engaging in extended word reading practice. Future research may also consider firmly establishing the standard pronunciation of a letter unit before introducing an alternate, variable pronunciation of the same letter unit.</p> <p>More broadly, the present research examined the impact of word reading instruction on word reading outcomes for students in grades 2–4 with school-identified WRD. Further research examining variation in instructional features (i.e., content focus and delivery) is needed to better understand the conditions supportive of long-term effects on reading outcomes for elementary-aged students with WRD.</p> <hd id="AN0186465936-48">Conclusion</hd> <p>Across Study 1 and Study 2, average student performance was positively impacted, regardless of randomly assigned condition, as evidenced by growth from pre- to posttest (Tables 2 and 4); however, differential growth specific to instructional condition suggests a potential impact of changes to sublexical content typically targeted in instruction and practice. The outcomes of this study provide us with preliminary understandings of the impact of these instructional adjustments; however, given the limitations of the sample—both size and use of the same sample for each study—further research is warranted to verify these findings. More specifically, further research is warranted to better understand the impact related to the size of letter units and the number of pronunciations targeted for a given letter unit on the acquisition of skilled word reading for the target population.</p> <hd id="AN0186465936-49">Funding</hd> <p>This research was supported by the Institute for Education Sciences under Grant #R324 A200209 to The University of Texas at Austin. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Institute of Education Sciences.</p> <hd id="AN0186465936-50">Declarations</hd> <p></p> <hd id="AN0186465936-51">Conflict of interest</hd> <p>The authors declare no competing interests.</p> <hd id="AN0186465936-52">Supplementary Information</hd> <p>Below is the link to the electronic supplementary material.</p> <p>Graph: Supplementary file1 (DOCX 276 KB)</p> <hd id="AN0186465936-53">Publisher's Note</hd> <p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p> <ref id="AN0186465936-54"> <title> References </title> <blist> <bibl id="bib1" idref="ref5" type="bt">1</bibl> <bibtext> Al Otaiba, S, McMaster, K, Wanzek, J, & Zaru, M. W. (2023). What we know and need to know about literacy interventions for elementary students with reading difficulties and disabilities, including dyslexia. 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  Group: Ti
  Data: Testing Variations in Sublexical Units to Improve Word Reading for Students with Word Reading Disabilities
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Alexis+N%2E+Boucher%22">Alexis N. Boucher</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0001-8719-4415">0000-0001-8719-4415</externalLink>)<br /><searchLink fieldCode="AR" term="%22Nathan+H%2E+Clemens%22">Nathan H. Clemens</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-8361-1303">0000-0002-8361-1303</externalLink>)<br /><searchLink fieldCode="AR" term="%22Sharon+Vaughn%22">Sharon Vaughn</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0001-8305-5549">0000-0001-8305-5549</externalLink>)<br /><searchLink fieldCode="AR" term="%22Greg+Roberts%22">Greg Roberts</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-7680-8757">0000-0002-7680-8757</externalLink>)<br /><searchLink fieldCode="AR" term="%22Marcia+A%2E+Barnes%22">Marcia A. Barnes</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-9446-3000">0000-0002-9446-3000</externalLink>)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Annals+of+Dyslexia%22"><i>Annals of Dyslexia</i></searchLink>. 2025 75(2):199-224.
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  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 26
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2025
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  Label: Sponsoring Agency
  Group: SrcSuprt
  Data: Institute of Education Sciences (ED)
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  Label: Contract Number
  Group: NumCntrct
  Data: R324A200209
– 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="%22Elementary+Education%22">Elementary Education</searchLink><br /><searchLink fieldCode="EL" term="%22Early+Childhood+Education%22">Early Childhood Education</searchLink><br /><searchLink fieldCode="EL" term="%22Grade+3%22">Grade 3</searchLink><br /><searchLink fieldCode="EL" term="%22Primary+Education%22">Primary Education</searchLink><br /><searchLink fieldCode="EL" term="%22Grade+2%22">Grade 2</searchLink><br /><searchLink fieldCode="EL" term="%22Grade+4%22">Grade 4</searchLink><br /><searchLink fieldCode="EL" term="%22Intermediate+Grades%22">Intermediate Grades</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Reading+Difficulties%22">Reading Difficulties</searchLink><br /><searchLink fieldCode="DE" term="%22Reading+Instruction%22">Reading Instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Students+with+Disabilities%22">Students with Disabilities</searchLink><br /><searchLink fieldCode="DE" term="%22Elementary+School+Students%22">Elementary School Students</searchLink><br /><searchLink fieldCode="DE" term="%22Grade+3%22">Grade 3</searchLink><br /><searchLink fieldCode="DE" term="%22Grade+2%22">Grade 2</searchLink><br /><searchLink fieldCode="DE" term="%22Grade+4%22">Grade 4</searchLink><br /><searchLink fieldCode="DE" term="%22Instructional+Effectiveness%22">Instructional Effectiveness</searchLink><br /><searchLink fieldCode="DE" term="%22Vocabulary%22">Vocabulary</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1007/s11881-025-00332-3
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0736-9387<br />1934-7243
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Word reading disabilities (WRD) represent the most common disability in reading; however, questions remain regarding how to design instruction that results in significant, long-lasting effects on word reading outcomes for individuals who experience considerable difficulties that persist within and beyond primary grades. Two related studies examined effects of variations in targeted sublexical content on word reading efficiency of students in grades 2-4 with WRD. Study 1 addressed effects of instruction and practice targeting complex vs. simple letter units. Study 2 addressed effects of instruction and practice targeting multiple pronunciations of a letter unit vs. standard pronunciations alone. In Study 1, statistically significant differences at posttest on taught ([beta]=9.43, t(56)=2.32, p=0.02; g=0.17, 95\% CI[0.01,0.33]) words included in Aligned Word Lists favored the complex letter unit condition. In Study 2, statistically significant differences at posttest on taught words included in Aligned Word Lists favored the standard pronunciations condition ([beta]=-4.15, t(60)=-2.04, p=0.045; g=-0.18, 95\% CI[-0.35,0.004]) and group differences in average student performance were non-significant on untaught words ([beta]=-0.22, t(60)=-0.06, p=0.96; g=-0.01, 95\% CI-0.17,0.17]). Given the modest sample sizes (N = 64) and amount of instruction provided in each study (i.e., 6 lessons), further research is warranted to better understand the impact of variations in targeted sublexical content on word reading outcomes for students with WRD in grades 2-4.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: CodeSource
  Label: IES Funded
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  Data: Yes
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  Label: Entry Date
  Group: Date
  Data: 2025
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  Label: Accession Number
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  Data: EJ1476426
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        PageCount: 26
        StartPage: 199
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      – SubjectFull: Reading Difficulties
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      – SubjectFull: Reading Instruction
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      – SubjectFull: Students with Disabilities
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      – TitleFull: Testing Variations in Sublexical Units to Improve Word Reading for Students with Word Reading Disabilities
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