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Copyright © 2024 by Cherkas Global University
Published in the USA
Media Education (Mediaobrazovanie)
Issued since 2005.
ISSN 1994-4160
E-ISSN 1994-4195
2024. 20(3): 431-443
DOI: 10.13187/me.2024.3.431 https://me.cherkasgu.press
Media Education (Mediaobrazovanie)
Artificial Intelligence as a Means of Visual Representation of the Lost Cultural and Historical Heritage of the Urban Landscape in Media Education
Nikolay Khilko a , b , *, Yulia Gorelova a , c
a Likhachev Siberian Branch of the Heritage Institute, Russian Federation b Dostoevsky Omsk State University, Russian Federation c Siberian Automobile and Road Academy, Russian Federation
Abstract
This study was carried out to modern world presents the problem of introducing and using artificial intelligence as a visual representation means of the lost cultural and historical heritage. It is the urban landscape in mass and professional media education. Thus, based on the study of losses in the cultural and historical heritage, the authors develop different methods of traditional and digital visual-shaped memorialization. The aim of the research lies in artificial intelligence research includes the technological aspect of scientific and educational activities of students. According to the degree of vocational education proximity the cultural heritage and media education specialties, the use of artificial intelligence in related specialties is considered. The developed synchronization system of inheritance and the cultural and historical heritage study in media education made it possible to single out the representative forms of its restoration in the educational course. The authors of the article explore the connection has been established between the loss of cultural and historical heritage and the methods of its reconstruction and integration into media education. Using these methods, the study identifies the role of neural networks and artificial intelligence in the reconstruction of cultural and historical heritage in media education has been determined.
Keywords: visual-imaginative representation, cultural and historical heritage, visual dominants, recreation, visual appearance, artificial intelligence, augmented reality, media education, memorialization.
1. Introduction
The reflection of the modern Russian information society is associated the problem of representing the lost cultural and historical heritage as a whole is mainly socio-moral, but at the same time civilizational. It is closely related to the process of memorialization of domestic heritage in general and, in particular, in the urban environment. The protection of memorable places and architecture plays an important role in the restoration of cultural and historical memory. It indirectly affects the restoration of events and facts gaps in the chain studied in media education. Memorialization the cultural and historical establishment and significance of heritage ultimately determines the nature of figurative ideas about it. The forms of memorialization can be very different: expositions, exhibitions, display of culturally significant objects, consecration of places of memory. These objects in various combinations, ensembles, exposed to the action of time, have various destruction and loss. The way to provide the nature of this process is to lack of public
* Corresponding author
E-mail addresses: fedorovich59@mail.ru (N.F. Khilko)
attention, indifference to the protection of historical and cultural monuments, oblivion of historical memory is fraught with serious socio-cultural consequences. For example, in Omsk recently many valuable monuments have been lost, including the Assumption Cathedral, the Serafimo-Alekseevskaya chapel, and so on. They are recreated through collections of landscape photographs, the creation of which is the prerogative of media education.
With this situation it is connected as well management of stresses as notes Mona Alhasani and Rita Orji "Guided by the study findings, we provided actionable design recommendations and future research directions to facilitate the development of impactful persuasive time and stress management interventions" (Alhasani, Orji,2024).
At the same time, according to Anne-Britt Gran, Peter Booth and Taina Buche, the problem depends on social change: "Algorithms are an increasingly important element of internet infrastructure in that they are used to make decisions about everything from mundane ... recommendations through tomore profound and oftentimes life changing" (Gran, 2024).
One of the effective means of recreating cultural and historical memory in the minds of recipients is visual-shaped presentation using media technologies. It is closely related to the possibilities of recreating losses based on the study of visual documents, filling gaps in history. In this process, a considerable role belongs to the samples of landscape photography. In this regard, the discovery of the lost cultural heritage in archival and author's photo collections of the photo clip allows you to see complexes of ensembles, estates, fortresses, which make it possible to compare the past and modern appearance of the city. In the future, the orientation of scientific activity to recreate the heritage of urban landscapes is necessary. Here an important part of the problem is the choice of the information field, which speaksJan Svelch: "A part of this strategy is the video game industry's selective information disclosure, which I explore empirically on the example of telemetry infographics.... how publicly disseminated infographics contribute to the normalization of player surveillance by presenting it as a source of harmless trivia to be collected and shared by fans and the specialized press" (Svelch, 2022: 5).
On this basis, it is quite possible to form a media landscape using its modeling, according to Li that as is it possible: "have found ways to build and maintain a vibrant media landscape composed almost exclusively of micro media industries and small-scale legacy and new media productions ranging from newspapers to podcasts, from radio shows to social media influencing" (Li, 2022).
An important component of this problem is to give the lost heritage a digital visual shape using the recreating capabilities of artificial intelligence. For this purpose, active digitalization is necessary, which allows, according to V.E. Vasilevskaya "not to lag behind the level of reality in an uncertain future" (Vasilevskaya, 2021). At the same time it can be noted the presence of social communications in universities, "in recent years, social media have developed the strong potential to effectively communicate and to create a value proposition about university educational services, research activities and their third role. The social media content should be designed in a way which creates value for social media users to build a stronger level of engagement and facilitate brand communication" (Eger, 2024: 157).
There is a thought attached to this teachingJoomi Lee , Dai-Yun Wu, Jih-Hsuan (Tammy) Lin, Jooyoung Kim, Sun Joo Ahn that exists "the unique affordance of time travel in virtual reality (VR) to enhance the perceived efficacy" (Lee et al., 2023: 6).
Our understanding of artificial intelligence is changing day by day because of point of view Laba N., that "visual generative media represent a novel technology with the potential to mediate public perceptions... Seeking to understand a visual culture in which algorithms become integrated into human processes of memory mediatization". It is indisputable that "representation: drawing on AI-enabled media to generate images for .another purposes where the lines between human and machine agencies blur" (Laba, 2024).
In this regard, the issue of the impact of virtual reality on cultural heritage becomes important. Byun and Ahn (Grace) states that "virtual influencers (VIs), computer-generated characters that serve as influencers, offer novel and cost-effective advertising strategies. VIs' roles and appearances are comparable to those of human influencers (HIs) in advertising in that they mimic humans in their behavior" (Byun, Ahn, 2023).
In this case, you need to see a deep differences , about which write W.Z. Hill: "Technological modernity understands media such as film in a way that produces a separation between nature and culture" (Hill, 2022).
At the same time, thehere it takes place to be the integration into the virtual world: "innovate the existing teaching mode, provide diversified teaching resources and environments, realize intelligent teaching evaluation and certification methods, etc., but also realize the real integration of people's physical world and virtual world" (Wu, Hao, 2023). The implementation of these competencies brings students to virtual reality, which writes Slavomir Galik: "Human identity is now extending to cyberspace of digital media. According to Turkle, cyberspace acts as a mirror in which one can get to know one another. However, virtual identity is not entirely virtual because it is continually linked to real identity through cognitive functions and abilities" (Galik, 2019: 8; Galik et al., 2024).
One of Russian authoritative scientists A.V. Ostroukh argues that content of digital heritage, the leading direction is on the use of artificial intelligence, highlighting two directions in its development: approaching the principles of human thinking and integrating already created systems into a single system (Ostroukh, 2020). In addition, one should agree with the opinion of Guk garding the inclusion in the digital cultural heritage of "systems with elements of augmented reality and the prospects for the further development of virtual reality technologies in the field of culture." The resulting virtual environment becomes not only a place to acquire, but also to spread new knowledge, which contributes to the fact that "over time, the paradigm of consumer culture is replaced by a culture of participation" (Gooke, 2021).
The use of social networks, according to Zhang, is important for cultural and historical memory, causing a crisis due to the fact that opportunity appeared "to identify various crisis memory narratives, and then, rank-order analysis, cross-lagged correlation analysis, and multiple regression quadratic assignment procedure were performed to evaluate the reciprocal influences of crisis memory agendas of the second level (narrative salience) and the third level (narrative network) among different users" (Zhang, 2024: 218).
As for some Russian scholars, who analyzed the difference the aspects of problem. For instance, historical and methodological approaches to the educational potential of artificial intelligence and the principles of its are analyzed study I.O. Kotlyarova. She distinguishes: philosophical, sociological, psychological and pedagogical aspects. It should be noted that the technological aspect of scientific and educational activities is not indicated. We agree that the use of artificial intelligence for interpersonal interaction, self-identification and socialization of students is quite effective. However, it is equally important for group interaction and interactive communication. Following the author's principles: axiological, humanism and personification, subject, cognitive can be supplemented by the principle of integration, which most of all corresponds to the pattern identified by the author, which consists in the co-evolution of education and the scientific sphere (Kotlyarova, 2022).
So, at the same time, the media has a stable connection with the picture of the world in "the process of creating a certain... among the audience of various media, while emphasizing the influence of events that are attributed high importance on the attitude of society to the specific mentioned persons" (Knowles et al., 2023: 21). Therefore in restoring the visual appearance of the lost heritage. In the regard of some researchers "visualization of nature in cities fundamentally impacts how we imagine the urban environment and our role in caring for it. the project of urban renewal imagines and designs specific typologies of urban nature». They discusses «an experiment creating photo diagrams, which expands visual methodologies used .augmented .us to 'read' the landscape" (Jones et al., 2024).
2. Materials and methods
In order to study materials and sources on cultural heritage, artificial intelligence, in the media educational environment, there is serious pedagogical potential for the development of artificial intelligence according to curricula by designers, journalists, architects, multimedia directors, and future film specialists.
The methodology for assessing the degree of destruction of objects and differentiation of the lost cultural and historical heritage is closely related to the study of integration methods and forms of scientific knowledge into the educational process leading to digital representation. In addition, a comparative analysis of the methods of using artificial intelligence in professional media education.
3. Discussion
An analysis of media's publications and on the Internet shows three points of view. Three points of view. the leading direction is the views of A.V. Ostroukh on the use of artificial intelligence, highlighting two directions in its development: approaching the principles of human thinking and integrating already created systems into a single system (Ostroukh, 2020). In addition, one should agree with the opinion of D.Yu. Hook regarding the inclusion in the digital cultural heritage of "systems with elements of augmented reality and the prospects for the further development of virtual reality technologies in the field of culture." The resulting virtual environment becomes "not only a place to acquire, but also to spread new knowledge," which contributes to the fact that "over time, the paradigm of consumer culture is replaced by a culture of participation (Gooke, 2021).
Promotion of media culture in the field of education relevant now so "culturally responsive pedagogy has received increasing research attention and has been applied in science, technology, engineering, and mathematics ... in higher education to support an increasingly diverse student body in recent years" (Xie, Ferguson, 2022: 1215).
Many scientists consider the major use of artificial intelligence in the space of digital historical and cultural heritage. So, in the first approximation, in the process of compiling the media content of the lost cultural heritage in the form of chronotopes (Yablokova, Kalitina et al., 2024; Tsareva, Tarasova, 2023). Itis necessary, according to Tsareva and Tarasova, to collect and analyze the wide space-time continuum to achieve the authenticity of the cultural heritage (Tsareva, Tarasova, 2023).
The similarity of artificial intelligence with human by the principles and his functioning on the basis of algorithms is noted by R. Dushkin and M. O'Connell which don't identify him with a human brain at all (Dushkin, O'Connell, 2022). According to a number of scientists, digital historical and cultural heritage is a promising area for the use of artificial intelligence technology. Digitalization of cultural heritage objects lays the foundation for the use of artificial intelligence in the process of converting artifacts into new forms that are part of the updated context, to which Tarasova and X include: "collection and analysis of data from a wide temporal and spatial content" (Tsareva, Tarasova, 2023).
However, digitalization does not yet provide the development dynamics provided by the processing of digitized data using artificial intelligence. In this regard, according to the strategy of using artificial intelligence presented by K.R. Oleshkovich, it becomes possible to create a reality that is not intended to replace people, but is a means of expanding human skills and capabilities and an excellent opportunity for the implementation of new ideas, including in the field of culture (Oleshkovich, 2021).
In the same direction, transactions of information systems are studied which «using conventional approaches to match entities share the common problem of missing important structural information beyond entities in the modeling process» and "allows graph neural network models to step in" (Zhiwen et al., 2023).
Further this strategy is M.M. Lariontsev, who gives the concept of the datafication of everyday life in the collective cooperation of people who are in the space of creative capital due to the expansion of reality in mixed reality technologies. The unified information space formed at this time ensures the popularization of cultural heritage (Lariontsev, 2020).
The third aspect of the cultural heritage preservation is developed by E.R. Abrukova, justifying the principles of the use of artificial intelligence in the restoration of cultural heritage objects, which make it possible to restore damaged objects, "analyzing materials with accuracy invisible to the human eye and providing opportunities for making more informed decisions. "The use of artificial intelligence in the field of restoration, as the author notes, not only increases the efficiency of work, but also allows a deeper understanding of the history and technology in creating works of art" (Abrukova, 2023). In the same direction A.B. Ivanov and V.G. Petrov explores various algorithms for the analysis and restoration of architectural monuments (Ivanov, Petrov, 2023).
It should be noted that the use of artificial intelligence is distributed, on the one hand, to the sphere of preservation of cultural heritage and, on the other hand, to its popularization and study for scientific and educational purposes, including media education. In this regard, the basic general principles for the use of artificial intelligence in modern education are justified.
The difference the aspects of artificial intelligence study and the principles of its use was carried out by I.O. Kotlyarova. She distinguishes: philosophical, sociological, psychological and pedagogical aspects. It should be noted that the technological aspect of scientific and educational activities is not indicated. We agree that the use of artificial intelligence for interpersonal interaction, self-identification and socialization of students is quite effective. However, it is equally important for group interaction and interactive communication. Following the author's principles: axiological, humanism and personification, subject, cognitive can be supplemented by the principle of integration, which most of all corresponds to the pattern identified by the author, which consists in the co-evolution of education and the scientific sphere (Kotlyarova, 2022).
We fully agree with D.A. Strunin, who claims that personification of artificial intelligence as a leading style of education is noted by, emphasizing purposeful support and feedback, personalized learning experiences that take into account assessment; style, preferences, fostering student engagement and motivation (Strunin, 2023) his point of view is developed by O.A. Pyrnova and R.S. Zaripova, noting that personalized learning refers to a variety of educational programs in which the pace of learning and the learning approach are optimized for the needs and interests of each student. It is noted that artificial intelligence will easily select the right pace for a student to gain knowledge using technological tools (Pyrnova, Zaripova, 2019).
It should be noted that in the studies of these authors, the collective experience of acquiring knowledge remains in the shadows. The collective-technological aspect stands out in the system view of the use of artificial intelligence in the work of A.S. Slavyanov and S.S. Feshina, who believe that the inclusion in the system of providing education based on artificial intelligence of a search information system that allows the formation of a database of the educational process from various sources will be able to simulate the thought process of students in a continuous mode of research activity (Slavyanov, Feshina, 2019). One cannot but agree with this provision.
According to O.R. Popov and O.A. Gorbachev, the interaction of artificial intelligence and neural networks in education is considered from the standpoint of cognitive science and a biological approach, which is aimed at progressing and "solving the riddle of the mind" by strengthening machine intelligence or creating humanoid intelligence in the form of an autonomous technical system of artificial intelligence. The authors imagine the integration of already created artificial intelligence systems into a single system capable of supporting machine learning (Machine Learnng, ML) using artificial neural networks, which is the most promising technological trend of our time. At the same time, truly artificial intelligence (Artificial Intelligence, AI) covers "any technology that reproduces human thinking and such skills as, for example, understanding complex information, independently deducing conclusions and the ability to conduct a meaningful and coherent dialogue" (Popov, Gorbacheva, 2019). However these skills to which the car studies serve, most likely, as incentives of formation of those at the person.
In recent years, holding round tables on media education issues has been use considered the artificial intelligence in the field of preserving cultural heritage through its popularization and study of the most convex in visible and audible audiovisual forms finds its adequate expression in mass and professional media education.
The need for the integrative use of information technologies is written Abedi, Prestridge, Geelan, Hodge. They concided that: "Exploring the perspectives of multiple stakeholders involved in the initial teacher education space, such as teacher educators, pre-service teachers, principals and policymakers, could offer a more all-inclusive insight into the challenges and opportunities present in preparing pre-service teachers for a more effective digital technology integration in inservice classrooms" (Abedi et al., 2024).
In the research of artificial intelligence for mass media education are allocated the studies of E.A. Bondarenko, N.Yu. Nosova, M.D. Sokolova, A.V. Ostroukha.
The fundamental principle of media education is recreation and reproduction, modeling of perception using artificial intelligence, affirm by E.A. Bondarenko. Her point of view involves stimulating full-fledged natural creativity using artificial intelligence. At the same time, a heuristic departure from algorithms is assumed with their mandatory development, focusing on "making creative decisions, recognizing and implementing cultural codes,... perception of the target audience" (Bondarenko, 2023). The principle of the stimulating effect of artificial intelligence is indeed objective and effective. This position is fully consistent with the principles of the human brain, highlighted by N. Yu. Nosov, based on the use of a mass of logical mechanisms (including the so-called "fuzzy logic" scheme), is able to switch and thereby help solve the main problem within
the framework of the neurodynamic model) (Nosov, Sokolov, 2016). In the use of artificial intelligence in the field of professional media education, it can be distributed according to the idea for the training of journalists, designers, heads of film, photo, video studios, multimedia directors, animators, videographers, producers, screenwriters, film and television directors, film and television editing specialists, etc. In this direction, a few specialized studies can be noted.
The study of the process of generating neural networks through artificial intelligence as the prerogative of media education, the possibilities of its application and its limits led I. Kozlikhin and A. Demidov to interpret them as a kind of "new media," which should be assessed, in our opinion, in the context of traditional values (Kozlikhin, Demidov, 2020). According to the degree of proximity of vocational education specialties to cultural heritage, on the one hand, and to media education, on the other hand, the use of artificial intelligence in related specialties should be considered: museology, architecture and in media education: design, animation, journalism, cinema and video.
This idea is consistently developed in the research Jiang, while it is noted that "based on the cognitive mediation model, this study explored the pathways through which social media use was linked to., taking into account different information acquisition patterns (e.g., media attention vs. information discussion), information processing (e.g., elaboration), and information seeking experience" (Jiang, 2022).
Research on the role of artificial intelligence in documenting history can be traced in the article Eduard Hovy, Martha Palmer, and Piek Vossen that states "unlike humans, artifical inteligence, at least current stage, processes stories in a much more atomistic fashion. While significant breakthroughs have been made over the past few decades, challenges continue as progresses necessitating creative solution" (Yang, 2023).
So, in the training of museum specialists, the use of artificial intelligence to form systems for creating electronic images of museum storage objects and integrating images, the most relevant is the digital transformation of traditional technical and technological methods for analyzing museum objects (Yumasheva, Guk , 2022). Since the systemic transformation of museum objects of cultural heritage for its development by students-museologists presupposes augmented reality, here the use of the media educational potential of artificial intelligence in the process of interaction with it is extremely necessary, as mentioned above.
At the same time, the use of artificial intelligence by students for architectural objects of cultural heritage is aimed, according to E.A. Akshov, at changing the creative process when creating architectural concepts using generative neural network modeling (Akshov, 2023).
Here, unlike museologists, the potential for media-educational interaction between students and artificial intelligence is much wider. E.L. Yelkina points out that in the media education areas and specialties themselves, emphasis is placed on audiovisual media systems. So, in the training of designers, where the creation of compositions in design plays a special role, according to, "neural networks do not create new ideas, are not the creators of innovative breakthrough visual concepts," a "the formation of professional skills in the education of student designers is impossible without the development of a special form of compositional thinking" with the help of new digital tools, actualizing the skills of working with artificial intelligence, which combines all the many visual information, created by masters of painting and design, which "develops the creativity, creativity of future designers" (Elkina, 2023). There is an interaction of the media educational potential of artificial intelligence with audiovisual creativity.
Didactic strategy training of designers, as claims D.A. Restrepo-Quevedo, R. Cuervo, J. Gonzalez-Tobon, J Camacho, E. Hernandez consists in "intersemiotic emergence ... for design learning, discussed from the perspective of social semiotics and communication studies. With this strategy, students orchestrate autotelic relationships using modes and personalized semiotic resources" (Restrepo-Quevedo et al., 2024).
It should be noted, as E.O. Katrangi, I. Yu. Kodenko, that the use of artificial intelligence for design students allows you to personalize the learning process in accordance with the individual needs of students, ensures their involvement in the process of cognition due to the advantages of material perception using virtual (augmented) reality (Katrangi, Kodenko, 2022). We see that here the process of interaction is personalized due to virtual reality.
However, according to M.B. Belyaeva and E.I. Kharisov, for animation students, media development using even more due to the visual images allocated by the author of the animated work, used in "such technologies as key forms (shape keys), motion capture (motion capture).
"Machine learning is used here for motion matching. The use of neural networks allows for markerfree capture of human face animations. Can be noticed, that it is necessary that the interaction of man and machine in the neural network space when creating identical images of the lost cultural heritage includes all the variety of situations, emotions, key forms of the appearance of the urban landscape. So there is a need that «to train the neural network on a pre-prepared set of different data, consisting of several thousand photographs of human faces in various situations that transmit numerous emotions, as well as a special coordinate grid indicating the key, according to the authors, points of the face" (Belyaeva, Kharisov, 2020: 27). As you can see, here the dominant role in media education with the help of artificial intelligence is played by the visual solution of animated images, including for cultural heritage.
To animate movement in the process of restoring historical memory, it is important to rely on the psychological sect, the pattern that "we can better describe the sensations of movement in animated films that are ostensibly created frame by frame, thus defying our perceptual habits for watching movies and making sense of the movements we see on-screen" (Jong, 2022).
Unlike animators, training journalists requires mastering algorithms, which is based, according to A.P. Sukhodolov, A.M. Bychkova, S.S. Hovhannisyan, on artificial intelligence machine learning and is applicable for generating and analyzing texts. It is noted that a new generation of algorithms based on artificial intelligence is able to recognize the emotional coloring of the text. The authors note that artificial intelligence in journalism is used in data processing and analysis, interactive communication with the audience; tracking information reasons; vlidation of facts (fact-checking) image recognition; production of video content, etc. (Sukhodolov et al., 2019). Obviously, it is not the artificial generation of information that is important for student journalists, but its monitoring for reliability, analysis and convincing interaction with the audience.
It should be noted that in this process the leading role is played, according to A.V. Fedorov, the development of media competence of students, including critical thinking and perception. The author states that these processes develop when analyzing the features of the structure and functioning of media texts based on six key concepts of media education: agency, category, language, technology, audience, representation (Fedorov, 2015). Indeed, media competence, also produced in the field of artificial intelligence, cannot be mastered without critical thinking.
4. Results
The system for synchronizing the processes of cultural and historical inheritance and the study of cultural and historical heritage in media education operates as follows. The actualization of heritage contributes to the emergence of opportunities is reflecting heritage in media education. The next stage in inheritance: the establishment of the cultural and historical value and significance of heritage sites predisposes to the development of the cultural and historical content of the heritage. The future memorialization fixes the value of objects of material and intangible heritage and allows students to obtain the media competencies necessary for media education
Fig. 1. System for synchronizing inheritance and the study of cultural and historical heritage in media education.
However, only the presence of a reflected heritage in photo landscapes does not guarantee its reconstruction. It is important to represent its appearance, figurative meanings, visual dominants, which requires a thorough study of the state of objects and classification by species.
Types of lost cultural and historical heritage and a representative form of development of its various types in media education. Representation of visual images is closely related, according to N. Laba, with memory image recovery, so "seeking to understand a visual culture in which algorithms become integrated into human processes of memory mediatization, this study addresses representation" (Laba, 2024).
The study of the state of cultural and historical heritage objects reveals the degree of destruction (loss). By gradation, it is distributed as follows by gradation levels: 1. damage, 2. partial destruction, 3. loss of ensemble, 4. appearance deformation, 5. disharmonization and dispersal of the ensemble, 6. ruinization, 7. total destruction. These levels determine the methods of levels of recreation and the corresponding recreating and integrated visual representation. Recreating representation of the images of the urban cultural landscape, its architecture is associated with restoration, renovation, reconstruction. Visual representation integrated into the process of media education involves the construction of the city images, the reconstruction and visual images generation in the process of restoring cultural heritage are closely interconnected through demonstrative and presentationes forms of their introduction into medical education practice. Thanks to this, the imaginary and metaphysical components are combined in an updated context. It should be noted that there is a close connection between the degree of destruction and loss of cultural and historical heritage and the methods of its reconstruction and integration into media education, mediated by digital memorialization methods, including using neural networks and artificial intelligence (Table 1). These include: cuarcoding, creating virtual reality, inclusion in augmented reality, digital reconstruction of the architectonics of the ensemble and cultural and historical appearance, digital design of the image of the city.
Thus, digital memorialization methods allow us to determine the methods of using artificial intelligence in media education. For this purpose, recently effectively used: digital stylization of architectural objects, cataloging artifacts of the cultural landscape, digital segmentation of the cultural landscape, computer identification of architectural styles, media representation of heritage objects.
With this aspect Anne Kaun and. Michael Forsman links the synthesis of digitalization of media competencies "in the process of translating digitalization into reality; they have become ambassadors of digitalization not only by fostering digital skills and competences in workshops and official training sessions but also, we argue, through a specific form of digital work, namely, digital care work" (Kaun, 2024: 5).
Table 1. The relationship between the degree of destruction and loss of cultural and historical heritage and the methods of its reconstruction and integration into media education
№ Degree of destruction of objects and types of lost cultural and historical heritage Methods of recreating visual representation Methods of recreating visual representation ethods of integrated visual representation Methods of digital memorialization
1. Damages Comparison of the damaged and pristine appearance of monuments Virtualization of the image of monuments Digital reconstruction of the architectonics of the ensemble and cultural and historical appearance.
2. Partial destruction Recreating the original images of the cultural landscape Animation of the cultural and historical landscape Creating integrity in virtual reality
№ Degree of destruction of objects and types of lost cultural and historical heritage Methods of recreating visual representation Methods of recreating visual representation ethods of integrated visual representation Methods of digital memorialization
3. Deformation of the appearance Recreation of the appearance of heritage objects Demonstration of the recreated reality Cuarcoding
4. Loss of the ensemble Immersion in the integrity of the heritage object Recreating the visual dominants of the cultural and historical landscape I Inclusion in augmented reality
5. Disharmonization and dispersal of the ensemble Generation of figurative representations of the urban landscape Immersia into the educational process of digital analogues
6. Ruinization. Complete destruction, disappearance The embodiment of the figurative meanings of the primogeniture of the monument The generation of urban imaginary and metaphysical meanings of cultural landscapes. Digital design of the city image
These methods extend to the study of a number of disciplines of student designers, future leaders of photo, video studios, and animators: both general art and professional cycles: Landscape Design, Landscape Studies and Architectural Design, Landscape Architecture and Media Landscape, Aesthetics and Philosophy of Art, General History of the Arts; Media studies, Media ecology, History of audiovisual arts. There is an objective connection between the methods of using artificial intelligence and methods of visual representation in the cycles of the studied disciplines (Table 2).
The concept of 'the artificial intelligence personification was coined by as a leading style of education is noted by D.A. Strunin, emphasizing purposeful support and feedback, personalized learning experiences that take into account assessment; style, preferences, fostering student engagement and motivation (Strunin, 2023).
Table 2. The connection of methods of using artificial intelligence and integrated methods of visual representation in the cycles of the studied disciplines
№ Methods of Integrated visual Representation Methods of Using Artificial Intelligence in Media Education Disciplines Studied
1. Virtualization of the image of monuments Media restoration of heritage sites. Landscape and architectural design
2. Animation of cultural and historical landscape Computer animation and pattern recognition Landscape design
3. Demonstration of the recreated reality Computer identification of architectural styles Aesthetics and philosophy of art
4. Recreating the visual dominants of the cultural and historical landscape Digital segmentation of the cultural landscape General art history
5. Immersion in the educational process of Cataloging artifacts of the cultural landscape History of audiovisual arts
№ Methods of Integrated visual Representation Methods of Using Artificial Intelligence in Media Education Disciplines Studied
digital analogues
6. Generation of urban imaginary and metaphysical meanings of cultural landscapes. Digital stylization and combination of architectural objects. Landscape Architecture and Media Landscape. Media studies. Media ecology.
This point of view is developed by O.A. Pyrnova and R.S. Zaripova, noting that personalized learning refers to a variety of educational programs in which the pace of learning and the learning approach are optimized for the needs and interests of each student. It is noted that artificial intelligence will easily select the right pace for a student to gain knowledge using technological tools (Pyrnova, Zaripova, 2019).
5. Conclusion
This study shows, that an objective connection between the methods of using artificial intelligence and the integration of methods of visual representation contains in the cycles of the studied disciplines in media education. It operates in a system of synchronizing inheritance and the study of cultural and historical heritage in media education. This connection is established between the degree of destruction and loss of cultural and historical heritage and the methods of its reconstruction and integration into media education. It extends to a set of methods for using artificial intelligence and integrated methods of visual representation in the cycles of the studied disciplines. Visual representation integrated into the process of media education. It involves the construction of images of the city, the various reconstructions, forms of media discourse, the generation of imaginary and metaphysical meanings of cultural landscapes.
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