5.8HCOct 24, 2020
XR-Ed Framework: Designing Instruction-driven andLearner-centered Extended Reality Systems for EducationKexin Yang, Xiaofei Zhou, Iulian Radu
Recently, the HCI community has seen an increased interest in applying Virtual Reality (VR), AugmentedReality (AR) and Mixed Reality (MR) into educational settings. Despite many literature reviews, there stilllacks a clear framework that reveals the different design dimensions in educational Extended Reality (XR)systems. Addressing this gap, we synthesize a broad range of educational XR to propose the XR-Ed framework,which reveals design space in six dimensions (Physical Accessibility, Scenario, Social Interactivity, Agency,Virtuality Degree, Assessment). Within each dimension, we contextualize the framework using existing designcases. Based on the XR-Ed Design framework, we incorporated instructional design approaches to proposeXR-Ins, an instruction-oriented, step-by-step guideline in educational XR instruction design. Jointly, they aimto support practitioners by revealing implicit design choices, offering design inspirations as well as guide themto design instructional activities for XR technologies in a more instruction-oriented and learner-centered way.
8.0CYSep 22, 2020
Designing AI Learning Experiences for K-12: Emerging Works, Future Opportunities and a Design FrameworkXiaofei Zhou, Jessica Van Brummelen, Phoebe Lin
Artificial intelligence (AI) literacy is a rapidly growing research area and a critical addition to K-12 education. However, support for designing tools and curriculum to teach K-12 AI literacy is still limited. There is a need for additional interdisciplinary human-computer interaction and education research investigating (1) how general AI literacy is currently implemented in learning experiences and (2) what additional guidelines are required to teach AI literacy in specifically K-12 learning contexts. In this paper, we analyze a collection of K-12 AI and education literature to show how core competencies of AI literacy are applied successfully and organize them into an educator-friendly chart to enable educators to efficiently find appropriate resources for their classrooms. We also identify future opportunities and K-12 specific design guidelines, which we synthesized into a conceptual framework to support researchers, designers, and educators in creating K-12 AI learning experiences.