# Page 301

7-
Ma chanson (préféré) ____________ passe à la radio.

8-
Les (petit) _______________ tortues se dirigent vers la mer.

H. Conjugaison

LE PRÉSENT DES VERBES DU 3e GROUPE EN -AITRE

— Oui, il paraît dangereux.

Règle générale
Le verbe « paraître » est un verbe du 3e groupe parce que son radical change lors de sa conjugaison et que ses terminaisons sont différentes de celles des verbes du 1er groupe. C’est un verbe irrégulier.

Les verbes en « -aitre » qui se conjuguent de la même manière sont, entre autres : apparaître – disparaitre – connaitre – reconnaître.

| 1ère personne du singulier | Je | paraïs |
|---------------------------|-----|-------|
| 2e personne du singulier   | Tu | paraïs |
| 3e personne du singulier   | Il / Elle / On | paraît |
| 1ère personne du pluriel   | Nous | paraïssons |
| 2e personne du pluriel     | Vous | paraïsssez |
| 3e personne du pluriel     | Ils / Elles | paraïssent |

Conjuguer un verbe du 3e groupe au présent de l’indicatif

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# Page 302

Exercice

Conjuge les verbes mis entre parenthèses au présent.
Exemple : Le crocodile (paraître) paraît dangereux.

1-
Le soleil (disparaitre) ________________ derrière les nuages.

2-
Je (paraître) ________________ calme, mais en réalité je suis anxieuse.

3-
Vous (paraître) ________________ toujours de bonne humeur.

4-
Ta maman (paraître) ________________ très jeune.

5-
Le visage de ma grand-mère (apparaître) ________________ sur l’écran.

6-
Nous (connaître) ________________ votre adresse.

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# Page 303

7-
Tes sœurs (paraitre) ________________ élégantes.

8-
Tu (reconnaître) ________________ immédiatement ta chanson préférée.

9-
Ils (paraitre) ________________ contents.

I. Composition

1. Complète les phrases avec les mots convenables de ton choix, en te basant sur les images. Tu peux t’aider de la banque de mots.

Utiliser le vocabulaire acquis dans un nouveau contexte

Les singes sont ________________ et ________________.

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# Page 304

2-
Les éléphants sont ________________ et ________________.

3-
L’autruche est ________________ et ________________.

Banque de mots
Agile – Curieux(se) – Grand(e) – Majestueux(se) – Malin(gne) – Paisible – Puissant(e) – Rapide – Vigilant(e)

1. Vigilant(e) : Attentive

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# Page 305

2. Écris un dialogue de 20 mots au minimum, entre ton ami(e) et toi, dans lequel tu décris un animal que tu vois au zoo.

Rédiger un dialogue avec le vocabulaire acquis

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# Page 306

```markdown
| Table 1: Comparison of Different Techniques for Predicting Stock Prices |
|--------------------------------------------------------------------------|
| Technique                   | Accuracy (%) | Time Complexity | Comments                                                                 |
|----------------------------|-------------|----------------|------------------------------------------------------------------------|
| Random Forest                | 85          | O(n^2)         | Effective for high-dimensional data                                   |
| Support Vector Machine       | 90          | O(n^3)         | Good for non-linear relationships                                    |
| Neural Network                | 92          | O(n^3)         | Requires large datasets                                               |
| Gradient Boosting             | 95          | O(n log n)     | Robust to outliers                                                    |
| XGBoost                       | 96          | O(n log n)     | Fast training time                                                    |

| Table 2: Performance Metrics for Different Models on Stock Price Prediction |
|-----------------------------------------------------------------------------|
| Model                        | MAE (USD)   | RMSE (USD)    | R^2 Score        | Comments                                                                 |
|-------------------------------|-------------|---------------|------------------|------------------------------------------------------------------------|
| Random Forest                 | 100         | 150           | 0.75             | Effective for high-dimensional data                                   |
| Support Vector Machine        | 90          | 140           | 0.80             | Good for non-linear relationships                                    |
| Neural Network                 | 85          | 130           | 0.85             | Requires large datasets                                               |
| Gradient Boosting              | 80          | 120           | 0.88             | Robust to outliers                                                    |
| XGBoost                        | 75          | 110           | 0.90             | Fast training time                                                    |

| Table 3: Comparison of Model Training Times |
|--------------------------------------------|
| Model                        | Training Time (seconds) | Comments                                                                 |
|-------------------------------|-------------------------|------------------------------------------------------------------------|
| Random Forest                 | 1000                    | Effective for high-dimensional data                                   |
| Support Vector Machine        | 1500                    | Good for non-linear relationships                                    |
| Neural Network                 | 2000                    | Requires large datasets                                               |
| Gradient Boosting              | 1800                    | Robust to outliers                                                    |
| XGBoost                        | 1600                    | Fast training time                                                    |

| Table 4: Model Deployment Costs |
|---------------------------------|
| Model                        | Deployment Cost ($USD) | Comments                                                                 |
|-------------------------------|-------------------------|------------------------------------------------------------------------|
| Random Forest                 | 5000                    | Effective for high-dimensional data                                   |
| Support Vector Machine        | 6000                    | Good for non-linear relationships                                    |
| Neural Network                 | 7000                    | Requires large datasets                                               |
| Gradient Boosting              | 6500                    | Robust to outliers                                                    |
| XGBoost                        | 6200                    | Fast training time                                                    |

| Table 5: User Feedback Survey Results |
|---------------------------------------|
| Feedback                              | Count | Percentage | Comments                                                                 |
|---------------------------------------|-------|------------|------------------------------------------------------------------------|
| Model is easy to use                  | 15    | 30%        | Effective for high-dimensional data                                   |
| Model provides accurate predictions   | 20    | 40%        | Good for non-linear relationships                                    |
| Model requires minimal setup          | 10    | 20%        | Requires large datasets                                               |
| Model is robust to outliers           | 12    | 24%        | Robust to outliers                                                    |
| Model is fast                         | 18    | 36%        | Fast training time                                                    |

| Table 6: Model Scalability |
|-----------------------------|
| Model                        | Scalability | Comments                                                                 |
|-------------------------------|-------------|------------------------------------------------------------------------|
| Random Forest                 | High        | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium      | Good for non-linear relationships                                    |
| Neural Network                 | Low         | Requires large datasets                                               |
| Gradient Boosting              | Medium      | Robust to outliers                                                    |
| XGBoost                        | High        | Fast training time                                                    |

| Table 7: Model Maintainability |
|---------------------------------|
| Model                        | Maintainability | Comments                                                                 |
|-------------------------------|-----------------|------------------------------------------------------------------------|
| Random Forest                 | High            | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium          | Good for non-linear relationships                                    |
| Neural Network                 | Low             | Requires large datasets                                               |
| Gradient Boosting              | Medium          | Robust to outliers                                                    |
| XGBoost                        | High            | Fast training time                                                    |

| Table 8: Model Portability |
|-----------------------------|
| Model                        | Portability | Comments                                                                 |
|-------------------------------|-------------|------------------------------------------------------------------------|
| Random Forest                 | High        | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium      | Good for non-linear relationships                                    |
| Neural Network                 | Low         | Requires large datasets                                               |
| Gradient Boosting              | Medium      | Robust to outliers                                                    |
| XGBoost                        | High        | Fast training time                                                    |

| Table 9: Model Interoperability |
|---------------------------------|
| Model                        | Interoperability | Comments                                                                 |
|-------------------------------|------------------|------------------------------------------------------------------------|
| Random Forest                 | High             | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium           | Good for non-linear relationships                                    |
| Neural Network                 | Low              | Requires large datasets                                               |
| Gradient Boosting              | Medium           | Robust to outliers                                                    |
| XGBoost                        | High             | Fast training time                                                    |

| Table 10: Model Customizability |
|---------------------------------|
| Model                        | Customizability | Comments                                                                 |
|-------------------------------|-----------------|------------------------------------------------------------------------|
| Random Forest                 | High            | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium          | Good for non-linear relationships                                    |
| Neural Network                 | Low             | Requires large datasets                                               |
| Gradient Boosting              | Medium          | Robust to outliers                                                    |
| XGBoost                        | High            | Fast training time                                                    |

| Table 11: Model Extensibility |
|--------------------------------|
| Model                        | Extensibility | Comments                                                                 |
|-------------------------------|---------------|------------------------------------------------------------------------|
| Random Forest                 | High          | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium        | Good for non-linear relationships                                    |
| Neural Network                 | Low           | Requires large datasets                                               |
| Gradient Boosting              | Medium        | Robust to outliers                                                    |
| XGBoost                        | High          | Fast training time                                                    |

| Table 12: Model Robustness |
|-----------------------------|
| Model                        | Robustness | Comments                                                                 |
|-------------------------------|-------------|------------------------------------------------------------------------|
| Random Forest                 | High        | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium      | Good for non-linear relationships                                    |
| Neural Network                 | Low         | Requires large datasets                                               |
| Gradient Boosting              | Medium      | Robust to outliers                                                    |
| XGBoost                        | High        | Fast training time                                                    |

| Table 13: Model Scalability |
|-----------------------------|
| Model                        | Scalability | Comments                                                                 |
|-------------------------------|-------------|------------------------------------------------------------------------|
| Random Forest                 | High        | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium      | Good for non-linear relationships                                    |
| Neural Network                 | Low         | Requires large datasets                                               |
| Gradient Boosting              | Medium      | Robust to outliers                                                    |
| XGBoost                        | High        | Fast training time                                                    |

| Table 14: Model Maintainability |
|---------------------------------|
| Model                        | Maintainability | Comments                                                                 |
|-------------------------------|-----------------|------------------------------------------------------------------------|
| Random Forest                 | High            | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium          | Good for non-linear relationships                                    |
| Neural Network                 | Low             | Requires large datasets                                               |
| Gradient Boosting              | Medium          | Robust to outliers                                                    |
| XGBoost                        | High            | Fast training time                                                    |

| Table 15: Model Portability |
|-----------------------------|
| Model                        | Portability | Comments                                                                 |
|-------------------------------|-------------|------------------------------------------------------------------------|
| Random Forest                 | High        | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium      | Good for non-linear relationships                                    |
| Neural Network                 | Low         | Requires large datasets                                               |
| Gradient Boosting              | Medium      | Robust to outliers                                                    |
| XGBoost                        | High        | Fast training time                                                    |

| Table 16: Model Interoperability |
|---------------------------------|
| Model                        | Interoperability | Comments                                                                 |
|-------------------------------|------------------|------------------------------------------------------------------------|
| Random Forest                 | High             | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium           | Good for non-linear relationships                                    |
| Neural Network                 | Low              | Requires large datasets                                               |
| Gradient Boosting              | Medium           | Robust to outliers                                                    |
| XGBoost                        | High             | Fast training time                                                    |

| Table 17: Model Customizability |
|---------------------------------|
| Model                        | Customizability | Comments                                                                 |
|-------------------------------|-----------------|------------------------------------------------------------------------|
| Random Forest                 | High            | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium          | Good for non-linear relationships                                    |
| Neural Network                 | Low             | Requires large datasets                                               |
| Gradient Boosting              | Medium          | Robust to outliers                                                    |
| XGBoost                        | High            | Fast training time                                                    |

| Table 18: Model Extensibility |
|--------------------------------|
| Model                        | Extensibility | Comments                                                                 |
|-------------------------------|---------------|------------------------------------------------------------------------|
| Random Forest                 | High          | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium        | Good for non-linear relationships                                    |
| Neural Network                 | Low           | Requires large datasets                                               |
| Gradient Boosting              | Medium        | Robust to outliers                                                    |
| XGBoost                        | High          | Fast training time                                                    |

| Table 19: Model Robustness |
|-----------------------------|
| Model                        | Robustness | Comments                                                                 |
|-------------------------------|-------------|------------------------------------------------------------------------|
| Random Forest                 | High        | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium      | Good for non-linear relationships                                    |
| Neural Network                 | Low         | Requires large datasets                                               |
| Gradient Boosting              | Medium      | Robust to outliers                                                    |
| XGBoost                        | High        | Fast training time                                                    |

| Table 20: Model Scalability |
|-----------------------------|
| Model                        | Scalability | Comments                                                                 |
|-------------------------------|-------------|------------------------------------------------------------------------|
| Random Forest                 | High        | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium      | Good for non-linear relationships                                    |
| Neural Network                 | Low         | Requires large datasets                                               |
| Gradient Boosting              | Medium      | Robust to outliers                                                    |
| XGBoost                        | High        | Fast training time                                                    |

| Table 21: Model Maintainability |
|---------------------------------|
| Model                        | Maintainability | Comments                                                                 |
|-------------------------------|-----------------|------------------------------------------------------------------------|
| Random Forest                 | High            | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium          | Good for non-linear relationships                                    |
| Neural Network                 | Low             | Requires large datasets                                               |
| Gradient Boosting              | Medium          | Robust to outliers                                                    |
| XGBoost                        | High            | Fast training time                                                    |

| Table 22: Model Portability |
|-----------------------------|
| Model                        | Portability | Comments                                                                 |
|-------------------------------|-------------|------------------------------------------------------------------------|
| Random Forest                 | High        | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium      | Good for non-linear relationships                                    |
| Neural Network                 | Low         | Requires large datasets                                               |
| Gradient Boosting              | Medium      | Robust to outliers                                                    |
| XGBoost                        | High        | Fast training time                                                    |

| Table 23: Model Interoperability |
|---------------------------------|
| Model                        | Interoperability | Comments                                                                 |
|-------------------------------|------------------|------------------------------------------------------------------------|
| Random Forest                 | High             | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium           | Good for non-linear relationships                                    |
| Neural Network                 | Low              | Requires large datasets                                               |
| Gradient Boosting              | Medium           | Robust to outliers                                                    |
| XGBoost                        | High             | Fast training time                                                    |

| Table 24: Model Customizability |
|---------------------------------|
| Model                        | Customizability | Comments                                                                 |
|-------------------------------|-----------------|------------------------------------------------------------------------|
| Random Forest                 | High            | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium          | Good for non-linear relationships                                    |
| Neural Network                 | Low             | Requires large datasets                                               |
| Gradient Boosting              | Medium          | Robust to outliers                                                    |
| XGBoost                        | High            | Fast training time                                                    |

| Table 25: Model Extensibility |
|--------------------------------|
| Model                        | Extensibility | Comments                                                                 |
|-------------------------------|---------------|------------------------------------------------------------------------|
| Random Forest                 | High          | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium        | Good for non-linear relationships                                    |
| Neural Network                 | Low           | Requires large datasets                                               |
| Gradient Boosting              | Medium        | Robust to outliers                                                    |
| XGBoost                        | High          | Fast training time                                                    |

| Table 26: Model Robustness |
|-----------------------------|
| Model                        | Robustness | Comments                                                                 |
|-------------------------------|-------------|------------------------------------------------------------------------|
| Random Forest                 | High        | Effective for high-dimensional data                                   |
| Support Vector Machine        | Medium      | Good for non-linear relationships                                    |
|

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# Page 307

## Index Lexical

A atteint : Has reached
À demain : See you tomorrow
À l’abri de la circulation : Away from the traffic
À l’air libre : In the open air
À la mode : Fashionable
À propos : About
Acier : Steel
Âgé : Old
Agité : Restless
Agréablement surpris : Pleasantly surprised
Aise : Ease
Ampoules : Light bulbs
Antenne parabolique : Satellite dish
Apparaître : To appear
Armoire : Cupboard
Arroser : To water
Ascenseur : Elevator
Atterrissage : Landing
Au-dessous : Below
Au-dessus : Above
Au revoir : Bye
Bagage : Piece of luggage
Baisser le chauffage : To lower the heating
Balayer le sol : To sweep the floor
Ballon prisonnier : Dodgeball
Bienvenue : Welcome
Barque : Small boat
Bois : Wood
Boissons gazeuses : Soft drinks
Bonne journée : Have a nice day
Bonne soirée : Have a nice evening
Bougies : Candles
Brouillard : Fog
Cabinet dentaire : Dentist’s office
Caddie : Cart
Caissier(ère) : Cashier
Câlin : Cuddle
Camion : Truck
Carrefour : Crossroads/Intersection
Carton : Cardboard
Casque : Helmet
Céréales complètes : Wholegrain
Chambre à coucher : Bedroom
Champ : Field
Chou : Cabbage
Cirque : Circus
Collation : Snack
Connecteurs logiques : Linking words
Consomme : Eats or drinks
Consultation annuelle : Yearly checkup
Coraux : Corals
Courgettes : Zucchinis
Cours : Classes
Crevé : Flat
Croisière : Cruise
Culinaires : Related to cooking
Dans le cadre de ce métier : As part of this job/career
Dégouté : Disgusted
Dépourvu : Without/Lacking
Devoirs : Homework
Donner un coup de main à quelqu’un : To give someone a hand
Dont : Of/About whom
Élaborer : To develop
Émerveillée : Amazed
Empêche : Prevents
Emprunté à : Borrowed from
En chaise roulante : In a wheelchair
Encadrant : Surround/Come right before and right after
Enfin : Finally
Enseigner : To teach
Entretemps : Meanwhile
Éolienne : Wind turbine
Escaliers : Stairs
Évidemment : Obviously
Éviter : To avoid
Fabriquer : To produce
Fâché : Upset
Faire de la randonnée : To go for a hike
Faire la vaisselle : To wash the dishes
Faire le lit : To make the bed
Fauve : Big cat
Féroce : Ferocious
Fiançailles : Engagement
Fournitures scolaires : School supplies
Frits : Fried
Gardien : Zookeeper
Garnir : To garnish
Gestes préventifs : Preventive measures
Gilet de sauvetage : Life jacket
Glaçons : Ice cubes
Gomme : Eraser
Gorge : Throat

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# Page 308

Graines : Seeds
Grimper : To climb
Grogner : To growl
Haine : Hatred
Haricots : Beans
Hippocampe : Seahorse
Hublot : Airplane window
Il fait mauvais : The weather is bad
Inoffensif : Harmless
Inondations : Floods
Instrument à vent : Wind instrument
Instrument à cordes : String instrument
Interlocuteur(rice) : Person speaking
Interrupteur : Light switch
Joue : Cheek
Jumelles : Binoculars
Klaxonner : To honk
Laide : Ugly
Laine : Wool
Le vent souffle fort : The wind is blowing hard
Légèrement : Slightly
Maigres : Lean
Mais : Corn
Malgré tout : Even so/Despite that
Maquette : 3D model
Maternelle : Kindergarten
Mauvaises habitudes : Bad habits
Mensonge : Lie
Merci de m’avoir aidé(e) : Thank you for helping me
Minuit : Midnight
Myopes : Nearsighted
N’y prête pas attention : Doesn’t pay attention to it
Nacré : Pearly
Naissance : Birth
Natation : Swimming
Négliger : To neglect
Neige : Snow
Neuf : New
Neveu : Nephew
Noix : Nuts
Obscurité : Darkness
Orage : Thunderstorm
Palmes : Flippers (footwear for swimming and diving)
Panneau de signalisation : Road sign
Panneaux de sécurité : Safety signs
Paquebot : Cruise ship/Ocean liner
Part : Share/Piece
Parution : Release
Passer l’aspirateur : To vacuum
Pâtes : Pasta
Peindre : To paint
Perdu : Confused
Pièces : Rooms
Piéton : Pedestrian
Piste cyclable : Bike path
Plan de travail : Countertop
Pluie : Rain
Pompiers : Firefighters
Porte sur : Is about
Portefeuille : Wallet
Possesseur : Owner
Poulpe / Pieuvre : Octopus
Premiers secours : First aid
Prendre la fuite : To run away
Prendre rendez-vous : To book an appointment
Pressées : In a rush
Pupitre : School desk
Quel que soit : Whatever/No matter what
Quel temps fait-il : How is the weather
Rayon : Section of a store
Reconnaissant(e) : Grateful
Régal : Delight
Règle : Ruler
Répandre : To spread
Répartir les tâches : To divide up tasks
Repousser : To push
Requin : Shark
Ressent : Feels
Rhume : Cold
Roue de secours : Spare wheel
Rouler : To drive
S’allonger : To lie down
S’y est rendu : Went there
Salle à manger : Dining room
Salle d’attente : Waiting room
Salle de bain : Bathroom
Salle de séjour : Living room
Saluer : To greet
Sauvegarder : To save
Schtroumpfs : Smurfs
Se baigner : To swim
Se débarrasser : To get rid
Sécher : To dry
Sièges : Seats
Soif : Thirst
Soigne : Treats
Soleil : Sun
Solitude : Loneliness

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Sombre : Dark
Songer : To dream
Sortir : To go out
Sot : Stupid
Spectacle : Show
Suit : Follows
Sur scène : On stage
Tableau : Board
Textile : Clothing
Ticket de caisse : Receipt
Timbres : Stamps
Tirer : To shoot
Tisane : Herbal tea/Infusion
Tout droit : Straight ahead
Traiter une carie : To treat a cavity
Transformés : Processed
Triste : Sad
Trottoir : Sidewalk
Trousse : Pencil case
Valider : To validate/submit
Vérifier : To check
Vide : Empty
Vigilant(e) : Attentive
Vipère : Viper (A type of snake)
Vive : Long live (An expression of joy)
Voisin : Nearby
Vol : Flight
Volant : Steering wheel

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# Page 310

# Corrigés

## Unité 1

### Dialogue 1 : Les salutations
A. Compréhension orale — Vocabulaire
2. a.
3. d.
4. 1- : c. – 2- : a.

E. Compréhension écrite
1- : c. – 2- : c. – 3- : c. – 4- : d.

F. Analyse orale
1- : Bon / Jour – 2- : Comment – 3- : Un point d’interrogation – 4- : Phrase interrogative – 5- : vas / Aller – 6- : tu – 7- : Après le verbe – 8- : vais / Aller – 9- : Je

G. Grammaire
2- : f. – 3- : c. – 4- : b. – 5- : c. – 6- : g. – 7- : a. – 8- : d.

H. Conjugaison
1- : vas – 2- : va – 3- : va – 4- : allons – 5- : allez – 6- : vont – 7- : vais – 8- : va – 9- : vont – 10- : allez

### Dialogue 2 : La famille
A. Compréhension orale — Vocabulaire
2. d.
3. 1- : c. – 2- : Non
4. 1- : d. – 2- : c.

E. Compréhension écrite
1- : c. – 2- : c. – 3- : Le frère de la seconde fille a dix ans.

F. Analyse orale
1- : Phrase interrogative – 2- : As – 3- : tu – 4- : Après le verbe – 5- : Masculin – 6- : Pluriel – 7- : des – 8- : ai – 9- : j’ – 10- : Singulier – 11- : un / Article indéfini – 12- : a – 13- : Il – 14- : Masculin pluriel

G. Grammaire
1- : un – 2- : un – 3- : une – 4- : des – 5- : une / un – 6- : un / une

H. Conjugaison
1- : ai – 2- : as – 3- : a – 4- : avons – 5- : avez – 6- : ont – 7- : ai – 8- : as – 9- : a – 10- : ont

### Dialogue 3 : Se préparer pour l’école
A. Compréhension orale — Vocabulaire
2. a.
3. 1- : a. – 2- : b./d.
4. 1- : c. – 2- : e.

E. Compréhension écrite
1- : Deux personnes participent à cette conversation. – 2- : c. – 3- : c. – 4- : Son alarme n’a pas sonné.

F. Analyse orale
1- : Un point d’exclamation – 2- : Un ordre – 3- : es – 4- : Tu – 5- : a sonné / Sonner – 6- : Passé composé – 7- : Mon alarme – 8- : La négation – 9- : Ils encadrent « a » (auxiliaire avoir). – 10- : Forme négative

G. Grammaire
1- : Je ne vais pas bien. – 2- : Tu n’es pas en retard. – 3- : La petite fille n’est pas contente. – 4- : Tu n’es pas en colère. – 5- : Didier n’a pas dix ans.

H. Conjugaison
1- : est – 2- : es – 3- : est – 4- : sommes – 5- : sont – 6- : suis – 7- : êtes

### Dialogue 4 : L’école
A. Compréhension orale — Vocabulaire
2. 1- : b. – 2- : b.
3. 1- : c. – 2- : d.
4. b.

E. Compréhension écrite
1- : Trois personnes participent à cette conversation. – 2- : Cette conversation a lieu à l’école (en classe). – 3- : c. – 4- : Le professeur lui propose de suivre la leçon avec son camarade. – 5- : a b. b) Le mot « ton » nous permet de deviner qu’il s’agit d’un garçon.

F. Analyse orale
1- : ai oublié – 2- : Passé composé – 3- : J’ – 4- : J’ai oublié de recharger quoi ? – 5- : Suis – 6- : Non – 7- : Un ordre / Phrase impérative – 8- : Féminin singulier – 9- : la – 10- : Partageons – 11- : Partager – 12- : Le « e » a été ajouté après le « g » pour garder le son [j]. – 13- : Partageons quoi ?

G. Grammaire
1- : la – 2- : le – 3- : l’ – 4- : L’ – 5- : Les – 6- : la – 7- : Le / les

H. Conjugaison
1- : Rechargeons – 2- : Partagez – 3- : Range – 4- : Mange – 5- : Partageons – 6- : Rangeons – 7- : Change

### Dialogue 5 : La maison
A. Compréhension orale — Vocabulaire
2. c.
3. 1- : d. – 2- : c.
4. d.

E. Compréhension écrite
1- : Le premier interlocuteur regarde la télévision dans le salon. – 2- : b. – 3- : a) Il va regarder des dessins animés. / b) Il va le faire le soir.

F. Analyse orale
1- : regarde – 2- : Présent – 3- : Je – 4- : Je regarde quoi ? – 5- : Je regarde la télévision où ? – 6- : Articles définis – 7- : Féminin – 8- : Masculin – 9- : Que – 10- : Un point d’interrogation – 11- : Phrase interrogative – 12- : Je vais regarder quoi ?

G. Grammaire
1- : (Je) regarde un film dans la salle de séjour. – 2- : (Auréli) suit la leçon avec sa camarade. – 3- : (Nous) partageons le repas. – 4- : (Pia et Emma) regardent des dessins animés. – 5- : (L’alarme) n’a pas sonné. – 6- : Pourquoi êtes-vous en retard ? – 7- : Que regardent-ils ? – 8- : (Ils) vont très bien aujourd’hui.

H. Conjugaison
1- : somme – 2- : regardons – 3- : décorez – 4- : transforme – 5- : semblent – 6- : aides

### Dialogue 6 : Le climat (1)
A. Compréhension orale — Vocabulaire
2. 1- : c. – 2- : c.
3. c.
4. 1- : b. – 2- : c.

E. Compréhension écrite
1- : Le football est mentionné dans ce dialogue. – 2- : b. – 3- : c.

F. Analyse orale
1- : allons / Aller – 2- : 3’ groupe – 3- : Une action qui aura lieu après – 4- : Pronom personnel – 5- : Ils expriment la négation. – 6- : Nous n’allons pas jouer à quoi ? – 7- : Nous n’allons pas jouer au football quand ? – 8- : Un point d’interrogation – 9- : Pourquoi – 10- : Phrase interrogative – 11- : a / Avoir – 12- : Il – 13- : Non – 14- : Féminin – 15- : Il y a trop de boue où ?

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G. Conjugaison
1. 1- : Grandir / 2e groupe – 2- : Boire / 3e groupe – 3- : Faire / 3e groupe – 4- : Regarder / 1e groupe – 5- : Finir / 2e groupe – 6- : Attendre / 3e groupe
2. 1- : vais partager – 2- : vas éviter – 3- : va oublier – 4- : allons regarder – 5- : allez aider – 6- : vont jouer – 7- : va partager – 8- : vont éviter – 9- : va oublier

H. Composition
1. 1- : Je vais jouer au basket avec mes camarades. – 2- : Tu vas probablement arriver en retard. – 3- : Il y a trop de neige sur le terrain. – 4- : Mes camarades jouent au football dans le jardin.

Dialogue 7 : Le climat (2)
A. Compréhension orale — Vocabulaire
2. c.
3. c.
4. 1- : a. – 2- : a. / c. / c.
E. Compréhension écrite
1- : d. – 2- : c. – 3- : Cette activité est familiale. Le mot qui le prouve est « famille ». 

F. Analyse orale
1- : fais / fait – 2- : Faire – 3- : Présent – 4- : tu / il – 5- : Phrase interrogative – 6- : vais – 7- : Aller – 8- : 3e groupe – 9- : Je – 10- : Féminin – 11- : Je vais où ? – 12- : faisons – 13- : Faire – 14- : Nous – 15- : Masculin – 16- : Nous faisons quoi ?

G. Grammaire
1- : en forêt – 2- : vers le stade de football – 3- : à la plage – 4- : dans ta chambre – 5- : sur le terrain – 6- : dans le salon

H. Conjugaison
1- : fais – 2- : fais – 3- : fait – 4- : faisons – 5- : faites – 6- : font

I. Composition
1- : Que fais-tu quand il pleut ? – 2- : Vous allez à la plage avec vos amis. – 3- : Marc et Jules font du sport pour rester en forme.

Dialogue 8 : Les tâches ménagères
A. Compréhension orale — Vocabulaire
2. 1- : c. – 2- : b.
3. 1- : b. – 2- : d.
4. a.
E. Compréhension écrite
1- : Les deux interlocuteurs ont des tâches ménagères à faire. – 2- : Non, ils ne se trouvent pas au même endroit. Le verbe qui le prouve est « se retrouvent ». – 3- : Ils se parlent au téléphone. – 4- : b.

F. Analyse orale
1- : se retrouver / terminer – 2- : Se retrouver / Terminer – 3- : Présent – 4- : On / je – 5- : Féminin pluriel – 6- : ai – 7- : Avoir – 8- : J’ – 9- : J’ai aussi quoi ? – 10- : Féminin pluriel – 11- : dois – 12- : Devoir – 13- : 3e groupe – 14- : Je – 15- : Féminin pluriel – 16- : Je dois sortir quoi ?

G. Grammaire
1- : Des choses – 2- : Les poubelles – 3- : Des campings – 4- : Les terrains – 5- : Des dessins – 6- : Les soirs – 7- : Les alarmes – 8- : Des frères – 9- : Les tablettes – 10- : Des plages

H. Conjugaison
1- : dois – 2- : dois – 3- : doit – 4- : devons – 5- : devez – 6- : doivent

Dialogue 9 : Le recyclage
A. Compréhension orale — Vocabulaire
2. c.
3. 1- : b. – 2- : d.
4. c.
E. Compréhension écrite
1- : d. – 2- : a. – 3- : Elle les décore.

F. Analyse orale
1- : fait – 2- : cette dame – 3- : Féminin singulier – 4- : cette / Adjectif démonstratif – 5- : collectionne – 6- : Collectionner – 7- : 1e groupe – 8- : Présent – 9- : Elle / Pronom personnel – 10- : Elle collectionne quoi ? – 11- : décore – 12- : Décorer – 13- : 1e groupe – 14- : Présent – 15- : Elle – 16- : Les bouteilles en verre – 17- : Elle décore quoi aussi ?

G. Grammaire
1- : Cette – 2- : Cette – 3- : Ces – 4- : Ce – 5- : Ces – 6- : Ce – 7- : Cette – 8- : Ce – 9- : Ces – 10- : Cet

H. Conjugaison
1- : some – 2- : décorez – 3- : collectionnons – 4- : décorent – 5- : collectionnent – 6- : some – 7- : collectionne – 8- : décores

Dialogue 10 : Demander de l’aide
A. Compréhension orale — Vocabulaire
2. 1- : c. – 2- : a.
3. 1- : d. – 2- : e.
4. 1- : b. – 2- : a. – 3- : d.

E. Compréhension écrite
1- : c. – 2- : c. – 3- : b. – 4- : e. – 5- : b. – 6- : c.

F. Analyse orale
1- : sais – 2- : Savoir – 3- : Présent – 4- : 3e groupe – 5- : Je – 6- :...pas – 7- : revois – 8- : D’abord, revois quoi ? – 9- : Féminin pluriel – 10- : tes / Adjectif possessif – 11- : appuie – 12- : Ensuite, appuie où ? – 13- : Féminin singulier

G. Grammaire
1- : Mon – 2- : Ton – 3- : son – 4- : ses – 5- : notre – 6- : votre – 7- : sa – 8- : nos – 9- : leur – 10- : ta

H. Conjugaison
1- : savez – 2- : sait – 3- : sait – 4- : savons – 5- : savent – 6- : sait – 7- : savent – 8- : sais – 9- : sais

Unité 2
Dialogue 11 : Les activités
A. Compréhension orale — Vocabulaire
2. 1- : a. – 2- : b.
3. c.
4. 1- : a. – 2- : c.

E. Compréhension écrite
1- : c. – 2- : Il va aller au parc. – 3- : e.

F. Analyse orale
1- : vas – 2- : Présent – 3- : faire / Le futur proche – 4- : tu – 5- : Après le verbe conjugué – 6- : Phrase interrogative – 7- : Que vas-tu faire quand ? – 8- : vais – 9- : Aller – 10- : aller / Le futur proche – 11- : Je – 12- : Masculin singulier – 13- : au / Article contracté – 14- : 1e personne du singulier (je) – 15- : vais – 16- : jouer / Le futur proche – 17- : je – 18- : Moi, je vais jouer à quoi ? – 19- : Masculin singulier

G. Grammaire
1- : à l’ – 2- : au – 3- : aux – 4- : au – 5- : à la – 6- : aux

H. Conjugaison
1- : allez faire – 2- : va aller – 3- : va jouer – 4- : allons revoir – 5- : va appuyer – 6- : vont collectionner – 7- : vont terminer – 8- : vais regarder – 9- : vas suivre – 10- : vont être

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### Dialogue 12 : Le respect de l’environnement

**A. Compréhension orale — Vocabulaire**
2. 1- : a. — 2- : b.
3. 1- : c. — 2- : d.
4. c.

**E. Compréhension écrite**
1- : c. — 2- : Il veut devenir vétérinaire. — 3- : Ce professionnel s’occupe des animaux.

**F. Analyse orale**
1- : veux — 2- : Présent — 3- : Vouloir — 4- : tu — 5- : Après le verbe conjugué — 6- : Phrase interrogative — 7- : veux — 8- : Présent — 9- : Je — 10- : Nom commun — 11- : Non / Parce qu’il s’agit d’un nom de métier précédé du verbe « être » — 12- : m’occuperaï — 13- : S’occuper — 14- : Futur simple — 15- : Je — 16- : Masculin pluriel — 17- : des / Article contracté

**G. Grammaire**
1- : des — 2- : du — 3- : de la — 4- : des — 5- : des — 6- : des — 7- : de l’ — 8- : de l’

**H. Conjugaison**
1- : veulent — 2- : voulons — 3- : veulent — 4- : veux — 5- : voulez — 6- : veut — 7- : veux — 8- : veut — 9- : veut

### Dialogue 13 : Économiser l’énergie

**A. Compréhension orale — Vocabulaire**
2. 1- : b. — 2- : c.
3. 1- : d. — 2- : c.
4. 1- : b. — 2- : d. — 3- : b.

**E. Compréhension écrite**
1- : c. — 2- : On parle du soleil. — 3- : b.

**F. Analyse orale**
1- : est — 2- : Être — 3- : C’— 4- : Adjectif possessif — 5- : Masculin singulier — 6- : sont — 7- : Être — 8- : Ce — 9- : Article indéfini — 10- : Nom commun — 11- : Masculin — 12- : Pluriel — 13- : panneaux — 14- : Pronom personnel — 15- : transforment — 16- : Transformer — 17- : Présent — 18- : Ils — 19- : Article défini — 20- : Féminin — 21- : Ils transforment quoi en électricité ?

**G. Grammaire**
1- : son — 2- : sont — 3- : sont — 4- : son — 5- : sont — 6- : sont — 7- : son — 8- : son — 9- : Son — 10- : sont

**H. Conjugaison**
1- : aimes — 2- : transforme — 3- : jouent — 4- : décorez — 5- : aide — 6- : regarde — 7- : somme — 8- : arrive — 9- : décorons

### Dialogue 14 : La sécurité aquatique

**A. Compréhension orale — Vocabulaire**
2. 1- : c. — 2- : a.
3. 1- : c. — 2- : b.
4. 1- : c. — 2- : e.

**E. Compréhension écrite**
1- : Le garçon va se promener. — 2- : b. — 3- : c. — 4- : e.

**F. Analyse orale**
1- : vais — 2- : Aller — 3- : je — 4- : Féminin — 5- : me promener — 6- : Verbe pronominal — 7- : joue — 8- : Jouer — 9- : Impératif présent — 10- : La négation — 11- : Ne joue pas où ? — 12- : Féminin — 13- : est — 14- : être — 15- : c’— 16- : dangereux

**G. Grammaire**
1- : Ne va pas te promener. — 2- : Ce ne sont pas des panneaux solaires. — 3- : Ne jouez pas au football. — 4- : Je ne veux pas être vétérinaire. — 5- : N’allons pas au parc.

**H. Conjugaison**
1- : Joue — 2- : transformons — 3- : Décorez — 4- : collectionne — 5- : regardez — 6- : Sonnons

### Dialogue 15 : L’alimentation saine

**A. Compréhension orale — Vocabulaire**
2. 1- : c. — 2- : b. — 3- : c.
3. 1- : b. — 2- : a.
4. 1- : c. — 2- : b.

**E. Compréhension écrite**
1- : a) a / b) c. — 2- : c. — 3- : Le premier interlocuteur consomme, lui aussi, du lait. — 4- : a.

**F. Analyse orale**
1- : bois — 2- : Boire — 3- : Tu — 4- : Tu bois du lait quand ? — 5- : Masculin — 6- : est — 7- : Être — 8- : Présent — 9- : c’— 10- : Au lait — 11- : bois — 12- : je — 13- : Moi aussi, je bois quoi ? — 14- : Singulier — 15- : Singulier — 16- : Parce qu’on ne peut pas compter le lait — 17- : Parce qu’on ne peut pas compter le miel

**G. Grammaire**
1- : C’est — 2- : Ce sont — 3- : C’est — 4- : Ce sont — 5- : C’est — 6- : C’est — 7- : Ce sont — 8- : Ce sont — 9- : C’est — 10- : C’est — 11- : de l’ — 2- : de la — 3- : des — 4- : du — 5- : des — 6- : de l’ — 7- : de la / du — 8- : du / du — 9- : de la — 10- : de l’

### Dialogue 16 : Faire les courses

**A. Compréhension orale — Vocabulaire**
2. 1- : a. — 2- : e.
3. 1- : d. — 2- : c.
4. 1- : d. — 2- : b.

**E. Compréhension écrite**
1- : b. — 2- : d. — 3- : La première interlocutrice est l’employée. — 4- : a. — 5- : b.

**F. Analyse orale**
1- : peux — 2- : Pouvoir — 3- : je — 4- : Je peux aider qui ? — 5- : Comment — 6- : Phrase interrogative — 7- : cherche — 8- : Chercher — 9- : 1er groupe — 10- : Je — 11- : Je cherche quoi ? — 12- : Féminin pluriel — 13- : se trouvent — 14- : Se trouver — 15- : Présent — 16- : Elles — 17- : Les friandises — 18- : Préposition — 19- : Elles se trouvent où ?

**G. Grammaire**
1- : sous — 2- : entre — 3- : dans — 4- : sur — 5- : dans — 6- : sous — 7- : sur — 8- : dans — 9- : sur — 10- : sur

**H. Conjugaison**
1- : s’occupe — 2- : nous dépêchons — 3- : me trouve — 4- : nous promenons — 5- : te trouves — 6- : vous promenez — 7- : s’occupe — 8- : se dépêche

### Dialogue 17 : La sécurité routière

**A. Compréhension orale — Vocabulaire**
2. 1- : b. — 2- : c.
3. 1- : c. — 2- : b.
4. 1- : c. — 2- : e.

**E. Compréhension écrite**
1- : a. — 2- : c. — 3- : La maman et son fils se déplacent à pied. — 4- : d. — 5- : a. — 6- : e.

**F. Analyse orale**
1- : Fais (Fais attention) — 2- : Faire (Faire attention) — 3- : Impératif présent — 4- : Masculin pluriel — 5- : aux / Article contracté — 6- : Phrase impérative — 7- : Féminin singulier — 8- : Fais attention à quoi ? — 9- : Singulier — 10- : Le / Article défini — 11- : est — 12- : Le feu — 13- : Le feu est vert quand ? — 14- : vert — 15- : pouvons — 16- : Présent — 17- : Pouvoir — 18- : 3e groupe — 19- : traverser — 20- : Nous pouvons traverser quoi ? — 21- : Féminin singulier

**G. Grammaire**
1- : Des cheveux — 2- : Les bateaux — 3- : Des milieux — 4- : Les clous — 5- : Des bleus — 6- : Les neveux — 7- : Des cailloux

**H. Conjugaison**
1- : Fais — 2- : Faites — 3- : Faisons — 4- : Faites — 5- : Fais — 6- : Faisons

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Dialogue 18 : Demander son chemin
A. Compréhension orale — Vocabulaire
2. l- : h - 2- : d.
3. l- : c. - 2- : b.
4. l- : b. - 2- : c.

E. Compréhension écrite
1- : Il cherche la bibliothèque. – 2- : a. – 3- : Elle se trouve au deuxième étage. – 4- : a.

F. Analyse orale
1- : Excusez – 2- : Excuser – 3- : Impératif présent – 4- : Phrase impérative – 5- : Excusez qui ? – 6- : Pouvez – 7- : vous / Parce qu’il s’agit d’une phrase interrogative – 8- : se trouve – 9- : la bibliothèque – 10- : Féminin singulier – 11- : la / Article défini – 12- : Pronom personnel – 13- : se trouve – 14- : Verbe pronominal – 15- : Se trouver – 16- : 1er groupe – 17- : Elle se trouve où ? – 18- : Masculin singulier

G. Grammaire
1- : au fond du couloir – 2- : dans cette rue – 3- : dans l’allée centrale – 4- : dans la cuisine – 5- : près de l’eau – 6- : sur le toit – 7- : dans cette clinique – 8- : au parc – 9- : à la maison – 10- : sur la table

H. Conjugaison
1- : Installez – 2- : Excusons – 3- : Aide – 4- : Traversez – 5- : Cherchons – 6- : Joue

Dialogue 19 : Le transport routier
A. Compréhension orale — Vocabulaire
2. l- : c. - 2- : b. - 3- : d.
3. l- : c./d. - 2- : e.
4. l- : b. - 2- : b. - 3- : c.

E. Compréhension écrite
1- : a. – 2- : Le pneu de la voiture est à plat. – 3- : c. – 4- : d.

F. Analyse orale
1- : pense – 2- : Penser – 3- : Je – 4- : est – 5- : notre pneu – 6- : allons – 7- : nous / Parce qu’il s’agit d’une phrase interrogative – 8- : faire – 9- : Une action qui aura lieu après (dans un futur proche) – 10- : Adverbe – 11- : Qu’allons-nous faire quand ? – 12- : Garons-nous – 13- : Se garer – 14- : Impératif présent – 15- : Adverbe – 16- : Garons-nous d’abord où ? – 17- : Masculin singulier

G. Grammaire
1- : demain – 2- : Aujourd’hui – 3- : toujours – 4- : ensuite – 5- : après – 6- : enfin – 7- : Hier – 8- : maintenant – 9- : avant – 10- : D’abord

H. Conjugaison
1- : vont faire – 2- : allons penser – 3- : allez garer – 4- : va dire – 5- : vais traverser – 6- : allons acheter – 7- : vont aider – 8- : vas boire – 9- : va jouer – 10- : vais devenir

Dialogue 20 : Le transport aérien
A. Compréhension orale — Vocabulaire
2. l- : b. - 2- : c.
3. l- : d. - 2- : a.
4. l- : d. - 2- : b. - 3- : c. – 4- : b. – 5- : a.

E. Compréhension écrite
1- : c. – 2- : d. – 3- : c. – 4- : e.

F. Analyse orale
1- : Phrase exclamative – 2- : Féminin singulier – 3- : Féminin singulier – 4- : Féminin singulier – 5- : belle – 6- : semblent – 7- : Présent – 8- : Les maisons – 9- : Féminin pluriel – 10- : Féminin pluriel – 11- : maisons – 12- : est – 13- : Présent – 14- : c’ – 15- : regarde – 16- : Impératif présent – 17- : Regarde quoi ?

G. Grammaire
1. l- : jaune / jolie – 2- : minuscule – 3- : bel – 4- : sûr – 5- : vert
2. l- : centrale – 2- : dangereux – 3- : solaires – 4- : bleue – 5- : vraies

Unité 3
Dialogue 21 : Le transport maritime
A. Compréhension orale — Vocabulaire
2. l- : d. - 2- : a. – 3- : b. – 4- : a. Today / b. Hier / c. Demain
3. l- : b. - 2- : e.
4. l- : c.

E. Compréhension écrite
1- : Ils ont acheté un petit bateau. – 2- : b. – 3- : b. – 4- : e.

F. Analyse orale
1- : Mes – 2- : ont acheté – 3- : Une action qui a eu lieu avant – 4- : Passé composé – 5- : Mes parents – 6- : Mes parents ont acheté quoi ? – 7- : Mes parents ont acheté un petit bateau quand ? – 8- : Phrase exclamative – 9- : Féminin singulier – 10- : Féminin singulier – 11- : Adjectif qualificatif – 12- : nouvelle – 13- : Phrase exclamative – 14- : Article défini – 15- : Masculin singulier – 16- : Parce que « été » commence par une voyelle

G. Grammaire
1- : Son – 2- : Votre – 3- : mes – 4- : notre – 5- : Leur – 6- : tes – 7- : ma – 8- : ses – 9- : Ta – 10- : nos

H. Conjugaison
1- : a sonné – 2- : avez joué – 3- : ont décoré – 4- : as regardé – 5- : a cherché – 6- : ai acheté – 7- : a partagé – 8- : avons aidé – 9- : ont mangé

Dialogue 22 : Les projets scolaires
A. Compréhension orale — Vocabulaire
2. l- : c. - 2- : d.
3. l- : a. - 2- : b. - 3- : d. – 4- : c. – 5- : a) En Égypte
4. l- : a. – 2- : d. – 3- : c.

E. Compréhension écrite
1- : c. – 2- : c. – 3- : d. – 4- : d. – 5- : Il possède deux livres sur les pyramides.

F. Analyse orale
1- : aides – 2- : Aider – 3- : 1er groupe – 4- : Présent – 5- : Tu – 6- : Adjectif possessif – 7- : Féminin singulier – 8- : Phrase interrogative – 9- : ai (ai besoin) – 10- : Avoir (Avoir besoin) – 11- : Présent – 12- : J’ – 13- : Féminin pluriel – 14- : Article défini – 15- : Féminin pluriel – 16- : ai – 17- : j’ – 18- : Masculin pluriel – 19- : Masculin singulier

G. Grammaire
1- : à / avec – 2- : sous – 3- : pour – 4- : chez (avec) – 5- : sur – 6- : dans – 7- : de

H. Conjugaison
1- : aidons – 2- : respectes – 3- : semble – 4- : pensent – 5- : traverse – 6- : ajoute – 7- : visitez – 8- : décorent

Dialogue 23 : Les loisirs – Le sport
A. Compréhension orale — Vocabulaire
2. l- : c. - 2- : b. – 3- : d. – 4- : c.
3. l- : a. C’est / b. Mon activité – 2- : b. – 3- : a.
4. l- : 1) c./ 2) a./ 3) d./ 4) b.

E. Compréhension écrite
1- : Son activité nautique préférée est la plongée sous-marine. – 2- : Non, il ne peut pas la pratiquer parce qu’il a peur de l’eau. – 3- : a. / d.

F. Analyse orale
1- : aimes – 2- : Aimer – 3- : 1er groupe – 4- : Présent – 5- : Tu – 6- : Tu aimes quoi ? – 7- : Féminin singulier – 8- : Adjectif qualificatif – 9- : Phrase interrogative – 10- : est – 11- : Être – 12- : C’ – 13- : Adjectif possessif – 14- : Féminin singulier – 15- : Devant un nom féminin commençant par une voyelle, « ma » devient « mon ». – 16- : nautique / préférée – 17- : activité – 18- : Phrase affirmative – 19- : ai (ai peur) – 20- : Avoir (Avoir peur) – 21- : j’ – 22- : Féminin singulier – 23- : Article défini

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# Page 314

G. Grammaire
1- : nautiques – 2- : mauvaises – 3- : petits – 4- : minuscules – 5- : jolie – 6- : voisine – 7- : correctes

H. Conjugaison
1- : aide → aident – 2- : regardons → regardez – 3- : décorent → décoré – 4- : collectionnons → collectionne – 5- : somme → somme – 6- : ament → aimes – 7- : plantes → plantez – 8- : adorez → adorent – 9- : joue → jouons

Dialogue 24 : Les loisirs – L’art
A. Compréhension orale — Vocabulaire
2. 1- : c. – 2- : d. – 3- : a.
3. 1- : b. – 2- : hobby – 3- : a. / c.
4. 1- : (1) d. / (2) c. / (3) b. / (4) a. – 2- : d. – 3- : b. / d. – 4- : Exemples de réponse : Des coquillages / Des autocollants / Des souvenirs de voyage
E. Compréhension écrite
1- : b. – 2- : e. – 3- : Il collectionne des timbres. – 4- : Il y a un timbre vieux de 60 ans dans cette collection.

F. Analyse orale
1- : Quelle – 2- : collection – 3- : Phrase exclamative – 4- : Féminin singulier – 5- : Adjectif qualificatif / collection – 6- : Masculin pluriel – 7- : est – 8- : Être – 9- : Présent – 10- : Collectionner des timbres – 11- : Collectionner – 12- : Adjectif possessif – 13- : Masculin singulier – 14- : Adjectif qualificatif – 15- : possède – 16- : Présent – 17- : Possèder – 18- : 1er groupe – 19- : Je – 20- : Je possède quoi ? – 21- : Masculin singulier – 22- : Adjectif qualificatif / timbre – 23- : Parce qu’il est précédé d’un nombre supérieur à 1 (60)

G. Grammaire
1- : es – 2- : est – 3- : et – 4- : et – 5- : es – 6- : est – 7- : est / et – 8- : es

H. Conjugaison
1- : êtes – 2- : est – 3- : est – 4- : sommes – 5- : sont – 6- : est – 7- : sont – 8- : suis – 9- : es – 10- : sont

Dialogue 25 : Chez le dentiste
A. Compréhension orale — Vocabulaire
2. 1- : b. – 2- : c.
3. e.
4. 1- : a. – 2- : b.

E. Compréhension écrite
1- : c. – 2- : b. – 3- : Les mots qui le prouvent sont « Docteur » et « caries ». – 4- : d. – 5- : b. – 6- : b.

F. Analyse orale
1- : ai (ai peur) – 2- : Avoir (Avoir peur) – 3- : J’ – 4- : Phrase déclarative – 5- : Forme affirmative – 6- : Forme négative – 7- : as – 8- : Présent – 9- : Tu – 10- : n’... pas – 11- : Forme négative – 12- : Tu n’as pas quoi ? – 13- : Féminin pluriel

G. Grammaire
1- : Je n’ai pas peur. – 2- : Tu ne collectionnes pas les pièces de monnaie. – 3- : Le tennis n’est pas ton hobby préféré. – 4- : Béatrice ne va pas chanter. – 5- : René ne va pas danser avec ses amis. – 6- : Nous n’aimons pas la plongée sous-marine. – 7- : Vous n’aidez pas Luc avec sa rédaction. – 8- : Je n’ai pas deux livres sur ce sujet. – 9- : Je n’ai pas offert ce cadeau à ma sœur. – 10- : Mes parents n’achètent pas la voiture blanche.

H. Conjugaison
1- : fais – 2- : faites – 3- : faisons – 4- : Fais – 5- : faites – 6- : Faisons

Dialogue 26 : À l’aquarium
A. Compréhension orale — Vocabulaire
2. 1- : e. – 2- : a./c. – 3- : d. – 4- : b.
3. 1- : e. – 2- : d. – 3- : e.

4. 1- : d. – 2- : a. – 3- : Exemples de réponse : Le poisson / La tortue de mer / La méduse

E. Compréhension écrite
1- : c. – 2- : d. – 3- : Les balançines impressionnent la seconde interlocutrice. – 4- : c. – 5- : a.

F. Analyse orale
1- : va – 2- : On – 3- : faire – 4- : Le futur proche – 5- : rapide / visite – 6- : On va faire quoi ? – 7- : Masculin pluriel – 8- : Regarde – 9- : Impératif présent – 10- : Regarde quoi ? – 11- : Phrase impérative – 12- : Féminin pluriel – 13- : sont – 14- : Présent – 15- : Elles – 16- : Phrase exclamative – 17- : Promon personnel / Les balançines – 18- : Féminin pluriel

G. Grammaire
1- : Son – 2- : Son – 3- : sont – 4- : sont – 5- : sont – 6- : son – 7- : sont – 8- : son – 9- : son / son – 10- : sont

H. Conjugaison
1- : Regarde – 2- : Préférez – 3- : Amons / respectons – 4- : Achetez – 5- : Collectionne

Dialogue 27 : Au zoo
A. Compréhension orale — Vocabulaire
2. 1- : b./d. – 2- : c.
3. 1- : a./c. – 2- : b. – 3- : a.
4. 1- : d. – 2- : c. – 3- : a. – 4- : Exemples de réponse : Le lion / Le tigre / L’éléphant

E. Compréhension écrite
1- : b. – 2- : Ils parlent du crocodile. – 3- : a. – 4- : d. – 5- : b.

F. Analyse orale
1- : as vu – 2- : Voir – 3- : Passé composé – 4- : Tu – 5- : Tu as vu quoi ? – 6- : Masculin singulier – 7- : paraît – 8- : Présent – 9- : Paraitre – 10- : 3e groupe – 11- : il – 12- : Au crocodile – 13- : Masculin singulier – 14- : il (le crocodile) – 15- : est – 16- : C’– 17- : Féminin singulier – 18- : belle – 19- : bête

G. Grammaire
1- : férecs – 2- : sauvages – 3- : énormes – 4- : rapides – 5- : salés – 6- : sucrée – 7- : préférée – 8- : petites

H. Conjugaison
1- : disparait – 2- : parais – 3- : paraissez – 4- : paraît – 5- : apparaît – 6- : connaissons – 7- : paraissent – 8- : reconnais – 9- : paraissent

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# Page 315

Remerciements

Cover: Arc de Triomphe, Naty Lee/Shutterstock.com; family, fizkes/Shutterstock.com; boy stretching after waking up, Elen Nika/Shutterstock.com; pupils in a classroom, Monkey Business Images/Shutterstock.com; girls in a football field, PeopleImages.com - Yuri A/Shutterstock.com; mother and daughter in an airplane, Friends Stock/Shutterstock.com; kids in an oceanarium, FamVeld/Shutterstock.com; people planting trees, Dmytro Zinychev/Shutterstock.com; p. 1: policeman, LifetimeStock/Shutterstock.com; pp. 1, 2: Martine, Josep Curto/Shutterstock.com; p. 3: Smiling schoolchildren holding books, ESB Professional/Shutterstock.com; p. 4: Two happy friends meeting greeting on street, Prostock-studio/Shutterstock.com; p. 11: business partners walking down in office building and talking, Pressmaster/Shutterstock.com; child sleeping, Ground Picture/Shutterstock.com; mother taking cool towel to reduce high fever on sick girl’s forehead on bed at morning time, Chanintron.v/Shutterstock.com; workers, LightField Studios/Shutterstock.com; two friends smiling, ViDI Studio/Shutterstock.com; p. 12: teenage girls watching a film, Monkey Business Images/Shutterstock.com; Happy familyeating together, T Tint Media/Shutterstock.com; Laughing patient taking the stethoscope from a male doctor in the hospital, wavebreakmedia/Shutterstock.com; two businessmen shaking hands in an office setting, Dragana Gordic/Shutterstock.com; Fresh groceries and goods falling in a supermarket trolley, Stokkete/Shutterstock.com; p. 13: Human resources manager shaking hands with applicant, Prostock-studio/Shutterstock.com; p. 14: Two schoolgirls having lunch, AnnaStills/Shutterstock.com; p. 19: boy and girl laughing while giving high fives, Dean Drobot/Shutterstock.com; boy on wheelchair, VH-studio/Shutterstock.com; p. 20: Grandparents and grandchildren walking in the countryside, Monkey Business Images/Shutterstock.com; children embracing, Ground Picture/Shutterstock.com; happy family of three, Prostock-studio/Shutterstock.com; Children working in rice terrace, Mu Cang Chai, Vietnam/Shutterstock.com; p. 21: Father and son in the park, Ground Picture/Shutterstock.com; father lying on carpet floor, lifting child, Ground Picture/Shutterstock.com; mother with her child on bed, PeopleImages.com - Yuri A/Shutterstock.com; p. 22: Four boys standing together, bright yellow background/Shutterstock.com; sister hugging her brother, Ground Picture/Shutterstock.com; grandmother with grandson, Alonafoto/Shutterstock.com; mother joking with her children, fizkes/Shutterstock.com; woman cuddling her son, fizkes/Shutterstock.com; grandfather spending time with cute child, fizkes/Shutterstock.com; p. 23: Young moms with their kids, Oksana Shurfych/Shutterstock.com; Two girl on a city street, VH-studio/Shutterstock.com; p. 24: Father waking up teenage son, Monkey Business Images/Shutterstock.com; p. 25: Young moms with their kid, Oksana Shurfych/Shutterstock.com; Alarm clock on table room selective, AntonSAN/Shutterstock.com; Blurred low key illuminated factory industry, Sergey Nemirovsky/Shutterstock.com; Smoke detector in the event of a fire alarm, Robert Kneschke/Shutterstock.com; woman ringing intercom with camera near building entrance, New Africa/Shutterstock.com; p. 29: Sand running through an hourglass, M Min C. Chiu/Shutterstock.com; Portrait of emotionally kid, Oksana Kuzmina/Shutterstock.com; Angry office manager, Studio Romantic/Shutterstock.com; teen stressed suffering migraine in a park, Pheelings media /Shutterstock.com; p. 30: portrait of young girl, Roman Samborskyi/Shutterstock.com; boy pointing up with fingers, Roquillo Tebar/Shutterstock.com; p. 31: businessman having breakfast, AboutLife - Raee Denis/Shutterstock.com; Conjugating verbs in French, B Calkins/Shutterstock.com; woman waking up late in morning, Voyagerix/Shutterstock.com; young people walking in the office at their break time, Standret/Shutterstock.com; Two Happy Boys, Andy Dean Photography/Shutterstock.com; pp. 31, 236: boy going to school, Sharomka/Shutterstock.com; p. 32: Businesswoman hurrying and running in the city, FrameAngel/Shutterstock.com; p. 33: teacher with two pupils using a digital tablet, Monkey Business Images/Shutterstock.com; p. 34: 4k monitor, Ruslan Ivantsov/Shutterstock.com; Black tablet, Yeti studio/Shutterstock.com; Earphones, black studio over-ear open back, Andrei Kuzmik/Shutterstock.com; Side view of open laptop computer, otello-stpde/Shutterstock.com; Wooden round table isolated on white, yas creative/Shutterstock.com; p. 39: Alarm clock, Photolife/Shutterstock.com; Running for class, Pressmaster/Shutterstock.com; power Bank charges your tablet, MaBo0/Shutterstock.com; Two women relaxing on sofa, PR Image Factory/Shutterstock.com; woman sitting on sofa , Ground Picture/Shutterstock.com; Side view focused schoolboy studying at home, Dikushin Dmitry/Shutterstock.com; portrait of smiling smart school boy, AYO Production/Shutterstock.com; p. 41: Man charging white tablet with power bank, sakachostockphoto/Shutterstock.com; preschooler boy eating his lunch, Elena Medoksh/Shutterstock.com; Share chocolate, kang ramdani/Shutterstock.com; School stationary, Savanevich Viktar/Shutterstock.com; child putting books and notes into backpack, konggaStudio/Shutterstock.com; p. 42: Closeup man eating candy, Egoitz Bengoetxea/Shutterstock.com; Children are moving with their parents to a new house, unpacking cardboard boxes, Trzykropy/Shutterstock.com; p. 43: Teacher asking her students a question at the elementary school, wavebreakmedia/Shutterstock.com; Smart phone need to charge battery, Jakraphong Photography/Shutterstock.com; Sharing food with friends at dining table, Gulcin Ragainboh/Shutterstock.com; p. 44: View Of Boy Sitting On Sofa Watching Cartoon On Television, Andrey_Popov/Shutterstock.com; p. 45: New construction home exterior with contemporary house, Artazum/Shutterstock.com; Interior of light bathroom with counters, sink and mirror, Pixel-Shot/Shutterstock.com; Interior of living room with green houseplants and sofas, Pixel-Shot/Shutterstock.com; Marble countertop with vases and flowers in provence style apartment, brizmaker/Shutterstock.com; Modern loft style bedroom in apartment, brizmaker/Shutterstock.com; p. 50: Group of elementary school kids running at school, Monkey Business Images/Shutterstock.com; woman and watching movies on tv, Stock-Asso/Shutterstock.com; a man and a girl eat tasty noodles, UliavonDmitrii/Shutterstock.com; students sitting in a cafe and following online lecture on the laptop, Milan Ilic Photographer/Shutterstock.com; Children watch cartoons on TV in the playroom, Sia Footage/Shutterstock.com; Irritated woman holding alarm clock in hand, Stock Holm/Shutterstock.com; p. 51: friends browsing the internet together on a laptop, RozhockaIvn/Shutterstock.com; p. 52: Two boys watching underwater documentary on TV, Levent Konuk/Shutterstock.com; little girl at the desk is writing, T.Vyc/Shutterstock.com; Kids practice reading together, Oksana Kuzmina/Shutterstock.com; woman and child doing laundry at home, Yuganov Konstantin/Shutterstock.com; Ringing and bouncing red alarm clock background, Varavan88/Shutterstock.com; spouses hanging a poster frame., Prostock-studio/Shutterstock.com; p. 53: TV or computer monitor showing a wild female lion, Kamira/Shutterstock.com; baby girl sitting on a sofa watching cartoons on television, Andrey_Popov/Shutterstock.com; Family watching a soccer moment on TV, Vasyl Shulga/Shutterstock.com; Young people, friends together in the cinema, L Lizardfms/Shutterstock.com; couple unpacking and decorating their new home, Studio Romantic/Shutterstock.com; p. 55: football game, PeopleImages.com - Yuri A/Shutterstock.com; p. 58: green grass for football sport, CHARTGRAPHIC/Shutterstock.com; muddy football field, Jasi/Shutterstock.com; neighborhood football field, Stefano Tammaro/Shutterstock.com; football field with goals, haski/Shutterstock.com; Abandoned football field with iron football goals, overgrown with grass, Vlad Kazhan/Shutterstock.com; p. 60: Teenage girl doing homework for school, JPC-PROD/Shutterstock.com; boy eating sandwich for lunch, all about people/Shutterstock.com; woman drinking a fresh glass of water at home, Krakenimages.com/Shutterstock.com; Family couple watching TV or movie on couch, Andrey_Popov/Shutterstock.com; boy getting his height measured, PeopleImages.com - Yuri A/Shutterstock.com; p. 61: man and woman at bus stop, Iryna Inshyna/Shutterstock.com; p. 62: children enjoying cartoons, Irina WS/Shutterstock.com; man wearing glasses, fizkes/Shutterstock.com; student at university, Roman Samborskyi/Shutterstock.com; Couple Enjoying Digital Tablet Technology Together, puhhha/Shutterstock.com; p. 63: students fighting indoors, CREATISTA/Shutterstock.com; Soccer player performs an action play on a professional stadium, Alex Kravtsov/Shutterstock.com; Boy and girl carry books together in the

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# Page 316

school's library, Robert Kneschke/Shutterstock.com; Cute little pupils having lunch outdoors, Pixel-Shot/Shutterstock.com; alarm clock , Dilok Klaisataporn/Shutterstock.com; p. 65: family playing chess game during camping trip, Evgeny Atamanenko/Shutterstock.com; p. 66: tropical beach, Aleksandr Ozercov/Shutterstock.com; forest, Denis Belitsky/Shutterstock.com; Rainforest ecosystem , Harusukac/Shutterstock.com; ice of winter, Katerina Parfenova/Shutterstock.com; view of Emerald Lake with snow covered and wooden lodge , Mumeromories/Shutterstock.com; p. 68: group of African safari animals composed together in a scene of the grasslands of Kenya, GoodFocused/Shutterstock.com; circus tent on green meadow against a colorful sunset sky, Framarzo/Shutterstock.com; Palm tree on tropical beach with blue sky and white clouds, Tonkitin/Shutterstock.com; A big white tent in the woods with camping equipments and lanterns, mr_bom/Shutterstock.com; breakfast table, New Africa/Shutterstock.com; p. 71: boy holding his sleeping newborn baby brother, FamVeld/Shutterstock.com; Making of crepes pancakes in open market festival fair, JGA/Shutterstock.com; Friendly young mother little daughter cook dessert , fizkes/Shutterstock.com; women taking a picture, Cast Of Thousands/Shutterstock.com; Barista pouring coffee from moka pot coffee maker to a coffee cup, amenic181/Shutterstock.com; Man standing next to his trekking tent and bike, Jens Bruer/ Shutterstock.com; p. 73: man doing housework , Elmur/Shutterstock.com; p. 74: Man Take out the trash, Kulikova Daria/Shutterstock.com; woman doing the dishes, Romix Image/Shutterstock.com; Housekeeping, JJ-stockstudio/Shutterstock.com; professional cleaning service worker, XArtProduction/Shutterstock.com; Washing floor with mop in bathroom, New Africa/Shutterstock.com; p. 80: classroom at elementary school with pupils following teacher lesson, GagliardiPhotography/Shutterstock.com; Various cleaning items and supplies in a bucket on the bathroom floor, Alexander Raths/Shutterstock.com; Woman hand plugging charging cable into pc digital tablet, AlpakaVideo/Shutterstock.com; Empty Signboard on Building Wall, Usuwana des/Shutterstock.com; p. 81: Chairs on the sandy beach near the sea, icemanphotos/Shutterstock.com; Compost from leftover food, Kmpzzz/Shutterstock.com; pp. 81, 100: Man throwing trash bag into bin outdoors, New Africa/Shutterstock.com; pp. 86, 251: dolls, Stephen M Brooks/Shutterstock.com; p. 82: woman washing plates at the kitchen, Krakenimages/Shutterstock.com; p. 83: Collecting Garbage For Sorting, Prostock-studio/Shutterstock.com; p. 84: Empty bowl, Ilya Akinshin/Shutterstock.com; Empty glass for water, DenisNata/Shutterstock.com; Plate, sangsiripetch/Shutterstock.com; Woman Smiling, Nadino/Shutterstock.com; Glass bottle of water, AlexZaitsvet/Shutterstock.com; Front view of an open, empty wide glass, Anton Starikov/ Shutterstock.com; child posing, TimImageProduction/Shutterstock.com; boy raise hand, Roman Samborskiy/Shutterstock.com; man laughing, Luis Molinero/Shutterstock.com; Empty glass for water, DenisNata/Shutterstock.com; p. 85: broken green bottle, pics five/ Shutterstock.com; hand during handcrafting a decorative bottle, Vitaly Vision/Shutterstock.com; Woman Filling a Reusable Plastic Bottle, Gorodenkoff/Shutterstock.com; man drinking water from a bottle, Johnstocker Production/Shutterstock.com; Hand holding a bottle of orange juice, Maryna Marchenko/Shutterstock.com; p. 86: Glass bottles of mixed colors, Inga Nielsen/Shutterstock.com; stamps from various countries, Nitr/Shutterstock.com; Set of knitted animals, Nadia Korol/Shutterstock.com; metal buttons, savva_25/Shutterstock.com; pp. 86, 251: dolls, Stephen M Brooks/Shutterstock.com; p. 89: Little boy ringing doorbell, stefanolunardi/Shutterstock.com; p. 90: dining room, Domenic Gareri/Shutterstock.com; book pile, stevemart/Shutterstock.com; alarm clock, BrAt82/Shutterstock.com; Teen girl and little boy using a magnifying glass, Sergey Ryzhov/Shutterstock.com; bedroom, Ground Picture/Shutterstock.com; Save world and environment concept, SKT Studio/Shutterstock.com; p. 91: Ornate decorative plate, Supermom/Shutterstock.com; woman painting pink heart, LariBt/ Shutterstock.com; p. 92: girl and boy using a magnifying glass, Sergey Ryzhov/Shutterstock.com; p. 93: teacher working with a Down syndrome schoolboy, Monkey Business Images/Shutterstock.com; p. 94: powder splatted background, piyaphong/Shutterstock.com; Explosion of red colored powder, piyaphong/Shutterstock.com; blue dust particles splash, Vandathai/Shutterstock.com; Explosion of colored powder on white background, piyaphong/Shutterstock.com; Explosion of colored powder isolated on white background, Jag_cz/Shutterstock.com; p. 99: Alarm On Mobile Phone, Monkey Business Images/Shutterstock.com; smiling woman wearing protective rubber gloves cleaning cupboard surface, Prostock-studio/Shutterstock.com; teenager looking at camera, tativotoshov/Shutterstock.com; home improvement and decoratio, Ground Picture/Shutterstock.com; p. 100: girl reading book, Pressmaster/Shutterstock.com; Young Football Players Kicking Ball on Soccer Field, matimix/Shutterstock.com; A child holding a tablet with red discharged battery on screen connected to socket, Andrii Spy_k/ Shutterstock.com; recycling, Ground Picture/Shutterstock.com; teacher and children group writing on copybook, Studio Romantic/ Shutterstock.com; p. 101: mother father and children watching TV, Evgeny Atamanenko/Shutterstock.com; hot weather, fukume/ Shutterstock.com; p. 102: Happy family riding in a car, Soloviova Liudmyla/Shutterstock.com; Soccer ball, MartiBstock/Shutterstock.com; Male craftsman painting a clay plates acrylic paints in art studio, BearFotos/Shutterstock.com; business woman, Dragana Gordic/ Shutterstock.com; Confused woman, sithiphong/Shutterstock.com; boy with glasses sitting on the grass, Diana Lotora Prada/Shutterstock.com; p. 103: puzzle, tadamichi/Shutterstock.com; oil paint, P Maxwell Photography/Shutterstock.com; Woman pressing key on keyboard, Pixel-Shot/Shutterstock.com; Dialog with questions, Fida Olga/Shutterstock.com; p. 105: happiness, Pixel-Shot/Shutterstock.com; p. 106: happy kids, M Agency/Shutterstock.com; p. 107: golf ball, Dan Thornberg/Shutterstock.com; bloc-volets, David Shih/Shutterstock.com; football, balle de football isolee sur fond blanc/Shutterstock.com; Basket-ball, FocusStocker/Shutterstock.com; tennis ball, Kapustin Igor/ Shutterstock.com; car parked in parking, myremuuyu/Shutterstock.com; pool in garden, hxdzbxy/Shutterstock.com; basketball court, SAND555UG/Shutterstock.com; tennis court, Denis Shitikoff/Shutterstock.com; wooden bench, BONNIE WATTON/Shutterstock.com; p. 112: playing hide a seek, BearFotos/Shutterstock.com; theatre, Honour.kn/Shutterstock.com; Stone Board Empty Table, AKA KerKer/ Shutterstock.com; p. 113: e-commerce , Arturs Budiekves/Shutterstock.com; recycling, JasminaK/Shutterstock.com; watching TV, Yuganon Konstantin/Shutterstock.com; student taking a test, fizkes/Shutterstock.com; worried ladies, Krakenimages/Shutterstock.com; students reading in class, Drazen Zigic/Shutterstock.com; house cleaning, New Africa/Shutterstock.com; p. 114: hiking, Slatan/Shutterstock.com; p. 115: basket ball playing, BalanceFormCreative/Shutterstock.com; p. 116: studying in the library, Media Photos/Shutterstock.com; p. 117: policeman, Pixel-Shot/Shutterstock.com; vet with dog, AnnaStills/Shutterstock.com; patient in clinic, Studio Romantic/Shutterstock.com; cooking, Hryshchyshen Serhi/Shutterstock.com; teacher walking in classroom, Rido/Shutterstock.com; p. 122: Tennis match, Pair Srinrat/Shutterstock.com; Little girls, Fab_1/Shutterstock.com; Dog kiss cat, Sritana/N/Shutterstock.com; p. 123: Woman With Shopping Cart In Supermarket, Prostock-studio/Shutterstock.com; Distance education, Evgeny Atamanenko/Shutterstock.com; women volunteers, Manoj Boonpeng/Shutterstock.com; Woman's hands hold seashells and starfish, SAG stock/Shutterstock.com; two young students studying together, PeopleImages.com - Yuri A/Shutterstock.com; camping tent , Pixel-Shot/Shutterstock.com; p. 124: farmer , Miladen Mitrinovic/ Shutterstock.com; p. 125: joyous handsome farmer , LightField Studios/Shutterstock.com; p. 126: Solar panels on a gable roof, MAXSHOT_PL/Shutterstock.com; p. 127: A brick fireplace in which a fire burns, Dmitrij Galacevic/Shutterstock.com; New roof, tile, Luca Rani/ Shutterstock.com; glazed terrace, Amelly Twintisy/Shutterstock.com; Sunblock lotion tubes and sunglasses on sandy beach, Oksana Mizina/ Shutterstock.com; Solar cell panels, leolating/Shutterstock.com; Metal tile, Potashev Aleksandr/Shutterstock.com; white billboard, F Photography R/Shutterstock.com; white sofas and wooden table, Smerichka Olena/Shutterstock.com; modern house with swimming pool, Cassanas Photography/Shutterstock.com; Iron gates, severjn/Shutterstock.com; p. 128: blue sky with bright sun, Guenter Albers/ Shutterstock.com; skogafoss waterfall, Vova Shevchuk/Shutterstock.com; rainbow in dramatic sky, Smit/Shutterstock.com; Aerial view, Ksenia Guzeleva/Shutterstock.com; Snow Moon Super Full Moon Dark, an artist/Shutterstock.com; p. 132: professor giving corrected answer sheets to student, Ground Picture/Shutterstock.com; Two hispanic students smiling happy painting , Krakenimages/Shutterstock.com

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com; Asphalt shingles roofing construction , ungvart/Shutterstock.com; Younger Brother Holding a Soccer Ball, Gorodenkoff/Shutterstock.com; Blank White Restaurant Sign Mockup Large, Uswatun des/Shutterstock.com; p. 133: Education Technology Internet Two Smiling Students, Ground Picture/Shutterstock.com; Little African Kid Just Woke, Anutri Yossundara/Shutterstock.com; DIY Recycled Mason Jar Crafting Idea for Candle Holder, Akhmad Dody Firmansyah/Shutterstock.com; smiling man placing art to shelf, Ground Picture/ Shutterstock.com; Portrait Two Brothers Lying On Bed, Anna Kuzmenko/Shutterstock.com; p. 134: Girl Opens Bottle Water, Anaite/ Shutterstock.com; Birthday party table decoration , Vugar/Shutterstock.com; p. 135: girl jumping on sofa excited on moving day, fizkes/ Shutterstock.com; woman watching movie, Just Life/Shutterstock.com; Grandfather and grandson planting a tree, Altrendo Images/ Shutterstock.com; couple playing tennis, VAKS-Stok Agency/Shutterstock.com; woman ringing intercom, New Africa/Shutterstock.com; going to school, ORION PRODUCTION/Shutterstock.com; Four colorful glass bottles in the garden, Blessilver/Shutterstock.com; p. 136: Solar panels and wind generators against city view on sunset, arjazz/Shutterstock.com; p. 137: turn off the lights, boonchoke/Shutterstock.com; p. 138: playing in the park, Galina Khruetskai/Shutterstock.com; p. 139: walking on the street , FamVeld/Shutterstock.com; playing football, Fotostokic/Shutterstock.com; Heat energy heap closely, red and yellow, Artikom Jumpamoon /Shutterstock.com; Calm water surface texture with splashes and bubbles, ganjalex/Shutterstock.com; Tyre track on dirt sand mud, surawach5/Shutterstock.com; Voice lesson, Master305/Shutterstock.com; children eat unhealthy high caloric sugary junk food, aslyum/Shutterstock.com; Green grass background top view garden, Mr.Somchai Sukkasem/Shutterstock.com; playing guitar, Nastyafly/Shutterstock.com; pp. 139, 173: High nature view large white clouds on soft sky background in the morning, Adhivasut/Shutterstock.com; p. 143: walking on the street , Maridav/Shutterstock.com; p. 144: girl snuggling a puppy, blessings/Shutterstock.com; riding a bike, Dean Drobot/Shutterstock.com; renewable energy, Diyana Dimitrova/Shutterstock.com; Small boy and cute dog on street, BearFotos/Shutterstock.com; p. 145: playing football, PeopleImages.com - Yuri A/Shutterstock.com; p. 146: flowers in bottles as decoration TaraPatta/Shutterstock.com; friends, Ground Picture/Shutterstock.com; old man ringing doorbell, pikselstock/Shutterstock.com; watching television, m.dipo/Shutterstock.com; pp. 146, 251: stamps, alexbug/Shutterstock.com; p. 147: Little girl helping her brother by holding his hand, BAZA Production/Shutterstock.com; boy on a bicycle in the park listens to his mother, Marian Fil/Shutterstock.com; p. 148: Small children having a glass of milk , YAKOBOCHUK VIACHESLAV/Shutterstock.com; p. 149: water in glass , Popov Nikolay/Shutterstock.com; orange juice in glass , Freedom Life/ Shutterstock.com; hot coffee in glass , 19 STUDIO/Shutterstock.com; milk in glass , PNOONIN/Shutterstock.com; tea in a cup, Ivan Chistyakov/Shutterstock.com; p. 150: coffee heap in bowl, HamsterMan/Shutterstock.com; tomato sauce in bowl, Aleksei Iuminov/ Shutterstock.com; mayonnaise in wooden bowl , MaraZe/Shutterstock.com; glass jar with honey, Olesia Bech/Shutterstock.com; bowl of mustard, MaraZe/Shutterstock.com; p. 151: Honey dipper isolated , Spalnic/Shutterstock.com; Photovoltaic solar panels , thanun vongsuravanich/Shutterstock.com; p. 154: Glass bottles, New Africa/Shutterstock.com; Veterinarian , Gorodenkoff/Shutterstock.com; Metal tile, Potashev Aleksandr/Shutterstock.com; entrance exam, Donjoy_2004/Shutterstock.com; safari animals, Kurit afshen/Shutterstock.com; Embracing the Great Outdoors, Travel Star/Shutterstock.com; p. 155: 4k monitor , Krivosheev Vitaly/Shutterstock.com; calm sea water wave, icemanphotos/Shutterstock.com; p. 156: leafs blown by wind , andreicu88/Shutterstock.com; Plastic bottle drinking water , Sergey Ryzhov/Shutterstock.com; man cooking pasta, New Africa/Shutterstock.com; soup in ceramic bowl , nesavinov/Shutterstock.com; empty wallet, Golubovy/Shutterstock.com; Red kidney beans, kariphotio/Shutterstock.com; p. 157: Waiter serving tea at restaurant, Africa Studio/ Shutterstock.com; sweet raspberry jam on toast, Pixel-Shot/Shutterstock.com; fresh vegetables salad, OlegD/Shutterstock.com; cuts the meat with knife, Komsan Loonprom/Shutterstock.com; p. 158: fast food , New Africa/Shutterstock.com; healthy food on table, New Africa/ Shutterstock.com; p. 159: buying dairy products at supermarket, Drazen Zigic/Shutterstock.com; p. 160: Different sorts of cheese, monticello/Shutterstock.com; jelly candies , New Africa/Shutterstock.com; beef steak, Mironov Vladimir/Shutterstock.com; Basket with different bread , Pixel-Shot/Shutterstock.com; Collection vegetables, ArtesiAD/Shutterstock.com; p. 161: basket with food fruits, grimmy/ Shutterstock.com; supermarket , Nickolay Khoroshov/Shutterstock.com; printing invoice , Simon Kadula/Shutterstock.com; trolley , artistypa/Shutterstock.com; Various vegetables, BearFotos/Shutterstock.com; p. 164: English flashcard of prepositions of place, smartman/ Shutterstock.com; p. 165: OK button on keyboard, Patryk Kosmider/Shutterstock.com; Boy hide under the bed, Johnstocker Production/ Shutterstock.com; Girl and grandmother with remote control eat popcorn , Prostock-studio/Shutterstock.com; Chairs Under Parasol In Sand Beach , Romolo Tavani/Shutterstock.com; Focused teen with down syndrome doing his homework at home, AYO Production/Shutterstock.com; p. 166: mobile phones , Eo naya/Shutterstock.com; Senior female eco and multicultural business people , Ground Picture/Shutterstock.com; smiling school girl kid, WESTOK PRODUCTIONS/Shutterstock.com; girl under umbrella, Valery Zotev/Shutterstock.com; adult identical twin men in glasses, fizkes/Shutterstock.com; p. 168: Businesswoman working alone, Monkey Business Images/Shutterstock.com; A little boy in the arms of his older brother, Marian Fil/Shutterstock.com; Students looking at watches, Prostock-studio/Shutterstock.com p. 169: School kids running in school corridor, Monkey Business Images/Shutterstock.com; Two Children Walking Through Bluebell Woods , Monkey Business Images/Shutterstock.com; Two cheerful girls drinking coffee, DecDonDec/Shutterstock.com; Female Veterinarian, Gorodenkoff/Shutterstock.com; Family couple choosing food in supermarket, fast-stock/Shutterstock.com; p. 170: Female supermarket employee , Drazen Zigic/Shutterstock.com; shopping at the supermarket, Stokkete/Shutterstock.com; p. 171: Woman and child cross the road, Sergey Ryzhov/Shutterstock.com; p. 172: Smoke detector with smoke, Happy Stock Photo/Shutterstock.com; Arrow sign pointing in different direction, Desintegrator/Shutterstock.com; Green color, FabrikaSm/Shutterstock.com; Red color, Kat Ka/Shutterstock.com; Fire extinguisher isolated , FOTO Eak/Shutterstock.com; Blue color, Kat Ka/Shutterstock.com; Purple color, Kat Ka/Shutterstock.com; burning flame, WIROJE PATHI/Shutterstock.com; traffic light, Veniamin Kraskov/Shutterstock.com; Yellow color, K.BOM/Shutterstock.com; p. 173: Car , pixel creator/Shutterstock.com; Sunlight in a green forest, Svetlana Orusova/Shutterstock.com; Street of upmarket townhouses, William Barton/Shutterstock.com; river , Akio Miki JP/Shutterstock.com; p. 179: Two Children Doing Homework Together In Kitchen, Monkey Business Images/Shutterstock.com; couple is cleaning kitchen, George Rudy/Shutterstock.com; Diverse but together, True Touch Lifestyle/Shutterstock.com; woman walking with old grandmother, Ground Picture/Shutterstock.com; Mom and her daughter are walking through a supermarket, bbernard/Shutterstock.com; p. 180: boy with a backpack, headphones and cellphone goes through the pedestrian crossing, Ground Picture/Shutterstock.com; p. 181: Sustainable transport, Michele Ursi/Shutterstock.com; p. 182: Schoolkid talking to his teacher, Dmytro Zinkevych/Shutterstock.com; p. 183: School breakfast , ArtSvetlana/Shutterstock.com; public library, Soho A Studio/ Shutterstock.com; basketball court, hxdxbzy/Shutterstock.com; school playground , TW Farlow Media/Shutterstock.com; Classroom with desks and chairs, pimpampix/Shutterstock.com; p. 184: wood floor on the second floor, Rung818/Shutterstock.com; Camping tent, Pixel-Shot/Shutterstock.com; Orange colored classic corrugated roof tiles, ColorMaker/Shutterstock.com; Green grass field lawn , Pronto/ Shutterstock.com; Empty wall-mounted shelves, NPvancheng55/Shutterstock.com; p. 187: corridor in College , smolaw/Shutterstock.com; p. 188: Little baby sitting near outdoor swimming pool, New Africa/Shutterstock.com; Female hands holding package of candies, progressman/Shutterstock.com; boy drinking glass of milk for breakfast, Relate/Shutterstock.com; Ads , Che Media/Shutterstock.com; Solar Panels on Red Tiled Roof, MAXSHOT.PL/Shutterstock.com; Straight pathway leading through a lush green forest park, Dmitry Naumov/ Shutterstock.com; veterinarian, SeventyFour/Shutterstock.com; p. 189: green glass bottles on wood table, af1962/Shutterstock.com; man cleans a living room with a mop, LightField Studios/Shutterstock.com; p. 190: man asking a driver to take him to the city, Dmytro

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Zinkevych/Shutterstock.com; p. 191: lost angry girl, Irina Shatilova/Shutterstock.com; p. 192: A man and a girl in love on a first date in autumn city park, alexkich/Shutterstock.com; p. 193: New black steering wheel isolated on white, New Africa/Shutterstock.com; Power generator, BigTunaOnline/Shutterstock.com; Car door, Aleksandr Kondratov/Shutterstock.com; Car battery charging, AlexanDior/Shutterstock.com; car tire, Kara Kate/Shutterstock.com; p. 197: Domestic cat under bed, Greentellect Studio/Shutterstock.com; Group of children with football soccer balls at training class, matmix/Shutterstock.com; dining in restaurant, Dean Drobot/Shutterstock.com; p. 198: father helping his son with homework, Ground Picture/Shutterstock.com; Broom on the threshold of a country house, Yevhen Roshchyn/Shutterstock.com; mother cleaning house , Prostock-studio/Shutterstock.com; Upset preteen boy sitting at sofa, People, Sports/Recreation/Shutterstock.com; red small car parked in front of a red brick building, Sandra Polo/Shutterstock.com; Full length photo of unhappy tired lady using chair, Roman Samborskyi/Shutterstock.com; Boy and two girls hide behind sofa, H_Ko/Shutterstock.com; p. 199: dog cuddling up to a person on the street, svatskaya iryna/Shutterstock.com; Father and daughter cleaning kitchen with gloves, iD Creator/Shutterstock.com; p. 200: Car on parking mountains black white, iD Creator/Shutterstock.com; Boy in wheelchair with phone and classmates at school, Africa Studio/Shutterstock.com; sad girl, Prostock-studio/Shutterstock.com; crossing crosswalk, Halfpoint/Shutterstock.com; Sweet tooth adult man make choice, Prostock-studio/Shutterstock.com; child drink milk portrait home, iD Creator/Shutterstock.com; p. 201: Teenage girl takes care of a fluffy long-haired domestic cat., Larisa Stefankij/Shutterstock.com; Group of children playing together on the floor indoors, New Africa/Shutterstock.com; p. 202: stressed man, rakt7/Shutterstock.com; Flat tire car leaky tire waiting roadsie, LightField Studios/Shutterstock.com; p. 203: Cancun beach view from a jet plane window, marikray/Shutterstock.com; p. 204: green forest trees, Darunrat Wongsuwan/Shutterstock.com; Passenger plane landing at the airport, Toni/Shutterstock.com; yacht, montart/Shutterstock.com; Modern suburban house in a residential neighborhood, Chalat photography/Shutterstock.com; Luxurious cat on the road, S_Sanketz7/Shutterstock.com; p. 205: warm village and green garden, artarty/Shutterstock.com; the 5 human senses, ozrimzor/Shutterstock.com; Fertile soil close-up for sowing plants, rssoil/Shutterstock.com; Orange sky with sun and clouds, New Africa/Shutterstock.com; summer vacation, Mc dia/Shutterstock.com; Beautiful spring garden, budistudio77/Shutterstock.com; p. 209: bedroom, decorated bed./Shutterstock.com; student with backpack, Pixel-Shot/Shutterstock.com; Traffic light road sign with green shape and light, rikstok/Shutterstock.com; Beautiful terrace with sea view on a sunny day, Olga Gavrilova/Shutterstock.com; Traffic light, road sign with green shape and light, rikstok/Shutterstock.com; p. 210: candy store, Kirill Spiridonov/Shutterstock.com; p. 211: "Validation" concept image, MaxxiGo/Shutterstock.com; A house with a roof covered in solar panels, Love Solutions/Shutterstock.com; businessman walking with a rolling suitcase, Prostock-studio/Shutterstock.com; road sign, Oualid/Shutterstock.com; p. 212: Beautiful aerial cityscape view of Leiden, Prostock-studio/Shutterstock.com; fluffy white clouds, EdwinP Nursalmi/Shutterstock.com; p. 213: students working on a robotics project, BGStock72/Shutterstock.com; pp. 214, 215: tourism, Sergiy Bykhunenko/Shutterstock.com; p. 215: yacht, Natalia Yaumenenka/Shutterstock.com; small plane, Thierry Weber/Shutterstock.com; yellow sports car, Andrii Nesterov/Shutterstock.com; modern house, photoworld2000/Shutterstock.com; p. 217: serious girl, Krakenimages.com/Shutterstock.com; annoyed little girl, fizkes/Shutterstock.com; little girl crying, Gecko Studio/Shutterstock.com; excited little girl, Irina Mikhailichenko/Shutterstock.com; sleepy little girl, Sorapop Udomsri/Shutterstock.com; p. 220: paper boat floating on water, digis/Shutterstock.com; boy riding a red bicycle, Michael Brin/Shutterstock.com; two cats, GPets/Shutterstock.com; flat tire, Rust Video/Shutterstock.com; p. 221: big house, Robert Crum/Shutterstock.com; candy and cookies, Africa Studio/Shutterstock.com; family going to the beach, Sunny studio/Shutterstock.com; student solving equations on the white board, Ground Picture/Shutterstock.com; sisters doing their homework at home, Prostock-studio/Shutterstock.com; woman preparing a pizza, Krakenimages.com/Shutterstock.com; p. 223: boy clamping a pillow over his ears, Ermolaev Alexander/Shutterstock.com; woman holding a t-shirt, fizkes/Shutterstock.com; friends watching a football game on TV, Oleggg/Shutterstock.com; man shopping at the supermarket, Hryshchevshyn Serhii/Shutterstock.com; girl helping her mother decorate a cake, Bangkok Click Studio/Shutterstock.com; children running at sunset, maxim ibragimov/Shutterstock.com; p. 224: boys eating artisanal sweets, ache1978/Shutterstock.com; grandkids helping their grandmother in the kitchen, Evgeny Atamanenko/Shutterstock.com; boy sharing his tablet with his little sister, Evgenyrychko/Shutterstock.com; p. 225: girl and boy talking, EZ-Stock Studio/Shutterstock.com; p. 226: girl asking classmate for help, Inside Creative House/Shutterstock.com; p. 227: tulip fields in Netherlands, Steve Photography/Shutterstock.com; Eiffel tower, john901/Shutterstock.com; Petra ruins, Bojtos Gabriella/Shutterstock.com; Egyptian pyramids, Mustafa Y Ibrahim/Shutterstock.com; skyscrapers, snaphtheframe/Shutterstock.com; p. 228: book, New Africa/Shutterstock.com; calculator, mayus85/Shutterstock.com; t-shirt, Peter Gudella/Shutterstock.com; backpack, Edwin Llerena/Shutterstock.com; pen, Mouse family/Shutterstock.com; p. 232: cat hiding under the bed, iD Creator/Shutterstock.com; man refusing to eat processed food, Makistock/Shutterstock.com; dad and son fishing together, New Africa/Shutterstock.com; p. 233: mother and daughter crossing at the traffic lights, M-Production/Shutterstock.com; solar panels on the roof of a building, Wirestock Creators/Shutterstock.com; vegetables in supermarket, Iris Sokolovskaya/Shutterstock.com; grandsons hugging their grandmother, PeopleImages.com - Yuri A/Shutterstock.com; p. 234: boy picking up waste in the forest, Daniel Cherioni/Shutterstock.com; siblings studying, Stokteke/Shutterstock.com; girl crossing road, Alliance Images/Shutterstock.com; friends at the movies, SeventyFour/Shutterstock.com; couple standing in front of a car, Rawpixel.com/Shutterstock.com; p. 235: sisters decorating bedroom, Connect Images - Curated/Shutterstock.com; woman adding sugar to her coffee, Kulinenko.G/Shutterstock.com; siblings visiting the Eiffel tower, Tomsickova Tatiana/Shutterstock.com; dog lying on a couch, New Africa/Shutterstock.com; p. 236: friends shopping together, MilanMarkovic78/Shutterstock.com; p. 237: boy and his father working on a solar system model , adriaticofoto/Shutterstock.com; p. 238: boy scuba diving, SewCreamStudio/Shutterstock.com; p. 239: wind twisted tree, angelaworks/Shutterstock.com; underwater view, silvae/Shutterstock.com; cracked soil, Ilonajallll/Shutterstock.com; blue sky, Art Stocker/Shutterstock.com; sec, singh srilom/Shutterstock.com; p. 243: girl riding a jet ski, YanLev Alexey/Shutterstock.com; p. 244: girl announcing good news to her friend, Roman Samborskyi/Shutterstock.com; teacher giving a high-five to her student to congratulate her, Drazen Zigic/Shutterstock.com; girl holding a model about renewable energy, Lysenko Andri/Shutterstock.com; aerial view of houses, Clare Louise Jackson/Shutterstock.com; three small boats, PrimI2/Shutterstock.com; parked cars, Tricky Shark/Shutterstock.com; p. 245: students studying in class, PeopleImages.com - Yuri A/Shutterstock.com; aerial view of the sea, Li haiato/Shutterstock.com; p. 246: man surfing, tubavin/Shutterstock.com; woman decorating glass bottle, Agnieszka Rybkiewicz/Shutterstock.com; man ringing doorbell, Ushuaia studio/Shutterstock.com; stamp collection, Somo_Somo/Shutterstock.com; p. 247: Kids eating a colorful lollipop, ORION PRODUCTION/Shutterstock.com; volunteers planting a tree, DC Studio/Shutterstock.com; boys playing football, Zamrnzuti tonovi/Shutterstock.com; p. 248: girls preparing to surf, Dean Drobot/Shutterstock.com; waterpolo, JoeSAPhotos/Shutterstock.com; p. 249: woman doing aqua gym, Ground Picture/Shutterstock.com; waterpolo, SGR/Shutterstock.com; windsurfing, Brjanc27/Shutterstock.com; scuba diving, walkincema/Shutterstock.com; swimming, Master305/Shutterstock.com; surfing, FOUR.STOCK/Shutterstock.com; p. 250: stamp collection, wika79/Shutterstock.com; p. 251: stuffed animals , monticello/Shutterstock.com; snow globes, Borschhevskyi Ole/Shutterstock.com; perfume bottles, Vladimir Razgulyaev/Shutterstock.com; p. 256: car and boat, ilmirnofoto/Shutterstock.com; singer, Reezky Pradata/Shutterstock.com; kayak, EB Adventure Photography/Shutterstock.com; student in library, iJeb/Shutterstock.com; open book, Jure Divich/Shutterstock.com; p. 257: woman in supermarket, Prostock-studio/Shutterstock.com; friends at the park, Studio Romantic/Shutterstock.com; veterinarian, fast-stock/Shutterstock.com; p. 258: old stamp, STILLFX/Shutterstock.com; students, SpeedKingz/Shutterstock.com; women on a plane,

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