# data[].attributes.body
1. On Sartuday
2. On Christmas
3.at the weekends
4. At 10 o'clock
5.on next weeks
6. In 2008
7. In the winter
8. For breakfast
9. Nothing
10. Nothing
11. At 6.am
12. Nothing
13. On 14 August
14. In a year's time
15 nothing
16in
17 nothing
18 in
19 for three years
20 at 13:00

# data[].attributes.body
2. at christmas
3.on the week
4.at 10 o'clock
5.noting
6 in 2008
7 in the winter
8 nothing
9 in the afternoon
10 for a long time
11 at 6 a.m
12 for two weeks
13 on 14 august
14 for a year's time
15 on my birthday
16 nothing
17 in the evening
18 for three years
19 at 13

# data[].attributes.body
on sunday
on/at christmas
on/at the weekend
in 2008
at 10 o'clock
on/at the winter
for breakfast
for a long time
at 6a.m
for 2 weak
on august
in the evening
for three years
at 13:00
on my birthday
in a year's time

# data[].attributes.body
1. on saturday
2. at christmas
3. in the weekend
4. at 10 o'clock
5. next weeks
6. in 2008
7. in the winter
8. for breakfast
9. this afternoon
10. a long time
11. at 6 am
12. for two week
13. on 14 august
14. a year's time
15. yesterday
16. on my birthday
17. today
18. in the evening
19. for three years
20.  at 13:00

# data[].attributes.body
on satrurday
on christmas
in the weekend
at 10 o'clock
on next weeks
in 2008
for the winter
for breakfast
for this afternoon
at 6am
in two weeks
on 12 august
at yesterday
on my birthday
at today
for the evening
in three years
at 13:00

# data[].attributes.body
1. On Saturday
2. On Christmas
3. In the weekend
4. At 10 o'clock
5. Nothing
6. In 2008
7. In the winter
8. Nothing
9. Nothing
10. Nothing
11. At 6a.m
12. For two weeks
13. On 14 August
14. Nothing
15. Nothing
16. On my birthday
17. Nothing
18. In the evening
19. For three years
20. At 13.00

# data[].attributes.body
1. on Saturday
2. on Christmas
3.  in the weekend
4. at 10 o'clock
5. next week
6. in 2008
7. in winter
8. at breakfast
9. this afternoon
10. for a long time
11. at 6 a.m
12. for two weeks
13. on 14 August
14. a year's time
15. on my birthday
16.  today
17. in the evening
18. for three years
at 13:00

# data[].attributes.body
1 on saturday
2 on chrismas
3 at the weekend
4 at 10 o'clock
5 on next week
6 in 2008
7 in winter
8 breakfast
9 on this afternoon
10 for for a long time
11 at
12 at
13 on 14 august
14 a year's time
15 yesterday
16 on my birthday
17 today
18 in the evening
19 for three years
20 at 13.00

# data[].attributes.body
A3
B4
C5
D6
E2
F1

# data[].attributes.body
A3
B4
C5
D6
E2
F1

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

# data[].attributes.body
1 - F
2 - E
3 - A
4 - B
5 - C
6 - D

# data[].attributes.body
A -
B
C
D
E
F

# data[].attributes.body
A - 3
B - 4
C - 5
D - 6
E - 2
F -1

# data[].attributes.body
F-1
A-3
B-4
C-5
D-6
E-2

# data[].attributes.body
A - 3
B -  4
C - 5
D - 6
E - 2
F - 1

# data[].attributes.body
A - 3
B - 4
C - 5
E - 2
F - 1
D - 6

# data[].attributes.body
1/ Does the price include meals ?
2/Do you use local hotels?
3/Is

5/How much is the travel's commission
6/Does the price include tranport
7/Do group leaders get free for travel and accommodation?

# data[].attributes.body
1. Does the price meals include?
2. Do you use local hotels
3. Is there the discount for groups?
4. How much the discount  ?
5. How much is the comisstion?
6. Does the price transpot inlcude ?
7. Do groups leader get free travel and accommodation ?

# data[].attributes.body
1. Does the price include meals?
2. Do you use local hotel?
3. Is there a discount for group?
4. How much is the discount?
5. How much is the travel's commission?
6. Does the price include transport?
7. Do group leaders and accommodation get free?

# data[].attributes.body
VIẾT CÂU:
1
2
3
4
5
6
7

# data[].attributes.body
1. Does the price meals include?
2. Do you use local hotels?
3. Is there a discount for groups?
4. How much is the discount?
5. How much is the travel's commission?
6. Does the price include transpost?
7. Do groups leaders get free travel and accommodation?

# data[].attributes.body
1 Does the price include meals?
2 Do u use local hotels?
3 Is there  a discount for groups?
4 How much is the discount?
5 How much is the travel's comission?
6 Does the price include transport ?
7 Do group leaders get free travel and accomodation?

# data[].attributes.body
1 Does the price include meals ?
2 do you use local hotels?
3 Is there a discount for groups?
4 How much is the discount?
5 how much is the travel's commision ?
6 Does the price include  transport ?
7 do group leader get free travel and accommodation ?

# data[].attributes.body
1. Does the price include meals?
2. Do you use local hotels?
3. Is there a discount for groups?
4. How much is the discount?
5. How much is the travel's commission?
6. Does the price include transport?
7. Do get travel accommodation and group leaders free?

# data[].attributes.body
1) does the price include meals?
2) do you use local hotels?
3) is there a discount for group ?
4) how much is the discount ?
5) how much is travel's commission ?
6) does the price include transport?
7) do group leaders get free travel and accommodation ?

# data[].attributes.body
1
2
3
4
5
6
7
8
9
10

# data[].attributes.body
1. Advantages
2. Save
3. Cheaper
4.
5.
6. Price
7.
8.
9.
10.
11.

# data[].attributes.body
1
2
3
4 IN BULK
5 IN ADVANCE
6
7
8 ACCOMMODATION
9
10 TRAVELLER
11

# data[].attributes.body
1. advance
2. saving
3. cheaper
4. bulk
5. advance
6.
7.
8.
9.
10.
11.

# data[].attributes.body
1.advance
2. saving
3. cheaper
4. bulk
5.advance
6.price
7. seat
8.accommodation
9. services
10.
11. low

# data[].attributes.body
listening
1 advantage
2
3 cheaper
4
5
6
7
8
9
10
11

# data[].attributes.body
1 advantage
2 saving
3
4 bulk
5 advan
6 servecies
7
8
9

# data[].attributes.body
1/
2/SAVING
3/CHEAPER
4/BULK
5/ADVANCE
6/PRICE
7/SEATS
8/ACCOMMODATION
9/
10/TRAVELLERS
11/

# data[].attributes.body
1/ ADVANTAGES
2/ SAVING
3/ CHEAPER
4/ BULK
5/ ADVANCE
6/ PRICE
7/ SEATS
8/ ACCOMMODATION
9/ SERVICES
10/ TRAVELLERS
11/ LOW

# data[].attributes.body
1. advantages
2. saving
3. cheaper
4. bulk
5. advance
6. prices
7. seats
8. accommodation
9. service
10. travellers
11. low

# data[].attributes.body
1
2 salling
3 cheper
4 buck
5 advance
6 prices
7
8
9
10 traveling
11 advantage

# data[].attributes.body
Listening Operator

1.  Advantage
2.
3.. Cheaper
4.  In bulk
5.  Advance
6.

# data[].attributes.body
Listening
1) advantage
2)saving
3) cheaper
4)  bulk
5) advance
6) prices
7) seats
8) accomodation

9) services
10) traveller

11) low

# data[].attributes.body
1. C is looking
2. B Finish
3. D is waiting
4. A to use
5. A at
6. C is taking place
7.  C for
8. D for
9 C to work
10. A Speaking
11. C are
12. D is/are
13. B to smile
14. A At 7.30a.m
15. D because

# data[].attributes.body
1. C is looking
2. B finish
3. D is waitting
4. A to use
5. At
6. C is talking place
7. For
8. B about
9. B working
10. B speak
11. C Are
12. A is/has
13. B To smile
14 a at
15. D because

# data[].attributes.body
1/A.LOOK
2/B.FINISH
3/IS WAITING
4/A.TO USE
5/A.AT
6/C.TAKEING PLACE
7/C.FOR
8/D.FOR
9/B. WORKING
10/ A.SPEAKING
11/C.ARE
12/D.IS/ARE
13/B.TO SMILE
14/A.AT
15/D BECAUSE

# data[].attributes.body
1. is looking
2. finish
3. is waiting
4. to use
5. at
6. is talking place
7. for
8. for
9. working
10. speaking
11. are
12. is/are
13. to smile
14. at
15. because

# data[].attributes.body
1. C. is looking
2. B. finish
3. D. is waiting
4. A. to use
5. A. at
6. B. take place
7. C. For
8. B. About
9. B. working
10. B. Speak
11. A. is
12. B. has/are
13. B. to smile
14. A. at
15. D. Because

# data[].attributes.body
1 C IS LOOKING
2 B FINISH
3 D IS WAITTING
4 A  TO USE
5 A AT
6 IS TAKING PLACE
7 C FOR
8 D FOR
9 B WORKING
10 B SPEAKING
11 C ARE
12 B HAS/ ARE
13 B TO SMILE
14 A AT
15 D BECAUSE

# data[].attributes.body
1 is looking
2 do
3 is waiting
4 to use
5 at
6 taking place
7 about
8 for
9 working
10 spoken
11 are
12 is/are
13 smiles
14 at
15 because of

# data[].attributes.body
1. is looking
2. finish
3. is waiting
4. to use
5. at
6. is taking place
7. For
8. for
9. working
10. speaks
11. are
12. is/are
13. to smile
14. at
15. because

# data[].attributes.body
1 is looking
2 do
3 is waiting
4 use
5 at
6
7 about
8 about
9 to work
10 speak
11 are
12 is/are
13 smiles
14 at
15 because

# data[].attributes.body
GRAMMAR
1 is looking
2 finish
3 is waiting
4 use
5 at
6 takes place
7 about
8 for
9 working
10 speaking
11 are
12 is/ are
13 to smile
14 at
15 because

# data[].attributes.body
Grammar
1.  C is looking
2.  B Finish
3.  A Wait
4.  A To use
5.  A At
6.  C Is taking place
7.  D About
8.  D For
9.  A Work
10.  B Speaking
11.  C Are
12.  D Is/Are
13.  B To smile
14.  A At
15.  D Because
16.

# data[].attributes.body
Grammar
1) C: is looking
2) B: finish
3) D: Is waiting
4) A: to use
5) A: At
6) C: is taking place
7) C: For
8) B: about
9) B: Working
10)A: speaking
11)C: Are
12) D: is/ are
13) B: to smile
14)  A: At
15) D: Beacause

# data[].attributes.body
1) C receptionist
2) C domestic tourism
3) A. friendly
4) C. Shy
5) C. full time
6) A. tourist attractions
7) B. Theme park
8) D inbound
9) C. heritage
10) A. Coastline
11) C in large quantities
12) B. Flight attendant
13)D. Tour operators
14) C VFR
15) A tourist informaiton office
16) C chef
17) C friendly

# data[].attributes.body
1. C reception
2. C Domestic tourism
3. A friendly
4. D shy
5. A shift
6. ATourist atraction
7. B them park
8. C outbound
9. C Heritage
10. A coastline
11.b  In large quantities
12.b  Flight aittendant
13. D Tour guides
14.a  Inclusive tours
15. A Tour infomation
16. Chef
17. Hand working

# data[].attributes.body
1 c receptionist
2 domestic tourism
3 a friendly
4 d shy
5 a shift
6
7 B THEME PARK
8 D INBOUND
9 C HERITAGE
10 A COASTLINE
11 A ON THE INTERNET
12 B FLIGHT ATTENDENT
13 D TOUR OPERATORS
14 D INDIVIDUAL TOUR
15 A TOUR INFORMATION OFFICER
16 C CHEF
17 D ORGANIZED

# data[].attributes.body
Review Vocabulary
1.  C. Receptionist
2.  C. Dometics Tourims
3. A. Friendly
4. D. Shy
5. A. Shift
6.  A. Tourist attractions
7.  A. Theme Park
8. D. Inbound
9. C. Heritage
10.   A. Coastline
11. C. in large quantities
12. B. Flight Attendent
13. D. Tour operator
14. A. inclusive tour
15. A. tourist informations office
16.  C. chef
17.  D. organized

# data[].attributes.body
1 receptionist

2 domestic tourism
3 friendly
4 shy
5 full time
6 tourist attractions
7theme park
8 inbound
9 herytage
10 coastline
11 in large quantities
12 flight attendant
13 tourguide
14
15 tourist information officer
16 restaurant manager
17 friendly

# data[].attributes.body
review vocabulary
1) C: receptionist
2) C: domestic tourism
3) A: friendly
4) D: shy
5) A: shift
6) A: tourist attraction
7) B: Theme park
8) C: inbound
9) C: heritage
10) A: coastline
11) B:  In a large quanities
12)  B: flight attendant
13) D:  Tour Operators
14) A: inclusive tour
15) A: tourist information officer
16) B: restaurant manager
17) D: organized

# data[].attributes.body
1/ receptionist
2 / domestic tourism
3/ freindly
4/ nervous
5/ full time
6/ tourist attractions
7/ theme park
8/ inbound
9/ heritage
10/coastline
11/ in large quantities
12/ flight attendant
13/
14/inclusive tour
15/ tourist information offer
16/chef
17/ friend

# data[].attributes.body
Review Vocabulary
1.  C Receptionist
2.  C Domestic tourism
3.  A Friendly
4.  D Shy
5.  D Broken
6.  A Tourist attractions
7.  B Theme park
8.  D Inbound
9.  C Heritage
10.  A Coastline
11.  B In large quantities
12.  B Flight attendant
13.  D Tour operator
14.  A Inclusive tour
15.  A Tourist information officer
16. C Chef
17. C Friendly

# data[].attributes.body
1/C.RECEPTIONNIST
2/C.DOMESTIC TOURISM
3/A.FRIENDLY
4/D. SHY
5/A. SHIFT
6/A TOURIST ATTACTIONS
7/B.THEME PARK
8/D. INBOUND
9/C.HERITAGE
10/A. COASTLINE
11/B. IN LARGE QUANTITIES
12/B FLIGHT ATTENDANT
13/D. TOUR OPERATORS
14/A. INCLUSIVE TOUR
15/A. TOURIST INFORMATION OFFICER
16/C.CHEF
17/D.ORGANIZED

# data[].attributes.body
1. ceceptionist
2. domestic tourism
3.friendly
4.shy
5.shift
6. tourist attractions
7. theme park
8. Inbound
9. heritage
10. coastline
11.  in large quantities
12. flight attandant
13. tour operator
14. inclusive
15. tourist infomation officer
16. chef
17. hardworking

# data[].attributes.body
1. Receptionist
2. Domestic tourism
3. Friendly
4. Shy
5. Shift
6. Tourist attractions
7. Theme park
8. Inbound
9. Herritage
10. Coastline
11. In large quantities
12. Flight attendant
13. Tour operators
14. Inclusive tours
15. Tourist information officer
16. Chef
17. Organized

# data[].attributes.body
REVIEW VOCABULARY
1. RECEPTIONIST
2. domestic tourism
3. friendly
4. shy
5. shift
6. accomm
7. theme park
8.
9. heritage
10. coastline
11. in secret
12. waiter
13. managers
14.
15. touris information office
16. chef
17. hardworking

# data[].attributes.body
1/
2/
3/
4/
5/