Gamified Engagement for Data Crowdsourcing and AI Literacy

An Investigation in Affective Communication Through Speech Emotion Recognition

Bibliographic Data

ID13025199
AuthorsEleni Siamtanidou (0009-0009-9678-4666, Aristotle University of Thessaloniki), Lazaros Vrysis (0000-0003-2900-4657, Aristotle University of Thessaloniki), Nikolaos Vryzas (0000-0002-4801-0115, Aristotle University of Thessaloniki), Charalampos A Dimoulas (0000-0001-7923-9361, Aristotle University of Thessaloniki, corresponding author)
Year2025
Volume15
Issue3
Pages54-54
Publication date2025-02-22
Open AccessYes
TypeARTICLE
VenueSocieties (JOURNAL)
Journal identifiersISSN: 2075-4698 • E-ISSN: 2075-4698
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/soc15030054
OpenAlexW4407902417
LanguageEN
Citations received1
References cited51

This research investigates the utilization of entertainment approaches, such as serious games and gamification technologies, to address various challenges and implement targeted tasks. Specifically, it details the design and development of an innovative gamified application named “J-Plus”, aimed at both professionals and non-professionals in journalism. This application facilitates the enjoyable, efficient, and high-quality collection of emotionally tagged speech samples, enhancing the performance and robustness of speech emotion recognition (SER) systems. Additionally, these approaches offer significant educational benefits, providing users with knowledge about emotional speech and artificial intelligence (AI) mechanisms while promoting digital skills. This project was evaluated by 48 participants, with 44 engaging in quantitative assessments and 4 forming an expert group for qualitative methodologies. This evaluation validated the research questions and hypotheses, demonstrating the application’s diverse benefits. Key findings indicate that gamified features can effectively support learning and attract users, with approximately 70% of participants agreeing that serious games and gamification could enhance their motivation to practice and improve their emotional speech. Additionally, 50% of participants identified social interaction features, such as collaboration, as most beneficial for fostering motivation and commitment. The integration of these elements supports reliable and extensive data collection and the advancement of AI algorithms while concurrently developing various skills, such as emotional speech articulation and digital literacy. This paper advocates for the creation of collaborative environments and digital communities through crowdsourcing, balancing technological innovation in the SER sector

Crowdsourcing · Data collection · Knowledge management · Netnography · Social media · World Wide Web · AI in Service Interactions · Computer Science · Emotion and Mood Recognition · Media Influence and Health · Psychology

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Open DOIOpen Access