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Nowadays, audiovisual media technologies and audiovisual content (audiovisual media communications) play an important role in our physical/psychological health, education, and lifelong learning, causing the redefinition of the teaching methodology. As presented in the literature, the use of audiovisual media communications presuppose a new way of approaching effective teaching, which requires the educators on all educational levels and disciplines to display with competence many advanced skills and abilities. The aim of this research is to provide data that will contribute to the effective teaching utilizing audiovisual media communications in adult education. This research is a secondary research from two researches, which are qualitative and based on a quantitative method of analyzing. The primary data were collected through experiment method from adults (18 years and older), in Cyprus and Greece. The results confirm the current debate of using audiovisual media technologies within the educational process in technology-enhanced learning in education, both from the literature, and from the findings and results of various researches. This research is part of a larger, ongoing research that explores the multidisciplinary field that incorporates media, audiovisual content, and education (MACE), information and communications technologies (ICTs) in adult education (in Greece and Cyprus).

Digital entrepreneurship through the employment of smartphones and other handheld device applications is an innovative form of customer approach. Particularly, in the cultural marketing sector, new technologies, such as social media, YouTube channels, and mobile applications may increase the artists’ visibility and attract new partnerships and audiences. In this framework, entrepreneurs-musicians who attended a seminar on Management of Cultural Heritage, Communication and Media in Greece were asked to promote their activities through the creation of a smartphone application. After having completed their endeavor and further evaluated it, they participated in qualitative research based on the theory of experts’ interviews, as a case study. The aim of this paper, through thematic analysis of the conducted interviews, is to reflect upon the dynamics of new technologies in music entrepreneurship. As derived by the analysis, the use of mobile applications may effectively approach prospective partnerships and audiences, especially if combined with other contemporary forms of communication, and results in presenting enhanced professionalism. Audience engagement, which is an issue that is sought while attempting to optimize promotion processes, may be achieved if a further practice is performed. As the research was conducted during the COVID-19 pandemic, the demand for this form of making publicly known their artwork was considered essential.

The rapid development in the fields of science, and information and communications technologies (ICTs) in recent years, as well as the COVID-19 pandemic, have brought about and continue to generate transformations in education, especially in adult education. In the present enhanced research article, an interactive audiovisual-supported lesson plan template and its non-verbal role in our psychological and mental health are presented in-depth. Applying a multi-methodological approach, this interactive communication-themed adult lesson plan was executed and researched in the framework of an interactive seminar in Greece and Cyprus. The research sample consisted of adult educators as adult learners and involved empirical research where technology-enhanced research methods were applied as qualitative action research with quasi-experiments. Specifically, the attitudes and views of an adult educators’ group regarding the research interactive seminar that they participated in were re-investigated through secondary analysis. Similarly, the suitability of specific ICTs as well as whether they help or change the physical or psychological and mental health of the participants at the end of a teaching–learning procedure as a pilot case study were explored. The research results, effects and findings confirm the current debate on the employment of contemporary ICTs within the framework of the educational process of technology-enhanced learning in education (including adult education) as derived both by the literature, and by the research results, effects and findings of various other studies and research papers. Finally, this study can be used as a basis for creating and/or developing an audiovisual-supported lesson plan aimed at adult learners as an alternative approach.

Generation Z’s members are considered to have a strong preference for streaming and on-demand media only. This article is dedicated to Generation Z and comes to investigate the triptych of attitudes, opinions, and behaviors regarding radio and music preferences of its members in Greece through an Internet survey. The research data were collected through a web-based questionnaire, while for the analysis, descriptive and inductive statistics were applied from and through Internet applications and services. The research results and findings confirm previous empirical studies and research regarding the radio, the genealogical characteristics, habits, and ethos of Generation Z as well as that Generation Z can also be characterized as a sound generation. Finally, these research results and findings are considered encouraging and could be leveraged primarily by the radio media ecosystem with the aim of reorganizing or decentralizing the radio for its future form.

This systematic literature review explores the socio-ethical implications of Artificial Intelligence (AI) in contemporary media content generation. Drawing from 44 peer-reviewed sources, policy documents, and industry reports, the study synthesizes findings across three core domains: bias detection, storytelling transformation, and ethical governance frameworks. Through thematic coding and structured analysis, the review identifies recurring tensions between automation and authenticity, efficiency and editorial integrity, and innovation and institutional oversight. It introduces the Human–AI Co-Creation Continuum as a conceptual model for understanding hybrid narrative production and proposes practical recommendations for ethical AI adoption in journalism. The review concludes with a future research agenda emphasizing empirical studies, cross-cultural governance models, and audience perceptions of AI-generated content. This aligns with prior studies on algorithmic journalism.

Purpose. To evaluate the efficacy of the smartphone-based K-color test to detect color defects in patients with Age-related Macular Degeneration (AMD). Methods. 88 patients (n = 135 eyes) with AMD and 28 controls (n = 53 eyes) underwent color testing with the Hardy–Rand–Rittler (H-R-R), the K-color test, and the Ishihara test. The K-color test presents randomized colored shapes in decreasing steps of intensity, providing also a record system for result tele-transmission. Sensitivity, specificity, and reliability were examined to investigate the validity of the novel test. 26 participants with AMD also completed a questionnaire regarding the feasibility of the test. Results. Linear mixed-effects models indicated a significant difference (p<0.001) between AMD and normal eyes. The areas under the curve (AUC) were estimated to be 0.897 [95% CI: 0.841–0.952], 0.943 [95% CI: 0.901–0.984], and 0.931 [95% CI: 0.886–0.977] for the red, green, and blue color, respectively. Based on the H-R-R, the sensitivity of the test was 0.79, 0.90, and 0.95 for the red, green, and blue colors, respectively, and specificity was 0.88 for all colors. The new test recognized more abnormal cases than the Ishihara (sensitivity of 0.98 and 1.0 and specificity of 0.48 and 0.38 for red and green colors, respectively). Test-retest reliability was found to be high for the red [ICC = 0.996 (0.990–0.999)], green [ICC = 0.974 (0.929–0.990)], and blue [ICC = 0.992 (0.981–0.997)] colors. The majority of the asked participants stated that they could easily perform the test. Conclusion. The K-color test was found to be sensitive and specific in detecting color defects in AMD patients. The K-color test may serve as a useful tool both for patients and their physicians.

The current paper focuses on the investigation of spoken-language classification in audio broadcasting content. The approach reflects a real-word scenario, encountered in modern media/monitoring organizations, where semi-automated indexing/documentation is deployed, which could be facilitated by the proposed language detection preprocessing. Multilingual audio recordings of specific radio streams are formed into a small dataset, which is used for the adaptive classification experiments, without seeking—at this step—for a generic language recognition model. Specifically, hierarchical discrimination schemes are followed to separate voice signals before classifying the spoken languages. Supervised and unsupervised machine learning is utilized at various windowing configurations to test the validity of our hypothesis. Besides the analysis of the achieved recognition scores (partial and overall), late integration models are proposed for semi-automatically annotation of new audio recordings. Hence, data augmentation mechanisms are offered, aiming at gradually formulating a Generic Audio Language Classification Repository. This database constitutes a program-adaptive collection that, beside the self-indexing metadata mechanisms, could facilitate generic language classification models in the future, through state-of-art techniques like deep learning. This approach matches the investigatory inception of the project, which seeks for indicators that could be applied in a second step with a larger dataset and/or an already pre-trained model, with the purpose to deliver overall results.

In this article, the quality of media studies education through effective teaching utilizing audiovisual media technologies and audiovisual content (audiovisual media communications) to budding journalists as adult learners (18 years and older) is researched, with results primarily intended for application in radio lessons at all educational levels and disciplines (including adult education). Nowadays, audiovisual media communications play an important role in the modern and visual-centric way of our life, while they require all of us to possess multiple-multimodal skills to have a successful professional practice and career, and especially those who study media studies, such as tomorrow’s new journalists. Data were collected after three interactive teachings with emphasis on educational effectiveness in technology-enhanced learning, through a specially designed written questionnaire with a qualitative and quantitative form (evaluation form), as case study experiments that applied qualitative action research with quasi-experiments. The results (a) confirmed (i) the theory of audiovisual media in education, as well as (ii) the genealogical characteristics and habits of budding journalists as highlighted in basic generational theory, something which appears to be in agreement with findings of previous studies and research; and (b) showed that (i) teaching methodology and educational techniques aimed primarily at adult learners in adult education kept the interest and attention of the budding journalists through the use of such specific educational communication tools as audiovisual media technologies, as well as (ii) sound/audio media, as audiovisual content may hold a significant part in a lecture.

This work studies the task of automatic emotion detection in music. Music may evoke more than one different emotion at the same time. Single-label classification and regression cannot model this multiplicity. Therefore, this work focuses on multi-label classification approaches, where a piece of music may simultaneously belong to more than one class. Seven algorithms are experimentally compared for this task. Furthermore, the predictive power of several audio features is evaluated using a new multi-label feature selection method. Experiments are conducted on a set of 593 songs with six clusters of emotions based on the Tellegen-Watson-Clark model of affect. Results show that multi-label modeling is successful and provide interesting insights into the predictive quality of the algorithms and features.