Building Mental Resilience Through Psychology Literacy
Note on naming:
This project was originally developed under the name MindMaster.
It has since been renamed PowerMind to reflect its focus on building mental resilience through psychology literacy, strengthening learners’ confidence, self-efficacy, and independence by helping them understand how their minds work.
You may see both names used in this repository; they refer to the same project.
MindMaster is an EdTech platform that teaches psychology literacy to primary students, helping them understand how the mind works and how thoughts, feelings, and actions connect. By turning knowledge into self-efficacy, MindMaster builds lasting mental resilience and everyday problem-solving ability.
Unlike typical SEL programmes that focus mainly on coping skills, MindMaster treats psychology as a science subject that children can learn, apply, and master. Its pedagogy follows a consistent Explore → Practise → Reflect learning arc, moving students from knowledge to self-understanding, self-efficacy, and mental resilience.
This repository brings together the curriculum framework, Alpha-stage prototype, and submission materials for the UNICEF Venture Fund 2025 (Stage 2 RFP).
This repository is organised so that the content-design/ and software-design/ folders contain the active, evolving work of PowerMind, including the development of the core curriculum, learning design, system architecture, and playable prototypes.
| Folder | Purpose |
|---|---|
| content-design/ | Full psychology literacy curriculum and learning design materials, including grade-level scope and sequence, unit structures, learning outcomes, and pedagogical rationale. |
| software-design/ | Technical architecture, navigation standards, and Alpha-stage prototype files, including playable HTML prototypes demonstrating the Explore → Practise → Reflect learning flow. |
| unicef-venture-fund-2025-submission/ | Archived documentation from the UNICEF Venture Fund Stage 1 (EOI), retained for reference and transparency. |
MindMaster integrates three complementary AI systems designed to enhance engagement, feedback, and personalised support while keeping all learners aligned to the same standardised curriculum:
Mimi (Learning Buddy Chatbot):
A context-aware conversational companion that guides learners across all stations — from Lesson Summary to Reflection — while maintaining motivation and curiosity. Mimi also functions as a Psychology Encyclopedia, allowing free-form Q&A within safe, knowledge-bound parameters.
She does not deliver formal lessons but connects, encourages, and orients learners throughout their journey, nurturing curiosity and self-efficacy.
Rabbit Tutor Avatar:
A warm, teacher-like instructional persona who delivers standardised lesson content and appears consistently in both Lesson Summaries and adaptive revision sessions.
The Rabbit models expertise and curiosity, providing instructional stability and emotional reassurance.
ALT (Adaptive Learning Tool):
The AI engine that provides targeted reinforcement and revision. ALT analyses each learner’s performance data to adapt the pathway of instruction and practice — pacing, scaffolding, and activity type — while keeping the curriculum and learning goals fixed.
This reflects MindMaster’s pedagogical philosophy: the pedagogy is personalised, but the curriculum remains standardised. Every child learns the same psychology concepts and achieves the same defined outcomes, but the journey can differ based on how they learn best.
ALT’s adaptive cycles include concise instructional recaps, tailored practice, and reflective prompts that build mastery and confidence.
Together, these AI components ensure consistency in what students learn while intelligently adapting how they learn, practise, and consolidate understanding.
MindMaster’s learning design is grounded in three principles:
PWA implementation for Android (Unit 01 reference build):
Converting the existing web prototype into a Progressive Web App, using Unit 01 as the reference implementation. This establishes deployment, navigation, and device-integration patterns required to scale reliably across all 10 units.
AI interaction prototyping within Unit 01:
Integrating early-stage AI behaviours into selected screens and games in Unit 01, including lesson summaries, guided practice, and reflection prompts. This phase validates how AI-supported guidance and adaptive feedback can be embedded consistently before scaling to the full curriculum.
Curriculum-wide lesson plan review for reflection and summary design:
Reviewing lesson plans across all units to finalise pedagogical requirements for lesson summary screens and home reflection screens, ensuring cognitive alignment, consistency, and readiness for full product development.
The Beta prototype will integrate the three AI components into a unified, data-driven learning experience:
MIT License © 2025 EdSol Technology (Thailand) Co., Ltd.