Piloting an Approach to Family-Implemented Decoding Instruction for Kindergarten-Aged Children

Abstract

Although phonics knowledge and decoding skill are crucial for academic and life success, there is little research that examines the effects of home-based, family-implemented instruction on the development of these early literacy skills. The purpose of this multiple baseline across participants single case experimental design study was to evaluate the effects of a family-implemented decoding instructional approach that was designed to “launch” young children into reading. We also measured the extent to which family members were able to implement instruction with fidelity and their perceptions about the appropriateness, feasibility, and acceptability of procedures and materials. The Launch into Reading intervention produced moderate to large effects, on average, on decoding outcomes for kindergarten-aged children. On average, participating families were able to implement the intervention with fidelity. Family members reported a high degree of satisfaction with intervention materials and procedures. Results suggest the need for additional supports for individuals who are having difficulty implementing with fidelity and for children who need more practice to learn letter-sound correspondences and use phonics knowledge to decode words. Still, this relatively simple home-based intervention shows initial evidence of promise.

Most family-implemented reading interventions evaluated in prior research have involved families in reading aloud to children and engaging in picture book-based discussion to promote children’s language development and knowledge of story structure (e.g., Barone et al., 2019; Dowdall et al., 2020). Fewer research-tested interventions have focused on supporting families in helping primary-grade children read words at home (Dahl-Leonard et al., 2025). There is a need for more research in this area, because early knowledge of letter-sound correspondences and decoding skills are strong predictors of later reading achievement (Schatschneider et al., 2004), and families have the potential to be good partners in supporting children’s decoding development. School-aged children spend less than 20% of their time at school (Hall & Nielsen, 2020); more of their time is spent at home. As a result, family-implemented reading interventions offer children more opportunities to practice retrieving new phonics knowledge and decoding words than they receive in the classroom (Wanzek et al., 2014). Family-implemented interventions can be cost-effective (Barnett et al., 1988) and may increase child motivation for reading (Terlitsky & Wilkins, 2015). These factors, combined with previous research suggesting that families can have a positive impact on the development of early literacy skills (e.g., Sénéchal & Young, 2008; Van Steensel et al., 2011), motivated us to develop and evaluate the effects of a home-based, family-implemented approach to instruction focused on building children’s initial knowledge of letter-sound correspondences and word decoding skills in the fall of kindergarten (K).

The Science of Reading as it Relates to Word Reading

Component skills models of reading (e.g., the simple view of reading; Gough & Tunmer, 1986) recognize the important contributions of both decoding and language comprehension to English reading comprehension. One implication of such models is that reading instruction may be effective if it addresses word reading, language comprehension, or both. Improvement in one factor of the equation will amplify the effects of competencies in the other factor. Another implication is that, if a reader has no ability to comprehend the meaning of the words they read, they will have no ability to comprehend text, regardless of their level of word recognition skill. Similarly, if you cannot recognize words on the page, you will be unable to comprehend text—regardless of your level of language comprehension proficiency.

For more than 200 years, there has been intense debate about the best way to teach children to read words, with proponents of phonics-based instructional approaches (i.e., approaches that explicitly teach children to link letters or letter patterns [i.e., graphemes] with sounds [i.e., phonemes]) squaring off against advocates for “whole language” approaches, which assume word reading will develop naturally given exposure to authentic texts and literacy-rich environments (Castles et al., 2018). Today, comprehensive reviews of research reveal widespread consensus that word reading depends on phonemic awareness, phonics knowledge, and decoding skill—and that phonics instruction is critical for reading development (Castles et al., 2018; Rayner et al., 2001). Researchers largely agree that phonics and decoding instruction is most effective when it systematically teaches grapheme-phoneme correspondences and provides practice that facilitates automatic retrieval and effortless mapping of these graphemes to phonemes (e.g., Foorman et al., 2016).

Previous Research on Family-Implemented Literacy Instruction

Three recent meta-analyses (Barone et al., 2019; Dowdall et al., 2020; Fikrat-Wevers et al., 2021) have examined the effects of family-implemented literacy instruction. Primarily, these meta-analyses have focused on read-aloud activities designed for preschool and K-aged children. Barone et al. (2019) examined 30 randomized controlled trials of home-based, family-implemented read-aloud interventions for children aged 0–6 years old. On average, included interventions were effective at improving children’s language skills (mean effect size = 0.16); a subset of studies evaluating the effects of dialogic reading interventions were associated with somewhat larger, positive effects on children's language skills (mean effect size = 0.26). Dowdall et al. (2020) evaluated 19 randomized controlled trials of family-implemented, read-aloud interventions with children aged 1–6 years old. They reported positive effects of included interventions on measures of both expressive language (mean effect size = 0.41) and receptive language (mean effect size = 0.26).

Fikrat-Wevers et al. (2021) meta-analyzed experimental or quasi-experimental studies of a wider range of home and/or school-based, family-implemented literacy interventions that sought to improve emergent literacy skills for preschool and K children in families experiencing economic disadvantage. They reported that 24 of the 48 studies included in their meta-analysis evaluated interventions that had a “code-related” (Fikrat-Wevers et al., 2021, p. 578) focus, which they operationalized as a focus on phonological awareness, letter names, letter sounds, and/or word reading. Code-related instruction was often provided in combination with a read-aloud, language-comprehension-focused component (n = 22), although sometimes it was the sole focus (n = 2). It was noteworthy that only six of the 24 interventions with a code-related component were exclusively implemented at home (Bierman et al., 2015; Ford et al., 2003, 2009; Korat et al., 2013; Rochdi, 2009; Thompson-Grubham, 2014), and only one of these six home-based interventions (Bierman et al., 2015) included word reading instruction or practice; the other five evaluated instruction designed to develop knowledge and skills foundational to word reading (e.g., phonological awareness, letter identification) but did not actually engage children in reading words. Bierman et al. studied the Research-Based Developmentally Informed Parent (REDI-P) program, in which researchers conducted home visits with families of preschool children enrolled in Head Start and coached them to engage children in read-alouds and a variety of other activities to support language, literacy, and social and emotional development.

We were able to identify only one study published in a peer-reviewed journal within the last 15 years that evaluated a home-based, family-implemented intervention that engaged K children in developing phonics knowledge and reading words. McConnell and Kubina (2016) used a multiple-baseline across participants research design to evaluate the effects of parents’ delivery of lessons from the published book Teach Your Child to Read in 100 Easy Lessons (TYCTR; Engelmann et al., 1983) on K-aged children’s word reading fluency. During 15-minute sessions, 5 nights a week, for six weeks, parents taught the first 30 lessons in the TYCTR program. Lesson activities included explicit instruction of and practice retrieving letter-sound correspondences. In every other lesson, children were taught one to two new letter sounds, such that 15 new letter sounds were introduced during the study. After the first session, each session also included review of previously taught letter sounds. Parents also used explicit instruction to build children’s phonological awareness and teach them to decode words and simple sentences that drew on previously taught letter-sound knowledge. Results indicated that the program held promise for improving K children’s word reading. All three children were unable to read any words in baseline; only with the introduction of the intervention did each child begin to read words in the list of curriculum-aligned sentences that was used as an outcome measure. By the end of their participation in the intervention, all three participants were able to read up to 7–10 words correct in the 30 seconds allotted during each assessment session. The average percentage of accuracy and completion for all three parent implementers was 88%. McConnell and Kubina did not explore families’ perceptions related to the intervention procedures and materials.

Study Purpose

The acquisition of early phonics knowledge and decoding skill are crucial for academic and life success. That so few studies in the last 15 years have examined the effects of home-based, family-implemented instruction focused on the development of these early literacy skills indicated there was a need for further research on this topic. Therefore, we set out to develop and evaluate the effects of a science-aligned phonics and decoding intervention that could be implemented by families to “launch” children into reading.

Unlike TYCTR, the instructional approach tested in this study incorporates decodable books (i.e., books featuring words that contain taught grapheme-phoneme correspondences) rather than only using word or sentence lists for reading practice. Our reasons for incorporating books were fourfold. First, there is empirical evidence suggesting that use of decodable texts during reading instruction for young children is associated with positive effects on real and pseudoword reading (Odo, 2024). Second, including books during instruction (i.e., rather than only providing opportunities to decode isolated words) has the potential to increase children’s motivation to read (Wigfield & Guthrie, 2000). This is because books have plots or convey information; children can read not only to decode a word accurately but also to find out what happens next or learn a new fact. Even though their author was constrained by the need to make most of the words on the page decodable, the decodable books we used in Launch into Reading lessons have humorous plots, portray situations with which children can relate (e.g., experiencing anxiety on the first day of school), or convey interesting information. The third reason for incorporating decodable books is that doing so produces an intervention that better reflects the way families and children typically read together. Families may see decoding instruction that incorporates book reading as more feasible and appropriate than one that only incorporates the reading of isolated words. Finally, providing opportunities for children to read decodable books may be desirable because reading and comprehending connected text is the ultimate objective during reading. Reading words and comprehending text simultaneously involves a more complex cognitive juggling act than reading isolated words alone (Foorman et al., 2016). It may be helpful to provide children with additional practice engaging in this kind of real-world reading that involves not only decoding words but also activating knowledge and constructing meaning.

In this single case experimental design study, we aimed to explore initial evidence of promise (i.e., to explore the extent to which Launch into Reading instruction demonstrated positive effects on children’s decoding ability). We also sought to assess families’ fidelity of implementation and perceptions of intervention materials and procedures. Our dual focus resembles that of the “effectiveness-implementation hybrid design” study described by Curran et al. (2012) in the context of medical interventions. In Curran’s conception, such designs can test the effects of a clinical intervention on relevant outcomes while simultaneously observing and gathering information on implementation. Gitlin (2013), in describing typical trajectories via which medical innovations make their way from conceptualization to impact on public health, argues for the importance of an “incremental and iterative process to build a robust body of evidence that initially supports feasibility and safety, then proves efficacy and effectiveness, and subsequently involves translation, implementation, and sustainability in a real-world context” (Gitlin, 2013, p. 1), and describes six phases that include (a) one or more pilot studies (i.e., studies primarily examining safety, feasibility, and acceptability), (b) an underpowered randomized controlled trial (RCT) that explores initial evidence of promise, (c) a fully-powered but smaller-scale RCT that compares the intervention with an appropriate alternative to examine efficacy within a controlled setting, (d) a larger-scale RCT that evaluates intervention effectiveness within a less controlled, more real-life setting, and then (e) studies that identify facilitators of and barriers to implementation, evaluate fidelity, and develop implementation supports to ensure effective implementation at scale (Gitlin, 2013). Gitlin nevertheless laments the elongated time frame involved in bringing innovations through this pipeline and argues that “new hybrid models that blend test phases and involve a team approach consisting of stakeholders and end users up front in developing and testing interventions may shorten the timeframe and enhance adoption” (Gitlin, p. 183).

This study is a pilot study of the Launch into Reading intervention. It explores initial evidence of promise while also focusing on family member implementers’ perceptions of the intervention and their ability to implement with fidelity in real-world contexts, thus addressing issues of feasibility and acceptability that are sometimes addressed later in the intervention discovery pipeline. Proctor et al. (2011) identified eight implementation outcomes that may influence an intervention’s success in context: acceptability, appropriateness, feasibility, fidelity, adoption, cost, penetration, and sustainability. In this study, we focused on the first four outcomes because, as Weiner et al. (2017) point out: “(a) they are often used in formative research or pilot studies as ‘leading indicators’ of implementation success” and (b) they are conceptually distinct but likely to be empirically inter-related in complex ways” (p. 2). Proctor et al. (2011) define appropriateness as the perceived fit, relevance, or compatibility of the treatment for a given practice setting or provider; feasibility is defined as the extent to which the treatment can be successfully used or carried out by a given provider within a given setting; acceptability is the perception that a given treatment is agreeable, palatable, or satisfactory. Finally, fidelity is the degree to which a treatment was implemented as prescribed or intended.

We addressed three research questions:

1. What is the effect of the Launch into Reading family-implemented reading intervention on decoding for K-aged children?

2. To what extent do families consider the Launch into Reading intervention materials and procedures to be appropriate, feasible, and acceptable?

3. To what extent are families able to implement the intervention with fidelity?

Method

Setting and Participants

Eight K-aged children and their families participated in the current study. To recruit families, we initially worked with an organization in Virginia that supports families living in under-resourced communities by providing access to family classes and coaching, mentoring, tutoring, and micro-financing. An individual at this organization who directs early learning initiatives reached out to families of K-aged children and shared a flyer with information about the study and family consent forms. Because we were not able to recruit the planned sample of eight children and their families through this community organization (i.e., we were only able to recruit five families), we also extended the invitation to participate to colleagues and neighbors of members of the research team. Recruitment ended once we had eight consenting families. Consenting families identified one family member who would act as the primary implementer; this family member was the one who received the training and delivered instruction. Two families withdrew during the baseline phase of the study: for one family, a change in the family member implementer’s work schedule meant that they could no longer attend any weekday afternoon/evening or weekend sessions; the other family found it too difficult to schedule sessions in advance and attend pre-scheduled sessions. After attrition, six families participated. Table 1 provides demographic information for each participating child. Participating family members reported a range of early literacy practices and resources at home (Supplemental File A). All study activities occurred in participants’ homes. Study procedures were approved by the local Institutional Review Board and required written family consent and verbal child assent.

Table 1.

Demographic Information

Participant	Age	Gender	Race/Ethnicity	Home Language Other Than English	School Type	Eligible for FRPL	DIBELS PSF and LNF RS	Implementer	Implementer’s Highest Level of Education
Imani	5	F	B/AA	N	Public	Y	0 and 6	Caregiver	10th–11th Grade
Ciara	5	F	B/AA	N	Public	NR	2 and 18	Mother	G/P Degree
Nicolas	4	M	A	Y	Private	NR	0 and 16	Mother	G/P Degree
Logan	5	M	W	N	Private	N	7 and 22	Mother	G/P Degree
Lindsay	5	F	W	N	Public	Y	5 and 18	Mother	G/P Degree
Abigail	5	F	W	N	Private	N	2 and 9	Mother	G/P Degree

Note. F = female; M = male; B/AA = Black or African American; A = Asian; W = White; N = no; Y = yes; FRPL = free or reduced-price lunch; NR = not reported; DIBELS = Dynamic Indicators of Basic Early Literacy Skills; PSF = Phoneme Segmentation Fluency; LNF = Letter Naming Fluency; RS = raw score; G/P Degree = graduate/professional degree.

Launch into Reading Instructional Materials

The research team provided families with all necessary materials to implement Launch into Reading instruction. These materials (see Supplemental File B for samples) included a family implementation manual with scripted lesson plans and lists of decodable words, letter-sound flashcards, “special word” flashcards, a laminated scaffolding guide, and a set of 41 Flyleaf decodable books (i.e., the complete Emergent Reader Series). Flyleaf decodable books are designed to be both decodable and interesting (e.g., with thoughtful messages and humorous plot twists); they feature colorful illustrations and protagonists who are diverse in terms of race and ethnicity. Families also received a 40-minute video-recorded training on how to implement the intervention with fidelity. The training included an overview of the purpose of the study, a description of materials, instructions for how to implement each lesson activity, and activity demonstrations. All family member implementers reported having watched the training video prior to implementing the first intervention lesson.

Research Design

To test the impact of the Launch into Reading intervention on decoding, we employed a concurrent, multiple-baseline-across-participants, single-case experimental design. Single-case experimental design studies are appropriate for determining causal effects (What Works Clearinghouse, 2022) as well as facilitating further development and customization of treatments (e.g., Barton et al., 2016). Such designs minimize threats to internal validity (e.g., maturation, testing), and allow for external validity to be demonstrated through systematic replications (Ledford & Gast, 2018). We chose to use a multiple-baseline single-case experimental design because the reading knowledge and skills that children learn during Launch into Reading instruction are not reversable (e.g., Maggin et al., 2018). Our use of this study design allowed us to closely monitor and analyze individual students’ decoding performance over time. We could identify individual response variation within a heterogenous sample and consider response patterns at a session-by-session level (Barton et al., 2016).

All families began the baseline phase at the same time. Data was collected during each session, and within-experiment replications were derived from the lagged introduction of the intervention. Phase change decisions were based on a visual inspection of the decodable word reading data (i.e., we used response-guided single-case experimental design procedures; Ledford et al., 2018). We chose to use a response-guided approach (i.e., in contrast to a randomized approach) because this study was intended as a pilot test of the Launch into Reading intervention; as such, it focused more on minimizing threats to internal validity (e.g., maturity, testing) than threats related to external validity.

Measures

This study included (a) pretest early literacy measures to characterize the sample, (b) a per-session measure of decodable real word reading that was used to answer the primary research question, and (c) a posttest survey and interview that both assessed family members’ perceptions related to the intervention. All child assessments were administered via Zoom by graduate-level research assistants (RAs). The lead assessor provided all other assessors with a one-hour training, which included practice with test administration and scoring. Assessors achieved independent test administration and scoring with 100% reliability with the lead assessor prior to administering and scoring assessments during the study. Every assessment was double scored. Interscorer agreement was calculated as the number of agreements divided by the number of agreements plus disagreements multiplied by 100. Disagreements were resolved via discussion and consensus. The average interscorer agreement was 99% (range = 85%–100%).

Early Literacy Measures

Dynamic Indicators of Basic Early Literacy Skills (DIBELS) 8th Edition (University of Oregon, 2018) is a set of standardized fluency measures designed to monitor the development of early literacy. Before beginning the intervention, we used the DIBELS Letter Naming Fluency (LNF) subtest to assess children’s letter-name knowledge and the DIBELS Phoneme Segmentation Fluency (PSF) subtest to assess children’s phonemic awareness. The median delayed alternate form reliability for LNF in K is .81 and the median concurrent alternate form reliability of PSF in K is .86 (University of Oregon, 2018).

Decodable Real Word Reading Measure

A researcher-developed measure was used during each session to assess the child’s ability to read decodable real words (i.e., words that contained regular grapheme-phoneme correspondences that were taught during Launch into Reading lessons). The 20-item measure was designed to align with the scope and sequence of the Launch into Reading intervention. For example, the first word on the measure (“am”) contains letter-sound correspondences taught during Week 1 of the intervention. The next words (“can” and “man”) contain letter-sound correspondences taught during Week 3 of the intervention. The last word on the measure (“flip”) contains letter-sound correspondences addressed during Week 14 of the intervention. The full list of decodable words included on the measure is provided in Supplemental File C. Children were administered the same words, in the same order, each time they were assessed (i.e., during each baseline session and at the end of each intervention session).

To administer the assessment, an RA used screen sharing to show children one decodable word at a time on PowerPoint slides. Correct responses were scored as “1” and incorrect responses were scored as “0.” Assessors followed a protocol that provided guidance on administration. For example, the protocol stated that if the child was reading a word sound by sound for more than 3 seconds, the assessor was to prompt, “Try to read the whole word.” Additionally, assessors were instructed to provide general encouragement and praise effort (e.g., “Nice work!” or “Thanks for trying to read that word!”). The assessment was discontinued once the child provided three consecutive incorrect responses.

Family Interview and Survey

After completing the last intervention session, each family participated in a semi-structured Zoom interview. Semi-structured interviews, commonly used as a flexible approach to gather in-depth information about participants’ perceptions (Creswell & Poth, 2017), allowed us to engage in conversations with family members about their experiences using the intervention. The flexible interview structure enabled us to ask follow-up questions or provide probes that encouraged family members to elaborate on their responses (e.g., the interviewer could ask, “Can you tell me more about that?”). At the end of the study, we also administered a 17-item, researcher-created survey (see Supplemental File D) designed to assess the implementer’s perceptions about the appropriateness, relevance, usefulness, feasibility, and quality of the intervention materials and procedures. Each item was rated on a 5-point Likert scale (1 = strongly disagree; 5 = strongly agree). This survey was informed by previous surveys measuring related constructs (e.g., Heidlage et al., 2023). Both measures were designed to inform potential revisions to the Launch into Reading intervention.

Procedures

Before beginning baseline, each family participated in a brief “meet and greet” session in which the research team provided introductions, discussed study expectations/logistics (e.g., using iPads/Zoom, scheduling sessions), and administered the pretest early literacy measures (see Table 1 for pretest data). The baseline and intervention phases are described below.

Baseline

During the baseline phase, families did not have access to the intervention materials. They were asked to engage in typical home literacy practices (see Supplemental File A for families’ descriptions of typical home literacy practices and resources). All children began baseline on the same day and remained in baseline for a minimum of four sessions. Baseline decoding data were collected twice per week until each child demonstrated a stable or decreasing trend and began the intervention phase. Three children who had four consecutive “zero” scores were the first to enter the intervention condition; the fourth, fifth, and sixth children to enter the intervention condition remained in baseline for eight, ten, and twelve sessions, respectively (the Research Design section describes our response-guided approach to phase change decisions).

Intervention

During the intervention phase, each family received the recorded training and all the materials (i.e., lessons, flashcards, scaffolding guide, and decodable books) needed to implement the researcher-developed reading intervention at home for 15 minutes a day, two days a week, for up to 15 weeks. The lessons were scripted and included the same four activities (see Supplemental File E for example activity scripts).

In the first activity, families introduced (in the first lesson of the week; e.g., Lesson 1.1) or reviewed (in the second lesson of the week; e.g., Lesson 1.2) the new letter-sound correspondence or correspondences that were the focus for both lessons that week. Families used flashcards to introduce new letter sounds and provide practice retrieving knowledge of newly and previously taught letter sounds. In the second activity, family members explicitly taught children to decode words that featured taught letter-sound correspondences. In the third activity, families taught children to recognize what they called “special words” (i.e., words that contained irregular letter-sound correspondences, or ones that had not yet been taught). To read “special words,” children were guided to recognize the whole word (i.e., not to decode it sound by sound), but family member implementers learned to point out any grapheme-phoneme correspondences in the word that had already been addressed during Launch into Reading lessons. These “special words” were selected for instruction because they appeared in the books that children read in the last activity of the lesson. In the last activity, children were guided to use their knowledge of letter-sound correspondences and “special words” to read Flyleaf decodable books. A new book was introduced each week. As noted previously, during the first lesson of each week (e.g., Lesson 1.1), children learned one to three new grapheme-phoneme correspondences and two to three new “special words”; they read the book for the first time. During the second session of each week (e.g., Lesson 1.2), children reviewed the letter-sound correspondence(s) and “special words” that had been taught during the previous session and read the book for the second time.

It is noteworthy that children are encouraged to read a decodable book from the very first intervention lesson. As shown in the scope and sequence (see Supplemental File F), the first lesson (Lesson 1.1) teaches the letter-sound correspondences for “s,” “m,” and “a.” It also teaches the special words “I” and “yes.” With knowledge of these letter sounds and words, children read the decodable book “I am Sam.” This book includes sentences such as “Am I Sam?” and “Yes!” I am Sam!” The third intervention lesson (Lesson 2.1) introduces the letter-sound correspondence for “c” and the special words “and” and “likes,” which prepares children to read the next decodable book in the series, “Cam and Sam.” The lessons continue to build in this manner throughout the intervention. Supplemental File F represents the complete scope and sequence of the intervention evaluated in this study.

The research team used baseline decoding assessment performance to place children in the curriculum. We placed the child at the lesson after the last letter-sound for which they demonstrated knowledge, when all previous letter-sounds in the sequence of instruction were also known. The three children who entered the intervention after four baseline sessions with a performance of zero on the decoding assessment (Imani, Ciara, and Nicolas) started with Lesson 1.1. Based on their performance on the baseline decoding assessment, Logan began with Lesson 10.1 whereas Lindsay and Abigail began with Lesson 6.1.

One of the three RAs attended every family-implemented intervention session via Zoom to provide support for families. All RAs identified as female; two identified as White and one identified as being of mixed race. During each session, the RA was expected to follow a protocol that included directions related to greeting families, assisting with gathering materials for the lesson, answering any intervention-related questions, and starting the Zoom recording. RAs were intended to be passive observers (i.e., so the family could engage in the lesson as if the RA was not present) but were instructed to answer any direct questions from the families. They were also instructed to, when necessary, briefly provide corrective feedback and/or modeling to the implementer (e.g., “the sound of that letter is /k/”) with the goal of ensuring high levels of implementation fidelity. As such, the amount of support provided during each session varied depending on the family's needs. Additionally, on three occasions, the first author also joined the session to provide more intensive support (e.g., modeling multiple activities).

Intervention Fidelity.

All intervention sessions were videorecorded and coded for fidelity of implementation (i.e., adherence to activity steps and quality of delivery) using a researcher-developed measure (see Supplemental File G). The measure examined three activity steps (introduction, parent model, and child practice) for each of the four lesson activities. Activity steps were rated as 0 (no adherence), 1 (some adherence), or 2 (high adherence). Each lesson could receive an adherence score of 0 to 24 (e.g., a score of 18 out of 24 would equal 75% lesson adherence). For each of the four lesson activities, a rating was also given for four quality of delivery indicators: modeling, scaffolding, pacing, and preparation/organization. Each quality indicator was rated on a three-point Likert scale (1 = low quality, 2 = moderate quality, and 3 = high quality). A lesson could receive a quality score of 16 to 48 (e.g., a score of 36 out of 48 would equal 75% lesson quality).

The second author, a researcher with extensive coding experience, served as the “gold standard” for coding. Coders participated in a one-hour training followed by practice during which coders watched two videos, coded the sessions independently, and then discussed codes. Interrater agreement was established prior to coding, with the “gold standard” establishing a set of correct fidelity codes. Percent agreement was calculated as the number of agreements divided by the total number of possible codes multiplied by 100. Coders achieved 98% interrater agreement on two independently coded lessons. Approximately 20% of the lessons were double coded. Coders achieved 93% overall agreement across double-coded lessons. Disagreements were resolved by coders engaging in discussion and reaching consensus.

Data Analyses

To measure the intervention’s effect, we used visual analysis (e.g., Horner et al., 2012; Kratochwill et al., 2013; Ledford et al., 2018), one non-overlap effect size, and one parametric effect size. We report all effect sizes as baseline-intervention phase comparisons.

We first used visual analysis of the plotted data on a line graph to determine if the introduction of the intervention was associated with an effect on decoding for each participant. The visual analysis procedure included a comparison of within- and across-phase data characteristics (e.g., Horner et al., 2012; Kratochwill et al., 2013; Ledford et al., 2018). Within-phase characteristics included level (i.e., average score), trend or slope, and variability around the trend line. Across-phase characteristics included immediacy of effect (i.e., level change from last three to first three data points in adjoining phases), overlap of data points across phases, and consistency of data in similar phases. Next, we investigated if a demonstration of effect replicated across participants. Finally, we determined whether the effect was replicated a minimum of three times, a requirement for establishing a functional relation between receipt of the intervention and improvement in decoding (e.g., Horner et al., 2012; Ledford et al., 2018).

To measure the extent to which data overlapped across phases, we calculated a non-overlap effect size known as nonoverlap of all pairs (NAP; Parker & Vannest 2009) that represents the proportion of all pairwise comparisons with scores ranging from 0 to 1. In the context of our study, NAP represents an estimate of the probability that a randomly selected decoding data point in the intervention or maintenance phase exceeds a randomly selected data point in the baseline phase. The What Works Clearinghouse (2022) recommends using NAP to measure overlap of data across phases. We also calculated a within-case standardized mean difference effect size (WC-SMD; Busk & Serlin, 1992; Gingerich, 1984), a parametric effect size representing the difference between the baseline phase mean and intervention phase mean divided by the baseline standard deviation. We chose to use WC-SMD for two reasons. First, WC-SMD is more comparable than measures of non-overlap to group design study effect sizes (Maggin et al., 2019). Second, a single case experimental design study’s procedural differences (e.g., number of sessions per phase, length of observation or measure) strongly influence the magnitude of overlap for effect sizes, making it difficult to compare non-overlap effect sizes across studies (Valentine et al., 2016). For all effect size calculation, we used the effect size calculator at https://jepusto.shinyapps.io/SCD-effect-sizes/ (Pustejovsky et al., 2023).

Results

Visual Analysis of Effects

Figure 1 represents child decoding data in graphical form to allow for visual analysis. Imani, Ciara, and Nicolas were the first children to transition from baseline to the intervention phase. Because each child had four consecutive scores of zero on the decoding outcome measure, we entered them into the intervention after Session 4. Imani did not experience any gains upon the introduction of the intervention, and she only completed five intervention sessions before her family needed to drop out of the study because they were having difficulty finding time to implement lessons. During Ciara’s first intervention session (Session 5), she did not decode any words on the assessment correctly. By Session 17, she had learned to decode three words correctly. Upon entering the intervention, Nicolas experienced an immediate and steady increase in decoding performance that was maintained through Session 18, his final session.

Figure 1.

Child Decoding Data

Logan was the next to transition to the intervention phase. He had an upward trend in his decoding knowledge during baseline but experienced an immediate increase in decoding performance upon entering the intervention during Session 9. After that immediate increase, he experienced a slight decline and then had very low performance on Session 12. Still, the overall trend was positive, and Logan performed near the ceiling of the assessment (i.e., 20 correct words) for the last five sessions (Sessions 14–18).

Lindsay transitioned to the intervention phase after Session 10. Her performance on the decoding assessment during baseline was somewhat variable, but her scores trended generally downward for the last four sessions before the introduction of the intervention. Her decoding performance during the first session in the intervention phase (Session 11) did not represent an increase from her decoding performance during the final baseline session. However, during subsequent intervention sessions, her performance trended steeply upward: she went from decoding three words during Session 11 to decoding 16 words during Session 14; by her last session (Session 18), she was able to decode 19 of 20 words correctly.

Abigail was the final child to enter the intervention phase. Her baseline performance trended very steeply upward between Session 6 and Session 8—but remained relatively stable between Session 8 and Session 12, her last baseline session. After the introduction of the intervention (Session 13), her decoding scores did not immediately increase. In fact, during the first three intervention sessions, Abigail scored at approximately the same level that she scored during baseline. During Session 16, she demonstrated the ability to decode two more words than she had been able to decode in baseline, but then she experienced a dip in performance at Session 17. In the final session, she decoded 18 of the 20 words on the assessment correctly (i.e., four more words than her highest performance during baseline).

Effect Size Statistics

Table 2 reports means, standard deviations, ranges, and effect sizes for each child. The average NAP effect size for the intervention phase was 0.92 when the data for the child who dropped out of the study after five intervention sessions was excluded, and 0.85 when her data were included. NAP effect size values greater than 0.90 are generally considered large, and those between 0.60 and 0.90 are considered moderate (Maggin et al., 2019). The average WC-SMD effect size was 1.96, which can be interpreted as a large positive effect.

Table 2.

Decoding Data

Participant	Phase	M (SD)	Range	NAP (SE)	SMD (SE)
Imani	Baseline	0.00 (0.00)	0–0
	Intervention	0.00 (0.00)	0–0	0.50 (0.14)	N/A
Ciara	Baseline	0.00 (0.00)	0–0
	Intervention	1.54 (0.78)	0–3	0.96 (.04)	2.10 (0.65)
Nicolas	Baseline	0.00 (0.00)	0–0
	Intervention	7.29 (2.70)	3–13	1.00 (0.02)	2.85 (0.72)
Logan	Baseline	8.50 (3.77)	0–12
	Intervention	16.70 (4.97)	12–20	0.91 (0.09)	1.67 (0.53)
Lindsay	Baseline	3.50 (2.63)	0–6
	Intervention	13.00 (5.76)	3–19	0.91 (0.09)	2.20 (0.58)
Abigail	Baseline	6.42 (6.52)	0–14
	Intervention	12.83 (5.60)	2–18	0.82 (0.10)	0.98 (0.50)
Overall Intervention Mean (SE)				0.85 (0.04)	1.96 (0.27)

Note. NAP = nonoverlap of all pairs; SMD = standardized mean difference; Effect sizes compare the intervention phases to the baseline phases.

Implementation Fidelity

Table 3 represents each family member’s average adherence rating and average quality rating. The average fidelity of implementation was 92.87% for adherence to activity steps and 88.03% for quality of delivery. Thus, on average, the families in our sample were able to implement the intervention with fidelity.

Table 3.

Implementation Fidelity

	Average Adherence	Average Quality
Imani	72.92%	55.21%
Ciara	92.63%	90.38%
Nicolas	100.00%	98.81%
Logan	99.17%	98.13%
Lindsay	95.31%	90.89%
Abigail	97.22%	94.79%
Average	92.87%	88.03%

Note. The child’s name represents their family member’s implementation.

Family Surveys and Interviews

As Table 4 indicates, family members who implemented the intervention reported positive perceptions of the intervention materials and procedures. In response to the open-ended question asking families to share additional feedback (see Supplemental File H for all responses), one parent responded: “We are thankful for being a part of this study!” Another stated:

Table 4.

Family Survey Ratings

Item	Imani	Ciara	Nicolas	Logan	Lindsay	Abigail	Average
Appropriateness
The reading skills targeted in the program are important.	5	5	5	5	5	5	5.00
The books selected for the lessons were appropriate for my child.	5	5	5	5	5	5	5.00
The learning activities in the lessons (e.g., Learning Letter Sounds, Decoding Words) were appropriate for my child.	5	5	5	5	4	5	4.83
Feasibility
The lessons were easy to implement.	5	5	5	5	4	5	4.83
The lesson materials were easy to use.	5	5	5	5	4	5	4.83
I could complete the lessons in a reasonable amount of time.	4	5	5	5	4	5	4.67
I could implement the lessons without extensive preparation.	4	5	5	5	5	5	4.83
The research team provided me adequate support to implement the program.	5	5	5	5	5	5	5.00
I was confident in my ability to implement the reading lessons.	4	5	4	4	4	4	4.17
I am more confident working with my child on reading-related tasks after participating in the program.	4	4	5	5	5	5	4.67
I feel empowered to support my child as they continue to develop their reading skills.	5	5	5	5	4	5	4.83
Acceptability
The program improved my child’s ability to read words.	5	5	5	5	4	5	4.83
I think continuing to use the reading lessons with my child will make them a better reader.	5	5	5	5	4	5	4.83
I believe the learning that occurred during this program will help my child be successful in their future education.	5	5	5	5	4	5	4.83
I have noticed that my child has generalized the skills they learned from the program to other environments and contexts.	5	5	5	5	4	4	4.67
I think this program holds promise for other children.	5	4	5	5	5	5	4.83
I was satisfied with the program.	5	5	5	5	5	5	5.00

Note. The child’s name represents their family member’s response. 1 = strongly disagree; 5 = strongly agree.

“We are so grateful to have been part of this pilot study. Our child went from barely being willing to even try reading at the beginning, to trying to read not only the program's books and books we have at home, but shouting out miscellaneous words all around him, from street signs and store names to food packaging and menus. That first decodable book he was able to read entirely on his own was like a lightbulb moment that changed his attitude toward reading. Instead of asking his two older siblings to read to him, he now insists that they go away so that he can try to read on his own and gets frustrated if they don't give him time to puzzle out the sounds. His teacher reports he is really engaging with the school's literacy program in a way he hadn't been before…We look forward to reading our way through the remainder of the Flyleaf decodable books at home and then sharing them with friends and family afterward. We love the Flyleaf books—not only the way they are decodable, but the way they are engaging and funny and depict a diverse sample of people of many different ages and backgrounds …I hope that the program will reach many other children in future and give them a chance to experience the same wonderful, exciting outcome.”

This parent also noted that “having a script and sample sounds for us to use in reading with my child was a great help, since I didn't learn to read using a phonetic system and I was very nervous that I would teach him the wrong things and set him back by telling him things that were inconsistent with what he was learning at school.”

Survey and interview responses did suggest a need for some improvements to the Launch into Reading intervention. On the survey, for which each item was rated on a 5-point Likert scale (1 = strongly disagree; 5 = strongly agree), Lindsay’s mother registered a 4 for several items. She explained in her interview that she felt like Lindsay was “a little bit bored” with the intervention. She also shared, “I didn't really always know if I was doing everything right.” She further described feeling “rushed and anxious” when delivering the lessons. Although a perceived lack of confidence when implementing the intervention was common across interviews, it is noteworthy that some parents, such as Ciara’s mother, “felt like [their] confidence grew over the sessions.” She stated that once she began “taking [her] time and not rushing” through the lessons, she felt more confident. At the same time, some family members suggested in their interviews that having more support, such as a “debrief” after each lesson or every few lessons, would have been helpful in building their confidence and ensuring successful implementation.

Discussion

The purpose of the present study was to pilot a science-aligned, family-implemented phonics and decoding instructional approach that was designed to “launch” young children into reading in the summer before or early fall of their K year. We used a single case experimental design study to examine effects on student decoding outcomes for participating students. We also measured the extent to which family members were able to implement with fidelity and their perceptions about the appropriateness, feasibility, and acceptability of procedures and materials.

The Launch into Reading intervention produced moderate to large effects, on average, on decoding outcomes for participating kindergarten-aged children. Although there was heterogeneity in instructional response, findings suggest that the intervention holds promise. In addition, family members reported perceiving the intervention materials and procedures to be appropriate, feasible, and acceptable. They were confident they could implement the lessons effectively, in a reasonable amount of time, and without extensive preparation. In terms of transfer to other reading and academic contexts, families reported that participation in the program increased their confidence working with their child on other reading-related tasks and supporting their future reading development. They believed the program was not only helpful in the present, but that continuing to use it at home would make their children better readers and help them be successful academically.

On average, participating families were able to implement the Launch into Reading intervention with fidelity (mean adherence = 93%; mean quality = 88%). Only one family received an average adherence score of less than 90%, indicating that it was feasible for most families to adhere to activity steps without difficulties. Quality of implementation followed a similar pattern. Only one family received an average quality score of less than 90%, indicating that it was feasible for most families to deliver instruction that was of relatively high quality. It is noteworthy that the family member who had difficulties with implementation reported that her highest level of education was 10th-11th grade; her level of education was lower than that of all other family member implementers. Based on this finding, it is possible that parents with lower levels of education may need more support to implement this intervention with fidelity.

When comparing our findings with those reported in previous studies of family-implemented decoding interventions, the most obvious point of comparison is the TYCTR study reported by McConnell and Kubina (2016). The TYCTR intervention tested in the McConnell and Kubina (2016) study was both similar to and different from Launch into Reading instruction. Both studies evaluated instructional approaches that emphasized explicitly and systematically building phonics knowledge and provided opportunities to read words that included taught grapheme-phoneme correspondences. Both studies tested the effects of 15 weeks of instruction (although children received daily sessions in the McConnell and Kubina study and only two sessions per week in the present study). During these 15 weeks, the TYCTR intervention addressed 15 grapheme-phoneme correspondences; the Launch into Reading intervention addressed 18. Perhaps the biggest difference between the two programs lay in the way in which Launch into Reading instruction engaged children in reading decodable books rather than only using word or sentence lists for reading practice. In addition, unlike the Launch into Reading intervention, the TYCTR intervention had a separate focus on phonological awareness (i.e., with purely auditory activities that involved identifying, blending and segmenting sounds in words).

In the McConnell and Kubina (2016) TYCTR study, introduction of the intervention was associated with immediate or almost immediate increases in level and trend for children in all three participating families. In contrast, there were two participants in the Launch into Reading study who did not make much progress in decoding even after receiving multiple intervention sessions. Imani was still not able to decode a single word on the assessment after the fifth intervention session, when she dropped out of the study. By the end of Ciara’s participation (i.e., after 13 intervention sessions), she was only able to decode 2–3 words correctly. For children like Imani and Ciara who do not show immediate progress when provided with Launch into Reading instruction, it may be necessary to implement the intervention with greater intensity. In the TYCTR study (McConnell & Kubina, 2016), families completed 15-minute sessions five nights a week (compared to the two, 15-minute sessions per week provided in the present study). In that study, families were not surveyed or interviewed to determine their perceptions related to the feasibility of delivering five sessions per week. Still, the fact that fidelity of TYCTR implementation was high (i.e., the average percentage of completion, or adherence to lesson steps, and accuracy of modeling was 88%) suggests that the intervention was feasible for families to implement. At the same time, in interviews conducted as part of the present study, participants suggested that higher intensity of intervention delivery could be a challenge. Ciara’s mother felt there was “no way” it would be practical to have three sessions a week. She noted on more than one occasion that time was a barrier to her implementation of lessons (“time is just of the essence for families”; “again, time is just an issue”). It is possible that the real hurdle was the need to schedule sessions in advance during a time when an RA could attend (i.e., rather than fitting in a lesson at the spur of the moment, when the family found an unexpected 15-minute slot of time and felt a quick reading lesson would fit with the flow of their evening time together). If additional sessions did not need to be scheduled in advance, it might be possible for families to make time for more lessons each week.

Although two of the six participants in the present study experienced limited growth, the remaining four did experience noteworthy growth in their decoding ability, with immediate or almost immediate increases in level and trend upon the introduction of the Launch into Reading intervention. By the end of between 6 and 14 intervention sessions, these four participants were decoding 13 to 20 words correctly. For purposes of comparison, the three participants in the McConnell and Kubina (2016) study of TYCTR were able to read 7 to 10 words correctly after 17 to 29 intervention sessions.

Descriptively speaking, higher fidelity of Launch into Reading implementation appeared to be associated with larger intervention effects. Might there have been ways to better support families in implementing Launch into Reading instruction with high levels of fidelity? For classroom teachers, professional learning opportunities that are associated with positive change in knowledge, classroom practice, and student achievement tend to have the same core features (e.g., Desimone, 2009), including opportunities for active learning (i.e., learning by “doing”) and duration (i.e., distribution of trainings and opportunities for practice across an extended period of time; Desimone, 2009). It stands to reason that learning and training opportunities for families would also be more effective when they provide opportunities to engage in active practice and when they are distributed across time. The training provided to family members in the present study did not afford any opportunities for active practice with expert feedback. A member of the research team delivered kits of intervention materials to each family and the family member implementer watched a 40-minute training video that was delivered via email. For most families, this training video combined with scripted lesson guides was adequate to support high-fidelity implementation. However, it may be necessary to design and provide additional supports for families who initially demonstrate low levels of implementation fidelity (e.g., training “booster” sessions that provide opportunities to practice and receive feedback) while recognizing the trade-off between providing individualized support for each family member implementer and designing the intervention so that it can be implemented at scale, by a larger number of families.

Coaching families during intervention delivery is another way to ensure that learning is active and distributed across time. Individualized coaching that is ongoing, embedded in an authentic classroom context, and linked to an evidence-based curriculum has been shown to be an effective approach for improving reading instruction (e.g., Sibley & Sewell, 2011; Vernon-Feagans et al., 2012). It is logical that such coaching would also support families in implementing instruction with fidelity. In the present study, a research team member was present (virtually) during each intervention session, available to answer family member questions and provide polite, corrective feedback and/or modeling to the implementer (e.g., “the sound of that letter is /k/”) when necessary. Additionally, on three occasions, the first author also joined the session to provide more intensive support (e.g., modeling implementing an activity in its entirety). Still, it may have been useful to provide more formal coaching to each participant before or after their intervention sessions. Some family members articulated in their interviews that more mid-intervention support (e.g., a “debrief” after each lesson or every few lessons) would have been helpful in building their confidence and ensuring successful implementation.

In general, families reported a high degree of satisfaction with the intervention. Because we were unable to identify a previous study that explored kindergarten families’ perceptions related to family-implemented decoding instruction intervention procedures and materials, this was an important finding. Our results suggest that such instruction can be highly appropriate, feasible, and acceptable, even when families typically spend little time teaching children to read or spell words prior to participation. The presence of decodable books appeared to contribute to the Launch into Reading intervention’s acceptability. One family member implementer noted that her son “likes the books” and is “planning to go through the whole set of books.” She said that “from that first book when he realized he could go through a book on his own. It was a huge turning point. He was so excited.”

Limitations and Implications

We recruited families both by working with a local community organization serving families in under-resourced neighborhoods and by word of mouth, resulting in a sample of families that was diverse along multiple dimensions (e.g., implementer’s level of education, family income, presence of a home language other than English, child’s school, child’s previous exposure to word reading or spelling instruction). This was both a strength of our study and a weakness. Recruiting a diverse sample of families allowed us to explore the degree to which the intervention would be feasible to implement and effective within a variety of family and community contexts. That said, the diversity of our sample also introduced exogenous sources of variability that may have made it more difficult to isolate the effects of the independent variable on the outcome of interest.

It is important to note that many children were being exposed to phonics and decoding instruction at school, not just at home, during the weeks when the study was being conducted. Three participating children made significant gains in word reading during the baseline phase. All three children reached a point of stability in their performance before they were entered into the intervention phase, and they experienced an immediate or almost-immediate change in level and trend of performing after they began receiving Launch into Reading instruction. Phase changes (i.e., the introduction of the intervention) did not coincide with any changes in schooling. Still, lack of information about the nature and duration of word reading instruction participating children received at school makes it harder to attribute their gains to receipt of the intervention alone. That we did not measure the amount of phonics and decoding instruction children received at school was a limitation of this study.

We also see it as a limitation that two of the eight families we initially recruited to participate in this study withdrew during the baseline phase, and one family was withdrawn after five intervention sessions. It is especially problematic because these three families were three of the five families recruited through a local community organization that serves families living in under-resourced neighborhoods. We had intended for this intervention to be feasible for implementation by all families, including those experiencing the stressors associated with living in under-resourced contexts. However, families that withdrew indicated it was difficult to find time to implement given unpredictable work schedules and competing responsibilities at home. Again, outside of a research context it would not be necessary for families to coordinate with research assistants to schedule sessions in advance. Implementing in a non-research context (i.e., with the possibility of sitting down with a child for a spur-of-the-moment reading lesson) could make Launch into Reading lessons more feasible to fit in. Still, there is a need to conduct further research on implementation and effects of this intervention within diverse family contexts, and to identify implementation supports for families when it is difficult for an adult to find time to work on reading with children after school. It is important to acknowledge the systemic inequities in our society that make it harder for families with lower levels of income to provide children with access to outside-of-school enrichment activities, including reading instruction. For example, adults in lower-income families are more likely to work multiple jobs and/or to be employed during non-standard hours (e.g., in the evening or overnight; e.g., Dressner et al., 2018; Pilkauskas et al., 2016), making it challenging to find time for these families to engage in reading activities together. Hall and Nielson (2020) reported that the top third of school-aged children in terms of family income spent roughly 40 percent (or about 2 hours/week) more time engaged in outside-of-school enrichment activities than the bottom two-thirds of the sample in terms of family income. Children in households in which both parents completed college spent, on average, 67 percent more time engaged in enrichment activities than children in households for which neither parent has completed college. When scaling up a program like Launch into Reading, it is important to consider possible implications (i.e., unintended consequences) related to opportunity gaps between children in lower-income and higher-income families.

The measure we used to examine a potential functional relation between the intervention and improvement in decoding outcomes was a researcher-developed, near-transfer measure, designed to be sensitive to changes in decoding due to participation in the intervention. It is a limitation that we were not able to examine the technical adequacy of the measure prior to implementing the study. That said, the measure had strong face validity: it directly tested children’s ability to decode real words containing the grapheme-phoneme correspondences that had been taught in the curriculum. Another measurement limitation relates to the fact that the same measure (i.e., the same words, in the same order) was administered each session, in both the baseline and intervention phases of the study. As a result, children’s performance was vulnerable to testing effects. However, visual inspections of the data revealed that changes in performance occurred due to the implementation of the intervention and that this effect was replicated across most participants. Such evidence provides strong support for a functional relation between the intervention and decoding performance. As a final measurement limitation, the fact that we were administering assessments via Zoom constrained our ability to measure children’s phonics knowledge. Although we had intended to use a measure in which we would show children a letter and ask them to supply the sound associated with that letter, we quickly realized that Zoom audio did not do a great job picking up single letter sounds when spoken aloud by K-aged children. This was unfortunate, because using a curriculum-aligned measure of letter-sound knowledge would have allowed us to determine the degree to which there were proximal gains even when children were not yet able to associate all the graphemes in a word with their associated phonemes or to blend those phonemes together to read whole words.

It would be ideal if a future, group-design randomized experiment examining the effects of this intervention could include a large sample of children and explore potential moderators of intervention effects (e.g., looking at within-child, within family-implementer, and environmental factors). To avoid the schooling-related confound we encountered in this study, researchers could conduct the study during the summer months prior to K entry, when it is less likely that children will be exposed to additional decoding instruction beyond that provided during the intervention. Another option would be to carefully measure exposure to decoding instruction children receive outside of the intervention and control for differences during analyses. There may be value in learning more about the effects of families’ implementation of the intervention while children are receiving instruction in K. Research suggests aligning learning (e.g., ensuring approaches and materials are similar) across home and school settings during the preschool years may enhance child skill acquisition (Sheridan et al., 2010). In addition, teachers may support families in implementing instruction effectively at home.

Overall, this study demonstrated that the Launch into Reading intervention is feasible for families to implement and holds promise for improving K-aged children's word reading. It is noteworthy that Launch into Reading instruction requires families to implement only two, 15-minute lessons per week. It can be implemented with fidelity by adults who receive only 40 minutes of asynchronous training. Materials required to implement Launch into Reading instruction are minimal (i.e., decodable books, flashcards, and a spiral-bound book of scripted lessons). As we further develop the Launch into Reading intervention, it will be important to design additional supports for implementers who are having difficulty delivering lessons with fidelity and for children who need more practice to learn letter-sound correspondences and use phonics knowledge to decode words. Still, it is encouraging that this relatively simple, home-based intervention has the potential to “launch” young children into reading.