Public speaking training and public speaking anxiety (PSA) treatment increasingly rely on technology-mediated systems, including web, mobile, desktop, and immersive virtual reality (VR) tools. This comprehensive review identifies and maps information and communication technology (ICT)-based public speaking interventions for educational training and anxiety-oriented treatment, focusing on platform choice, audience simulation, feedback timing, physiological and behavioral sensing, therapeutic framing, practitioner involvement, and evaluation methods. A PRISMA-inspired process documented identification and screening across Scopus, Web of Science, PubMed, IEEE Xplore, and ERIC for English-language journal articles and conference papers published between 1 February 2015 and 1 February 2025. From 6602 records, 82 participant-validated studies were included. No formal risk-of-bias assessment was conducted. VR accounted for 82.93% of interventions, while research prototypes comprised 72.0% of the evidence base, demonstrating the field’s strong emphasis on immersive and experimental development. At the same time, 64.6% of interventions provided no automated feedback and 36.6% used no physiological or behavioral sensing, highlighting opportunities for more responsive and data-informed systems. The findings can guide the development of future public-speaking training and treatment systems by highlighting recurring design components, promising implementation patterns, and priorities for stronger comparative validation.
Dragoș-Ion Dogioiu, A. A. Morar, A. Moldoveanu et al.· Information· 0 citations
Procedural generation is widely applied, from accelerating development of large and detailed virtual worlds to providing highly varied game content during gameplay. However, for procedural generators to be widely adopted, developers and artists must be able to select a suitable approach and contextualize it with respect to artifact design objectives. This paper presents an overview of the four main procedural generation approaches: constructive, search-based, solver-based, and machine learning. The paper also introduces three lenses for understanding how to use procedural generators in practice: benefits, capabilities, and usability. The benefits lens examines what objectives can be achieved with procedural generators. The capabilities lens distinguishes between artist-assisting procedural generation tools, procedural materials, automated designers, and expert systems capable of generating reliable artifacts. Finally, the usability lens addresses how to integrate procedural generators into practice and how users interact with them. Examples of generation approaches from academia and commercial works are provided to illustrate each lens. This review synthesizes the characteristics, benefits and drawbacks of various procedural generation methods, helping developers choose the most appropriate technique based on a particular use case. A decision support matrix is also provided to illustrate how to apply this practical view in different development scenarios.
Robert Andrei Caragicu, Anca Morar, A. Moldoveanu et al.· IEEE Access· 0 citations
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