# data[].attributes.headline
Complete the email using present simple form of the verb in the brackets.

# data[].attributes.subject
Complete the email using present simple form of the verb in the brackets.

# data[].attributes.headline
Complete the conversation using present continuous form

# data[].attributes.subject
Complete the conversation using present continuous form

# data[].attributes.body
28.09
2. how many
3.how much
4.how much many
5.how much
6.how many
7.how much

# data[].attributes.body
28.09
2.a lot of
3.a few
4.some
5.much
6.any
7. any some
8.some

# data[].attributes.body
23.09
2.Haven't got your pen
3.All my friends have got laptops
4.My grandfather hasn't got black hair
5.You have got a nice room
6.Have you got my book?
7.We haven't got a car
8.Has your sister got a big desk?

# data[].attributes.body
23.09
2.lives
3.had
4.doesn't have
5.loves
6.loves
7.doesn't like
8.is
9.doesn't like
10.is
11.doesn't work
12.is

# data[].attributes.body
23.09
2.Are they playing
3.They are playing
4.Is your doing
5.Doing
6.He's doing
7.Not doing
8.He's watching

# data[].attributes.headline
Among the landmarks in..., I want to visit...the most.

# data[].attributes.subject
Among the landmarks in..., I want to visit...the most.

# data[].attributes.body
30.09
Among the landmarks in Sydney, I want to visit Sydney Harbour Bridge the most.
Among the landmarks in Singapore, I want to visit Marina Bay Sands the most.
Among the landmarks in Los Angeles, I want to visit Walt Disney Concert Hall the most.
Sydney is famous for its operaS.
Singapore is famous for its seaportS.
Los Angeles is famous for its tourist attractionS.

# data[].attributes.body
28.09
2. How many
3. How much
4. How much
5. How much
6. How many
7. How much

# data[].attributes.body
28.09
2. a lot of
3. a few
4. some
5. much
6. any
7. any
8. some

# data[].attributes.body
30.09
Among the landmarks in Hong Kong, I want to visit Disneyland the most.
Among the landmarks in Singapore, I want to visit Merlion Park the most.
Among the landmarks in Malaysia, I want to visit Petronasa Twin Towers the most.
Hong Kong is famous for its Disney characters.
Singapore is famous for its parks.
Malaysia is famous for its tourist attractions.

# data[].attributes.body
05.10
2. heavier, the heaviest
3. harder, the hardest
4. more exciting, the most exciting
5. cheaper, cheapest
6. more expensive, the most expensive
7. better, the best
8. worse, the worst

# data[].attributes.body
05.10
2. the biggest
3. better
4. worse
5. cheapest
6. more exciting

# data[].attributes.body
23.09
2. lives
3. had
4. doesn't have
5. loves
6. loves
7. doesn't like
8. is
9. don't like
10. were
11. don't work
12. was

# data[].attributes.body
23.09
2. Are they playing
3. They are playing
4. What are you doing
5. am doing
6. What is he doing?
7. is not doing
8. is watching

# data[].attributes.body
23.09
2. I haven't got your pen
3. All my friends have got laptops
4. My grandfather hasn't got black hair
5. You have got a nice room
6. Have you got my book?
7. We haven't got a car
8. Has your sister got a big desk?

# data[].attributes.body
05.10
A
1.heavier, heaviest
2.harder, hardest
3.more exciting, most exciting
4.cheaper, cheapest
6.more expensive, most expensive
7.better, best
8.worse, worst

# data[].attributes.body
05.10
B
2.the biggest
3.better
4.harder
5.the cheapest
6.more exciting

# data[].attributes.headline
Look at the pictures of Ben and complete the sentences about him. Use too / enough and the adjectives BELOW

# data[].attributes.subject
Look at the pictures of Ben and complete the sentences about him. Use too / enough and the adjectives BELOW

# data[].attributes.body
small     heavy      short     young     old       strong     long    big

# data[].attributes.body
07.10
1. is playing
2. 'm not usually wearing
3. Do you know
4. 're having
5. aren't
6. has

# data[].attributes.body
07.10
2. are watching
3. are eating
4. watching
5. are coming
6. cooks
7. doesn't cook
8. gets
9. travels

# data[].attributes.body
07.10
2. too old, young enough
3. too heavy, short enough
4. too small, big enough

# data[].attributes.headline
Correct the mistakes. Write a complete sentence 

# data[].attributes.subject
Correct the mistakes. Write a complete sentence 

# data[].attributes.body
12.10
2. a bowl of soup
3. a can of beans
4. a cup of tea
5. a glass of orange juice
6. a plate of chips
7. a piece of cheeses
8. a box of chocolates

# data[].attributes.body
12.10
2. box
3. can
4. dish
5. bottle
6. piece
7. cup

# data[].attributes.body
12.10
2. I want
3. I need
4. I have
5. is
6. like
7. Do you know

# data[].attributes.body
2. don't have to
3. have to
4. have to
5. have to
6. have you
7. have your mother

# data[].attributes.body
19.10
2. don't have to
3. have to
4. have to
5. have to
6. Have you
7. Have your mother

# data[].attributes.body
6. Do you have to
7. Does your mother have to

# data[].attributes.body
Does your mother have to work every day?

# data[].attributes.body
Does your mother has to work every day?

# data[].attributes.body
21.10
2. him
3. them
4. you
5. you
6. me

# data[].attributes.body
21.10
2. Did, had to
3. Do, have to
4. Do, have to
5. Did, had to
6. Do, have to
Match to the answers
2. d
3. f
4. b
5. c
6. e

# data[].attributes.body
1/
2.him
3.her
4.it
5.you
6.me
2/
2.Do-have to      d
3.Do-have to       f
4.Do-have to       b
5.Does- have to     c
6.Do-have to       e

# data[].attributes.body
28.10
2. biology 2. g
3. physics 3. h
4. geography 4. e
5. chemistry 5. c
6. history 6. a
7. language 7. f
8. maths 8. i
9. sport 9. d

# data[].attributes.body
28.10
2. fail
3. study
4. pass
5. learn
6. take

# data[].attributes.body
28.10
2. us
3. him
4. We
5. it
6. They
7. us
8. They
9. I
10. them
11. It

# data[].attributes.body
1/
2.biology-g
3.physics-h
4.geography-e
5.chemistry-c
6.history-a
7.language-f
8.math-i
9.sport-d
2/
2.take
3.study
4.pass
5.learn
6.fail
3/
2.us
3.him
4.we
5.it
6.they
7.us
8.they
9.I
10.them
11.it

# data[].attributes.body
2. take

# data[].attributes.body
2.11
2. were
3. decided
4. hated
5. joined
6. liked
7. moved
8. showed
9. wanted
10. began
11. felt
12. found
13. got
14. gave
15. left
16. met
17. won

# data[].attributes.body
2.were
3.decided
4.hated
5.joined
6.liked
7.moved
8.showed
9.wanted
10.began
11.felt
12.found
13.got
14.gave
15.left
16.met
17.won

# data[].attributes.body
4
3. don't eat
4. buy
5. don't forget
6. visit
7. be
8. don't travel

# data[].attributes.body
1
2. throw / catch
3. draws
4. slept / leave
5. drive / give
6. won
7. taught
8. hearing / seeing

# data[].attributes.body
2
2. enjoyed
3. choosed
4. spent
5. bought
6. paid
7. drank
3
2. didn't go
3. didn't buy
4. didn't keep
5. didn't drive
6. wasn't

# data[].attributes.body
2.were
3.decided
4.hated
5.joined
6.liked
7.moved
8.showed
9.wanted
10.began
11.felt
12.found
13.got
14.gave
15.left
16.met
17.won

# data[].attributes.body
4.11
2. throw, catch
3. draws
4. slept, left
5. drove, gave
6. won
7. taught
8. hearing, seeing

# data[].attributes.body
4.11
2
2. enjoyed
3. choosed
4. spent
5. bought
6. paid
7. drank
3.
2. didn't go
3. didn't buy
4. didn't keep
5. didn't drive
6. wasn't

# data[].attributes.body
4.11
3. don't eat
4. buy
5. don't forget
6. visit
7. be
8. don't travel

# data[].attributes.body
1.
2/ throw, catches
3/draws
4/slept, leaves
5/drive, give
6/won
7/taught
8/hearing, seeing

# data[].attributes.body
2.
2/enjoyed
3/choosed
4/spent
5/bought
6/paid
7/drank
3.
2/didn't go
3/didn't buy
4/didin't keep
5/didn't drive
6/wasn't

# data[].attributes.body
Grammar
3.Don't eat
4.Buy
5.Don't forget
6.Visit
7.Be
8.Don't travel

# data[].attributes.body
2. threw, caught
3. drew
4. slept, left
5. drove, gave
6. won
7. taught
8. heard, saw

# data[].attributes.body
Vocabulary:
2.straight
3.turning
4.over
5.on
6.traffic

# data[].attributes.body
1.a
Library: 5
Restaurant: 4
Post office: 8
Police station: 7
Supermarket: 3
castle: 6
theatre: 1
b.
b/ theatre
c/ post office
d/ supermarket
e/ police station
f/ museum
g/ restaurant
h/ garage

# data[].attributes.body
2. straight
3. turning
4. over
5. on
6. traffic

# data[].attributes.body
1a
library: 5
restaurant: 4
post office: 8
police station: 7
supermarket: 3
castle: 6
theatre: 1
1b
b theatre
c post office
d supermarket
e police station
f castle
g restaurant
h garage

# data[].attributes.body
9.11
2. straight
3. turning
4. over
5. on
6. traffic

# data[].attributes.body
9.11
1a
library: 5
restaurant: 4
post office: 8
police station: 7
supermarket: 3
castle: 6
theatre: 1
1b
b. theatre
c. post office
d. supermarket
e. police station
f. castle
g. restaurant
h. garage

# data[].attributes.headline
Film a video telling about your health problem

# data[].attributes.subject
Film a video telling about your health problem

# data[].attributes.body
11.11
1
2. was watching
3. were playing
4. was raining
5. was your brother doing
6. wasn't playing
7. were writing
2
2. was starting
3. decided
4. was getting
5. turned on
6. was downloading
7. called
8. was wanting
9. waited
10. was listening
11. saw

# data[].attributes.body
18.11
2. a
3. b
4. c
5. e
6. d

# data[].attributes.body
23.11
3. in
4. at
5. at
6. in
7. on
8. on
9. at
10. on
11. on
12. on

# data[].attributes.body
23.11
1. A
2. C
3. C
4. B
5. B
6. A
7. B

# data[].attributes.body
3.in
4.at
5.at
6.in
7.on
8.in
9.at
10.on
11.on
12.on

# data[].attributes.body
1.A
2.C
3.C
4.A
5.B
6.B
7.C

# data[].attributes.body
1. A
2. C
3. B
4. A
5. C
6. B
7. C

# data[].attributes.body
25.11
2. washing
3. to come
4. walking
5. to drive
6. passing