Early prediction of children's literacy skills is crucial for successful literacy development. However, standardized screenings for pre-readers are mainly paper-based and designed for one-on-one sessions, demanding significant resources. We present the development and feasibility evaluation of a digital, game-based literacy screening for German pre-readers that supports group sessions. The screening comprises five tasks that do not rely on written language skills. We detail critical design decisions and guidelines for the effective implementation of this group-based screening. We evaluated the feasibility and user experience with 34 German second- and third-graders. Results revealed that the screening is suitable for use in group settings and that it was positively perceived by the children. Children found the tasks enganging and straightforward, often perceiving them as games. This study demonstrates that digital game-based screenings can be used effectively in group settings with young children with minimal adult guidance, offering a motivating and engaging assessment method.

Assessing children’s literacy skills is a key requirement for successful learning. However, standardized assessments are almost exclusively available as paper-and-pencil tests, discarding digital testing’s advantages. In this article, we develop and evaluate two different tablet versions for a paper-based reading fluency test for German primary school children: one true-to-original design (TDId) and a tablet-optimized design (TDOpt). We investigate the reliability, equivalence, and user experience of the tablet-based versions by comparing it to each other and to the paper-based version in a user test with 21 fourth graders. The results suggest very high reliability of both tablet-based versions (r’s >.94). Children scored significantly higher on TDId than on the other tests while reading scores assessed with TDOpt matched the conventional test. Children preferred both tablet versions over the paper-based test, whereby TDOpt was consistently rated best. This study suggests that a tablet-optimized reading fluency test not only retains test reliability but is also more appealing to primary school children.

The choice of appropriate interaction style for children’s application has been a divisive subject of debate. For example, drag-and-drop is often said to perform worse than point-and-click in educational applications – and vice versa. In this article, we argue for the need to choose the interaction style in context, considering a range of factors. We compare drag-and-drop, point-and-touch, and simple touch for selecting letters to form words in a spelling line as part of an educational spelling game. We evaluate the perceived workload, user experience, preference, and writing times of twenty-five children (8–11 years), eight of whom were dyslexic. We found that touch received better ratings and was ranked highest most often on all subscales compared to drag-and-drop and point-and-touch. Children needed less time using touch and 68% chose it as their favorite interaction style. We also found small advantages for drag-and-drop over point-and-touch, which runs counter to some recent recommendations. This becomes particularly clear when using ranking responses, which support a particularly fine-grained picture.

Training the distinction of vowel lengths or learning to differentiate between voiced and voiceless plosive sounds in form of minimal pair differentiation is one of the treatments fostering phonological awareness for people with reading and/or writing disabilities. While text-to-speech systems can automatically generate minimal pairs (e.g., bin and pin), the quality of the pronunciation of pseudowords is not always optimal. We present a novel approach for using text-to-speech tools to artificially generate the pronunciation of German pseudowords, which is evaluated in a crowdsourcing task of the discrimination of minimal pairs. While the input for generating audio files for real words is provided as plaintext, the audio files for pseudowords are generated from the SAMPA transcription, a computer-readable phonetic alphabet, of their real-word counterparts. The task of selecting the correct word from a minimal pair of a pseudoword and its lexical counterpart was completed equally successfully when a pseudoword was generated by our method or pronounced by a human (χ2(1) = 2.43, p = .119).