Lin baowei （林 宝尉）
RESEARCH TITLE:
Computer-Supported Self-Questioning Exercises and Its Authoring
INTRODUCTION:
BACKGROUND
WHAT IS SELF-QUESTIONING
It is a learning strategy that guides a student performance before during and after a task performance.
Example 1: Readers pose questions what they understand to improve the retention.
Example 2: Readers pose questions what they not yet understand to improve the comprehension.
Example 3: Readers pose questions what are not given directly in the text. (the answer is came out by analyzing the whole contect)
WHY IS SELF-QUESTIONING
It can improve the students awareness and control of their thinking. This in turn improves their performance.
It improves long time retention of knowledge and skills.
It can improve the ability to apply and transfer knowledge and skills what the student learns.
It improves attitude and motivation.
SELF-QUESTIONING STRATEGIES
Step 1: Attend to Clues as you read.
Step 2: Say some questions.
Step 3: Keep Predictions in Mind
Step 4: Identify the answer.
Step 5: Talk about the answer.
BASED RESEARCH
Mr. Kunichika’
s system have four functions such as:
To understand English sentences
To generate various kinds of question sentences automatically
To select a suitable question for a learner from a set of generated question sentences
To analyze learner's answer sentences and to diagnose errors
DETAILS
For Teacher’s Authoring Model
Input the learning materials to ‘Automated question generation system’ to generate questions and answers.
To modify the sentences from 1 and to save the sentences into database.
To view the categorization of the questions’ type.
To select the clue words for student’s self-questioning model.
To select the clue words for student's self-questioning model.
For Student’s Self Questioning Model
Example:
The text is as following:
John had breakfast at eight this morning. Then he went to West Park on a blue bicycle.
He sat on a white bench in the park. There was a red bicycle near the small bench.
Step 1: Teacher should prepare the text firstly.
Step 2: learners select a clue word what he feel interesting about from the clue list.
John had breakfast at eight this morning......
Step 3: Based on the selected word, system generate all of the possible questions and its answers.
Then support the interrogative pronoun to learner. (technique of automated generation system)
Who had breakfast this morning?
---john had breakfast this morning.
Who went to west park on a blue bicycle?
---john went to west park on a blue bicycle.
What kind of bench did john sit on?
---it is a kind of white bench.
When did john had breakfast?
---john had breakfast at eight this morning.
Where is the white bench?
---it is in the park.
learner select one of the interrogative pronoun what he/she would like to.
here the system support the words as:
who , when, where, what
Step 4: If there are more than one interrogative pronouns exist,
system should support the sub words to learner to be selected.
here the system support the words as:
Breakfast, West Park
Step 5: System support the related words based on selected words, and
learner construct question sentence with the supported words.
so the generation words now are:
at, this, had, eight, morning, breakfast, who
Step 6: ①learner selects and manages the words to generate the question sentence.
②Then compare the question to the already exist one in the system.
③Give the feedback to the learner.
At last, the question should be:
----Who had breakfast at eight this morning?
INTERFACES
...........
FUTURE RESEARCH
The evaluation experiment of the system
To add the technique of NLP (nature language processing)
1.Support lively feedbacks for learners
2.Add ‘why’ questions to perfect the categories of questions
3.Add the automatically analyzing and diagnosis functions to reduce the workload of teacher