GPT Tasks

🤖 GPT Tasks: Role-Play Avatars for Dynamic Human–AI Collaboration

In Classlet, GPT-powered avatars are more than automated response agents—they are configured role-play partners embedded within immersive or desktop learning tasks. These avatars are designed to simulate real-world roles, such as mentors, clients, peers, or assessors, with controlled behavioral logic. Through carefully authored prompts and response settings, they enable rich, responsive, and contextually grounded learning experiences.

A GPT avatar interaction involves the learner engaging in dialogue with an AI-powered character configured using GPT. The student types input, and the avatar responds based on preconfigured prompts that define its personality, knowledge scope, and conversational style. This setup allows for dynamic, contextual exchanges—ranging from informational to reflective—depending on the instructional goal. This is an avatar in Singapore Institute of Technology, for learning consumer behavior (Tourism) while brainstorming with a 'Professor AI avatar'.

---

🎭 Avatar Configuration: Operational Overview

Each GPT avatar in Classlet is initialized with a “Background” prompt that defines its identity, tone, and role—for example, a clinical supervisor, a supportive peer, or a curious museum visitor. Developers or teachers also specify Response Behavior Instructions, determining how the avatar should reply based on learner input.

For more advanced avatars, Classlet supports Retrieval-Augmented Generation (RAG). Educators can upload structured materials—PDFs, flowcharts, or scenario rules—that condition the avatar’s logic. For instance, a PDF containing procedural steps or branching decisions enables the GPT avatar to reference specific phases and adjust dynamically, aligning its behavior with the intended pedagogical script.

Critically, designers can also define the interaction cadence—that is, how many times the avatar should speak, when it should defer, or whether it loops with a scaffolded hint or reinforcement.

---

📚 Pedagogical Rationale: Theories Behind the Design

From a pedagogical standpoint, GPT avatars in Classlet operationalize Human–AI Collaborative Learning, drawing on principles from social constructivism, dialogic pedagogy, and formative scaffolding.

1. Dialogic Learning and Knowledge Co-Construction

Building on Mercer and Howe’s (2012) dialogic teaching framework, GPT avatars engage learners in structured conversations that foster reasoning and exploration. Whether the avatar is giving feedback, prompting reflection, or playing a character, it is designed to stimulate active participation rather than passive reception (Wegerif, 2007). By holding space for the learner to articulate, revise, or justify responses, these avatars catalyze deeper learning.

2. Scaffolding Within the Zone of Proximal Development (ZPD)

Inspired by Vygotsky (1978), avatars act as dynamic scaffolds. Through progressive questioning or gentle feedback, they help learners reach performance levels just beyond their independent ability. For instance, if a learner hesitates, the avatar might simplify the task or offer a hint. If confident, it may challenge the learner to reflect or expand.

3. Adaptive Feedback and Emotional Framing

GPT avatars are also emotional moderators. Their tone and pacing can be tuned to learner needs—encouraging, neutral, or urgent. This supports affective engagement and adaptive trust calibration, as shown in studies by Choi et al. (2025), where avatar behavior aligned to learner disposition yielded higher motivation and task completion.

---

🧠 Designing with Intention

To build a pedagogically sound GPT avatar:

1. Clarify its role: What task is it helping with—explanation, diagnosis, critique?

2. Define behavioral scope: How many utterances? When to yield? How to escalate?

3. Embed constraints: Use flowcharts, PDF steps, or guidelines for predictable outputs.

4. Balance agency: Avoid over-talking; empower learners to drive the interaction.