JP7644971B2 - Test question specification method and program - Google Patents

Description

The present invention relates to a method and program for identifying exam questions.

Technology for evaluating past exam questions for qualification exams is known. For example, Patent Literature 1 discloses a technology for analyzing past exam questions and evaluating the degree to which correct answers to past exam questions are required to pass the exam.

JP 2020-95686 A

However, the technology in Patent Document 1 can only evaluate the importance of past exam questions, making it difficult for people studying for exams to know which of the large number of past exam questions they need to be able to solve in order to pass the exam.

The present invention was made in consideration of these points, and aims to enable people studying for exams to know which exam questions they need to be able to solve in order to pass the exam.

In a first aspect of the present invention, a test question identification method is provided, which includes the steps of: acquiring a plurality of test questions that were asked in a test within a predetermined period of time in the past, executed by a computer; assigning a term importance rank to a predetermined technical term contained in each of the plurality of test questions; classifying the plurality of test questions into a plurality of problem importance ranks by assigning a problem importance rank to each of the plurality of test questions based on the term importance rank assigned to the technical term; calculating an occurrence rate, which is a ratio of the number of the test questions for each of the classified problem importance ranks to the total number of the plurality of test questions, for each of the plurality of problem importance ranks; calculating an integrated value by accumulating the occurrence rates corresponding to each of the problem importance ranks in order of increasing problem importance rank from the occurrence rate corresponding to the highest problem importance rank; identifying the problem importance rank corresponding to the occurrence rate accumulated immediately before the point in time when the integrated value exceeds a reference value corresponding to the correct answer rate required for passing and after the point in time; and outputting information for identifying the plurality of test questions corresponding to the highest problem importance rank to the identified problem importance rank.

The test question identification method may further include a step of acquiring term information including the plurality of technical terms, which is executed before the step of assigning the term importance rank, and in the step of assigning the term importance rank, the term importance rank may be assigned to the technical term included in the term information among the plurality of terms included in the plurality of test questions.

The step of assigning the term importance rank may include a step of identifying one or more portions of the question text, correct answer options, or incorrect answer options in the plurality of test questions that contain the technical term; a step of assigning a total point to the technical term that is the sum of standard points determined for each of the identified one or more portions; and a step of assigning a higher term importance rank to each of the plurality of technical terms as the total point increases.

The step of assigning the term importance rank to the technical term includes a step of calculating the number of unranked terms, which is the number of technical terms to which the term importance rank has not been assigned, by subtracting the total number of technical terms to which the term importance rank has been assigned from the total number of the plurality of technical terms; a step of calculating the number of distributions of the technical terms to one of the term importance ranks by dividing the number of unranked terms by the remaining number of ranks obtained by subtracting the number of the term importance ranks assigned to the technical terms from the total number of the term importance ranks; and a step of calculating the number of distributions of the technical terms to one of the term importance ranks by dividing the number of the unranked terms by the remaining number of ranks obtained by subtracting the number of the term importance ranks assigned to the technical terms from the total number of the term importance ranks. The method may include a step of calculating an accumulated term count value by accumulating the number of technical terms corresponding to each of the points in order from the point, a step of identifying the point that corresponds to the number of technical terms accumulated immediately before the point at which the accumulated term count value exceeds the distribution number and is subsequent to the point at which the accumulated term count value exceeds the distribution number, and a step of assigning the lowest term importance rank among the term importance ranks that are not assigned to other technical terms to the technical term that corresponds from the minimum point to the identified point among the technical terms to which the term importance rank has not been assigned.

The classifying step may include a step of assigning to the plurality of test questions the question importance rank corresponding to the lowest term importance rank among the term importance ranks of the plurality of technical terms contained in each of the plurality of test questions.

The test question identification method may further include a step of acquiring the reference value input by a user, which is executed before the step of identifying the question importance rank.

In a second aspect of the present invention, a program is provided for causing a computer to execute the steps of: acquiring a plurality of test questions that were asked in tests within a specified period of time in the past; assigning a term importance rank to a specified technical term contained in each of the plurality of test questions; classifying the plurality of test questions into a plurality of problem importance ranks by assigning a problem importance rank to each of the plurality of test questions based on the term importance rank of the assigned technical term; calculating an occurrence rate, which is the ratio of the number of test questions for each of the classified problem importance ranks to the total number of the plurality of test questions, for each of the plurality of problem importance ranks; calculating an integrated value by accumulating the occurrence rates corresponding to each of the problem importance ranks in order of increasing problem importance rank from the occurrence rate corresponding to the highest problem importance rank; identifying the problem importance rank corresponding to the occurrence rate accumulated immediately before the point in time at which the integrated value exceeded a reference value corresponding to the correct answer rate required for passing, and outputting information for identifying the plurality of test questions corresponding to the highest problem importance rank through the identified problem importance rank.

The present invention has the effect of enabling people studying for exams to understand which exam questions they need to be able to solve in order to pass the exam.

FIG. 1 is a diagram for explaining an overview of a test question specification system. 1 is a diagram for explaining a configuration of a test question specifying device 1. 1 is an example of a technical term list. This is an example of points determined according to the location of appearance. This is a classification table of technical terms. This is a classification table of technical terms obtained by assigning a term importance ranking to all technical terms. This is a classification table of test questions. 13 is a flowchart showing an example of a process for assigning a term importance rank to a technical term. 13 is a flowchart illustrating an example of a process for identifying test questions.

[Overview of the test question identification system S]
1 is a diagram for explaining an overview of a test question identification system S. The test question identification system S is a system for outputting, to an examinee U studying for an exam, question identification information for identifying test questions that need to be solved in order to pass the exam from among a plurality of past exam questions. In the following explanation, the test questions asked in the exam are described as multiple-choice questions, but the format of the test questions is arbitrary.

The test question identification device 1 is a device that identifies test questions that need to be solved from multiple past test questions. First, the test question identification device 1 classifies multiple test questions that have been asked in past tests into multiple importance ranks based on the term importance rank, which is the importance rank of the technical terms contained in each test question. In this specification, the importance rank of a test question is referred to as a problem importance rank. Next, the test question identification device 1 identifies test questions that the examinee U needs to solve from among the multiple test questions, based on the order of problem importance rank, starting from the test question with the highest problem importance rank. The test question identification device 1 identifies test questions that need to be solved so that the ratio of the number of identified test questions to the total number of multiple test questions exceeds a reference value corresponding to the correct answer rate required to pass the test.

Then, the test question identification device 1 outputs problem identification information to the examinee terminal 2 to identify the test questions that need to be solved. The test question identification device 1 outputs, for example, the problem numbers of the identified test questions as problem identification information to the examinee terminal 2 that sent the instruction to output the problem identification information. The examinee terminal 2 displays the problem numbers on the display unit. In the example of Figure 1, 2, 3, 5, and 7 are displayed on the display unit of the examinee terminal as the problem numbers of the test questions that need to be solved.

In this way, the test question identification device 1 can notify the test taker U which test question out of the large number of past test questions he or she needs to be able to solve in order to pass the test. As a result, the test taker U can know which test question he or she needs to be able to solve in order to pass the test, thereby improving the efficiency of test study.

[Configuration of test question identification device 1]
2 is a diagram for explaining the configuration of the exam question identification device 1. The exam question identification device 1 comprises a communication unit 11, a storage unit 12, and a control unit 13. The communication unit 11 is a communication module capable of transmitting and receiving various information. The communication unit 11 can transmit and receive various information to and from the examinee terminal 2 and the administrator terminal 3, for example, via the Internet. The administrator terminal 3 is a terminal used by a teacher at a cram school who uses the exam question identification device 1 to teach examinees U how to study for exams.

The storage unit 12 is a storage medium including a ROM (Read Only Memory), a RAM (Random Access Memory), a hard disk, etc. The storage unit 12 stores the programs executed by the control unit 13.

The memory unit 12 stores a number of past test questions. The number of past test questions can be stored by an administrator using the administrator terminal 3. For example, the administrator inputs a number of past test questions into the administrator terminal 3, and causes the administrator terminal 3 to transmit the input number of past test questions to the test question identification device 1, thereby storing a number of past test questions in the memory unit 12.

The memory unit 12 stores terminology information (hereinafter referred to as a "terminology list") that includes multiple technical terms used in multiple test questions. Figure 3 is an example of a technical term list. The technical term list in Figure 3 is an example of technical terms used in the national nursing examination.

The control unit 13 is a computational resource including a processor such as a CPU (Central Processing Unit). The control unit 13 executes the programs stored in the storage unit 12 to realize the functions of an information acquisition unit 131, a term classification unit 132, a question classification unit 133, an occurrence rate calculation unit 134, a question identification unit 135, and an information output unit 136.

The information acquisition unit 131 acquires a predetermined period (hereinafter referred to as the "question acquisition period") for acquiring multiple test questions from multiple test questions asked in past exams. For example, the information acquisition unit 131 acquires the question acquisition period from the examinee terminal 2. The information acquisition unit 131 then acquires from the memory unit 12 multiple test questions asked in exams held during the question acquisition period. As an example, if 10 years is input into the examinee terminal 2 as the question acquisition period, the information acquisition unit 131 acquires from the memory unit 12 multiple test questions asked in exams over the past 10 years. The information acquisition unit 131 may also acquire the question acquisition period from the administrator terminal 3.

The information acquisition unit 131 acquires the technical term list from the storage unit 12. The information acquisition unit 131 may acquire, from the administrator terminal 3, the technical term list that the administrator input to the administrator terminal 3. In this case, the information acquisition unit 131 stores the acquired technical term list in the storage unit 12.

The information acquisition unit 131 acquires a reference value corresponding to the percentage of correct answers required to pass from the administrator terminal 3. The reference value is a value for determining the number of test questions that need to be solved to pass the exam. The process of determining the number of test questions using the reference value will be described later, but the larger the reference value, the more test questions that need to be solved, and the smaller the reference value, the fewer test questions that need to be solved. The reference value is, for example, a value obtained by adding a predetermined additional value to the percentage of correct answers required to pass. The percentage of correct answers required to pass is set for each exam, for example, by the administrator. In this case, the administrator inputs the percentage of correct answers required to pass and the additional value into the administrator terminal 3, and the information acquisition unit 131 acquires the percentage of correct answers required to pass and the additional value from the administrator terminal 3.

The information acquisition unit 131 may acquire information for setting a reference value input by the examinee U to the examinee terminal 2, and determine a reference value based on the acquired information for setting a reference value. For example, the information acquisition unit 131 may acquire probability information indicating the pass probability desired by the examinee U from the examinee terminal 2 as information for setting a reference value, and set a reference value based on the acquired probability information. The probability information may be numerical information, or may be text information associated with the pass probability, such as "high pass probability," "medium pass probability," or "minimum pass level."

When the information acquisition unit 131 acquires probability information, it acquires a reference value stored in the storage unit 12 in association with the acquired probability information. If an initial value of the reference value is determined in advance, the information acquisition unit 131 may determine the reference value by adding an additional value corresponding to the acquired probability information to the initial value. For example, when the information acquisition unit 131 acquires probability information indicating a "medium probability of passing," it determines the reference value by adding an additional value that is smaller than an additional value corresponding to a "high probability of passing" and larger than an additional value corresponding to a "minimum passing line" to the initial value.

The term classification unit 132 assigns multiple term importance ranks to multiple technical terms in the technical term list. For example, the term classification unit 132 assigns term importance ranks to technical terms included in the technical term list stored in the memory unit 12, among multiple terms included in all multiple test questions. Below, a specific example of the process executed by the term classification unit 132 to assign term importance ranks to technical terms is described.

First, the terminology classification unit 132 identifies technical terms included in the technical term list from among the multiple terms contained in all of the multiple test questions. Next, the terminology classification unit 132 identifies one or more locations in the question text, correct answer options, or incorrect answer options in the multiple test questions where the technical term is included. Hereinafter, the location where the technical term is included in the test question is referred to as the occurrence location.

Next, the term classification unit 132 assigns a total point to the technical term, which is the sum of the reference points determined for each of the one or more identified occurrences. The points determined for each of the multiple occurrences are stored in advance in the storage unit 12. FIG. 4 is an example of points determined for the occurrences. Also, as shown in FIG. 4, points may be set according to the question category. As an example with reference to FIG. 4, the points determined for the technical term included in the [correct answer option] of the [mandatory] test question is 6 points. For example, when the technical term [caregiving migration] is included in the [correct answer option] of the [mandatory] test question and the [question text] of the [general/situation setting] test question, the term classification unit 132 assigns a total of 8 points, which is the sum of 6 points and 2 points, to [caregiving migration].

The term classification unit 132 may assign points to a technical term based on the number of times the technical term is included in each location in multiple test questions. Specifically, the term classification unit 132 assigns points to the technical term that are the reference point for a location multiplied by the number of times the technical term is included in that location in all of the multiple test questions. As an example, if the technical term "extrinsic" is included three times in the required correct answer options in multiple test questions from the past 10 years, the term classification unit 132 assigns 18 points (6 points x 3 times) to "extrinsic."

Then, the term classification unit 132 performs the above process for each of a plurality of portions (e.g., correct answer options, question text, and incorrect answer options), and calculates the final points for the technical term by adding up the points calculated for each of the plurality of portions. For example, if the technical term [extrinsic] appears three times in the required correct answer options, two times in the required question text, and two times in the required incorrect answer options in multiple test questions from the past 10 years, the term classification unit 132 assigns 30 points to the technical term [extrinsic] (see formula (1) below).
6 points x 3 times + 4 points x 2 times + 2 points x 2 times = 30 points Formula (1)

Figure 5 is a terminology point classification table. The terminology point classification table in Figure 5 is obtained as a result of assigning points to all terminology. In the example in Figure 5, the number of terminology assigned 0 points is 141. Similarly, the number of terminology assigned 1 point is 242, the number of terminology assigned 2 points is 292, and the number of terminology assigned 221 points is 1.

The term classification unit 132 assigns a higher term importance rank to technical terms the more points the term is assigned. Below, we will specifically explain the process of assigning term importance ranks to technical terms, assuming that there are a total of 2092 technical terms, and that the term importance ranks are S, A, B, C, D, E, F, G, and H (9 ranks) in descending order.

First, the term classification unit 132 identifies the total number of technical terms to which a term importance rank has been assigned (hereinafter referred to as "ranked terms"). Next, the term classification unit 132 subtracts the total number of ranked terms from the total number of multiple technical terms (2092) to calculate the number of technical terms to which a term importance rank has not been assigned (hereinafter referred to as "unranked terms"). If no term importance ranks have been assigned, the total number of ranked terms is 0 and the number of unranked terms is 2092.

Next, the term classification unit 132 identifies the number of term importance ranks (hereinafter referred to as "processed ranks") assigned to technical terms. The term classification unit 132 then calculates the number of remaining ranks by subtracting the number of processed ranks from the total number of term importance ranks (in the above specific example, there are nine ranks from S to H, so the total number of term importance ranks is nine). The term classification unit 132 then divides the number of unranked terms by the number of remaining ranks to calculate the distribution number for distributing technical terms to one term importance rank. If no term importance ranks have been assigned, the number of processed ranks is 0, the number of remaining ranks is 9, and the distribution number is 232 (rounded down to the nearest whole number) (see formula (2) below).
2092÷9=232.444. ．． ．． Formula (2)

Then, the term classification unit 132 calculates the accumulated term count value by accumulating the number of technical terms in ascending order of points, starting from the technical term corresponding to the smallest point among the points corresponding to unranked terms. For example, when no term importance ranks have been assigned, the term classification unit 132 calculates the accumulated term count value by accumulating the number of technical terms in ascending order of points, starting from the technical term corresponding to 0 points, which is the smallest point. As an example, the term classification unit 132 calculates the accumulated term count value (383) by accumulating the number of technical terms with 0 points (141) and the number of technical terms with 1 point (242).

Next, the term classification unit 132 determines whether the accumulated term count value has exceeded the distribution number. In the above example, the term classification unit 132 determines that the accumulated term count value (383) has exceeded the distribution number (232). Next, the term classification unit 132 identifies a point that corresponds to the number of technical terms accumulated after and immediately before the time when it was determined that the accumulated term count value exceeded the distribution number. As a specific example, the term classification unit 132 identifies one point that was accumulated immediately before it was determined that the accumulated term count value (383) exceeded the distribution number (232).

Then, the term classification unit 132 assigns the lowest term importance rank among those not assigned to technical terms to technical terms corresponding to one or more points from the minimum point corresponding to an unranked term to the specified point. For example, the term classification unit 132 classifies technical terms with 0 points and 1 point accumulated when it is determined that the term count accumulated value (383) has exceeded the distribution number (232) into the same term importance rank. As an example, the term classification unit 132 assigns an H rank to technical terms corresponding to 0 points to 1 point.

The term classification unit 132 repeats the above classification process until there are no more unranked terms. For example, the process after the term classification unit 132 assigns an H rank is as follows.

The term classification unit 132 subtracts the total number of ranked terms (383) from the total number of multiple technical terms (2092) to determine the number of unranked terms (1709). Next, the term classification unit 132 divides the number of unranked terms (1709) by the number of remaining ranks (8) to determine the distribution number (213). Next, when the number of technical terms with 2 points is 292, the term classification unit 132 determines that the points corresponding to the number of technical terms most recently accumulated at the time when the accumulated value (292) exceeded the distribution number (213) are 2 points. Then, the term classification unit 132 assigns the technical term corresponding to 2 points the G rank, which is the lowest term importance rank among the term importance ranks (S to G ranks) not assigned to technical terms.

This process is then repeated, and unranked terms are assigned a term importance rank in the following order: F, E, D, C, B, A, S.

Figure 6 is a classification table of technical terms obtained by assigning a term importance rank to all technical terms. In the example of Figure 6, S rank is assigned to technical terms corresponding to points 25 to 221. In the example of Figure 6, the number of S rank technical terms is 122, and the ratio of the number of S rank technical terms to the total number of technical terms is 6%. The ratios of the number of technical terms belonging to each rank from S rank to H rank are 6%, 6%, 8%, 8%, 8%, 13%, 18%, 14%, and 18%, respectively. By the term classification unit 132 classifying the term importance rank of technical terms in the above procedure, the number of technical terms with high term importance ranks can be made smaller than the number of technical terms with low term importance ranks.

The question classification unit 133 classifies the multiple test questions into multiple question importance ranks by assigning a question importance rank to each of the multiple test questions. As an example, specifically, the question classification unit 133 classifies the multiple test questions by assigning the lowest term importance rank among the term importance ranks of multiple technical terms contained in the test questions as the problem importance rank of the test question. More specifically, the question classification unit 133 assigns the lowest term importance rank among the technical terms contained in the question text and correct answer options of the test question as the problem importance rank of the test question.

An example of how to assign a question importance rank to the next test question will be described below.
Q: Which mental health and welfare center is appointed by the prefectural governor to provide counseling to people with mental disorders and their families?
Correct answer: Mental health social worker Incorrect answer: Gatekeeper

The term "Mental health and welfare center" in the question text is a D-rank terminology, the correct answer option "gatekeeper" is a G-rank term, and the incorrect answer option "mental health and welfare counselor" is an A-rank terminology. In this case, the question classification unit 133 assigns the lowest term importance rank of D and A as the question importance rank of the test question.

Technical terms with high term importance ranks are included in more test questions than technical terms with low term importance ranks. Therefore, if the highest term importance rank of the technical terms included in a test question is assigned as the problem importance rank of the test question, there will be too many test questions with high problem importance ranks. On the other hand, if the lowest term importance rank of the technical terms included in a test question is assigned as the problem importance rank of the test question, only test questions that contain only technical terms with high term importance ranks will be assigned a high problem importance rank. In other words, the problem classification unit 133 can assign a higher problem importance rank to test questions that can be answered correctly by studying only technical terms with high term importance ranks, than to test questions that require studying technical terms with low term importance ranks.

The question classification unit 133 assigns a question importance rank to all of the multiple test questions administered in the test during the period set as the question acquisition period (for example, the past 10 years). The question classification unit 133 identifies the number of test questions classified into each question importance rank. FIG. 7 is a classification table of test questions. In the classification table shown in FIG. 7, the rank, the number of questions, the occurrence rate, and the cumulative occurrence rate value are associated with each other. The occurrence rate is the ratio of the number of test questions for each classified problem importance rank to the total number of multiple test questions. The cumulative occurrence rate value is a value obtained by accumulating the occurrence rates corresponding to each problem importance rank in order of increasing problem importance rank, starting from the occurrence rate corresponding to the S rank, which is the highest problem importance rank. In the example of FIG. 7, the number of test questions classified into the S rank is 18. As shown in FIG. 7, the question classification unit 133 identifies the number of classified test questions for each problem importance rank.

The occurrence rate calculation unit 134 calculates the occurrence rate of the test questions classified into each question importance rank. The occurrence rate calculation unit 134 calculates the occurrence rate for each of the multiple question importance ranks. In the example of FIG. 7, the occurrence rate of S rank is 9%, and the occurrence rate of A rank is 8%.

The occurrence rate calculation unit 134 calculates an accumulated occurrence rate value by accumulating the occurrence rates corresponding to each problem importance rank in order of increasing problem importance rank, starting from the occurrence rate corresponding to the S rank, which is the highest problem importance rank. For example, the occurrence rate calculation unit 134 calculates the accumulated occurrence rate value from the S rank to the A rank to be 17% (see FIG. 7).

The problem identification unit 135 identifies a problem importance rank that corresponds to the occurrence rate accumulated immediately before the point in time when the accumulated occurrence rate exceeded the reference value. This problem importance rank is the lowest problem importance rank of the test questions for which the examinee U should study, and is referred to as the "lower limit study rank" in the following explanation. For example, when the reference value set by the examinee U is 60%, the problem identification unit 135 identifies E rank, which is a problem importance rank that corresponds to the accumulated occurrence rate value [62%], as the lower limit study rank (see FIG. 7).

The question identification unit 135 identifies the lower limit study rank using a reference value set by the information acquisition unit 131. For example, the question identification unit 135 identifies the lower limit study rank using a reference value corresponding to the probability information acquired from the examinee terminal 2. As a specific example, when the reference value set by the information acquisition unit 131 is 90%, the question identification unit 135 identifies G rank, which is a question importance rank corresponding to the appearance rate integrated value [90%], as the lower limit study rank.

When the question identification unit 135 identifies the lower limit study rank, it generates question identification information for identifying exam questions that need to be solved in order to pass the exam. The question identification information is information for identifying multiple exam questions that correspond from the highest question importance rank to the lower limit study rank. The question identification information is, for example, the question number of the exam question. The question identification information may include the date the exam was conducted and the question category. The question identification information may also be the identified exam question itself. For example, the question identification unit 135 generates question identification information that indicates the question numbers of multiple exam questions that correspond to ranks S to E.

The information output unit 136 outputs the problem identification information generated by the problem identification unit 135 to the examinee terminal 2. For example, the information output unit 136 outputs problem identification information indicating the problem numbers of a plurality of test questions corresponding to ranks S to E to the examinee terminal 2. The examinee terminal 2 then displays the problem numbers indicated in the problem identification information output from the test question identification device 1 on the display unit of the examinee terminal 2. This allows the examinee U, who has checked the displayed problem numbers, to know which test questions he or she needs to solve in order to pass the exam.

[Process of assigning term importance rank to technical terms]
8 is a flowchart illustrating an example of a process for assigning a term importance rank to technical terms, which is performed before a process for identifying test questions that need to be solved to pass an exam is performed.

First, the term classification unit 132 calculates the number of unranked terms by subtracting the total number of ranked terms from the total number of multiple technical terms (step S1). Next, the term classification unit 132 calculates the distribution number by dividing the calculated number of unranked terms by the number of remaining ranks obtained by subtracting the number of processed ranks from the total number of term importance ranks (step S2).

The term classification unit 132 calculates the accumulated term count value by accumulating the number of technical terms in ascending order of points, starting with the technical term with the smallest point among the points corresponding to unranked terms (step S3).

The term classification unit 132 determines whether the accumulated term count value is greater than the distribution number (step S4). If the accumulated term count value is equal to or less than the distribution number (No in step S4), the term classification unit 132 returns to step S3 and calculates the accumulated term count value again. When returning from step S4 to execute step S3, the term classification unit 132 adds the number of technical terms corresponding to the second largest point among the points corresponding to the already accumulated number of technical terms to the calculated accumulated value.

If the term count cumulative value is greater than the distribution number (Yes in step S4), the term classification unit 132 assigns the lowest term importance rank among those not assigned to the technical term (step S5). For example, if no term importance rank has been assigned, the term classification unit 132 assigns an H rank.

The term classification unit 132 determines whether there are any unranked terms (step S6). If there are any unranked terms (No in step S6), the term classification unit 132 repeats the process from step S1 to step S6 until there are no unranked terms. If there are no unranked terms (Yes in step S6), the term classification unit 132 ends the process of classifying technical terms.

[Process for identifying test questions to be presented to examinee U]
Fig. 9 is a flowchart showing an example of a process for identifying test questions to be presented to the examinee U. The flowchart in Fig. 9 is executed, for example, when the information acquisition unit 131 acquires an instruction to output question identification information from the examinee terminal 2.

The occurrence rate calculation unit 134 calculates the occurrence rate of the test questions (step S11). For example, the occurrence rate calculation unit 134 calculates the occurrence rate by dividing the number of test questions for each question importance rank by the total number of test questions.

The occurrence rate calculation unit 134 calculates the accumulated occurrence rate value (step S12). Specifically, the occurrence rate calculation unit 134 calculates the accumulated occurrence rate value by accumulating the occurrence rates corresponding to each problem importance rank in order of increasing problem importance rank, starting from the occurrence rate corresponding to the highest problem importance rank. As an example, the occurrence rate calculation unit 134 calculates the accumulated occurrence rate value from S rank to A rank to be 17% (see FIG. 7).

The occurrence rate calculation unit 134 determines whether the occurrence rate integrated value is greater than the reference value (step S13). If the occurrence rate integrated value is equal to or less than the reference value (No in step S13), the occurrence rate calculation unit 134 returns to step S12 and calculates the occurrence rate integrated value again. When returning from step S13 to execute step S12, the occurrence rate calculation unit 134 adds the occurrence rate corresponding to the problem importance rank next to the highest problem importance rank among the problem importance ranks corresponding to the occurrence rates already calculated to the calculated occurrence rate integrated value.

If the occurrence rate cumulative value is greater than the reference value (Yes in step S13), the occurrence rate calculation unit 134 identifies the lower limit study rank (step S14). For example, if the reference value set by the examinee U is 60%, the question identification unit 135 identifies E rank, which is a question importance rank corresponding to an occurrence rate cumulative value of 62%, as the lower limit study rank (see FIG. 7).

The question identification unit 135 generates question identification information for identifying multiple test questions that correspond to question importance ranks ranging from the highest question importance rank to the lowest study rank. For example, the question identification unit 135 generates question identification information indicating question numbers for identifying test questions ranging from S rank to E rank. The information output unit 136 then outputs the generated question identification information to the examinee terminal 2 (step S15).

[Effects of the test question identification device 1]
As described above, the test question identification device 1 classifies a plurality of test questions into a plurality of problem importance ranks by assigning a problem importance rank to each test question based on the term importance rank of the technical term contained in each test question. Next, the test question identification device 1 calculates an integrated value by integrating the occurrence rates corresponding to each problem importance rank in order of increasing problem importance rank, starting from the occurrence rate corresponding to the highest problem importance rank. Then, the test question identification device 1 outputs to the examinee terminal 2 problem identification information for identifying a plurality of test questions corresponding to the problem importance rank from the highest problem importance rank to the problem importance rank corresponding to the occurrence rate that is after the time when the integrated value exceeds the reference value and is most recently integrated at that time.

In this way, the examinee terminal 2 can display, for example, the question numbers of the exam questions that should be studied in order to pass the exam on the display unit of the examinee terminal 2. As a result, the examinee U who checks the displayed question numbers can know which exam questions he or she needs to be able to solve in order to pass the exam, which reduces the need to study more questions than necessary and improves the efficiency of studying for the exam.

Although the present invention has been described above using embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments, and various modifications and changes are possible within the scope of the gist of the invention. For example, all or part of the device can be configured by distributing or integrating functionally or physically in any unit. In addition, new embodiments resulting from any combination of multiple embodiments are also included in the embodiments of the present invention. The effect of the new embodiment resulting from the combination also has the effect of the original embodiment.

S Examination question identification system 1 Examination question identification device 11 Communication unit 12 Memory unit 13 Control unit 131 Information acquisition unit 132 Term classification unit 133 Question classification unit 134 Appearance rate calculation unit 135 Question identification unit 136 Information output unit 2 Examinee terminal 3 Administrator terminal U Examinee

Claims (7)

The computer executes
Obtaining a plurality of test questions that were asked in a test within a predetermined period of time in the past;
a step of assigning a term importance rank to a predetermined technical term contained in each of the plurality of test questions;
classifying the test questions into a plurality of question importance ranks by assigning a question importance rank to each of the test questions based on the term importance ranks assigned to the technical terms;
calculating an appearance rate, which is a ratio of the number of the test questions for each of the classified question importance ranks to the total number of the test questions, for each of the plurality of question importance ranks;
a step of accumulating the occurrence rates corresponding to the respective problem importance ranks in descending order of the problem importance rank, starting from the occurrence rate corresponding to the highest problem importance rank, to calculate an accumulated value;
a step of identifying the question importance rank corresponding to the appearance rate accumulated immediately before the time point when the accumulated value exceeds a reference value corresponding to a correct answer rate necessary for passing the test;
outputting information for identifying the plurality of test questions corresponding to the highest question importance rank through the identified question importance rank;
A method for identifying test questions. The method further includes a step of acquiring term information including a plurality of the technical terms, the step being executed before the step of assigning the term importance rank;
In the step of assigning the term importance rank, the term importance rank is assigned to the technical term included in the term information among a plurality of terms included in the plurality of test questions.
2. The method of claim 1. The step of assigning a term importance rank includes:
Identifying one or more portions of a question, a correct answer option, or an incorrect answer option in the plurality of test questions that include the technical term;
a step of adding up reference points determined for each of the one or more identified portions to give the technical term a total point;
a step of assigning a term importance rank to each of the plurality of technical terms such that the greater the total point, the higher the rank of the term importance;
having
3. The method of claim 1 or 2. The step of assigning the term importance rank to the technical term comprises:
A step of calculating a number of unranked terms, which is the number of technical terms to which the term importance rank has not been assigned, by subtracting a total number of technical terms to which the term importance rank has been assigned from a total number of the plurality of technical terms;
a step of dividing the number of unranked terms by a remaining number of ranks obtained by subtracting the number of the term importance ranks assigned to the technical terms from the total number of the term importance ranks to calculate a distribution number for distributing the technical terms to one of the term importance ranks;
a step of accumulating the number of technical terms corresponding to each of the points of the technical terms to which the term importance rank has not been assigned, in order from the smallest point, to calculate an accumulated term number value;
Identifying the point that corresponds to the number of technical terms that is accumulated immediately before the time point when the accumulated value of the number of terms exceeds the distribution number and is subsequent to the time point when the accumulated value of the number of technical terms exceeds the distribution number;
a step of assigning the lowest term importance rank among the term importance ranks not assigned to other technical terms to the technical terms corresponding to the minimum point to the specified point among the technical terms to which the term importance rank has not been assigned;
4. The method of claim 3, further comprising: The step of classifying includes a step of assigning to the plurality of test questions the question importance rank corresponding to the lowest term importance rank among the term importance ranks of the plurality of technical terms included in each of the plurality of test questions.
A method for identifying test questions according to any one of claims 1 to 4. The method further includes a step of acquiring the reference value input by a user, the step being performed before the step of identifying the problem importance rank.
A method for identifying test questions according to any one of claims 1 to 5. On the computer,
Obtaining a plurality of test questions that were asked in a test within a predetermined period of time in the past;
a step of assigning a term importance rank to a predetermined technical term contained in each of the plurality of test questions;
classifying the test questions into a plurality of question importance ranks by assigning a question importance rank to each of the test questions based on the term importance rank of the assigned technical term;
calculating an appearance rate, which is a ratio of the number of the test questions for each of the classified question importance ranks to the total number of the test questions, for each of the plurality of question importance ranks;
a step of accumulating the occurrence rates corresponding to the respective problem importance ranks in descending order of the problem importance rank, starting from the occurrence rate corresponding to the highest problem importance rank, to calculate an accumulated value;
a step of identifying the question importance rank corresponding to the appearance rate accumulated immediately before the time point when the accumulated value exceeds a reference value corresponding to a correct answer rate necessary for passing the test;
outputting information for identifying the plurality of test questions corresponding to the highest question importance rank through the identified question importance rank;
A program for executing.

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