This review is the first step in a long-term research project exploring how social robotics and AI-generated content can contribute to the creative experiences of older adults, with a focus on collaborative drawing and painting. We systematically searched and selected literature on human-robot co-creativity, and analyzed articles to identify methods and strategies for researching co-creative robotics. We found that none of the studies involved older adults, which shows the gap in the literature for this often involved participant group in robotics research. The analyzed literature provides valuable insights into the design of human-robot co-creativity and informs a research agenda to further investigate the topic with older adults. We argue that future research should focus on ecological and developmental perspectives on creativity, on how system behavior can be aligned with the values of older adults, and on the system structures that support this best.
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Deze Powerpoint presentatie werd door lector Cock Heemskerk gebruikt voor een lezing over zorgrobots in het Slimste Huis in Alkmaar. Na een korte uitleg over het werkveld van het lectoraat en de wetenschappelijke definitie van een robot wordt nader ingegaan op de inzetbaarheid van zorgrobots anno 2017. De testresultaten van de zorgrobots Alice en ROSE worden duidelijk uiteengezet. Er wordt ingezoomd op de 21ste eeuw vaardigheden van studenten verpleegkunde en die onderzoekers. Tot slot wordt de opbouw en de doelstelling van een klinische les (nagespeelde praktijksituatie) gepresenteerd.
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In their study "How Perceived Fit Affects Customers’ Satisfaction of In-Store Social Robot Advice", Stephanie van de Sanden, Tibert Verhagen, Ewout Nas, Jacqueline Arnoldy, and Koen Hindriks explore how various dimensions of perceived fit influence customer attitudes and satisfaction toward social robots providing product advice in retail settings. Drawing on theories from marketing and information systems, the authors conceptualize four types of technology fit—task-technology, individual-technology, store-technology, and shopping experience-technology—and propose a model linking these fits to customer attitudes and satisfaction. A field study conducted in a garden center using a robot that advised on potting soil involved 224 participants, whose responses were measured through established Likert and semantic differential scales. The findings aim to inform future design and deployment of social robots in retail by highlighting the importance of contextual and experiential alignment between the robot, task, customer, and environment.
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