Examples of Modal Auxiliaries

Definition of Modal Auxiliaries

Modal auxiliaries are used where some deduction is needed for a situation. Here deduction means drawing a conclusion about a situation based on the available information.

Examples of Modal Auxiliaries

• Merry is looking so sleepy; she must have studied the whole night.
• Aric is absent at the meeting. He must not have arrived the city yet.
• Lisa couldn’t have broken the paperweight. She was absent in the office yesterday.
• I can’t find Allen’s assignment here. He must not have done it. (Assuming he did not do it)
• Andrew was hospitalized for a week, so he couldn’t have done the assignment. (Knowing it’s impossible for him to do)
• Jack is looking so exhausted. He must have worked the whole day at the office.
• Rick is absent in the program. He must not have arrived here yet.
• Paul is definitely going to love this movie. All the action sequences are so excellent, exactly the type he likes.
• The boys will definitely be thrilled when they will come to know that they are going on an excursion to the hills.
• You will definitely be excited when you will come to know that your favorite singer is coming to the concert.
• Your math test is at 10:00 am. You should get ready now.
• Can you please help him to do the work? It should take five minutes only.
• Bob has an exam He shouldn’t go out now.
• Alana is starting from home so early. She shouldn’t be late.
• George has a concert on next Tuesday. He should start rehearsing now.
• Jeff has an important exam this week. He should not leave the city now.
• Jen’s flight is at 3 pm. She should start from home now.
• You have to submit the project report tomorrow morning. You should complete it now.
• Can you show him the way to the Chairman’s room? It should take a few seconds only.
• Samantha has prepared herself so well for the exam. She shouldn’t get poor marks.

The types of modal auxiliaries based on the usage include:

• Modal Auxiliaries for Surety
• Modal Auxiliaries for Expectation
• Modal Auxiliaries for Probability