Affective Scaffolding in Creative Learning: The Vivience Framework for Empathic Digital Humans as Collaborative Partners
DOI:
https://doi.org/10.63084/cognexus.v2i2.266Keywords:
human-AI interaction, creative learning, Affective-Emotive Resonance, relational AI, affective scaffoldingAbstract
Generative artificial intelligence (GenAI) is increasingly used as a dialogic partner in creative learning, raising a question not captured by accuracy-centred evaluation alone: how might relational and affective qualities of AI interaction influence willingness to expose uncertainty, accept critique, revise work, and take creative risks? This conceptual paper advances the Vivience Framework for Affective Scaffolding, extending the Affective-Emotive Resonance (AER) model introduced in prior exploratory research. It integrates Vygotskian scaffolding, Self- Determination Theory, Control-Value Theory, Cognitive Load Theory, social-response research, and polyphonic approaches to creative learning. Two propositions are formalised. Affective Load is defined for prospective testing as task-irrelevant cognitive demand associated with regulating achievement-related affect and AI-mediated interactional uncertainty, while acknowledging prior uses of the term. The Neutrality Trap Hypothesis proposes that affectively sparse responses may, in some high-vulnerability contexts, be interpreted as indifference or implicit evaluation. The paper differentiates four AER dimensions, Persistence, Belonging, Continuity, and Layered Emotional Care, and presents a system-level architecture separating the base language model from memory, inference, pedagogical-state estimation, relational policy, generation, multimodal expression, and governance. Finally, the Vivience Protocol is proposed as a preregistrable mixed-methods design for empirical testing. The contribution is a falsifiable research programme for responsible relational AI in creative learning, not a claim that machine empathy or educational benefit has already been demonstrated.
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