Abstract
In next-generation classrooms and educational environments, interactive technologies such as surface computing, natural gesture interfaces, and mobile devices will enable new means of motivating and engaging students in active learning. Our foundational studies provide a corpus of over 10,000 touch interactions and nearly 7,000 gestures collected from nearly 70 adults and children aged 7 years and above, which can help us understand the characteristics of children’s interactions in these modalities and how they differ from adults. Based on these data, we identify key design and implementation challenges of supporting children’s touch and gesture interactions, and we suggest ways to address them. For example, we find children have more trouble successfully acquiring onscreen targets and having their gestures recognized than do adults, especially the youngest age group (7–10 years old). The contributions of this work provide a foundation that will enable touch-based interactive educational apps that increase student success.
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We did not include command gestures common today such as swipe and pinch-to-zoom, based both on initial studies finding that these gestures are difficult for children [9], and on the prevalence of tracing or handwriting practice activities in children’s education apps today [2]. Future work could examine other gestures in more depth.
User-dependent testing refers to recognition testing in which the recognizer is trained on samples of the same person’s writing on which it is to be tested. User-independent testing refers to training and testing on samples only from different users.
Note that the Tablet PC recognizer is only suited for handwriting gestures, so we removed arch, arrowhead, checkmark, diamond, heart, rectangle and triangle from the results; circle, line and plus have keyboard symbol equivalents and were kept, along with all the numbers and letters in the corpus.
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Acknowledgments
We would like to thank Chiamaka Okorohoa, Thaddeus Brown, Monique Ogburn, and Shreya Mohan for their support of this research. This work was partially supported by Department of Education HBGI Grant Award #P031B090207-11 and National Science Foundation Grant Awards #IIS-1218395/IIS-1218664. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect these agencies’ views.
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Anthony, L., Brown, Q., Tate, B. et al. Designing smarter touch-based interfaces for educational contexts. Pers Ubiquit Comput 18, 1471–1483 (2014). https://doi.org/10.1007/s00779-013-0749-9
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DOI: https://doi.org/10.1007/s00779-013-0749-9