JPH08171342A - Accounting learning method - Google Patents

Abstract

PURPOSE: To provide the accounting learning device which auto-matically generates problems to set them to a learner and outputs a correction message corresponding to the error discrimination result. CONSTITUTION: A problem template is selected from a classified problem template storage part 1, and a noun in the problem template is used as the keyword to retrieve a parameter table storage part 2, and numerical values adapted to the numerical range obtained as the result are set to the problem template, and the noun in the problem template is used as the keyword to retrieve a noun table storage part 3, and nouns obtained as the result are set to the problem template, and a rule stored in a problem sentence generation rule storage part 4 is applied to generate the problems to be set from the problem template, and generated problems are displayed on a display device 7, and correct answers of set problems are generated, and answers inputted from an input part 5 by the learner are compared with correct answers to discriminate the error, and the discrimination result is used to select a correction example from a correction template storage part 6, and the answer correction result for the learner is generated from the correction example and is displayed on the display device 7.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an accounting learning device capable of learning bookkeeping by itself.

[0002]

2. Description of the Related Art As a conventional accounting learning device, there is, for example, "accounting learning device" (Japanese Patent Laid-Open No. 5-333761).

FIG. 22 is a block diagram of a conventional accounting learning device. In the figure, 17 is a journal question storage unit that stores a large number of journal entries, 18 is a correct answer storage unit that stores the correct answers to the questions in the journal question storage unit, and 19 is an input unit for learners to input their answers. , 20 is a correctness / incorrectness determination unit for determining correctness / incorrectness of a question in the journal entry storage unit, 21 is a control unit for controlling display on a display or operation of the correctness / incorrectness determination unit in response to an input signal, and 22 is in response to a signal from the control unit Is a display that outputs predetermined information.

Next, the operation of the conventional accounting learning device will be described. First, the control unit 21 outputs the question in the journal entry question storage unit to the display. When the answer to this question is input by the input unit 19, the control unit 21 operates the correctness determination unit 20 to determine the correctness. In addition, the correct answer storage section 18 is operated according to the input signal of the input section to output the correct answer of the question to the display.

[0005]

Since the conventional accounting learning device is configured as described above, it has the following problems.

First, all the problems and their correct answers have to be prepared in advance, so that the burden of preparing teaching materials is very heavy.

Secondly, since only the correctness of the learner's answer is determined, only two kinds of messages, "correct answer" and "incorrect answer", can be output to the learner. Therefore, it was not possible to properly point out errors, and the learning effect of the system was low.

The present invention has been made in order to solve the above-mentioned problem. The problem is automatically generated from a problem template stored in advance, and the question is given to a learner. It is an object of the present invention to provide an accounting learning device having a method of comparing with a correct answer to judge an error, and outputting a correction message according to the error judgment result.

[0009]

In order to solve the above problems, the accounting learning method according to the present invention comprises a journal question template storage unit storing a large number of question templates for journal questions, and a noun and the noun. A parameter table storage unit that stores a range of possible numerical values, a noun table storage unit that holds a noun and a noun group associated with the noun, and a question sentence generation rule storage unit that holds a rule for generating an actual problem An input unit for the learner to input a problem request and a solution to the problem, and a correction template storage unit for storing a correction template corresponding to an error in the learner's answer,
It is provided with a display for displaying a journalizing question and a correction result, a control unit for controlling the storage unit, the display, and the input unit.

[0010]

According to the present invention, with the above-described structure, first, a question template is selected from the journal question template storage unit.
Next, the parameter table storage unit is searched using the noun described in the question template as a keyword. And, the numerical value that fits the range of numerical values obtained as a result of searching is
Set it in the problem template. The noun described in the question template is used as a keyword to search the noun table storage unit, and the noun obtained as a result of the search is set as the question template. Further, the rules stored in the question sentence generation rule storage unit are applied to generate a question to be actually given from the question template. Next, while displaying the generated question on the display, the correct answer of the question to be asked is generated. Here, if the learner inputs the answer from the input unit,
The entered answer and the correct answer are compared to determine the error. Then, the correction example is selected from the correction template storage unit using the result of the error determination, and the answer correction result of the learner is generated from the correction example. Finally, the result of the learner's answer correction is displayed on the display.

By the above processing, in this method, the journal entry question to be given to the learner can be automatically generated, and further, the correction message according to the learner's error can be output.

[0012]

Embodiments of the accounting learning method of the present invention will be described below with reference to the drawings.

FIG. 1 is a block diagram of an accounting learning device for realizing an accounting learning method according to an embodiment of the present invention. In the figure, 1 is a journal question template storage unit that stores a lot of question templates for journal entries, 2 is a parameter table storage unit that stores a noun and a range of numerical values that the noun can take, and 3 is a noun as a key. , A noun table storage unit capable of retrieving a noun having the same concept as the noun, 4 a problem sentence generation rule storage unit holding a rule for generating an actual problem, and 5 a learner's answer to the problem An input unit for inputting, a correction template storage unit for storing a correction template corresponding to an error in a learner's answer, a display for displaying a journalizing question and a correction result, a reference numeral 8 for the storage unit, the display and the input unit Is a control unit for controlling.

Next, the operation of the accounting learning device will be described. Figure 2
Is a data flow diagram of the present embodiment. First,
The learner 9 requests a problem from the input unit 5 of FIG. In response to the question request, the journal entry question generation process 10 selects the question template stored in the journal entry question template storage unit 1. Next, the parameter table storage unit 2 is searched by using the noun described in the question template as a keyword. Then, a numerical value that matches the numerical value range obtained as a result of the search is set in the question template. In addition, the noun described in the question template is used as a keyword to search the noun table storage unit 3, and the noun obtained as a result of the search is set in the question template. further,
The rules stored in the question sentence generation rule storage unit 4 are applied to generate a question to be actually given from the question template, and the question is given to the learner 9. The learner sends the answer to the given question to the error correction processing 12. On the other hand, the journal entry question generation processing 10 sends the question data of the question that has been asked to the journal entry question answer generation processing 11. The journal question answer generation process 11 generates answer data indicating a correct answer from the sent question data. The error correction process 12 compares the learner's answer with the correct answer to determine an error, generates a correction result of the learner's answer using the correction template stored in the correction template storage unit 6, and Display to.

Next, the data structure of the data shown in FIG. 2 and the flow chart of each process will be described by using concrete problems and solution examples.

First, the data structure of the question template will be described. FIG. 3 shows an example of the question template. The question template is composed of two types of question data, which shows the framework of the question to be generated, and scene data which shows the scene where the cost actually occurred. The problem data is a title that indicates the problem template, a situation description, a list of scenes in which costs were generated in this problem (scene list), a noun variable list to which a noun should be assigned when the problem is generated, and a numeric variable list to which a numerical value should be assigned when the problem is generated As a member. In addition, the scene data includes the name (title) of the scene where the cost is incurred, the situation description,
Destination name, actual amount paid, consumption tax classification, amount details (contents), noun variable list, numeric variable list, payment method, debit account, credit account, problem item that can be selected in this scene It has as a member a flag that indicates whether to select it as a scene. Note that "<...>" is a noun variable and indicates a noun that is a keyword of a noun table to be referred to. In addition, "{...}" is used as a numerical variable and indicates a noun that is a keyword of the parameter table to be referred to.
Further, in the amount column of the scene data, the formula for calculating using the numerical value of the numerical variable list is entered.

Next, the data structure of the parameter table, the noun table, and the question sentence generation rule will be described. FIG. 4 shows an example of these data. The parameter table is used when generating journal entries (noun, range of numerical values, unit)
It is a table that is a set. This table is used to assign numerical values to the variables in the numerical variable list. The noun table is a table holding a noun and a noun having the same concept as the noun. This table is used when assigning nouns to variables in the noun variable list. The question sentence generation rule is described by an IF-THEN expression rule. In the journal question generation process, this generation rule is applied to generate an actual problem.

Next, the operation of the journalizing question generation process will be described. FIG. 5 is a flowchart of the journalizing question generation process.
First, one question template is selected from the journal entry question template storage unit. Here, it is assumed that the question template of FIG. 3 is selected as an example. Next, one scene is selected from the scene list of the question data. Then, it is determined whether or not the selected scene is set as a question, and a flag of scene data is set. Next, the parameter table storage unit is searched by using the numeric variable in the numeric variable list as a keyword.
Then, a numerical value that matches the numerical range obtained as a result of the search is set in the numerical variable. Further, the noun variable in the noun variable list is used as a keyword to search the noun table storage unit, and the noun obtained as a result of the search is set as the noun variable. Finally, the amount of money for the selected scene is calculated using a numerical variable in which a numerical value is set, and set in the amount column. The above process is performed for all the scenes in the scene list, and after all the settings are completed, the rules stored in the question sentence generation rule storage unit are applied to generate the actual questions to be asked from the question template. And display it on the display. Note that FIG. 6 shows an example in which the question data and the scene data set from the template in FIG. 5 are generated, and a question is generated from FIG. 6 using the question sentence generation rule and displayed on the display. By performing the above processing, the journalizing question generation processing can freely change the numerical values and nouns to create the themes, and further, depending on the value of the flag in the scene data, the partial problem of the problem indicated by the problem template. Can be generated.

In the journal question generation process, at the same time as displaying the question on the display, the question data of the question presented in the journal question answer generation process is sent. The journal question answer generation process uses the sent question data to generate answer data that is the correct answer to the question. FIG. 8 shows correct answer data of the problem of FIG. The answer data is composed of a debit account item and a credit account item, and item data is stored in each item. The course data includes account items, amounts, consumption tax classifications, a list of scenes to which these courses correspond, correct course data (correct course), results of error correction processing (judgment),
It consists of correction sentences (correction). In addition, the correct answer subject, judgment,
Correction is an item used in error correction processing. Moreover, the amount of money is the amount of money before consumption tax calculation.

Next, the operation of the journal entry answer generation process will be described. FIG. 9 shows a flowchart of the journal entry answer generation process. First, select the scene to be asked from the question data.
Next, a scene having the same debit account item as the selected scene is selected. Then, the total amount of money for the selected scene is calculated. Next, the item data is generated, and the account item, the amount, the consumption tax category, and the scene list are set. As described above, the item data of all debit account items is generated and set as the debit account item of the answer data. Next, an answer is generated for the credit account item. Generating an answer for a credit account is exactly the same as generating an answer for a debit account. As a result, answer data that is the correct answer to the given question is generated. If another solution exists, all possible correct solutions are generated. FIG. 10 shows an example of question data in which another solution exists, and FIG. 11 shows a result of the journalizing question answer generation process generating a correct answer from the question data.

Next, a method for the learner to input an answer will be described. For the learner, the journal entry answer input menu shown in FIG. 12 is displayed together with the question. The journal entry solution answer input menu is the journal entry table 13, the account item button 14 in which the account items can be entered, and the consumption tax category button 1 in which the consumption tax category is entered.
5. The control button 16 controls the menu. The learner uses the input section to press the account item button and consumption tax category button in the journal entry answer input menu, enter the account item and consumption tax category in the journal, and select the amount column in the journal to select the amount. Enter. FIG. 13 shows an example in which the learner inputs the answer to the problem shown in FIG. Further, when the consumption tax calculation button, which is one of the control buttons, is pressed here, the consumption tax is automatically calculated and displayed as shown in FIG. If the learner determines that the answer has ended, he / she presses the answer end button. When the answer end button is pressed, the input unit creates answer data from the result input by the learner. FIG. 1 is shown in FIG.
The result which produced | generated the answer data from the input result of 4 is shown. The amount of money is the amount before the consumption tax is calculated.

Next, the operation of the error correction processing will be described. FIG. 16 is a flowchart of the error correction process. First, an error is determined by comparing all correct answer data including another answer with the learner's answer. Next, the learner's answer having the smallest error determination result and the corresponding correct answer are selected.
Then, using the error determination result as a key, an example is acquired from the correction template storage unit shown in FIG. 17, and a correction sentence is generated. Finally, a correction sentence is set in the correction column of the subject data in the answer of the learner, and the correction result is displayed on the display. FIG. 18 shows an example of displaying the correction result to the learner.

Next, a method of comparing the answer data of the learner with the correct answer data will be described. FIG. 19 is a flowchart of the routine. First, the difference between the learner's answer data and the correct answer data subject is obtained, and the combination of the correct answer subject and the learner's subject with the smallest difference is selected. Next, according to the difference between the learner's subject and the correct answer subject, a subject error, an amount error, and a consumption tax classification error are set in the judgment column of each subject. If the learner's error in the amount of money is in the amount of money and in the amount of error in the subject, both the amount of money and the error of the subject are set. Now, even if all the subjects in the answer of the learner have been judged, if there is still a correct subject that is not associated, create empty subjects in the answer of the learner as many as the correct subject and omit it. It is judged as an error, and the correct answer subject, judgment column, and correction column are set. On the contrary, if all the correct answer subjects are associated with each other, but there is a surplus in the learner's answer subjects, the surplus subjects are determined as redundant errors and set in the determination column of the subject.
Note that FIG. 20 shows the types of errors set in the judgment column of the subject data.

As described above, according to this embodiment, the question and the correct answer can be automatically generated from the question template stored in the journal entry question template storage unit. Further, the correction message in the correction template storage unit can be output according to the error of the learner.

In the above description, the noun table storage unit is expressed as a table holding a noun and a noun group having the same concept as the noun, but this is a reference systematized between words as shown in FIG. It is clear that even a dictionary having a relationship can obtain the same effect as that of the above embodiment.

[0026]

As described above, according to the present invention,
Since the question and the correct answer are automatically generated from the question template, it is not necessary to prepare all the questions and their correct answers in advance, and as a result, the burden of preparing teaching materials is reduced. Also,
Since the correction message according to the learner's error can be output, the learning effect is enhanced, and the practical effect is large.

[Brief description of drawings]

FIG. 1 is a configuration diagram of an accounting learning device according to an embodiment of the present invention.

FIG. 2 is a data flow diagram of the embodiment.

FIG. 3 is a diagram showing an example of a question template of the embodiment.

FIG. 4 is a diagram showing an example of a parameter table, a noun table, and a question sentence generation rule of the same embodiment.

FIG. 5 is a flowchart of journalizing question generation processing according to the embodiment.

FIG. 6 is a diagram showing an example of [question] data and [scene] data output by the journalizing question generation process of the embodiment.

FIG. 7 is a diagram showing an example of a question generated by the journalizing question generation process of the embodiment.

FIG. 8 is a diagram showing answer data indicating a correct answer to the question of FIG. 7;

FIG. 9 is a flowchart of the journal entry answer generation process of the same embodiment.

FIG. 10 is a diagram showing an example of question data in which a plurality of account items as answers exist.

11 is a diagram showing an example of answer data generated from the question data of FIG.

FIG. 12 is a diagram showing an example of a journal entry answer input menu displayed in the embodiment.

FIG. 13 is a diagram showing an example of inputting an answer to a journal entry answer input menu.

FIG. 14 is a diagram showing an example of pressing a consumption tax calculation button in a journal entry answer input menu.

FIG. 15 is a diagram showing an example of answer data generated from the answers in FIG.

FIG. 16 is a flowchart of an error correction process of the same embodiment.

FIG. 17 is a diagram showing a correction template storage unit of the embodiment.

FIG. 18 is a diagram showing an example of displaying a correction result to a learner in the same embodiment.

FIG. 19 is a flowchart showing a method of comparing the answer and the correct answer of the learner of the embodiment.

FIG. 20 is a diagram showing an example of types of errors set in the embodiment.

FIG. 21 is a diagram showing an example of an electronic dictionary having a hierarchical structure.

FIG. 22 is a block diagram of a conventional accounting learning device.

[Explanation of symbols]

 1 journal entry question template storage section 2 parameter table storage section 3 noun table storage section 4 question sentence generation rule storage section 5 input section 6 correction template storage section 7 display 8 control section 9 learner 10 journal entry question answer generation processing 11 journal entry answer generation processing 12 Error correction processing 13 Journal entry table 14 Account item selection button 15 Consumption tax category selection button 16 Control button 17 Journal entry problem storage section 18 Correct answer storage section 19 Input section 20 Correctness determination section 21 Control section 22 Display

 ─────────────────────────────────────────────────── ─── Continuation of the front page (72) Inventor Shinichi Shigenaga 1006 Kadoma, Kadoma City, Osaka Prefecture Matsushita Electric Industrial Co., Ltd.

Claims (2)

[Claims] 1. A journal question template storage unit that stores a large number of question templates for journal entries, a parameter table storage unit that stores a noun and a range of numerical values that can be taken by the noun, and a noun and the noun. A noun table storage unit that holds a set of nouns, a problem sentence generation rule storage unit that holds rules for generating an actual problem, an input unit for a learner to input a problem request and a solution to a problem, and a learner Correction template storage unit that stores a correction template corresponding to an error in the answer, a display that displays a journal entry question and a correction result, the journal entry question template storage unit, the parameter table storage unit, the noun table storage unit, and the question A sentence generation rule storage unit, the correction template storage unit, the input unit, and a control unit for controlling the display, A question template is selected from the journal question template storage unit, the noun described in the question template is used as a keyword, the parameter table storage unit is searched, and a numerical value that matches the range of numerical values obtained as a result of the search is searched. The question template is set in the question template, the noun described in the question template is used as a keyword, the noun table storage unit is searched, and the noun obtained as a result of the search is set in the question template. By applying the rule stored in the storage unit, the question to be actually given is generated from the question template and displayed on the display, and the correct answer of the question to be given is generated, and the answer and the correct answer input from the input unit are given. To determine an error, and use the result of the error determination to select a correction example from the correction template storage unit. Accounting learning method, wherein the generating answers correction results of the learner from correction example, be displayed on the display. 2. The accounting learning method according to claim 1, wherein the noun table storage section is replaced with a dictionary having a reference relation systematized between words.