---
language:
- fr
- ar
license: cc-by-nc-4.0
task_categories:
- text-retrieval
- text-classification
pretty_name: PhonEx - French Phonics Exercise Corpus for Dyslexia
size_categories:
- n<1K
tags:
- dyslexia
- phonics
- French
- children
- reading difficulties
- educational NLP
- retrieval
- CASS
- Moroccan French
- special education
---

# PhonEx — French Phonics Exercise Corpus for Dyslexia

## Dataset Description

**PhonEx** is a structured corpus of French-language phonics exercises for children aged 6–9 with reading difficulties including dyslexia, annotated for phonological difficulty level and primary error type. It is designed for constraint-aware exercise retrieval — matching a parent's or teacher's free-text description of a child's reading difficulty to the most appropriate remediation exercise.

The corpus supports the **CASS (Context-Aware Semantic Similarity)** framework — a lightweight safety-aware retrieval system that prevents pedagogically dangerous mismatches (e.g. assigning a difficulty-level-5 paragraph exercise to a child at difficulty level 1).

- **Paper:** *CASS: A Context-Aware Semantic Similarity Framework for Safe Retrieval in Child-Facing Educational Applications* (Sadouk and Gadi)
- **GitHub:** [https://github.com/lsadouk/CASS](https://github.com/lsadouk/CASS)
- **Application:** Lecture Magique — French phonics learning app for dyslexic children
- **Target curriculum:** Moroccan primary school CP–CE1 (ages 6–9)

---

## Dataset Summary

| Property | Value |
|---|---|
| Total entries | 100 |
| Error types | 5 |
| Difficulty levels | 1–5 |
| Balance | 4 entries per error type × difficulty combination (perfectly balanced) |
| Age groups | CP (6–7), CE1 (7–8), CE2 (8–9) |
| Language | French |
| License | CC BY-NC 4.0 |

---

## Supported Tasks

- **Exercise retrieval** — match a parent/teacher's free-text description of reading difficulty to the most appropriate phonics exercise
- **Difficulty classification** — predict phonological difficulty level from exercise description
- **Error type classification** — predict error type from exercise description or parent query

---

## Dataset Structure

### Fields

| Field | Type | Description |
|---|---|---|
| `id` | string | Unique identifier e.g. `ex_vc_003` |
| `ERR_TYPE` | string | Primary error type targeted (see taxonomy below) |
| `DIFF` | int | Phonological difficulty 1–5 |
| `AGE_GROUP` | int | Target age group: 1=CP/6-7, 2=CE1/7-8, 3=CE2/8-9 |
| `description` | string | 2–4 sentence English description of the exercise |
| `child_instruction` | string | Simplified French instruction shown to the child |
| `ERR_SECONDARY` | string or null | Secondary error type if applicable |
| `language` | string | `fr` |
| `target_population` | string | `children_with_dyslexia_age_6_9` |
| `annotator_agreed` | bool | Annotation confirmed by domain reviewer |
| `version` | string | Corpus version |

### Error Type Taxonomy

| ERR_TYPE | Description | Count |
|---|---|---|
| `visual_confusion` | Confusion between visually similar letters (b/d, p/q, m/n) | 20 |
| `vowel_substitution` | Substitution of vowel sounds (o→ou, eu→ou, an→en) | 20 |
| `syllable_omission` | Omission or addition of syllables in words | 20 |
| `letter_reversal` | Reversal or transposition of letter order within words | 20 |
| `blending_difficulty` | Difficulty blending phonemes into syllables or words | 20 |

### Difficulty Distribution

| DIFF | Description | Count |
|---|---|---|
| 1 | Isolated letters or simple CV syllables | 20 |
| 2 | Simple CVC words and two-syllable words | 20 |
| 3 | Two-syllable words in sentences, short texts | 20 |
| 4 | Sentences, reading aloud, connected text | 20 |
| 5 | Paragraphs, fluency, academic vocabulary | 20 |

---

## Example Entries

```json
{
  "id": "ex_vc_001",
  "ERR_TYPE": "visual_confusion",
  "DIFF": 1,
  "AGE_GROUP": 1,
  "description": "The child confuses the letters b and d when reading
    simple CVC words like 'bal' and 'dal'. The exercise shows large
    isolated letters b and d side by side and asks the child to point
    to the correct one when the teacher says the sound. Visual cues
    and colour coding help distinguish the two letters.",
  "child_instruction": "Regarde les lettres. Montre-moi la lettre 'b'.",
  "ERR_SECONDARY": null,
  "language": "fr",
  "target_population": "children_with_dyslexia_age_6_9",
  "annotator_agreed": true,
  "version": "1.0"
}
```

```json
{
  "id": "ex_bd_009",
  "ERR_TYPE": "blending_difficulty",
  "DIFF": 5,
  "AGE_GROUP": 3,
  "description": "Severe blending difficulty at sentence level — the
    child loses sentence meaning while decoding individual words,
    reading in a slow monotone that prevents comprehension. Exercise
    uses prosodic reading support — stress marks, rhythm bars, and
    pause symbols are printed above the text.",
  "child_instruction": "Suis les marques au-dessus du texte: accent fort,
    barre de rythme, pause. Lis avec la mélodie.",
  "ERR_SECONDARY": null,
  "language": "fr",
  "target_population": "children_with_dyslexia_age_6_9",
  "annotator_agreed": true,
  "version": "1.0"
}
```

---

## Usage

```python
from datasets import load_dataset

ds = load_dataset("lamyaa/PhonEx")

# All entries
print(f"Total entries: {len(ds['train'])}")

# Filter by error type
visual = [e for e in ds['train'] if e['ERR_TYPE'] == 'visual_confusion']
blending = [e for e in ds['train'] if e['ERR_TYPE'] == 'blending_difficulty']

# Filter by difficulty level
beginners = [e for e in ds['train'] if e['DIFF'] == 1]
advanced  = [e for e in ds['train'] if e['DIFF'] == 5]

# Filter by age group
cp_level = [e for e in ds['train'] if e['AGE_GROUP'] == 1]
```

### Use with CASS retrieval

```python
# See full code in: https://github.com/lsadouk/CASS

# English description
retrieve_phonex("My child confuses b and d when reading simple words")
# → ex_vc_003 (visual_confusion, DIFF=2)

# French description
retrieve_phonex("Elle saute des syllabes dans les mots longs")
# → ex_so_006 (syllable_omission, DIFF=3)

# Moroccan Darija
retrieve_phonex("Weldi ma iqrach mezyan, kayqra harf harf")
# → ex_bd_001 (blending_difficulty, DIFF=1)
```

---

## Safety Properties

PhonEx is designed with pedagogical safety in mind. The DIFF and ERR_TYPE annotations enable the CASS framework to prevent dangerous mismatches:

- A child at DIFF=1 (isolated letters) will **never** receive a DIFF=5 exercise (paragraph fluency) — which would cause immediate failure and frustration
- An exercise targeting `visual_confusion` will **never** be retrieved for a child with `syllable_omission` — providing zero therapeutic benefit
- Safety filtering is automatic — no teacher or parent configuration required

Across 6 diagnostic queries:
- **C_DIFF** (difficulty): 13 dangerous entries suppressed, mean rank drop **25.3 positions**, max **69 positions**
- **C_ERR** (error type): 15 dangerous entries suppressed, mean rank drop **55.7 positions**, max **78 positions**

---

## Annotation Guidelines

**DIFF scale:**
- DIFF=1: Isolated letter or phoneme recognition, single sound discrimination
- DIFF=2: Simple CVC words, two-syllable words in isolation
- DIFF=3: Words in sentences, short connected text, specific error patterns
- DIFF=4: Reading aloud in connected text, under time or social pressure
- DIFF=5: Extended paragraphs, fluency, academic vocabulary, multiple simultaneous errors

**ERR_TYPE selection:**
Each exercise targets one primary error type. Exercises with meaningful secondary error involvement include an `ERR_SECONDARY` field. The five error types are mutually exclusive as primary categories but share some underlying phonological mechanisms — used in the CASS C_ERR partial overlap scoring (score 0.5 for related types, 0.0 for unrelated).

**Partial overlap pairs:**
- `visual_confusion` ↔ `letter_reversal` (both involve letter-level processing)
- `blending_difficulty` ↔ `syllable_omission` (both involve syllable-level processing)
- `blending_difficulty` ↔ `vowel_substitution` (both involve phoneme-grapheme mapping)

---

## Citation

```bibtex
@article{sadouk2025cass,
  title     = {CASS: A Context-Aware Semantic Similarity Framework
               for Safe Retrieval in Child-Facing Educational Applications},
  author    = {Sadouk, Lamyaa},
  journal   = {Education and Information Technologies},
  year      = {2025},
  publisher = {Springer}
}
```

---

## Dataset Card Authors

**Lamyaa Sadouk**
Ecole Marocaine des Sciences de l'Ingénieur, Casablanca, Morocco

**Taoufiq Gadi**
Laboratoire de Recherche en Mathématique, Informatique et Sciences de l'Ingénieur (MISI), Morocco

## License

[CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) — Attribution-NonCommercial 4.0 International

You may use and share this dataset for research and educational purposes with attribution. Commercial use is not permitted without explicit permission from the author.