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Social robots can enhance deeper learning through social processes by providing companionship during typically isolated learning activities. Yet, there is limited exploration into the use of authoring tools for teachers to create and customize social robot-assisted lessons. To address this need, we present PATHWiSE, an authoring tool that utilizes teacher-in-the-loop AI-assisted verbal and non-verbal robot interaction design to customize RAL lessons to the needs and strengths of individual students and classrooms. We demonstrate the operation, AI-assist functions, and practical applications of the PATHWiSE UI. Our work underscores the need for developing tools for computing novices utilizing AI and RAL technologies 

Educational technologies can provide students with adaptive feedback and guidance, but these systems lack personal interactions that make social and cultural connections to the student's own classroom and prior experiences. Social or companion robots have a high capacity for these types of interactions, but typically require advanced levels of expertise to program. In this study, we examined teachers use of an authoring tool to enable them to leverage their classroom-based expertise to design robot-assisted homework assignments, and explore how seeing a robot enact their designs influences their work. We found that the tool enabled the teachers to create novel social interactions for homework activities that were similar to their classroom interaction patterns. These interaction designs evolved over time and were shaped by the teacher's emerging mental model of the social robot, their concept of the students' perspective of these interactions, and a shift towards informal classroom-like interaction paradigms, thus transforming their view of what they can achieve with homework. We discuss how these findings demonstrate how the context of the activity can influence initial mental models of social activities and suggest practical guidance on designing authoring tools to best facilitate the creation of computer or robot supported social activities, such as homework. 

Mechanical properties of polymers with polymer grafted nanoparticles. Role of nanoparticle morphology is studied critically 

ABSTRACT Cobaltocenium‐containing polyelectrolyte block copolymer nanoparticles were prepared via polymerization‐induced self‐assembly (PISA) using aqueous dispersion RAFT polymerization. The cationic steric stabilizer was a macromolecular chain‐transfer agent (macro‐CTA) based on poly(2‐cobaltocenium amidoethyl methacrylate chloride) (PCoAEMACl), and the core‐forming block was poly(2‐hydroxypropyl methacrylate) (PHPMA). Stable cationic spherical nanoparticles were formed in aqueous solution with low dispersity without adding any salts. The chain extension of macro‐CTA with HPMA was efficient and fast. The effects of block copolymer compositions, solid content, charge density, and addition of salts were studied. It was found that the degree of polymerization of both the stabilizer PCoAEMACl and the core‐forming PHPMA had a strong influence on the size of nanoparticles. © 2019 Wiley Periodicals, Inc. J. Polym. Sci.2020,58, 77–83