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1. Article2026Open Access

   User Experience Evaluation in Non-Immersive 3D Digital Environments Using Facial Emotion Recognition(opens in a new tab)

   

   Veríscimo, Erico de Souza; Bernardes Júnior, João Luiz; Digiampietri, Luciano A.

   User experience (UX) is fundamental for the acceptance and use of information systems. Although there are well-known and widely used UX evaluation techniques for traditional interfaces, a literature review revealed several gaps regarding UX evaluation in non-immersive 3D interaction. One significant gap is the predominant use of pragmatic criteria in assessments, while another is the lack of an approach that evaluates hedonic aspects using facial emotion recognition. This work proposes an approach for automatically evaluating user experience in non-immersive three-dimensional environments, focusing on its hedonic aspects based on facial emotion recognition. An experimental protocol was developed and approved by the Ethics Committee. The experiment was conducted with 52 participants. Throughout the testing period (before, during, and after the interaction), participants' faces were recorded using a low-cost camera. The experiment involved participants playing a game and answering questionnaires, including categorization and mood profile instruments, as well as the UEQ-S and the PLEX Framework. The Face-api.js library was used for facial emotion recognition. The hypothesis that automatic facial emotion recognition can support user experience evaluation was confirmed. This method enabled the estimation of UEQ-S and PLEX questionnaire responses with an average error of approximately ±1 point using only emotion extraction through an artificial intelligence model. Given that UX evaluation is crucial for the acceptance of new software or functionality, this work contributes to improving system quality and acceptance.

   DOI: 10.5753/jis.2026.7625User experience designCategorizationEmotion recognitionUsability
2. Working Paper2025Open Access

   The multiversatory: fostering diversity and inclusion in research information by means of a multiple-perspective observatory(opens in a new tab)

   

   Rafols, Ismael; Costas, Rodrigo; Bezuidenhout, Louise; Brasil, André

   For science and technology to contribute to social justice, scientometrics analyses need to be able to produce descriptions that are appropriate to specific contexts and values. Given that the participation of stakeholders in the analyses is crucial for these perspectives to be realized, this requires research information analyses that are “open”. In this paper, we propose that this “openness” in research information concerns several dimensions. In the first place, research information should be open in the sense of being transparent and accessible. Second, research information should be open in the sense of being inclusive and diverse, which includes two dimensions: that stakeholders can actually use it, and that the contents include different types of knowledge. Third, the research information should be provided in forms that empower interrogation by stakeholders, so that they can retrieve and construct the descriptions of science and technology that are more appropriate for their context. This last step implies efforts to make visible many scientific contributions from the global south which are currently invisible. We call this vision “the multiversatory”: an approach to the observation of science that facilitates pluralistic analyses of the knowledge created across a variety of places and contexts, the pluriverse.

   DOI: https://doi.org/10.31235/osf.io/dn2axdiversityevaluationinclusioninformationmonitoringobservatoryresearch