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A good amount of research has explored the use of wearables for educational or learning purposes. We have now reached a point when much literature can be found on that topic, but few attempts have been made to make sense of that literature from a holistic perspective. This paper presents a systematic review of the literature on wearables for learning. Literature was sourced from conferences and journals pertaining to technology and education, and through anad hocsearch. Our review focuses on identifying the ways that wearables have been used to support learning, and provides perspectives on that issue from a historical dimension, and with regards to the types of wearables used, the populations targeted, and the settings addressed. Seven different ways of how wearables have been used to support learning were identified. We propose a framework identifying five main components that have been addressed in existing research on how wearables can support learning, and present our interpretations of unaddressed research directions based on our review results.

 

In the face of information technology changes, not all students will have access to the means to prepare for this future of work. In addressing this issue, in this study, the authors investigate the impact of a ‘Making as Micro-Manufacturing (M2)’ model in motivating STEM-activity participation and developing self-efficacy among high-schoolers hailing from an underserved community. The approach involved integrating practice-based learning and activities into a high-school class curriculum resulting in the production of small-batch volumes of products in real-world settings for everyday use like instructional kits for elementary school learning. Pre- and post-surveys were administered to ascertain the differences in students’ Making and engineering self- efficacy tendencies. Our results saw increases in the students’ Making and engineering self-efficacy across multiple dimensions and in-situ during a production process. In addition, our results also quantify and characterize that kinds of helping behaviours that occur in the students’ own self-organised production team. 

An eXtreme Gradient Boosting (XGBoost) machine learning model is built to predict the electrocaloric (EC) temperature change of a ceramic based on its composition (encoded by Magpie elemental properties), dielectric constant, Curie temperature, and characterization conditions. A dataset of 97 EC ceramics is assembled from the experimental literature. By sampling data from clusters in the feature space, the model can achieve a coefficient of determination of 0.77 and a root mean square error of 0.38 K for the test data. Feature analysis shows that the model captures known physics for effective EC materials. The Magpie features help the model to distinguish between materials, with the elemental electronegativities and ionic charges identified as key features. The model is applied to 66 ferroelectrics whose EC performance has not been characterized. Lead-free candidates with a predicted EC temperature change above 2 K at room temperature and 100 kV/cm are identified.

 

Over the past year, our AI4GA team of university faculty and middle school teachers have co-designed a middle school AI curriculum. In this poster we share how we used co-design both as a tool for collaboratively developing engaging AI activities and as a mechanism for mutual professional development. We explain our co-design process, give examples of curriculum materials provided to teachers, and showcase several teacher-created activities. We believe this approach to curriculum development centers the lived experiences of teachers and leverages the knowledge and expertise of university researchers to create high quality and engaging AI learning experiences for K-12 students. 

Storytelling is a critical step in the cognitive development of children. Particularly, this requires children to mentally project into the story context and to identify with the thoughts of the characters in their stories. We propose to support free imagination in creative storytelling through an enactment- based approach that allows children to embody an avatar and perform as the story character. We designed our story creation interface with two modes of avatar: the story-relevant avatar and the self-avatar, to investigate the effects of avatar design on the quality of children’s creative products. In our study with 20 child participants, the results indicate that self-avatars can create a stronger sense of identification and embodied presence, while story-relevant avatars can provide a scaffold for mental projection. 

This paper explores avatar identification in creative story- telling applications where users create their own story and environment. We present a study that investigated the effects of avatar facial similarity to the user on the quality of the story product they create. The children told a story using a digital puppet-based storytelling system by inter- acting with a physical puppet box that was augmented with a real-time video feed of the puppet enactment. We used a facial morphing technique to manipulate avatar facial similarity to the user. The resulting morphed image was applied to each participants puppet character, thus creating a custom avatar for each child to use in story creation. We hypothesized that the more familiar avatars appeared to participants, the stronger the sense of character identification would be, resulting in higher story quality. The proposed rationale is that visual familiarity may lead participants to draw richer story details from their past real-life experiences. Qualitative analysis of the stories supported our hypothesis. Our results contribute to avatar design in children's creative storytelling applications. 

Little is understood on how to design wearables for education, especially for children. We explore how smartwatches may allow children to see the world through the lens of science. In our study, 20 children are tasked to record stories related to specific scientific concepts in their daily life and drawing from their embodied experiences using a commodity smartwatch. Our findings describe the types of ‘science stories’ that the children capture through the smartwatch, and how the stories relate to science. From our findings, we elicit seven areas of future research needed to catalyze the design of wearable apps to support informal science learning for children.