JPH0895484A - Education apparatus - Google Patents

Abstract

PURPOSE: To make it possible to realize explanation of solution along with the understanding of respective learners by forming the explanation by applying the solution which is one of solutions for questions correctly answered by the learners in the past and is most similar to the solution to be explained, in the case of explaining the solution to the learners. CONSTITUTION: Whether the answer made by the learner obtd. by an answer input means 102 is correct or not, is diagnosed by an answer diagnosing means 103. The correctly answered question is stored in a learned question storage file 104 if the diagnosis is correct answer. The result of the diagnosis is displayed for the learner by a display means 110. The question is selected by a selecting means 105 in the case of incorrect answer. The degree of similarity of the selected question and the learned question of the learned question storage file 104 is calculated by a degree of similarity calculating means 106. The learned question most similar to the question selected by a selecting means 105 is determined from the learned questions of the file 104 in accordance with the degree of similarity. The question to be applied in formation of the explanation of the answer is selected by an applied question selecting means 107. The explanation of the solution is formed by an explanation forming means 109 and is displayed by the display means 110.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an educational apparatus for generating explanations of a solution to a learner's answer.

[0002]

2. Description of the Related Art When explaining to a learner how to solve a calculation problem that involves combining several formulas, the teacher is most likely to choose from among the problems that the learner has answered correctly in the past. Select a similar problem and teach with an explanation that uses the relationship between the selected problem and the presented problem.

[0003]

When the teacher explains the solution of the problem to one learner, the method as described in the prior art is sufficient. However, in an actual educational setting, there are many learners taught by teachers, and there are various problems that each learner has answered correctly in the past.
It cannot be said that each learner is instructed with an appropriate solution by using only one example of the solution taught by the teacher.

Further, the burden of one teacher managing all the problems that each learner has correctly answered in the past is enormous, which is impossible in practice.

The present invention has been made in view of such a situation, and the problem that the learner has answered correctly in the past and the problem most similar to the problem that the learner has answered in the past has been explained. Is used to realize automatic generation by a computer.

[0006]

In order to solve such a problem, the present invention selects a question from an unacquired question storage file and presents it to the learner, and the learner's answer to the question presented by the answer input means. The learning device stores the questions that the learner has correctly answered in the past in an educational device that diagnoses the correctness of the learner's answer with the answer diagnosis means and displays the output data to be displayed to the learner with the display means. A file, a selection means for selecting a question, a similarity calculation means for calculating a similarity between the question selected by the selection means and a question stored in the learned question storage file, and applied to generation of explanation of a solution It is characterized by further comprising an applied question selecting means for selecting a question to be executed, an applied question storage file for storing the question selected by the applied question selecting means, and an explanation generating means for generating an explanation.

[0007]

When the learner's correct answer is managed by the learned problem storage file and the learner needs to explain the solution, the problem selected by the selecting means and the learned problem storage file are stored in the learned problem storage file. The similarity to the stored learned question is calculated by the similarity calculation means, and the problem to be applied to the generation of the explanation of the solution is selected from the applied problem selection means based on the value of the similarity obtained from the similarity calculation means. Then stored in the application problem storage file, and applying the application problem stored in the application problem storage file from the explanation generation means,
It is possible to generate the explanation of the solution.

[0008]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described with reference to FIGS. Note that the same reference numerals denote the same objects throughout the drawings.

FIG. 1 shows the system configuration of an educational device in an embodiment of the present invention. In the figure, 101 is an unacquired question storage file for storing questions to be presented to learners, 102
Is an answer input means for obtaining the answer of the learner, 103 is an answer diagnosis means for diagnosing the correctness of the answer, 104 is a learned question storage file for storing the questions that the learner has answered correctly in the past, 105
Is a selecting means for selecting a question, and 106 is a similarity calculating means 1 for calculating the similarity between the question selected by the selecting means 105 and the question stored in the learned question storage file 104.
Reference numerals 06 and 107 are applied question selecting means 107 and 108 for selecting a question to be applied to the generation of the explanation of the solution method. , 11
Reference numeral 0 is a display means for displaying output data.

The question stored in the unacquired question storage file 101 is presented to the learner, the learner's answer to the presented question is obtained from the answer input means 102, and the learner's answer is obtained from the answer input means 102. Answer diagnosis means 10
When the diagnosis result of the answer from the answer diagnosis means 103 is correct, the correct answer is stored in the learned question storage file 104, and the diagnosis result of the answer is displayed to the learner by the display means 110. If the answer diagnosis result is incorrect, a question is selected from the selection means 105, and the similarity between the selected question and the learned question stored in the learned question storage file 104 is calculated by the similarity calculation means 106. Based on the value of the similarity calculated by the similarity calculation means 106, the learned question most similar to the question selected by the selection means 105 from the learned questions stored in the learned question storage file 104 is calculated. The problem to be applied to the generation of the explanation of the solution, including the determined and already-acquired problem, is selected by the applied problem selection means 107 and stored in the applied problem storage file 108. Generated from description generating unit 109 a description of Algorithm Using application problems stored in file 108,
The diagnosis result of the question or the answer or the explanation of the solution is displayed to the learner by the display means 110.

FIG. 2 shows the hardware configuration of the terminal according to the present invention. In the figure, 201 is a display for displaying output data, 202 is a keyboard for receiving input data, 203 is an external storage device for storing data, 20
Reference numeral 4 denotes a main storage device that temporarily stores input / output data and programs, and 205 denotes an external storage device 203 to the main storage device 2.
The system program called in 04 is executed, and 20
Display 201 and keyboard 20 connected to 5
2, a CPU that controls input / output operations of the external storage device 203 and the main storage device 204.

The unacquired question storage file 101 is stored in the external storage device 203, and is output as an unacquired question to the main storage device 204 under the control of the CPU. The learned question storage file 104 is stored in the external storage device 203, and is output as a learned question to the main storage device 204 under the control of the CPU. The application problem storage file 108 is stored in the external storage device 203, and is output as a solution generation application problem to the main storage device 204 under CPU control.

The unlearned questions stored in the main storage device 204 are displayed on the display 201 under the control of the CPU.

The learner's answer to the presented question is input from the keyboard 202 and output to the main storage device 204 under the control of the CPU.

Correct / wrong diagnosis of answers, management of learned question storage file 104, selection of questions required for similarity calculation, calculation of similarity of questions, selection of learned questions applied to generation of explanation of solution, application problem storage file The CPU manages 108 and generates an explanation of the solution according to the processing procedure of the system program stored in the main memory 204.

The generated solution explanation is displayed on the display 201 under the control of the CPU.

FIG. 3 shows the data structure of the problem in the present invention. As shown in FIG. 3, it is assumed that the problem is that the data structure is made up of the address of the parameter n to be obtained and the addresses of the parameters 1 to n-1, which are prerequisites, or the addresses of the known number n and the known number n.

FIG. 4 shows the data having the data structure shown in FIG. 3 in a tree structure. The processing operation of this embodiment will be described below with reference to the flowchart shown in FIG.

The unlearned questions stored in the unlearned question storage file 102 are presented to the learner (step 50).
1), the learner's answer to the presented question is obtained from the answer input means 102 (step 502), and the answer input means 10
The answer diagnosing means 103 diagnoses whether the answer obtained from 2 is correct (step 503).

In step 504, when the diagnosis result of the answer is correct, the presented unacquired question is stored in the learned question storage file 104 as a learned question, and the diagnosis result is displayed to the learner by the display means 110. (Step 5
15-step 516). The diagnosis result of the answer is incorrect,
When the process of loop1 (steps 505 to 513) is the first time, the selection means 105 selects the question presented to the learner (step 506), and when the process of loop1 is the second time or later, the selection means 105. A more unshared subproblem is selected (step 507).

With respect to the question selected by the selecting means 105 and the learned question stored in the learned question storage file 104, partial questions to be shared / non-shared are acquired (step 508).

Based on the shared / non-shared sub-problems obtained in step 508, the similarity calculation means 106 calculates the similarity between the question selected by the selection means 105 and the learned question (step 509).

In step 509, the similarity calculation means 1
Based on the value of the similarity calculated from 06, from among the learned questions stored in the learned question storage file 104,
A learned question most similar to the question selected by the selection means 105 is determined (step 510).

In step 511, if there is a sub-problem that is common to the learned problem that has been decided and the problem that has been selected by the selection means 105, then the application problem to be applied to the generation of the explanation of the solution is selected from the application selection means 107 and applied It is stored in the question storage file 108 (step 512). If there is no shared sub-problem, the explanation of the solution is generated using the application problem stored in the application problem storage file 108 (step 5).
14), the diagnosis result of the answer and the explanation of the generated solution are displayed on the learner by the display means 110 (step 51).
6).

In step 511, if there is a partial question that is not shared with the question that has been learned and the question that has been selected by the selection means 105, then steps 513 to 505.
If there is no non-shared sub-problem, the explanation of the solution is generated using the application problem stored in the application problem storage file 108 (step 514), the diagnosis result of the answer and the description of the generated solution. Is displayed to the learner by the display means 110 (step 516).

The processing operation of this embodiment will be described below using data examples. FIG. 6 shows a learner's unacquired problem in this embodiment, and this problem is presented to the learner.

FIG. 7 shows the unlearned problem 1 shown in FIG.
8 is shown as a tree structure based on the data structure of FIG. 8, and FIG. 8 is shown as a tree structure based on the data structure of FIG. Learner 1
Assumes that the problem shown in FIG. 8 has been solved in the past and has been answered correctly.

The unacquired question 1 shown in FIG. 7 is stored in the unacquired question storage 101 file, and the learned question of the learner 1 shown in FIG. 8 is stored in the learned question storage file 104. To do.

Present question 1 to learner 1 (step 50
1), the answer of the learner 1 to the presented question is obtained from the answer input means 102 (step 502), and the answer input means 1
The correctness of the answer of the learner 1 obtained from 02
The diagnosis is made from 3 (step 503 to step 504).

When the diagnosis result of the answer of the learner 1 is correct, the problem 1 is stored as a learned problem in the learned problem storage file 104, and the learner 1 receives the diagnosis result of the answer as shown in FIG. indicate. (Step 515 to Step 81
6). If the diagnosis result of the answer of the learner 1 is incorrect, the question 1 is selected by the selecting means 105 (step 5).
06).

With respect to the learned problems 2, 3, 7 stored in the learned problem storage file 104 and the problem 1 selected by the selection means 105 in step 506, respective shared / non-shared partial problems are acquired. (Step 50
8) Based on the acquired shared / non-shared sub-problems, the learned problems 2, 3, 7 and the problem 1 selected by the selection means 105.
Is calculated by the similarity calculation means 106 (step 509).

Based on the value of the similarity calculated in step 509, the learned question 2 is selected as the question most similar to the question 1 (step 510).

At step 510 in the three loop 1 processes, the learned problem 2, the learned problem 3, and the learned problem 2 are sequentially selected based on the calculated similarity value.

FIG. 9 shows a shared partial question and a non-shared partial question with the learned question selected in step 510 according to the similarity value calculated by the question selected by the question selecting means 105 and obtained in three loop 1 processes. Indicate a problem.

Until the second processing of loop1, there is a shared partial problem with the problem selected by the selection means 105, so the learned problems 2 and 3 are applied selection means 107 as the application problems to be applied for generating the explanation of the solution. It is further selected and stored in the application question storage file 108 (step 512). l
When the processing of oop1 is the third time, the learned problem 2 and step 5 selected from the similarity value in step 510
Since the problem 4 selected by the selecting means 105 in 07 does not have a shared sub-problem, the explanation of the solution is generated by using the applied problem stored in the applied problem storage file 108 (step 514), and FIG. The diagnostic result of the answer shown in and the explanation of the generated solution are displayed on the learner 1 by the display means 110 (step 516).

FIG. 11 shows the learned problems of the learner 2 in this embodiment in a tree structure based on the data structure of FIG. 3, and the learner 2 has solved these problems in the past and has correctly answered them. I shall.

When the learner 2 needs to explain the solution method, in step 510 in one loop 1 process, the learned question 5 is selected based on the calculated similarity value. However, the learned question 5 and the selection means are selected. Since the problem 1 selected from 105 does not have a shared partial problem, the learned problem 5 and the non-shared partial problem 4 are stored in the applied problem storage file 108, and the explanation of the solution method is generated using these problems. , The explanation of the diagnostic result of the answer and the generated solution as shown in FIG.

FIG. 12 shows a shared partial question and a non-shared partial question with the learned question selected in step 510 according to the similarity value calculated by the question selected by the question selecting means 105 and obtained in one loop 1 process. Indicate a problem.

For the learner 1 who has correctly answered the problem shown in FIG. 8 in the past, the explanation as shown in FIG. 10 is given, and the problem as shown in FIG. By giving an explanation as shown in FIG. 13 to a certain learner 2, it is possible to provide each learner with an appropriate solution instruction.

[0040]

As described above, according to the present invention, when a solution is explained to a learner, a solution to a problem that the learner has correctly answered in the past, and a solution most similar to the solution to be explained is applied. By generating the explanation by doing so, it is possible to realize the explanation of the solution method according to the understanding of each learner.

[Brief description of drawings]

FIG. 1 is a diagram showing a configuration of an embodiment of the present invention.

FIG. 2 is a diagram showing a hardware configuration of an embodiment of the present invention.

FIG. 3 is a diagram showing a data structure of a problem in an embodiment of the present invention.

FIG. 4 is a diagram showing a tree structure of the data structure shown in FIG.

FIG. 5 is a diagram showing the operation of the embodiment of the present invention.

FIG. 6 is a diagram showing an example of a problem presented to a learner.

FIG. 7 is a diagram showing the problem shown in FIG. 6 in a tree structure.

FIG. 8 is a diagram showing an example of a learned problem that the learner 1 has correctly answered in the past in a tree structure.

FIG. 9 is a diagram showing an example of a shared subproblem and a non-shared subproblem used for generating an explanation of a solution to a learner 1.

FIG. 10 is a diagram showing an example of a diagnosis result of an answer to the learner 1 and an explanation of a generated solution.

FIG. 11 is a diagram showing, as a tree structure, a learned problem that the learner 2 has correctly answered in the past.

FIG. 12 is a diagram showing an example of a shared subproblem and a non-shared subproblem used to generate an explanation of a solution to a learner 2.

FIG. 13 is a diagram showing an example of a diagnosis result of an answer to the learner 2 and an explanation of a generated solution.

FIG. 14 is a diagram showing an example of a diagnosis result of a solution method for a learner who correctly answers the presented problem.

 ─────────────────────────────────────────────────── ─── Continuation of the front page (72) Hiroyuki Yoshida, 1006 Kadoma, Kadoma City, Osaka Prefecture Matsushita Electric Industrial Co., Ltd. (72) Satoshi Kajita, 1006 Kadoma, Kadoma City, Osaka Matsushita Electric Industrial Co., Ltd. 72) Inventor Kazuyuki Imagawa 1006 Kadoma, Kadoma City, Osaka Prefecture Matsushita Electric Industrial Co., Ltd.

Claims (1)

[Claims] 1. An unacquired question storage file for storing a question to be presented to a learner, a learned question storage file for storing a question that the learner has answered correctly, and an answer input means for obtaining the answer of the learner. , Answer diagnosing means for diagnosing whether the answer is correct, selecting means for selecting a question, and similarity calculation for calculating a similarity between the question selected by the selecting means and the question stored in the learned question storage file Means, an application problem selection means for selecting a problem to be applied to the solution explanation generation, an application problem storage file for storing the problem selected by the application problem selection means, an explanation generation means for generating an explanation, and output data. Display means for displaying, presenting the question stored in the unacquired question storage file to the learner, and obtaining the answer of the learner to the presented question from the answer input means. If the correctness of the learner's answer obtained from the answer input means is diagnosed by the answer diagnosis means, and the diagnosis result of the answer obtained from the answer diagnosis means is correct, the correct question is stored in the learned question storage file. Then, the diagnosis result of the answer is displayed to the learner by the display means, and if the diagnosis result of the answer is incorrect, the question is selected by the selecting means and stored in the learned question storage file. The similarity between the learned question and the selected question is calculated by the similarity calculating means, and the problem to be applied to the generation of the explanation of the solution is selected by the applied problem selecting means based on the value of the similarity obtained by the similarity calculating means. Stored in the applied question storage file, and a description of the solution method using the applied problem stored in the applied question storage file is generated by the explanation generation means, and a diagnosis result or solution of the problem or answer is generated. An educational apparatus comprising means for displaying a method explanation to a learner from the display means.