Following the Sector Protocol for Quality Assurance for Practice-Based.Contributors Academy for AI, Games and Media:Mata Haggis Burridge (prof. EG), Qiqi Zhou, Hillevi Boerboom, Maria Pafi (postdoc, WuR), Alexander van Buggenum, Ella Betts, Wilma Franchimon (dir. AGM), Nick van Apeldoorn (Coord.Digireal), Harald Warmelink (Coord. Cradle & MSP Challenge), Magali Patrocínio Gonçalves, Ard Bonewald (MT Games), Marin Hekman, Marie Lhuissier, Carlos Santos (CTO Cradle), Jeremiah van Oosten (MT, games), Kevin Hutchinson, Frank Peters (MT ADS&AI), Bram Heijligers, Joey Relouw, Marnix van Gisbergen (Prof. DMC), Shima Rezaei Rashnoodi (Coord. DMC), Phil de Groot, Igor Mayer (prof. SG), Niels Voskens, Fabio Ferreira da Costa Campos, Tuki Clavero, Jens Hagen, Wilco Boode, Natalia Harazhanka-Pietjouw (PPC), Jacopo Fabrini & Silke Hassreiter.
The adoption of tablets by young children has raised enthusiasm and concern among speech and language pathologists. This study investigated whether tablet games can be used as effectively as real play objects in vocabulary intervention for children with developmental language disorder (DLD). A randomized, controlled non-inferiority trial was conducted with 70 3-year-old children with DLD. The novel intervention group (n = 35) received 12 10-min scripted intervention sessions with symbolic play using a tablet game spread out over 8–9 weeks. The standard intervention group (n = 35) received the same amount of intervention with real objects using the same vocabulary scripts. In each session, children were exposed to 22 target words. The primary outcome was the number of new target words learned. This was measured using a picture selection task including 22 target words and 22 control words at 3 time intervals: before the intervention, immediately post-intervention, and 5 weeks later. In both intervention groups, the children learned significantly more target words than control words. No significant differences in gains between the two intervention conditions were found. This study provides evidence that vocabulary intervention for toddlers with DLD using a tablet game is equally as effective as an intervention using real objects.
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In many Real-Time Strategy (RTS) games, players develop an army in real time, then attempt to take out one or more opponents. Despite the existence of basic similarities among the many different RTS games, engines of these games are often built ad hoc, and code re-use among different titles is minimal. We created a design pattern called "Resource Entity Action" (REA) abstracting the basic interactions that entities have with each other in most RTS games. The paper discusses the REA pattern and its language abstraction. We also discuss the implementation in the Casanova game programming language. Our analysis shows that the pattern forms a solid basis for a playable RTS game, and that it achieves considerable gains in terms of lines of code and runtime efficiency. We conclude that the REA pattern is a suitable approach to the implementation of many RTS games.
