Evaluating the efficacy of the Headsprout© reading program with children who have spent time in care

Abstract

This study investigated whether Headsprout©, an internet‐based phonics program designed on behavioral principles, is an effective supplementary tool to improve literacy skills of children who have spent time in care and are at risk of reading failure. Participants were 8 children (aged 5 to 10) who had spent over 3 years in care and were fully adopted at the time of the study. Participants' literacy skills were assessed prior to intervention using 2 standardized reading attainment tests. Participants were then randomly assigned to either treatment or a waiting list comparison group. There were 2 Headsprout© treatments, but all participants in the treatment group completed 1 HeadsproutStartCopTextStartCopText© lesson 4 times per week, under the supervision of the first author, while participants in the comparison group interacted with the first author 4 times per week engaging in nonliteracy‐based computer activities. Results from 2 standardized reading attainment tests showed an improvement in word recognition age and oral reading fluency for the HeadsproutStartCopTextStartCopText© learners but scores either remained the same or decreased over a 4‐month period for participants in the comparison group. The findings support the wider use of HeadsproutStartCopTextStartCopText© with at‐risk children though more research is clearly warranted at this time.

Headsprout Early Reading for Specific Literacy Difficulty: A Comparison Study

“…The HER treatment group experienced a significant and substantial improvement of 48.4 words from pre-intervention to postintervention on this measure in comparison with the TAU group. This study adds to a growing body of the literature that demonstrates the positive effects of HER on children's literacy skills, when delivered either as one-to-one, small group or classroom-based programs (Grindle et al 2013;Huffstetter et al 2010;Layng et al 2003Layng et al , 2004Storey et al 2017;Tyler et al 2015).…”

“…In order to be considered systematic, instruction should be based on the principles of setting clear learning outcomes, teaching that is individual to the learner and setting high-performance targets (typically 90%) that learners must meet or repeat components until these criteria have been met. In addition, data should be collected on each response and corrective feedback should be delivered immediately (Layng et al 2003;Storey et al 2017).…”

Toward trauma‐informed applications of behavior analysis

“…Despite a growing acknowledgement of the importance of understanding the impacts of trauma on therapeutic approaches across human service disciplines, discussions of trauma have been somewhat less prevalent in the behavior analytic literature. This is not to say that particular aspects of trauma have not been addressed from a behavior analytic perspective (e.g., Friman et al, 1998a; Prather, 2007; Prather & Golden, 2009), or that behavior analysts have not addressed some of the issues encountered by individuals with documented trauma histories (e.g., Clark et al, 2008; Storey et al, 2017) or those who care for them (e.g., Berard & Smith, 2008; Crosland et al, 2008; Tertinger et al, 1984). Clinical behavior analysts have investigated the efficacy of Acceptance and Commitment Therapy (ACT) in reducing trauma‐related symptoms (e.g., Batten & Hayes, 2005; Fiorillo et al, 2017; Spidel et al, 2018).…”

The use of automated data collection in applied behavior analytic research: A systematic review.

“…The remaining studies used human data collectors to collect additional dependent variables other than the main dependent variable collected automatically or used human data-collectors in addition to the automated apparatus to collect at least one dependent variable. These included standardized assessment results to accompany the dependent variable collected through an apparatus (e.g., Storey et al, 2017); additional surveys and self-reports collected from the participants (e.g., Darling et al, 2017); and data that could not be collected solely from an automated apparatus such as human data collectors first sorting recyclable materials before weighing them on a scale (e.g., Miller et al, 2016).…”