Measuring Teachers’ Orientations Regarding Reading Instruction for Students With IDD

Abstract

Reading skills are important to the academic success and long-term self-determination of individuals with disabilities. Teachers’ theoretical orientations toward reading instruction are relevant to their implementation of interventions that may be more or less effective in addressing students’ needs. Whereas reading instructional orientation has been studied previously in broader samples of general and special education teachers, there is little information about teachers working with students with intellectual and developmental disabilities (SET-IDDs). We recruited a nationally representative U.S. sample of SET-IDDs (n = 318) to complete a measure of theoretical orientations toward reading specific to students with IDD. This study describes the adaptation of the Teacher Perceptions about Early Reading and Spelling-IDD scale and its psychometric properties. Results of exploratory factor analysis indicate two subscales: explicit orientations and implicit orientations. SET-IDDs had a stronger preference for explicit approaches than implicit approaches. In addition, the two subscales were significantly negatively correlated. We discuss the value of assessing SET-IDDs’ theoretical orientations toward reading instruction and implications for reading intervention for students with IDD.

Keywords

reading/literacy intellectual disability instruction

Reading skills are essential for academic success, independent living, and increased employment prospects for students with intellectual and developmental disabilities (IDD; for example, Browder et al., 2006).¹ Though whole word instruction has been frequently used with this population in the past (e.g., Bruni & Hixson, 2017), contemporary research underlines the efficacy of code-based approaches to word reading for students with IDD (e.g., Sermier Dessemontet et al., 2019). Explicit, code-based approaches are favorable because skills taught are transferable. That is, students can apply knowledge of letter-sound correspondences efficiently to read new, untaught words. In contrast, whole word approaches focus on teaching words as whole units without teaching letter-sound correspondences which provides little opportunity for transfer of skills to read new words beyond those taught.

Despite the growing body of empirical evidence supporting code-based word reading instruction, descriptive observation studies examining business-as-usual reading instruction for students with IDD raise concern. Results suggest that some special educators continue to provide whole word instruction (Lindström & Lemons, 2021) and/or use unsystematic approaches to phonics instruction (Sermier Dessemontet et al., 2022). Further, within these studies, researchers documented variation in approaches to reading instruction across classrooms, some of which were within the same school building.

Teachers’ theoretical orientations toward reading instruction, that is teachers’ “knowledge and belief system held toward reading [instruction],” may explain some of the observed differences in business-as-usual practices (DeFord, 1985, p. 353). In a prior study, Cunningham and colleagues (2009) investigated relations among teachers’ content knowledge, implicit beliefs about reading instruction, and instructional practices. Results suggested that teachers’ beliefs influenced their instructional decision-making, such that teachers allocated instructional time and selected activities that aligned with their implicit beliefs. Together, (a) relation between teachers’ beliefs about reading instruction and instructional practices and (b) evidence supporting code-based instruction as a more effective approach to word reading instruction for students with IDD (e.g., Sermier Dessemontet et al., 2019) highlight a pathway through which teachers’ theoretical orientations toward reading instruction may influence students’ learning opportunities and achievement.

Teachers’ theoretical orientations toward reading instruction have been studied in a broader population of pre- and in-service teachers (Bos et al., 2001). Bos and colleagues (2001) adapted DeFord’s (1985) Theoretical Orientation to Reading Profile (TORP) measure and developed a shortened scale titled Teacher Perceptions about Early Reading and Spelling (TPERS). The TPERS includes statements describing explicit (e.g., phonics and phonemic awareness instruction) and implicit (e.g., picture cues, exposure to text, deprioritization of accurate decoding) approaches to reading instruction. Bos and colleagues reported that in-service teachers with a stronger explicit orientation felt significantly more prepared to teach reading, to teach reading using code-based approaches, and to teach students with reading difficulties. Conversely, in-service teachers with a stronger implicit orientation felt significantly more prepared to teach reading using implicit methods.

Research Questions

Because whole word reading instruction persists for students with IDD, it is important to investigate theoretical orientations (e.g., explicit vs. implicit) of the subpopulation of special education teachers working with students with IDD (SET-IDDs) pertaining to their students with IDD, specifically. SET-IDDs’ perceptions of early reading instruction have implications for their instructional practices (Lindström et al., 2025) and for students’ access to high-quality reading instruction. Thus, the purposes of this study were to (a) adapt Bos and colleagues’ (2001) TPERS measure for a sample of SET-IDDs, (b) re-examine the psychometric properties of the measure, and (c) report SET-IDDs’ theoretical orientations toward reading instruction. To this end, our study addressed the following research questions:

Research Question 1 (RQ1): What is the underlying factor structure of the Teacher Perceptions about Early Reading and Spelling-IDD measure?

Research Question 2 (RQ2): What are SET-IDDs’ theoretical orientations toward reading instruction?

Method

Participants and Sampling

Special education teachers who taught students with IDD in at least one elementary grade (K–6) were eligible to participate. In total, 337 participants responded to some or all survey components. Of those participants, 318 completed the theoretical orientations measure. Participants were primarily White (83.6%), female (92.8%), and had earned a master’s degree (64.8%). Respondents reportedly taught students with autism (91.2%), intellectual disability (71.7%), multiple disabilities (35.8%), and developmental delay (1.9%). Most taught in resource (50.6%), inclusive (28.3%), or self-contained cross-categorical (25.2%) classrooms. All participant demographics for the subset of participants eligible for these analyses are reported in Table 1, and their teaching contexts are reported in Table 2.

Table 1.

Demographics for Special Education Teacher Participants.

Characteristic	Total
	n	%
Gender
Female	295	92.8
Male	13	4.1
Nonbinary	2	0.6
No response	8	0.9
Race/ethnicity
White	266	83.6
Black/African American	19	6.0
Hispanic or Latinx	13	4.1
Asian or Pacific Islander	9	2.8
Multiracial	2	0.6
Native American/Alaska Native	2	0.6
No response	7	2.2
Highest degree earned
Bachelor’s degree	105	33.0
Master’s degree	206	64.8
Professional	1	0.3
Doctorate	6	1.9

Note. The totals for race/ethnicity exceed the total number of responses as categories are not mutually exclusive.

Table 2.

Teacher Participant Contexts.

Variable	n	%
Grade level
Pre-Kindergarten	20	6.3
Kindergarten	151	47.5
First	166	52.2
Second	178	56.0
Third	204	64.2
Fourth	199	62.6
Fifth	171	53.8
Sixth	48	15.1
Seventh	16	5.0
Eighth	19	6.0
Ninth	6	1.9
Tenth	4	1.3
Eleventh	4	1.3
Twelfth	6	1.9
Teaching environment
Resource classroom in a public school	161	50.6
Inclusive classroom in a public school	90	28.3
Self-contained cross-categorical classroom in a public school	80	25.2
Self-contained disability-specific classroom in a public school	43	13.5
Homebound instruction	4	1.3
Separate public school for students with disabilities	1	0.3
Not listed	7	2.2
Students’ primary disabilities
Autism	290	91.2
Intellectual disability	228	71.7
Specific learning disability	229	72.0
Speech or language impairment	188	59.1
Emotional disturbance/behavior disorder	130	40.9
Multiple disabilities	114	35.8
Other health impairment	49	15.4
Visual impairment	39	12.3
Hearing impairment	34	10.7
Orthopedic impairment	38	11.9
Traumatic brain injury	21	6.6
Developmental delay	6	1.9
Not listed	5	1.6

Note. The totals for grade level, teaching environment, and students’ primary disabilities exceed the total number of responses, as categories are not mutually exclusive.

To generate a nationally representative sample, we used Tipton & Miller’s (2025) Generalizer webtool. Specific procedures regarding use of this tool for the present study and measures to reduce likelihood of automated bot responses are detailed in Lindström et al. (2025). We directly emailed special education teachers working at schools serving students in grades K–6 as identified by the Generalizer output, and we placed advertisements in leading special education professional organization member newsletters. Respondents provided informed consent and completed the survey using the REDCap web platform.

We removed responses from ineligible participants and those whose submissions failed data quality checks. Following data cleaning and identification of our final sample, we used the Generalizer to estimate the generalizability of respondents’ schools against the national sample of elementary schools across the United States. The generalizability index was 0.97, indicating very strong similarities to the national sample.

Survey

These data were drawn from a larger survey with several modular components. They included (a) teacher demographics, (b) teaching context, (c) instructional practices, (d) foundational reading knowledge, (e) theoretical orientations toward reading, and (f) teacher expectations. In this study, we report results of Part E only.

Teacher Perceptions About Early Reading and Spelling-IDD

The TPERS measure includes 13 Likert-style items on a 6-point scale (strongly disagree to strongly agree; Bos et al., 2001). Twelve items are worded to indicate a preference for either an explicit (n = 6) or implicit (n = 6) approach to reading instruction, and we duplicated one item on the explicit subscale (I6- phonics instruction is beneficial), wording I6 to apply to all elementary students and I7 to students with IDD, specifically. Bos and colleagues (2001) collected three sources of validity evidence for the TPERS measure: content, internal structure, and relations to other variables (American Educational Research Association [AERA] et al., 2014). They reported a two-factor structure and reliability of α = .70 for the explicit orientation subscale and α = .50 for the implicit orientation subscale. We adapted item wording, rewording items in a way that required respondents to reflect on their approach to reading instruction for students with IDD, specifically (e.g., “Time spent reading contributes directly to reading improvement for elementary students with IDD,” Bos et al., 2001, p. 105). This adapted measure is titled Teacher Perceptions about Early Reading Instruction and Spelling-IDD (TPERS-IDD).

Data Analysis

Because we made minor adjustments to the TPERS, we evaluated only the internal structure of the TPERS-IDD to confirm its validity for measuring SET-IDDs’ theoretical orientations (AERA et al., 2014). We ran a two-factor confirmatory factor analysis on the 13 items, assigning items to each subscale as delineated by Bos and colleagues (2001). Model fit statistics were poor (see Table 3). Thus, we conducted an exploratory factor analysis (EFA) in Mplus Version 8 (Muthén & Muthén, 2017) to further examine the measure’s internal structure (Bandalos, 2018), including all 13 items. First, we examined correlation values on the inter-item correlation matrix, using the presence of correlation values ≥|±.30| to confirm that factor analysis was warranted (Tabachnick et al., 2013). All variables had correlations of ≥|±.30| with at least one other variable in the correlation matrix (Field, 2018), indicating that EFA was appropriate. To maximize interpretability of factors, we used maximum likelihood (ML) estimation with Geomin oblique rotation for factor extraction to allow for expected correlation of factors (Bandalos, 2018). The ML estimation allowed us to retain all cases with missing values.

Table 3.

CFA and EFA Model Fit Statistics.

Model	χ²(df)	RMSEA	CFI	TLI	SRMR
13 Items—CFA
Two-factor solution	300.44* (64)	0.11	0.80	0.76	0.12
13 Items—EFA
Two-factor solution	1,255.28* (78)	0.08	0.90	0.88	0.05
11 Items—EFA
Two-factor solution (Final model)	1,062.89* (55)	0.08	0.94	0.90	0.04

Note. RMSEA = root mean square error of approximation; CFI = comparative fit index; TLI = Tucker Lewis index; SRMR = standardized root mean square residual; CFA = confirmatory factor analysis; EFA = exploratory factor analysis.

p < .001.

The following criteria guided our factor reduction procedures: (a) eigenvalues >1 (Kaiser, 1960); (b) the scree test (Cattell, 1966); (c) parallel analysis (Horn, 1965); (d) factor meaningfulness; and (e) model fit indices (Bandalos, 2018; Pituch & Stevens, 2016). We examined various model fit indices and applied the following thresholds for good model fit: root mean squared error of approximation (RMSEA; ≤.06; Browne & Cudeck, 1992); comparative fit index (CFI; ≥.95; Hu & Bentler, 1999); Tucker–Lewis index (TLI; ≥.90; Byrne, 2016), and standardized root mean square residual (SRMR; ≤.05; Hu & Bentler, 1999). Although the chi-square test was significant for all tested models, this index has been criticized as being a stringent criterion that requires a perfect model fit (MacCallum, 1990) and is overly dependent on sample size (Bandalos, 2018). We therefore consulted other model fit statistics and the criteria specified previously to evaluate the fit of each model specification. To improve model fit, we removed two items that cross-loaded on two factors, both on the implicit subscale: I1 and I5. Removed items are flagged in Table 4. Our factor reduction procedures resulted in a two-factor model (see Table 3 for model fit statistics for all tested models) and a reduction from 13 to 11 items.

Table 4.

Descriptive Statistics for Teacher Perceptions about Early Reading and Spelling-IDD Scale.

Factor/Item descriptor	M (SD)
Explicit Code-Based Instruction
E1: Teachers/paraeducators of students with IDD should know how to assess and teach phonological awareness (i.e., knowing that spoken language can be broken down into smaller units: words, syllables, phonemes).	5.21 (1.28)
E2: Controlling text through consistent spelling patterns (The fat cat sat on a hat.) is an effective method for children with IDD who struggle to learn to identify words.	4.65 (1.04)
E3: Poor phonemic awareness (awareness of the individual sounds in words) contributes to early reading failure for students with IDD.	5.03 (1.01)
E4: When elementary students with IDD struggle with reading, it is important for teachers to demonstrate how to segment words into phonemes when reading and spelling.	5.06 (0.88)
E5: Teachers/paraeducators should know how to teach phonics (letter/sound correspondences).	5.46 (0.84)
E6: Phonics instruction is beneficial for all elementary students who are struggling to learn to read.	5.21 (1.11)
E7: Phonics instruction is beneficial for elementary students with IDD who are struggling to learn to read.	5.25 (0.92)
Total	5.12 (0.15)
Implicit Reading Instruction
I1^a: Time spent reading contributes directly to reading improvement for elementary students with IDD.	5.10 (0.98)
I2: Learning to use context clues (syntax and semantics) is more important than learning to use grapho-phonic cues (letters and sounds) when elementary students with IDD are learning to read.	3.27 (1.44)
I3: If a beginning reader with IDD reads ‘house’ for the written word ‘home,’ the response should not be corrected.	2.91 (1.34)
I4: Picture cues can help elementary students with IDD identify words in the early stages of reading.	4.89 (1.19)
I5^a: Adult-child shared book reading enhances language and literacy growth for elementary students with IDD.	5.44 (0.75)
I6: Elementary students with IDD can learn to read using literature-based, authentic texts.	4.42 (1.27)
Total	3.87 (0.11)

Note. Dropped items omitted from total mean calculations. Ratings: 1 = strongly disagree, 2 = disagree, 3 = mildly disagree, 4 = mildly agree, 5 = agree, 6 = strongly agree. IDD = intellectual and developmental disabilities.

Item removed after factor analysis.

Results

Of all 13 variables, eight had missing values (61.54%). Approximately 97.2% of participants (n = 309) had complete data, and 2.8% had missing data values (n = 9). In total, 99.8% of values were complete (n = 4,125), and just 0.2% (n = 9) were missing. There was no observable pattern in the missingness of data.

SET-IDDs indicated stronger preference for explicit approaches (M = 5.12, SD = 0.15) over implicit approaches to reading instruction (M = 3.87, SD = 0.11). Mean item ratings ranged from 4.65 to 5.46 for the seven explicit items and ranged from 2.91 to 4.89 for retained implicit items (see Table 4 for all descriptive statistics and complete item wording). On the explicit orientation subscale, SET-IDDs agreed least that controlled text is an effective method for teaching children with IDD who have decoding difficulty (Item E2, M = 4.65, SD = 1.04). They agreed most that teachers and paraeducators should know how to teach phonics (Item E5, M = 5.46, SD = 0.84). With regard to items on the implicit orientation subscale, SET-IDDs agreed least that a child with IDD should be corrected if they read “house” for the written word “home” (Item I3, M = 2.91, SD = 1.34). They agreed most strongly that picture cues can help children with IDD identify words in the early stages of reading (Item I4, M = 4.89, SD = 1.19).

Factor Analysis

All criteria indicated a two-factors solution (see “Data Analysis”). The 11 retained items clustered onto the two factors as expected and as reported previously by Bos and colleagues (2001), including our added item I7 which had nearly identical wording to I6. Thus, we interpreted the subscales as explicit orientation (n = 7) and implicit orientation (n = 4). Geomin rotated loadings for the EFA final model are reported in Table 5. Reliability for the explicit orientation subscale was above the acceptable value of ≥.7 (n = 7, α = 0.83; Nunnally, 1978), but it was slightly below this threshold for the implicit orientation subscale (n = 4, α = 0.63). The two factors were significantly and negatively correlated (r = −0.298, p < .05).

Table 5.

Geomin Rotated Loadings for the Exploratory Factor Analysis: Final Model.

Item	Factor
Item	Explicit	Implicit
Teachers/paraeducators should know how to teach/assess phonological awareness	0.431
Utility of controlled text	0.405
Poor phonemic awareness contributes to early reading failure	0.611
Importance of segmenting words into phonemes when reading and spelling	0.735
Teachers/paraeducators should know how to teach phonics	0.754
Phonics instruction is beneficial for all elementary students	0.766
Phonics instruction is beneficial for students with IDD	0.824
Context clues are more important than grapho-phonic cues		0.735
Reading ‘house’ should not be corrected if the written word is ‘home’		0.442
Picture cues can help identify words in early reading		0.629
Learn to read using literature-based, authentic texts		0.473

Discussion

Following item reduction, we confirmed the same two-factor structure for the Teacher Perceptions about Early Reading and Spelling-IDD measure as Bos and colleagues (2001). SET-IDDs had a stronger preference for explicit approaches to reading instruction than implicit approaches. Although SET-IDDs strongly endorsed some items on both subscales, the significant and negative correlation between the explicit and implicit orientation subscales indicates that the two theoretical orientations are distinct to some extent, as measured by the TPERS-IDD.

Limitations

The results of this study should be considered with the following limitations in mind. First, we disseminated the survey online. Although we took several precautions to increase confidence in the quality of our data (e.g., invitation-only recruitment, trap questions), there is a small possibility that respondents misrepresented their eligibility to participate or provided inattentive responses. Second, the implicit subscale requires further development to increase reliability. Further modifications should include development of additional items and ensuring items are polarizing enough to distinguish between the two approaches to reading instruction.

Implications for Practice

Teachers’ theoretical orientations toward reading inform their instructional practices (Cunningham et al., 2009). Those practices, in turn, have the potential to produce different levels of student achievement in reading (e.g., Sermier Dessemontet et al., 2019). Teachers’ theoretical orientations toward reading instruction are often deeply held and difficult to change (Leko et al., 2015), yet they serve as an important lever in improving the quality of reading instruction provided to students with IDD.

As students with IDD are more vulnerable to being excluded from high-quality reading instruction than any other population (Keefe & Copeland, 2011), assessment of teachers’ theoretical orientations toward reading instruction for this population of learners is of great importance. Prior research suggests that explicit approaches are a more efficient way to teach word reading skills to students with IDD. Thus, pre- and in-service training programs may consider using assessments such as the TPERS-IDD to gather information about teachers’ theoretical orientations and identify those needing more training and support to provide effective and equitable reading instruction.

Footnotes

Authors’ Note

Kimberly A. McFadden is currently affiliated with the University of Iowa.

ORCID iDs

Kimberly A. McFadden

Esther R. Lindström

Ethical Considerations

This study was approved by the Institutional Review Board of Lehigh University in Bethlehem, Pennsylvania, USA.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The research reported here was supported by the Institute of Education Sciences, U.S. Department of Education, through Grant R324B210020 to Lehigh University and internal funding from Lehigh University. The opinions expressed are those of the authors and do not represent views of the Institute or the U.S. Department of Education.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

Available upon request from authors.

Notes

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