24  Word Reading

24.1 Task Description

Children are shown words and are asked to read them.

24.2 Construct

The Word Reading task measures the construct of decoding accuracy, the ability to translate print into speech by correctly pairing graphemes (letters) with their corresponding phonemes (sounds) using pronounceable real words.

24.3 Item Development

24.3.1 English

For the development of the item pool, multiple curricula to create a list of frequent, decodable words, including curricula used in the United States, like McGraw-Hill’s “Wonders”, Benchmark’s “Benchmark Advance”, and HMH’s “Journey” were reviewed.

From this pool of items, we selected a sample of words, whose semantic meaning was overall easily accessed by the target population, with a variety of word types (e.g., nouns, verbs, adjectives, adverbs, etc.) and with varying orthographic and phonological length.

24.3.2 Spanish

For the development of the item pool, the research team reviewed multiple curricula to build up a list of frequent, decodable words, including curricula used in dual language programs in the United States, like the McGraw-Hill Maravillas, Estrellita, Houghton Mifflin Lectura, in addition to existing kindergarten and first-grade materials from Mexico, Panama, and Chile.

From the pool of items, we selected a sample of words, whose semantic meaning was overall easily accessed by the target population, with a variety of word types (e.g., nouns, verbs, adjectives, adverbs, etc.) and with varying orthographic and phonological length. Concepts represented by multiple words –that is, reflecting dialectic variability based on the cultural and/or geographic background of the respondent–were excluded to avoid benefiting certain cultural groups (e.g., “pig”: puerco, cerdo, chancho; “shirt”: polera, polo, remera; “avocado”: aguacate, palta). In addition to the selected pool of words, we included cognates to explore the possible interference or advancement of cognates in word reading for students in dual language programs.

24.3.3 Scoring

Dichotomous fixed response format of 0 points for incorrect responses or non-responses and 1 point for correct ones.

24.4 Calibration Samples

Table 24.1: Demographic Characteristics of Calibration Samples for the English and Spanish Word Reading Tasks
Characteristic
English
Spanish
G1
N = 3,249		 G2
N = 3,251		 G1
N = 1,354		 G2
N = 1,060
Timepoint



    Fall 2023 605 (19%) 648 (20%) 0 (0%) 0 (0%)
    Winter 2024 0 (0%) 0 (0%) 0 (0%) 432 (52%)
    Fall 2024 2,644 (81%) 2,603 (80%) 627 (100%) 396 (48%)
Administration Format



    CAT 2,644 (81%) 2,603 (80%) 827 (61%) 628 (59%)
    Forms 605 (19%) 648 (20%) 527 (39%) 432 (41%)
Race



    American/Alaskan Native 117 (3.8%) 63 (2.1%) 40 (4.9%) 15 (1.4%)
    Asian 247 (8.1%) 231 (7.6%) 32 (3.9%) 25 (2.4%)
    Black/African American 307 (10%) 343 (11%) 19 (2.3%) 14 (1.3%)
    Not reported 393 (13%) 366 (12%) 231 (28%) 443 (42%)
    Other 441 (14%) 376 (12%) 115 (14%) 68 (6.5%)
    White 1,543 (51%) 1,653 (55%) 379 (46%) 479 (46%)
    Unknown 201 219 538 16
Ethnicity



    Hispanic/Latin(o/a) 2,134 (70%) 2,105 (70%) 764 (96%) 951 (92%)
    Intentional nonreport 13 (0.4%) 5 (0.2%) 2 (0.3%) 4 (0.4%)
    Not Hispanic/Latin(o/a) 898 (29%) 892 (30%) 34 (4.3%) 75 (7.3%)
    Unknown 204 249 554 30
Gender



    Female 1,512 (50%) 1,479 (49%) 428 (55%) 549 (53%)
    Male 1,507 (50%) 1,509 (51%) 345 (45%) 489 (47%)
    Non-binary 0 (0%) 0 (0%) 0 (0%) 1 (<0.1%)
    Unknown 230 263 581 21
Home Language



    English 1,825 (64%) 1,821 (64%) 101 (12%) 148 (15%)
    Spanish 901 (32%) 884 (31%) 709 (87%) 855 (85%)
    Other 107 (3.8%) 144 (5.1%) 2 (0.2%) 7 (0.7%)
    Unknown 416 402 542 50
English Proficiency Label



    (Re-)Classified Proficient 159 (5.8%) 294 (10%) 84 (11%) 129 (13%)
    English Learner 835 (30%) 728 (26%) 599 (78%) 708 (73%)
    English-only 1,763 (64%) 1,800 (64%) 88 (11%) 138 (14%)
    Unknown 492 429 583 85
Ever IEP/504 229 (9.5%) 241 (10%) 63 (8.9%) 81 (10%)
    Unknown 829 918 649 255
    Unknown

727 232

24.5 Psychometric Analysis

24.5.1 Basic Item Statistics

We excluded 0 items from the English task and 0 items from the Spanish task based on low response counts (n < 90). 0 items were excluded because they had no variance in the Spanish task, and 0 items in the English task. Additionally, we excluded 2 items from the English task and 0 items from the Spanish task based on low point-biserial correlations (r < 0.2). Table 24.2 summarizes the basic item characteristics, Figure 24.1 shows the relationship between point-biserial correlations and the proportion of correct responses for each item.

Table 24.2: Basic Item Statistics Before and After Application of Exclusion Criteria, for the English and Spanish Word Reading Tasks
English
Spanish
Characteristic
Before Excl.
After Excl.
Before Excl.
After Excl.
N = 187 N = 185 N = 209 N = 209
No. of Responses 363 (325) 365 (326) 214 (146) 214 (146)
Proportion Correct 0.54 (0.23) 0.55 (0.22) 0.51 (0.16) 0.51 (0.16)
Point-biserial Correlation 0.64 (0.12) 0.65 (0.11) 0.69 (0.09) 0.69 (0.09)
Excluded (n < 90) 0 (0%) 0 (0%) 0 (0%) 0 (0%)
Excluded (pbis < .2) 2 (1.1%) 0 (0%) 0 (0%) 0 (0%)
Excluded (no variation) 0 (0%) 0 (0%) 0 (0%) 0 (0%)
Figure 24.1: Scatterplot Showing Point-biserial (Item-total) Correlations and Proportion of Correct Responses for the English (Panel A) and Spanish (Panel B) Word Reading Tasks

24.5.2 Rasch Analysis

24.5.2.1 Item Location Estimates

Figure 24.2: Scatterplot Showing Item Location and Proportion of Correct Response for the English (Panel A) and Spanish (Panel B) Word Reading Tasks

24.5.2.2 Item Fit Statistics

Table 24.3: Frequencies of Item Misfit Categories Based on Infit/Outfit MSE Values for the English and Spanish Word Reading Tasks
English
Spanish
Infit MSE
A B C D Total A B C D Total
Outfit MSE
A 144 0 0 0 144 171 0 0 0 171
B 28 0 0 0 28 26 0 0 0 26
C 8 0 0 0 8 7 0 0 0 7
D 3 0 2 0 5 4 0 1 0 5
Total 183 0 2 0 185 208 0 1 0 209

24.5.2.3 Person Location Estimates

Figure 24.3: Scatterplot Showing Person Location Estimates (Obtained using the MLE method) and the Proportion of Correct Responses for English and Spanish Word Reading Tasks

24.5.2.4 Person Fit Statistics

Table 24.4: Frequencies of Person Misfit Categories Based on Infit/Outfit MSE Values for the English and Spanish Word Reading Tasks
English
Spanish
Infit MSE
A B C D Total A B C D Total
Outfit MSE
A 2,718 0 36 2 2,756 1,363 0 2 2 1,367
B 1,581 1,794 3 0 3,378 172 745 0 0 917
C 90 0 30 7 127 26 0 3 0 29
D 80 0 44 18 142 15 0 11 0 26
Total 4,469 1,794 113 27 6,403 1,576 745 16 2 2,339

24.5.2.5 Distribution of Theta Estimates

Figure 24.4: Distribution of Theta Estimates for the English and Spanish Word Reading Tasks

24.5.2.6 Wright Maps

Figure 24.5: Wright Maps Showing the Relationship Between Item and Person Location Estimates for the English Word Reading Task
Figure 24.6: Wright Maps Showing the Relationship Between Item and Person Location Estimates for the Spanish Word Reading Task

24.5.2.7 Model Summary

Table 24.5: Summary of Rasch Model Statistics for the English and Spanish Word Reading Tasks
English
Spanish
Item
Person
Item
Person
Characteristic N = 185 N = 6,403 N = 209 N = 2,339
Logit Scale Location -0.19 (2.41) 0.05 (-2.02, 2.22) 0.53 (1.46) 0.33 (-2.68, 2.36)
Outfit 0.87 (0.73) 0.48 (0.28, 0.70) 0.89 (0.48) 0.65 (0.05, 0.90)
Infit 0.92 (0.15) 0.70 (0.43, 0.90) 0.96 (0.16) 0.80 (0.19, 0.94)
Reliability of Separation 0.8997 0.8540 0.9130 0.8429
24.5.2.7.1 Final Number of Items

Following the exclusion of items with point-biserial correlations < .20 and items with poor fit statistics, the final versions of the task contain 185 and 209 for the English and Spanish task, respectively.

24.6 Criterion Validity Evidence

24.6.1 Sample

Table 24.6: Demographic Characteristics of the Concurrent Criterion Validity Evidence Samples for the English and Spanish Word Reading Tasks
Characteristic
English
Spanish
G1
N = 221		 G2
N = 259		 G1
N = 191		 G2
N = 227
Timepoint



    Spring 2024 221 (100%) 259 (100%) 191 (100%) 227 (100%)
Race



    American/Alaskan Native 5 (2.3%) 1 (0.4%) 4 (2.1%) 4 (1.8%)
    Asian 25 (11%) 34 (13%) 6 (3.2%) 3 (1.3%)
    Black/African American 27 (12%) 32 (12%) 4 (2.1%) 4 (1.8%)
    Not reported 55 (25%) 68 (26%) 73 (39%) 96 (43%)
    Other 34 (15%) 26 (10%) 10 (5.3%) 14 (6.2%)
    White 75 (34%) 98 (38%) 92 (49%) 104 (46%)
Ethnicity



    Hispanic/Latin(o/a) 102 (46%) 140 (54%) 172 (90%) 198 (87%)
    Intentional nonreport 2 (0.9%) 0 (0%) 0 (0%) 2 (0.9%)
    Not Hispanic/Latin(o/a) 117 (53%) 119 (46%) 19 (9.9%) 27 (12%)
Gender



    Female 97 (44%) 127 (49%) 100 (52%) 128 (56%)
    Male 124 (56%) 132 (51%) 91 (48%) 99 (44%)
Home Language



    English 159 (73%) 177 (69%) 43 (23%) 57 (26%)
    Spanish 37 (17%) 41 (16%) 144 (76%) 164 (74%)
    Other 23 (11%) 40 (16%) 2 (1.1%) 1 (0.5%)
    Unknown 2 1 2 5
English Proficiency Label



    (Re-)Classified Proficient 21 (9.7%) 23 (9.0%) 33 (17%) 37 (17%)
    English Learner 47 (22%) 60 (23%) 120 (63%) 129 (59%)
    English-only 148 (69%) 173 (68%) 36 (19%) 54 (25%)
    Unknown 5 3 2 7
Ever IEP/504 22 (11%) 29 (14%) 16 (10%) 17 (9.3%)
    Unknown 23 47 34 45
    Unknown

2 2

English Word Reading was correlated with the Letter-Word Identification subtest from the Woodcock-Johnson IV (WJ IV ACH) test (Schrank, McGrew, and Mather 2014). Spanish Word Reading was correlated with the Identificación de Letras y Palabras subtest from the Batería IV Woodcock-Muñoz (Batería IV APROV) test (Woodcock et al. 2019).

Table 24.7: Concurrent Criterion Validity Correlations for the English and Spanish Word Reading Tasks
English
Spanish
All
EL
All
Grade n r [CI] n r [CI] n r [CI]
G1 220 0.90 [0.87, 0.92] 47 0.90 [0.83, 0.94] 191 0.85 [0.80, 0.88]
G2 259 0.77 [0.72, 0.82] 60 0.80 [0.69, 0.88] 227 0.80 [0.75, 0.84]