ShodhKosh: Journal of Visual and Performing Arts

SPECIAL ISSUE ON INTELLIGENT EVALUATION EMOTION ANALYTICS AND AI-BASED ASSESSMENT IN DIGITAL ART

Saurabh Bhattacharya — 2025-12-20

It is with great pleasure that we present this special issue of ShodhKosh: Journal of Visual and Performing Arts, titled “Intelligent Evaluation, Emotion Analytics, and AI-Based Assessment in Digital Art.” This special issue responds to a critical and timely need within contemporary creative practice and education, where digital art has evolved beyond static visual expression into an intelligent, data-driven, and emotionally responsive domain.
With the integration of Artificial Intelligence, digital artworks today function as interactive systems capable of adaptation, interpretation, and emotional engagement. While such advancements have expanded the expressive and pedagogical possibilities of digital art, they have also introduced complex challenges related to evaluation, assessment, and interpretation of creativity and emotional impact. Traditional evaluative frameworks often fall short in addressing the multidimensional, subjective, and experiential nature of digital creativity.
Recent developments in emotion analytics, affective computing, machine learning, and intelligent assessment systems offer promising pathways to address these challenges. AI-based models now enable the analysis of visual features, emotional responses, interaction patterns, and contextual data, allowing for more objective, scalable, and reproducible approaches to evaluating digital art and creative performance. These technologies also hold transformative potential for art education, supporting automated feedback, learning analytics, and fair assessment mechanisms.
The papers selected for this special issue reflect a rich interdisciplinary dialogue bridging technology, visual culture, psychology, pedagogy, and creative practice. Contributions explore intelligent evaluation models for digital art, AI-driven creativity assessment frameworks, deep learning approaches to aesthetic quality measurement, emotion recognition in visual and interactive art, and multimodal emotion analysis using image, video, and interaction data. Several studies also address automated grading systems, feedback generation, and data-driven evaluation strategies within digital art education environments.
This special issue welcomes both theoretical insights and applied research, highlighting how intelligent systems can support meaningful evaluation without undermining artistic subjectivity. A recurring theme across the contributions is the importance of ethical responsibility, interpretability, and human-centered design in AI-based assessment systems, ensuring that technological advancement complements rather than constrains creative expression.
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ShodhKosh: Journal of Visual and Performing Arts 2
The call for papers attracted a diverse range of submissions from researchers, educators, technologists, and practitioners working at the intersection of art and artificial intelligence. All manuscripts underwent a rigorous peer-review process to maintain the scholarly standards of ShodhKosh. The resulting collection represents a curated body of work that advances current understanding while opening new avenues for research and pedagogical innovation.
We express our sincere gratitude to all authors for their valuable contributions, to the reviewers for their critical insights, and to Granthaalayah Publications for their continued support in promoting interdisciplinary research in the visual and performing arts. Their commitment has been instrumental in bringing this special issue to fruition.
We hope this volume will stimulate thoughtful discussion, inspire future research, and contribute meaningfully to the evolving discourse on intelligent evaluation and emotional analytics in digital art. May it serve as a resource for scholars and practitioners seeking to navigate the complex relationship between creativity, emotion, and artificial intelligence.

Issue Editor:

Dr. Saurabh Bhattacharya
Assistant Professor, School of Computer Science & Engineering, Galgotias University, Greater Noida, UP, India
Email: babu.saurabh@gmail.com

Anuj Kumar
Assistant Professor, Department of Hindi, Nagaland Univeristy, Kohima Campus, Meriema, Nagaland, India
Email: anujkumarg@gmail.com

Prof Dr Shreyas Dingankar
Institute of Management and Entrepreneurship Development, Bharati vidyapeeth Deemed to be university, Pune, India
Email: shreyas.dingankar@bharatividyapeeth.edu

Dr. Pastor R. Arguelles Jr.
Director, Research and Publication Office, University of Batangas Lipa City, Philippines
Email: pastor.arguelles@ub.edu.ph

M. Rajendra Nath Babu
Associate Professor, Department of Education, Nagaland University, Kohima Campus, Meriema, Kohima (dt.), Nagaland, India
Email: mrnb.svu@gmail.com

Dr. Indrani Hazarika
Department of Business and Specialization Accounting, Higher Colleges of Technology, United Arab Emirates
Email: ihazarika@hct.ac.ae

DIGITAL TRANSACTIONS IN CULTURAL AND VISUAL ART SPACES AUDIENCE INTENTIONS AND LOYALTY TOWARD FINTECH PAYMENT PLATFORMS IN DELHI NCR

Simran Vij — 2025-12-23

With the fast adoption of fintech payment systems, fintech has changed transactional relationships in cultural and visual art spaces, but the empirical study on audience intention and loyalty in the experience setting is not highly researched. This paper will look at the drivers of audience intention and loyalty to the fintech payment systems in cultural and visual art venues in the Delhi National Capital Region (NCR). Based on Technology Acceptance Model, Unified Theory of Acceptance and Use of Technology, Trust Theory, and Relationship Marketing Theory, a conceptual framework was formulated and empirically verified with the help of survey data, processed with the help of Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that perceived usefulness, perceived ease of use, perceived security, and trust play a key role in the intention of the audience to use fintech payment platforms. The intention to the audience has a positive influence on satisfaction, and consequently, a central mediator of loyalty to fintech platforms. The findings indicate that the fintech adoption is fundamentally shifted towards trust and experience satisfaction that drives it to audience engagement in the cultural and visual art world. The project builds on existing studies on fintech adoption in cultural economies and offers applicable findings to cultural bodies, fintech services infrastructure, and the policy community on how to enhance digital payment infrastructures and customer retention in the creative industries.

ADAPTIVE INTERFACES IN AI-POWERED ART GALLERIES

Tripti Sharma — 2025-12-20

The introduction of artificial intelligence (AI) to art galleries is transforming the visitor-artwork interaction and establishing new adaptive and personalized experiences that are more context-relevant. This paper will discuss the concept of adaptive interface design and deployment within AI-assisted art spaces, and how dynamic systems can adapt the exhibition content to both a specific user profile, behavior, and emotional reaction. In an in-depth analysis of the literature on interactive technologies in museums, user experience design, and machine learning-based personalization, the research paper reveals current gaps in visitor interaction and the flexibility of the interface. The data are gathered using a mixed-method research design by using user observation, interviews, and analytics to comprehend the interaction patterns and the cognitive response to adaptive systems. The suggested system architecture is based on user profiling, behavior tracking, and real-time content adjustment algorithms that are implemented with the use of AI frameworks like TensorFlow and OpenCV. The examples of AI-boosted galleries that already exist and a prototype of an application at a local exhibition show that adaptive interfaces could have a significant potential to engage viewers further and lead to meaningful interactions with art. Measures of evaluation such as dwell time, emotional resonance and interaction diversity demonstrate a significant increase in user satisfaction and learning retention. The results point to the importance of AI-based adaptive interface as an intelligent mediator of art and audience, which can be scaled down to future digital curation activities and can contribute to inclusivity and accessibility in contemporary art environments.

STRATEGIC MANAGEMENT OF AI ART EXHIBITIONS

J. Refonaa — 2025-12-20

The art of AI exhibitions management is an emerging area of frontier by the array of technology, imagination, and culture administration. The emergence of artificial intelligence as a driver in the production of art has introduced new issues and opportunities to curators and managers regarding how to conceptualize, organize and maintain exhibitions dealing with the issue of algorithmic creativity. This study indicates that AI art exhibitions should be managed in a comprehensive manner that addresses the strategic management of art exhibitions, their curation, operations, and the audience. It begins by defining the scope of AI art and contextualising it within the context of bigger conversations on digital culture and innovation management. The framework focuses on creating effective visions, missions, and goals that outline the value and the meaning of AI-based experiences of art. Through market and audience analysis, institutions will be in a better position to have a clear vision of the new demands and position themselves in the competitive arena of the cultural sector. The essence of successful exhibition curation consists in the developed concept of AI-based works selection principles including ethical considerations, aesthetic characteristics, collaboration trends that can unite artists, technologists, and curators. The operational strategies prove the need of the good technological foundation, the effective resource allocation, and the active risk management, particularly taking into account the fact that AI systems can be described as dynamic and experimental. The marketing strategies such as the narrative based branding and the cooperation with the digital media and the immersion of the audiences also precondition the rise of the degree of the public interest.

AI AS A MEDIUM IN CONCEPTUAL ART PRACTICE

Dr. Peeyush Kumar Gupta — 2025-12-20

This paper sets out to review the advent of artificial intelligence as an important medium in modern conceptual art practice, with particular reference to its ability to both extend and confuse the traditional operating assumption of ideas being the primary element in conceptual art practice. The study is based on the historical development of conceptualism, starting with the early linguistic and systemic arts and moving to the subsequent computational experimentalism, which orients AI to a tradition of artistic and process-oriented approaches, in which processes, instructions, and networks of meaning take the place of conventional object-based production. The distinctive language, image, and symbolic manipulatory skills of AI present new forms of authorship, autonomy, and indeterminacy and provide artists with the opportunity to create works that predetermine system-directed meaning, algorithmic patterning, and computational aesthetics. By presenting the history of algorithmic practices and the current case study, the paper will show that AI is not only a technical tool but also an active conceptual agent that can act to construct the propositions of art. This incorporates its role as partner, actor, and even proxy author, and leads to a rethinking of the agency of the creative and agency, and purposefulness. The theoretical consequences of the changes throw down challenges to the accepted versions of interpretation, work of art, and the limits of the intelligent in the artistic frames. Finally, the paper concludes that AI has a transformative potential to conceptual art that relates to the possibility of producing novel types of ideas, speculative questions, and bringing immaterial ideas to life.

CLOUD-BASED PRINT MANAGEMENT SYSTEMS

Dharmesh Dhabliya — 2025-12-20

Cloud-Based Print Management Systems represent a paradigm shift of the old style of on-shelf print infrastructures to an innovative, scalable, secure, and cost-effective print systems hosted by the cloud. These systems use cloud computing to print jobs, user authentication, and device communication without any complications in various platforms and network environments. The architecture is usually made up of the following core components which are: print servers, connectors, clients, and end-user devices and they are built using standardized workflows and APIs to guarantee that they will be interoperable with enterprise systems and networks. Some of the main features are secure print release system, highly developed authentication, smart routing of print jobs, mobile device-ability, which guarantees flexibility and access by distributed workforces. Centralized control and compliance monitoring help organizations to save on capital expenditure, streamline maintenance, increase scalability levels, and ensure better security. It is still facing challenges with data privacy, network latency and interoperability with legacy systems though, and it requires a strong encryption solution, redundancy plans and deployment choices on a hybrid basis. The comparative analysis of the top known solutions, namely, Microsoft Universal Print, Papercut, and PrinterLogic, reveals three different degrees of scalability, integration with the main enterprise, and compliance preparedness after Google Cloud Print was discontinued.

INTELLIGENT PRINT QUALITY CONTROL USING CNN MODELS

Vaibhav Kaushik — 2025-12-20

Controlling the quality of prints is a vital process in the current printing industries so as to maintain the quality of the mass production in terms of consistency, accuracy, and aesthetic features. The typical machine-vision systems find it difficult to detect the invisible defects like streaks, blotches, misalignment and color differences because of shortcomings of hand-made extraction of features. The proposed research is an intelligent print quality control system based on the Convolutional Neural Network (CNN) models to detect and classify defects automatically. The method starts with the generation of a set of complete dataset which consists of high-resolution images of controlled light and camera conditions. All images are annotated and labelled based on certain types of defects in order to enable supervised learning. The preprocessing of the data, such as normalization, resizing, augmentation, color enhancement, etc. are used to enhance model robustness and generalization. Various CNNs, including VGG, ResNet and MobileNet, are studied using the method of transfer learning to maximize the accuracy and performance. The CNN model created to be customized comprises of other layers as well covering localization of defect and region based detection. The real-time image capture, CNN inference and decision-making modules are incorporated into the system architecture, and executed at the edge computing devices or on the GPU, to offer them fast processing. The classification accuracy and real-time processing results suggest that the experimental results are better than the traditional vision-based systems.

AI-GENERATED PHOTOBOOKS FOR EDUCATIONAL USE

Fehmina Khalique — 2025-12-20

The fast development of artificial intelligence has created new opportunities in the creation of educational materials, previously, the so-called AI-based photobooks to learn visually. This paper will look into the creation, application, and instructional worth of AI-created photobooks on various education levels. Based on the existing models of visual cognition and multimedia education, the study seeks to understand how visual images and layouts created by AI could contribute to student engagement, understanding, and memorization. It employed a mixed-methods research design, which became a combination of surveys, controlled experiments, and qualitative analysis of photobook samples to determine the reactions and usability of learners. Students and teachers of primary, secondary, and higher educational establishments were randomly chosen to participate in this study with the help of purposeful and stratified sampling. The paper defines the technological process of creating AI-generated photobooks, including prompt engineering, image-generating applications, content selection guidelines, and layout designing plans in accordance with the educational requirements. It also breaks down the ways such photobooks could be used in various subject areas like science, history, and language learning and demonstrates that differentiated instruction can be achieved with the application of customizable visual materials. The benefits of AI-generated content in terms of accessibility are specifically highlighted, specifically by the students with visual, cognitive, or linguistic impairments.

SMART CONTRACTS FOR AI-GENERATED ART RIGHTS

C Komalavalli — 2025-12-20

The swift AI-generated art development has further fueled the discussion on both authorship and ownership, as well as on whether digital rights can be enforced. The existing intellectual property paradigms lack the ability to recognise works produced by autonomous systems fully or in part, which presents proxies in the maintenance of copyright, derivatives and cross-jurisdictional identification of AI-related rights. With more and more creative outputs based on algorithmic processes, there is an urgent requirement to have transparent, tamper-resistant processes that would be able to define, assign and protect right at scale. One of the promising infrastructures to facilitate legal and economic aspects of AI-generated art is the use of smart contracts, which are the self-executable agreements that run on blockchain networks. This paper discusses how authorship claims can be encoded in smart contracts, how royalty payments can be automated, and how programmable access controls can be offered, at the same time, offering verifiable provenance by tokenizing the provenance. We analyze technical specifications of creating powerful metadata standards to cover creation parameters, level of contributions, and model lineage. Moreover, we discuss interoperability issues in the heterogeneous blockchains and digital marketplaces, which are limited to the immutability, upgradability, and long-term security. In addition to the technical design, the paper evaluates the ethical impact, such as the fairness to human designers, responsible design of AI innovators, and risks to society in general of bias, exploitation, and its unequal distribution of rights-management systems.

VIRTUAL ART SPACES AND MACHINE LEARNING CURATION

Poonam Kumari — 2025-12-20

With the development of machine learning (ML), the concept of virtual space in art is becoming a reality, and it is changing the established curatorial procedures and altering the ways in which audiences experience art. This paper explores the dynamic overlap between ML-driven systems and immersive digital spaces to know how curatorial decision-making, experience of audiences, and interpretation of art is being redefined. The study presents findings of virtual galleries, online archives and interactive display sites based on qualitative and quantitative approaches to assessing how algorithms predict, classify and even create visual artworks. Specific focus is made on the recommendation engines, neural models of style analysis, and generative networks that help to come up with new forms of curators. Simultaneously, the paper examines virtual and augmented reality (VR/AR) as experiential models with a particular focus on how the designs of immersivity, interactivity, and international openness broaden the curatorial practice. These virtual spaces give the viewer a chance to engage more, allowing them to create their own paths in collections of art and disrupting traditional ideas of authorship and originality as well as interpretive power.