Digital game based learning to monitor and support early reading acquisition. Studies in GraphoLearn-Dutch.

Digital game based learning to monitor and support early reading acquisition. Studies in GraphoLearn-Dutch.

First Author: Ben Maassen -- University of Groningen
Additional authors/chairs: 
Toivo Glatz
Keywords: Reading acquisition, Dynamic assessment, Dynamic intervention, Game-based learning, Dyslexia
Abstract / Summary: 

Purpose
Early detection of reading acquisition failure is crucial since intervention is most effective if started early. Digital game based learning (DGBL) can provide for early dynamic assessment in combination with a motivating computerized environment to train basic literacy skills. The present study makes use of the GraphoLearn (GL) environment that was presented to several hundreds of Dutch first graders, as well as children with DLD. Aim of the study is to evaluate the predictive value and effectiveness of game progress during the first months of playing.
Method
Typically developing children and children with DLD participated in a research protocol consisting of a pretest at the start of reading education, followed by a period of playing GL, and concluded with a posttest. The pre- and posttests comprised a standard set of preliteracy tests (PA, LK, RAN); the posttest also included word decoding tests. In between the children played GL for 5 to 7 weeks on a daily basis for 10 – 15 minutes per school day. Playing consisted of matching graphemes, written syllables, words or pseudowords presented on a computer screen with auditorily presented spoken fragments. Parameters expressing amount of practice were grouped into two categories: (1) exposure to GL (e.g. total playing time), and (2) game progress (e.g. accuracy; highest level reached).
Results and Conclusions
Results show a mainstream learning trajectory (strong correlations) from PA –stronger than LK or RAN—via accuracy and speed of letter-sound association during playing, to early (posttest) and later (follow-up) word and pseudoword decoding. Patterns of qualitative (e.g. error types) and quantitative (e.g. learning rate) in-game data predicting and influencing later reading fluency were found for different subgroups of children (e.g. with and without DLD). We conclude that GL is an effective tool to monitor and support early reading acquisition, and thus increases our insight in learning trajectories