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Much of lifelong learning is driven by our curiosity to ask ourselves questions about the things around us in everyday life. Unfortunately, we often fail to pursue these questions to acquire new knowledge, resulting in missed opportunities for lifelong learning. We investigated two approaches to technological support for lifelong learning from question-asking in everyday life: an in-situ approach – reflecting and learning in the situatedness of the moment when a question is asked, and a post hoc approach – self-reflecting and learning after the question-asking moment when one is available to reflect. The in-situ approach may enable people to tap into their embodied experience to gain understanding, while a post hoc approach may allow people to allocate greater cognitive and material resources to explore and understand. We implemented two systems embodying each of the two approaches. A study was conducted to compare the use of the two learning support systems in an everyday virtual environment. Results showed that the post hoc approach produces more curiosity questions and reflection than the in-situ approach. We discuss the implications of our results for the design of systems to support lifelong learning. 

Wearable devices are a popular class of portable ubiquitous technology. These devices are available in a variety of forms, ranging from smart glasses to smart rings. The fact that smart wearable devices are attached to the body makes them particularly suitable to be integrated into people’s daily lives. Thus, we propose that wearables can be particularly useful to help people make sense of different kinds of information and situations in the course of their everyday activities, in other words, to help support learning in everyday life. Further, different forms of wearables have different affordances leading to varying perceptions and preferences, depending on the purpose and context of use. While there is research on wearable use in the learning context, it is mostly limited to specific settings and usually only explores wearable use for a specific task. This paper presents an online survey with 70 participants conducted to understand users’ preferences and perceptions of how wearables may be used to support learning in their everyday life. Multiple ways of use of wearable for learning were proposed. Asking for information was the most common learning-oriented use. The smartwatch/wristband, followed by the smart glasses, was the most preferred wearable form factor to support learning. Our survey results also showed that the choice of wearable type to use for learning is associated with prior wearable experience and that perceived social influence of wearables decreases significantly with gain in the experience with a fitness tracker. Overall, our study indicates that wearable devices have untapped potential to be used for learning in daily life and different form factors are perceived to afford different functions and used for different purposes. 

Physical computing toolkits for children expose young minds to the concepts of computing and electronics within a target activity. To this end, these kits usually make use of a custom Visual Programming Language (or VPL) environment that extends past the functionality of simply programming, often also incorporating representations of electronics aspects in the interface. These representations of the electronics function as a scaffold to help the child focus on programming, instead of having to handle both the programming and details of the electronics at the same time. This paper presents a review of existing physical computing toolkits, looking at the What, How, and Where of electronics representations in their VPL interfaces. We then discuss potential research directions for the design of VPL interfaces for physical computing toolkits for children. 

Current systems that use gestures to enable storytelling tend to mostly rely on a pre-scripted set of gestures or the use of manipulative gestures with respect to tangibles. Our research aims to inform the design of gesture recognition systems for storytelling with implications derived from a feature-based analysis of iconic gestures that occur during naturalistic oral storytelling. We collected story retellings of a collection of cartoon stimuli from 20 study participants, and a gesture analysis was performed on videos of the story retellings focusing on iconic gestures. Iconic gestures are a type of representational gesture that provides information about objects such as their shape, location, or movement. The form features of the iconic gestures were analyzed with respect to the concepts that they portrayed. Patterns between the two were identified and used to create recommendations for patterns in gesture form a system could be primed to recognize.