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The paper aims to analyse the problem of quality evaluation and personalisation of virtual reality/ augmented reality/mixed reality (VR/AR/MR). First of all, systematic review of relevant scientific literature on the research topic was conducted. After that, findings of the systematic review concerning evaluation of quality and personalisation of VR/AR/MR learning environments are presented. The author’s VR/AR/MR learning systems/environments quality evaluation and personalisation framework is also presented in the paper. Evaluation of quality of VR/AR/MR platforms/environments should be based on (a) applying both expert-centred (top-down) and user-centred (bottom-up) quality evaluation methods and (b) separating ‘internal quality’ criteria, and ‘quality in use’ criteria in the set of quality criteria (model). Personalisation of VR/AR/MR platforms/environments should be based on learners’ models/profiles using students’ learning styles, intelligent technologies, and Semantic Web applications.