In the research field of cognitive aging, games have gained attention as training interventions to remediate age-related deficits. Cognitive training games on computer, video and mobile platforms have shown ample and positive support. However, the generalized effects are not agreed upon unanimously, and the game tasks are usually simple and decontextualized due to the limitations of measurements. This study adopted a qualitative approach of design-based research (DBR) to systematically review and pragmatically examine the regime, presentation and feedback design of a cognitive training game for older adults. An overview of the literature of cognitive aging and training games was conducted to form the theoretical conjectures of the design, and an iterative cycle and process were employed to develop a mobile game for older adults who are homebound or receiving care in a nursing home. Stakeholders, i.e., elderly users and institutional administrators, were invited to participate in the design process. Using two cycles of design and evaluation, a working prototype of an iPad-based app that accounted for the needs of elderly adults in terms of form, appearance and working function was developed and tested in the actual contexts of the participants’ homes and an assisted living facility. The results showed that the cognitive training game developed in this study was accepted by the participants, and a high degree of satisfaction was noted. Moreover, the elements of the interface, including its size, layout and control flow, were tested and found to be suitable for use. This study contributes to the literature by providing design suggestions for such games, including the designs of the cognitive training structure, interface, interaction, instructions and feedback, based on empirical evidence collected in natural settings. This study further suggests that the effectiveness of cognitive training in mobile games be evaluated through field and physical testing on a larger scale in the future.

Critical reading plays an important role in science learning, and previous studies have endeavored to objectively and precisely capture readers' cognitive processing in reading scientific texts. Since many factors affect readers' initiation and comprehension of scientific texts, studying the interactions of these factors was technically challenging for earlier studies. Recently, the use of artificial intelligent techniques for analyzing physiological signals has gained significant research attention, but exploitation of the educational data for proactive instructional use is still limited. This study proposed and evaluated an automatic approach incorporating the K-means++ clustering method for eye movement analytics. In this study, 64 undergraduate and graduate students read a multi-page popular science text while their eye movements were recorded. The results of the cluster analysis identified three patterns of reading behavior that were consistent and comparable to those of previous studies using self-reported measures and post-analysis analytics. Findings of the study support the potential and validity of a bottom-up, data-driven approach that can directly examine and analyze reading behaviors without interruption, and the contribution of the study to research and practice is outlined.

In children–robot interactions, an impression of a robot’s “social presence” (i.e., an interactive agent that feels like a person) links positively to an improved relationship with the robot. However, building relationships takes many exposures, and there is an intellectual gap in how social presence and familiarity collaborate in modulating children–robot relationships. We investigated whether social presence altered over time, how repeated exposure and social presence affected rapport, and how social presence would modulate children’s attitudes toward the robot. Fourteen children (four female, age = 10.79 ± 1.12) interacted with a companion robot for four days in spontaneous interactions. The findings revealed that children who perceived the robot as having a higher social presence developed a stronger rapport than those who perceived a lower social presence. However, repeated encounters did not change the children’s perceptions of the robot’s social presence. Children rated higher rapport after repeated interactions regardless of social presence levels. This suggests that while a higher social presence initially elevated the positive relationship between children and the robot, it was the repeated interactions that continued solidifying the rapport. Additionally, children who perceived a higher social presence from the robot felt less relational uneasiness about their relationship with robots. These findings highlight the importance of robots’ social presence and familiarity in promoting positive relationships in children–robot interaction.

This paper reports on the implementation of a learner identification system developed to facilitate real-time interaction in an international distance course. To increase the teacher immediacy and social presence, it proposes an integrative system for incorporating technology to improve the learning involvement, teaching effectiveness, and quality of interaction in the context of distance education. After the system was implemented in a formal international distance course involving universities in Japan and Taiwan for a semester, the results of the formative evaluation suggested that a perceived integrative classroom environment was achieved. The instructors and learners agreed that the system effectively and seamlessly integrated synchronous and asynchronous learning through the computing components of face and speech recognition. It was also found that the improved interaction led to a better sense of learning community and improved performance. This study concludes that the system could be useful in improving interactions and reducing students' feelings of isolation in distance courses by increasing their social presence. Suggestions for future studies and system development are also provided.