| Summary: | Software targeted at children does not typically take into consideration the significant variation in skills and capabilities across age and gender. The overall goal of our research was to design adaptive interfaces that change to accommodate the inherent age and gender differences among children. We conducted two studies towards this goal at Science World with 195 children between ages 3 to 12. In the first exploratory study, we observed how 111 children interacted with Tux Paint, a painting application designed for children, and the difficulties they encountered in general. We were also interested in the possibility of accelerating children's learning of the interface with the least help from adults. Hence, we observed how they used the help system and how they learned by watching their peers. We found that designing an effective help system for children was a tricky proposition fraught with challenges. As for our inquiry into the general difficulties, we identified that dialogs were a significant source of problems for children. We classified the problems with dialogs by age groups and set out to solve them with potential design solutions targeted at three different age groups. In the second observational study, we observed how 84 children interacted with our various dialog box designs embodying 8 design factors. The dialog boxes were designed with the goal of enabling efficient communication of information; children need to understand the information that is communicated and make informed decisions. We found that while some design factors helped achieve effective communication, some did not. We present our results and an analysis of children‟s information consumption behavior, especially with respect to age and gender differences, in the context of their interaction with dialog boxes. We put forth theories and present models on how children of different age and gender consumed information differently from different information channels (textual and non-textual). We discuss the design implications of our findings that could help designers in constructing adaptive interfaces that improve the interaction by taking the age and gender into account. === Science, Faculty of === Computer Science, Department of === Graduate
|
|---|
