AI for Arts Educators

AI for Arts Education was an intensive 2.5-hour workshop facilitated for the Arts Department faculty at Shiv Nadar School, Faridabad, exploring how artificial intelligence can be meaningfully integrated into arts education. The workshop brought together educators working across theatre, music, dance and visual arts to examine both the practical possibilities and the pedagogical questions emerging from the rapid development of generative AI.

Facilitated by Gaurav Singh Nijjer, the workshop began from the premise that introducing AI into arts education should not be about replacing artistic thinking or making creative work faster. Instead, AI can become a tool through which students are encouraged to experiment, compare, question, reflect and develop a deeper understanding of artistic processes. The session therefore focused on maintaining a balance between technological experimentation and human creativity, judgement and critical engagement.

A central component of the workshop was the introduction of four pedagogical frameworks for working with AI in arts classrooms: Enhancing with AI, Creating with AI, Comparing with AI and Evaluating with AI. These frameworks provided educators with different ways of positioning AI within an existing lesson, depending on whether the objective was to extend an idea, generate material collaboratively, examine artistic choices or develop critical reflection and assessment.

Under Enhancing with AI, participants explored how AI could scaffold and extend students' existing ideas without taking over the creative process. AI can be used to help students develop possibilities, ask questions, generate alternatives or overcome moments where they feel creatively stuck, while retaining the student's original intention as the starting point.

Creating with AI focused on co-creation and prompt engineering. Educators experimented with ways of constructing prompts and using generative systems as creative collaborators. Activities included transforming Shakespearean scenes into different theatrical or stylistic contexts and exploring how changing the parameters of a prompt can alter the resulting material.

Comparing with AI positioned AI-generated material alongside human-created work. Through comparison, educators explored questions of style, structure, composition and artistic decision-making. This approach allows students to examine not simply whether an AI-generated output is "good" or "bad", but what specific choices distinguish it from a student's own artistic work and what those differences reveal about artistic intention.

Finally, Evaluating with AI explored how AI could support feedback, reflection and self-assessment. Participants considered ways in which AI could be incorporated into assessment processes while maintaining the educator's judgement and the student's responsibility for their own work. The session also considered applications such as rubric development, grading support and generating differentiated learning materials for students with different needs.

The practical exercises were designed to move between different art forms. Participants explored possibilities such as rewriting Shakespearean scenes in absurdist styles, generating prompts for choreography and comparing AI-generated visual material with original student artwork. These exercises demonstrated that the pedagogical possibilities of AI differ significantly depending on the artistic discipline, while also revealing common questions around authorship, originality, interpretation and creative agency.

The workshop also addressed applications beyond direct artistic creation. Educators explored how AI could assist with lesson planning, rubric design, grading support and differentiated content, allowing teachers to consider AI as part of the wider pedagogical infrastructure of an arts classroom. The emphasis throughout was on using these capabilities intentionally, with educators remaining responsible for the learning objectives, context and quality of the material being presented to students.

A recurring concern throughout the session was critical distance. The workshop encouraged educators to create situations in which students could question AI outputs rather than accepting them as authoritative. This included examining bias, identifying limitations, comparing generated material with human work and reflecting on what happens when artistic decisions are delegated to computational systems.

The workshop formed part of Kaivalya Plays' wider exploration of the relationship between technology, artistic practice and education. It builds on Gaurav Singh Nijjer's research and practice in creative technology, including his work as a German Chancellor Fellow with Rimini Protokoll, his Parivartan Artistic Research grant investigating AI in Indian Theatre, and his ongoing engagement with international creative technology practices.

The session ultimately approached AI not as a substitute for human creativity, but as a material for experimentation and critical inquiry. By giving educators practical frameworks for introducing AI into different stages of the artistic learning process, the workshop aimed to help them develop classrooms in which students can use emerging technologies while remaining attentive to questions of authorship, ethics, artistic choice and human agency.