In recent years, there has been growing research interest in aligning technological designs with users’ lived experiences. The goal of this work is to review existing work on the current state-of-the-art on incorporating individual and community values and beliefs into various kinds of interactive computerized technologies, emphasizing socio-cultural sensitivity. After screening 235 records, 45 papers were included in this review. Our research reveals that researchers are at the forefront of developing advanced socio-cultural digital tools and interactive educational platforms. They frequently employ techniques like collaborative dialogue facilitation, personalized linguistic support, and the integration of culturally significant design principles, such as cultural narratives and symbols. This commitment to technology’s transformative potential extends beyond education, making its mark in healthcare, social networks, finance, and other domains. We conclude by providing an overview of the questions that other researchers can investigate in the future for designing technologies that are socio-culturally sensitive. Future studies would benefit from a wider use of theories to account for the complexity of human behavior while designing socio-culturally sensitive technologies.

Exergames are becoming increasingly popular and have shown potential for motivating physical activity. Past research suggests that social (multiplayer) exergames offer players an engaging experience and good aerobic exercises. Our systematic review summarizes existing work and identifies gaps, trends, and patterns on social exergame research in the domain of health and wellness. A search was conducted in the ACM Digital Library, IEEE Xplore, and PubMed. After screening 2272 records, we identified 73 studies from 2013 to 2023 that meet the inclusion criteria. Our results reveal that step tracking is the most commonly implemented measure of physical activity in social exergames, and that competition, rewards, and cooperation are the most common features used for designing the games. Our results also show that the effectiveness of social exergames is intricately linked to a combination of factors, including group size, player matching, and game features. The main contribution of this paper is (1) an analysis of features and group dynamics employed for designing social exergames, and (2) how game features affect the games’ outcome (both positive and negative) uncovering challenges and opportunities to advance future research in this area. Our findings in the current review provides insights for the design and implementation of social exergaming helping users to experience more socially satisfying game experiences thereby increasing the motivation for exercise, as well as gaining social benefits.

A co-design process involving autistic children can provide a substantial benefit and optimal utilization of technologies to an off-the-shelf design-based one. Having a voice and making a contribution plays a major role in the co-design process. Yet autistic children exhibit varying communication and social skill and some of them may be minimally verbal or non-verbal. For these reasons, harmonizing the techniques of the co-design process with autistic children with varying characteristics requires detailed and careful consideration. To understand the techniques of the co-design process that accommodates all categories of autistic children, a systematic review of a co-design process involving autistic children was conducted, using six large databases (Scopus, ACM Digital Library, ScienceDirect, IEEE Xplore, SpringerLink, and Google Scholar). The search result includes 2482 papers of which only 82 met the inclusion criteria. The result of the data extraction analysis collection is classified according to techniques for accommodating autistic children of varying characteristics, the challenges encountered, and methods of minimizing those challenges. The review identifies four prominent themes within co-design research for autism: advances in co-design objectives and outcomes, participant recruitment determinants, core co-design methods, and the management of co-design challenges. Highlighting the need for inclusivity and equitable support, the study proposes recommendations for better integration of diverse communication abilities and multiple diagnoses in the co-design process, underlining the importance of adaptive technologies and methods to accommodate the needs of all children.

Abstract Detecting the attention of children with autism spectrum disorder (ASD) is of paramount importance for desired learning outcome. Teachers often use subjective methods to assess the attention of children with ASD, and this approach is tedious and inefficient due to disparate attentional behavior in ASD. This study explores the attentional behavior of children with ASD and the control group: typically developing (TD) children, by leveraging machine learning and unobtrusive technologies such as webcams and eye-tracking devices to detect attention objectively. Person-specific and generalized machine models for face-based, gaze-based, and hybrid-based (face and gaze) are proposed in this paper. The performances of these three models were compared, and the gaze-based model outperformed the others. Also, the person-specific model achieves higher predictive power than the generalized model for the ASD group. These findings stress the direction of model design from traditional one-size-fits-all models to personalized models.