Abstract
For children who may face reading difficulties, early intervention is a societal priority. However, early intervention requires early detection. While much research has approached the issue of identification through measuring component skills at single timepoints, an alternative is the utilisation of dynamic assessment. To this point, few initiatives have explored the potential for identification through progress data from play in digital literacy games. This study explored how well growth curves from progress data in a digital intervention can predict reading performance after gameplay compared to measuring component skills at a single timepoint (school entry). 137 six-year-old students played the digital Graphogame for 25 weeks. Latent growth curve analyses showed that variation in trajectories explained variation in literacy performance to a greater extent than risk status at school entry. Findings point to a potential for non-intrusive reading assessment in the application of a serious digital game in first grade.
Highlights
For children who may face reading difficulties, early intervention is a societal priority
Successful reading is dependent on the integrity of a number of different perceptual, cognitive and linguistic skills (Pennington et al, 2012) and so, typically, assessments that aim to identify the risk, or overt manifestation of a reading difficulty need to measure a number of component skills, including phonological awareness, letter knowledge or word decoding, verbal short-term memory, rapid automatised naming and oral language (Pennington & Lefly, 2001; Thompson et al, 2015)
In comparison to risk status, as measured at school entry, how well does variation in growth curves of game progression predict literacy performance measured after gameplay?
Summary
Learning to read is one of the most important skills children will acquire in the early years of school and difficulties in acquiring this skill can have adverse educational outcomes (McLaughlin, Speirs, & Shenassa, 2014), vocational outcomes (McLaughlin et al, 2014; OECD, 2013) as well as a negative impact on both physical and mental health (DeWalt, Berkman, Sheridan, Lohr, & Pignone, 2004). Within that optimal time window measurements of letter knowledge may allow for strong prediction of word reading ability in subsequent school years (Georgiou, Torppa, Manolitsis, Lyytinen, & Parrila, 2012; Puolakanaho et al, 2008) This example points to the fact that the relative predictive ability of certain measures in relation to others may change over time (Solheim, Torppa, Uppstad, & Lerkkanen, 2020). (American Psychiatric Association, 2013) reiterates the need to consider a response to intervention in identification, stating that a diagnosis of dyslexia can only be made if difficulties have persisted for at least 6 months despite the provision of extra help or targeted instruction This approach to identification of difficulties takes into account dynamic assessment data from multiple time points. Graphogame is one of the minority of computerised reading interventions that has an emerging evidence-base exploring its efficacy (McTigue et al, 2020)
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