File size: 4,495 Bytes
24551d0 f216389 24551d0 f216389 24551d0 f216389 012f151 f216389 24551d0 f216389 24551d0 f216389 24551d0 f216389 24551d0 012f151 f216389 012f151 f216389 012f151 f216389 012f151 f216389 012f151 f216389 7938471 317c497 7938471 012f151 24551d0 012f151 317c497 7938471 012f151 24551d0 317c497 f216389 012f151 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 | ---
license: apache-2.0
tags:
- reinforcement-learning
- education
- doubt-prediction
- adaptive-learning
- multi-agent-systems
- gesture-recognition
- computer-vision
- q-learning
- grpo
- edtech
- mediapipe
- privacy
datasets:
- synthetic-learning-interactions
---
# ContextFlow: Predictive Doubt Detection in Adaptive Learning Systems
**A Research Implementation of RL-Powered Educational Technology**
| Property | Value |
|----------|-------|
| **Algorithm** | GRPO + Q-Learning |
| **State Dimension** | 64 features |
| **Action Dimension** | 10 doubt predictions |
| **Policy Version** | 50 |
| **Training Samples** | 200 |
| **Final Loss** | 0.2465 |
| **Avg Reward** | 0.75 |
## Overview
ContextFlow predicts student confusion **before** it occurs using reinforcement learning and behavioral signal analysis. When a learner's actions suggest they might be struggling (mouse hesitation, scroll reversals, help-seeking gestures), the system proactively offers assistance.
## Architecture
```
┌─────────────────────────────────────────────────┐
│ 9 Specialized Agents │
├─────────────────────────────────────────────────┤
│ • StudyOrchestrator • DoubtPredictorAgent │
│ • BehavioralAgent • HandGestureAgent │
│ • RecallAgent • KnowledgeGraphAgent │
│ • PeerLearningAgent • LLMOrchestrator │
│ • GestureActionMapper • PromptAgent │
└─────────────────────────────────────────────────┘
```
## Quick Start
```python
# Load the model
from huggingface_hub import hf_hub_download
import pickle
path = hf_hub_download(
repo_id='namish10/contextflow-rl',
filename='checkpoint.pkl'
)
with open(path, 'rb') as f:
checkpoint = pickle.load(f)
print(f"Policy version: {checkpoint.policy_version}")
print(f"Training samples: {checkpoint.training_stats['total_samples']}")
```
## State Vector (64 dimensions)
| Component | Dims | Description |
|-----------|------|-------------|
| Topic Embedding | 32 | TF-IDF of learning topic |
| Progress | 1 | Session progress (0.0-1.0) |
| Confusion Signals | 16 | Behavioral indicators |
| Gesture Signals | 14 | Hand gesture frequencies |
| Time Spent | 1 | Normalized session time |
## Actions (10 doubt predictions)
1. `what_is_backpropagation`
2. `why_gradient_descent`
3. `how_overfitting_works`
4. `explain_regularization`
5. `what_loss_function`
6. `how_optimization_works`
7. `explain_learning_rate`
8. `what_regularization`
9. `how_batch_norm_works`
10. `explain_softmax`
## Training Results
| Epoch | Loss | Epsilon | Avg Reward |
|-------|------|---------|------------|
| 1 | 1.2456 | 1.000 | 0.20 |
| 2 | 0.8923 | 0.995 | 0.35 |
| 3 | 0.6541 | 0.990 | 0.48 |
| 4 | 0.4127 | 0.985 | 0.62 |
| 5 | 0.2465 | 0.980 | 0.75 |
## Key Features
- **Predictive Detection**: RL-based confusion prediction before it happens
- **Multi-Agent Orchestration**: 9 specialized agents working together
- **Gesture Recognition**: Privacy-first hand gesture detection with MediaPipe
- **Face Blurring**: Real-time face blur for classroom deployment
- **Browser AI Launch**: Direct AI chat interface from predicted doubts
- **Spaced Repetition**: SM-2 based review scheduling
- **Knowledge Graphs**: Concept mapping and learning paths
## Files
| File | Description |
|------|-------------|
| `checkpoint.pkl` | Trained Q-network weights |
| `train_rl.py` | Training script with GRPO |
| `feature_extractor.py` | 64-dim state extraction |
| `inference_example.py` | Usage examples |
| `demo.ipynb` | Interactive notebook |
| `RESEARCH_PAPER.md` | Full research paper |
| `evaluation_results.json` | Training metrics |
| `requirements.txt` | Dependencies |
| `app/` | Backend agents (Flask API) |
| `frontend/` | React frontend |
## Evaluation
See [EVALUATION.md](EVALUATION.md) for detailed metrics and production readiness assessment.
## Citation
```bibtex
@software{contextflow,
title={ContextFlow: Predictive Doubt Detection in Adaptive Learning Systems},
author={ContextFlow Team},
year={2026},
version={1.0},
url={https://huggingface.co/namish10/contextflow-rl}
}
```
|