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Grounded in a theory-driven abductive methodology, the research draws on data from three empirical studies involving 270 undergraduate students who engaged with the voice-based robot Abii. Data collection methods included student diaries, focus groups, and participant observations, analysed through an integrated approach combining narrative analysis, text mining, and sentiment analysis. The findings reveal that the voice-based robot significantly enhances learning by providing personalised, real-time feedback and facilitating interactive, adaptive experiences. These robots broaden access to resources, extend student engagement, and augment learner agency, resulting in both hedonic and utilitarian value outcomes. 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