Xinyue Liu, Huicong Hu and Shumeng Hou 的作品 School Simulator 学前训练应用程序

设计师 Xinyue Liu, Huicong Hu and Shumeng Hou 的作品 School Simulator 学前训练应用程序荣获了极具声望的 2022 A' Design Award 铜奖，竞赛类别为教育、教学辅助与培训内容设计。

铜教育· 2022

School Simulator 学前训练应用程序

设计师： Xinyue Liu, Huicong Hu and Shumeng Hou

客户: Harbin Institute of Technology, Shenzhen

教育类别A' Design Award 铜奖获奖者

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关于 School Simulator 学前训练应用程序

《School Simulator》(学校模拟器)是一款专为自闭症谱系障碍儿童的学前训练而设计的移动应用程序,面向家长、教师及治疗师使用。训练课程涵盖四大类别:生活自理、指令理解、人际互动以及校园一日。儿童通过做出选择、与卡通角色对话并做出面部表情来完成练习,识别技术会即时给予反馈。错误的回应会被记录下来并反复练习,直至正确为止。应用还设有社区版块,供成年人分享经验与心得。

荣誉认可

关于A' Design Award 铜奖

School Simulator 学前训练应用程序是 A' Design Award 铜奖得主，这是授予以创造力、独创性和敏锐见长的杰出设计的极具声望的认可。铜奖得主是技艺娴熟、创意惊人的作品，印证了其设计师丰富的经验、想象力与机智。预计School Simulator 学前训练应用程序将成为一件备受推崇、令人钦佩且被珍爱的物品，兼具显著的专业性与创新性。这件赢得 A' Design Award 铜奖的设计融入艺术、科学、设计和技术领域的最佳实践，并因注重细节而出类拔萃。School Simulator 学前训练应用程序出色地满足需求，触动渴望，迷住情感，并吸引好奇心。

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由设计师提供的致谢、团队成员及技术详情。

独特属性: School Simulator is an app aiming at supporting parents, teachers and therapists to give preschool training of children with autism spectrum disorder. It mainly contains two parts: preschool training and community communication. Autistic children can get trained in four categories, self care, instruction understanding, interpersonal interaction, and one day in school, which are expected helpful for their future integration into inclusive classes.
尺寸与包装: Designed for iOS system
标签: Interface Design, Autism Spectrum Disorder, Speech and Gesture, Pre-school Training
生产技术: Desk research, field studies, focus group interviews, consumer journey map, and collage activities were conducted for the demand analysis part. Figma, Adobe Photoshop and Illustrator were used for the interfaces and interaction design in the project realization.
设计挑战: The design activity met two challenges: the integration of various training needs, and the design of training lessons. First, though all target autistic children, each of them met different problems in daily life, requiring the variety of content and intensity. Therefore, on the basis of four general training categories, various lessons are provided for users to choose accordingly. Second, since these young children can hardly concentrate for a long period, lessons must be succinct in content, interesting in form, and filled with interactive practice, therefore enhancing the training effectiveness.
研究: We first conducted a desk research, gathering preliminary information towards the autistic children and their common problems in the inclusive education. Second, through a field study, we recorded these children’s emotional problems and behavioral disorders, and observed some intervention methods used. Third, in depth interviews were conducted with experts in autistic research, which made our design focus on the preschool training. Fourth, we made the one-day journey map of a primary school student, exploring various context autistic children may have trouble in, therefore guided the design of training lessons. Finally, we recruited preschool autistic children and collected their preference of colors and cartoon characters via collage activity, used as the reference in the interfaces and characters design. The interfaces and training lessons were constantly iterated in the later evaluations.
灵感: School Simulator was inspired by the special needs of autistic children in the inclusive education. In an inclusive school, these children can sit in the same classrooms and join learning activities together with their typically developing peers. However, due to the disorder of emotion and social behavior, it always takes them longer time to get used to the schedule and environment around. We realized the meaningful effects of preschool training for the autistic children.
项目周期: The project started in October 2021 and finished in January 2022 in Shenzhen.
操作流程: Once the app is launched, users can freely choose training lessons for their children, or communicate with others. In each training lesson, children are encouraged to make choices, talk to cartoon characters, and show specified facial expressions based on the context or cues. The built-in algorithms of speech recognition and facial expression recognition can provide quick and accurate feedback to their responses. Once a wrong response is detected, the corresponding training part will be automatically recorded while encouraging the child to redo it till correct. In addition, users can view the training history with accuracy records and make notes at any time.
团队成员: Student: Xinyue Liu
Faculties: Huicong Hu
Shumeng Hou