Despite the prevalence of autism spectrum disorder (ASD) and other developmental disabilities (DD) worldwide, children with ASD and DD face tremendous difficulties receiving support due to physical, financial, and psychological barriers to onsite health and education clinics. As a result, researchers and practitioners have designed software solutions aimed at providing accessible support to meet users’ needs. However, we have limited knowledge of whether these solutions indeed work in real-world settings. To address this gap, we conducted a case study on a cognitive training program called Dubupang, designed by Dubu Inc. From in-depth interviews with multiple stakeholders and field observations of children with ASD and DD, we identify Dubu Inc.’s internal development processes, the critical design issues that emerged through a series of field trials (e.g., instructional design and feedback), and the key implications (e.g., importance of caregivers’ strategic human interventions) for design that better supports both children with ASD and DD and their caregivers.

Manual sign systems have been introduced to improve the communication of children with intellectual developmental disabilities (IDD). Due to the lack of learning support tools, teachers face many practical challenges in teaching manual sign to children, such as low attention span and the need for persistent intervention. To address these issues, we collaborated with teachers to develop the Sondam Rhythm Game, a gesture-based rhythm game that assists in teaching manual sign language, and ran a four-week empirical study with five teachers and eight children with IDD. Based on video annotation and post-hoc interviews, our game-based learning approach has the potential to be effective at teaching manual sign to children with IDD. Our approach improved children attention span and motivation while also increasing the number of voluntary gestures made without the need for prompting. Other practical issues and learning challenges were also uncovered to improve teaching paradigms for children with IDD.

Fuzzy navigator has been widely used in path planning for mobile robots because of its fast response. In this paper, evolutionary dual rule-based fuzzy path planner is proposed as a nobel path planner for omnidirectional mobile robots. The newly proposed fuzzy path planner utilizes a multiobjective evolutionary algorithm, which can take user's preference into account in path planning, for optimization of the path through scaling parameters used in fuzzification and defuzzification. The performance of evolutionary dual rule-based fuzzy path planner is evaulated through comparison of created paths and estimated Pareto-optimal fronts from dual multiobjective particle swarm optimization and dual multiobjective qauntum-inspired evolutionary algorithm. To show the validity of our path planner, path planning for omnidiretional mobile robot is simulated in MATLAB. Through the use of quantum-inspired evolutionary algorithm in Webots simulator, each unit movement of the omnidirectional mobile robot is optimized so that the non-holonomic motion of the mobile robot can be modified. The proposed evolutionary dual rule-based fuzzy path planner demonstrates the effectiveness through computer simulation for the omnidirectional mobile robot navigating in an environment with obstacles.