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We implemented a smartwatch prototype,\n            <jats:italic toggle=\"yes\">UbiLearn<\/jats:italic>\n            , which features hand gesture recognition for in-situ multi-context annotation to save moments when learners face difficulty. The annotation is used to generate personalized educational material powered by speech and natural language processing. Through a series of studies, we demonstrated the feasibility and preferred usability of UbiLearn, leading to learners\u2019 enhanced learning satisfaction. Moreover, the annotation data promoted the role of instructors by enabling the tracking of learners\u2019 in-situ proficiency outside their tutoring sessions. 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