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The EMO-AI Teaching Loop A Neurodidactic Microlearning Approach Using WhatsApp and Generative AI Prompts for Teacher Engagement

Fabiano Rodrigues de Souza (first author), Denise da Vinha Ricieri, Rafaela V. G. Barreto, Adriana M. G. de Farias  ·  X Inovacoes Curriculares 2025 (UNICAMP) — Online Presentation, May 2025  ·  Peer-reviewed conference paper

Abstract

This study examines how a neurodidactic microlearning intervention delivered via WhatsApp — combining Generative AI prompts with emotional engagement strategies — affects teacher learning outcomes. Two AI-generated prompts (GenAI Personalization and Ikigai) were deployed in a WhatsApp group spanning multiple time zones (USA and several Brazilian states). Qualitative data (text plus emoji reactions) were converted to quantitative sentiment analysis, revealing a correlation of 1.0. Results demonstrate that short, emotionally anchored interactions drive authentic enthusiasm, curiosity, and immediate intent to apply new knowledge.

Key Findings

  • 21% enthusiasm rate — participants reported strong personal connection to the AI-generated content.
  • 19% curiosity rate — documented desire to explore further applications.
  • Immediate classroom transfer — participants began building lesson plans during the session.
  • Emoji-to-sentiment correlation = 1.0 — qualitative and quantitative signals fully aligned.
  • Cross-timezone delivery — asynchronous session across USA and multiple Brazilian states, approx. 1.5 to 4 hours.
  • Replicable model — the EMO-AI loop can be adapted to other chat platforms beyond WhatsApp.

Method Design

  • Platform: WhatsApp group (asynchronous, multi-timezone)
  • Prompt 1 — GenAI Personalization: ChatGPT configured with user profile; AI generates a poster imagining the participant 50 years in the future.
  • Prompt 2 — Ikigai: Japanese concept applied to professional identity; participants reflect on purpose-driven teaching.
  • Data: Text messages plus emoji reactions converted via sentiment analysis.
  • Theory: Instructional Design, Andragogy, Neurodidactics, Microlearning, Self-Determination Theory.

Presentation Recordings (UNICAMP X Inovacoes Curriculares 2025)

Part 1 — WhatsApp screen, GenAI personalization prompt, Ikigai technique, outcomes (starts at 1:42):
https://www.youtube.com/watch?v=NWPI6LjiSiM&t=102s

Part 2 — Full presentation: EMO-AI loop, neurodidactics, Figure 3 correlation, replicability (starts at 0:57):
https://www.youtube.com/watch?v=_ulw3WDSQYs&t=57s

Technical Concepts and Skills

Learning Design: Neurodidactics Microlearning Instructional Design Andragogy Self-Determination Theory Emotional Engagement
AI & Technology: Generative AI Prompt Engineering ChatGPT Configuration GenAI Personalization WhatsApp as LMS
Research Methods: Sentiment Analysis Emoji Analytics Mixed Methods Ikigai Cross-timezone Research Action Research

Certificates of Presentation

References

Author Bio

Fabiano Rodrigues de Souza — PhD in Biotechnology · Harvard Graduate School of Education · Dual MBAs · Kirkpatrick Certified Professional · 2x Braskem Award Winner · Editorial Board Member since 2006. Researcher at the intersection of neuroscience, AI, and education.

See also — Paper 1: Simulating Dialogues and Characters in ChatGPT-4 (CoBICET 2023) — multilingual GPT-4 evaluation: English vs. Portuguese output quality, bias taxonomy, prompt engineering.
See also — Paper 3: PROMPT-EDU (SCIAS Educação, Comunicação e Tecnologia 2024) — structured fine-tuning command script for ChatGPT in educational contexts; Bloom’s Taxonomy prompts; tested Brazil & USA.
de Souza et al. (2025) — EMO-AI Teaching Loop — UNICAMP X Inovacoes Curriculares 2025 Versao em Portugues