JP4939887B2 - Learning strategy generation system and method - Google Patents

Description

  The present invention relates to a learning strategy generation system and method.

The learning strategy (Learning Strategy) is defined as “a mental operation or activity intentionally performed with the aim of enhancing the effect of learning” (see Non-Patent Document 1). However, it cannot be said that information about what learning strategy is appropriate is sufficiently conveyed to the learner. According to a survey by the applicant (Benesse Educational Research and Development Center), the percentage of those who answered "very likely" or "good" to the question whether "I don't know how to study well" applies 72.1%, and 75.7% in high school students.
Chino Kanno, “Psychology of Learning Strategies”, Shobunkasha, 1997

  Conventionally, based on the instructor's experience, one-on-one presents learning strategies to the learner, or from various learning instruction institutions, regardless of the actual learning strategy of each individual learner, It has been presented. However, according to the former, depending on the experience of the instructor, an appropriate learning strategy may or may not be presented. Further, according to the latter, there is a problem that it is not always possible to present a learning strategy appropriate for each learner.

  The present invention has been made in view of the above problems, and an object thereof is to provide a learning strategy generation system and method capable of presenting an appropriate learning strategy for each learner regardless of the experience of the instructor. .

  In order to solve the above-mentioned problems, a learning strategy generation system according to the present invention includes a questionnaire response and test result storage means for storing a questionnaire response regarding a learning strategy for each of a plurality of people and the test results of those people. And a first set selection means for selecting a plurality of sets of persons with the same answer pattern to the questionnaire among the plurality of persons, and each of the plurality of sets selected by the first set selection means, A statistic calculating means for calculating a statistic related to the test result of a person belonging to the set, and a plurality of sets selected by the first set selecting means based on the statistic calculated by the statistic calculating means; A second set selecting means for selecting a plurality, a learner answer acquiring means for acquiring answers to the questionnaire to the learner, and the learner answer acquiring means A difference amount calculating means for calculating a difference amount between an answer obtained from the answer and an answer pattern for the questionnaire common to people belonging to the plurality of sets selected by the second set selecting means; and the difference amount calculation Based on the difference amount calculated by the means, the third set selecting means for selecting at least one of the plurality of sets selected by the second set selecting means, and the third set selecting means are selected by the third set selecting means. Learning strategy generating means for generating a learning strategy to be presented to the learner based on an answer pattern to the questionnaire common to persons belonging to the set.

  Further, the learning strategy generation system according to the present invention includes a means for acquiring a questionnaire response to a learner, a means for storing a response pattern for the questionnaire common to each person belonging to a set of a plurality of persons, and the learning At least one of the stored answer patterns is selected based on the calculated difference amount and means for calculating the difference amount between the questionnaire response to the person and each stored answer pattern And means for generating a learning strategy to be presented to the learner based on the selected answer pattern.

  In addition, the learning strategy generation method according to the present invention includes a questionnaire response and a test result acquisition step for acquiring a questionnaire response regarding a learning strategy for each of a plurality of persons, and a test result of those persons, and a plurality of persons A first set selection step of selecting a plurality of sets of people who share a common answer pattern to the questionnaire, and a test of persons belonging to the set for each of the plurality of sets selected in the first set selection step A statistic calculating step for calculating a statistic related to the result, and a second set selecting step for selecting a plurality of sets from the plurality of sets selected in the first set selecting step based on the statistics in the statistic calculating step. And a learner response acquisition step for acquiring the questionnaire response to the learner and the learner response acquisition step. And a difference amount calculating step for calculating a difference amount between the answer and an answer pattern for the questionnaire common to the persons belonging to the plurality of sets selected in the second set selection step, and the difference amount calculating step And a third set selection step for selecting at least one of the plurality of sets selected in the second set selection step, and a set selected in the third set selection step based on the difference amount A learning strategy generation step of generating a learning strategy to be presented to the learner based on an answer pattern to the questionnaire common to people.

  According to the present invention, a questionnaire regarding a learning strategy is made to a plurality (preferably a large number) of people, and the answers and test results of each person are obtained. A plurality of groups of people who share the same answer pattern to the questionnaire are selected, and a statistic (for example, an average value) regarding the test results of the people belonging to each group is calculated. Each set is preferably selected so that variations in test results of persons belonging to the set satisfy a predetermined criterion. Then, for example, a plurality of sets are selected based on the statistic such as a set having the highest average value and a set having the next highest average value, or a set having an average value equal to or greater than a predetermined reference value.

  Next, a questionnaire response to the learner is acquired, and a difference amount (a value indicating the degree of difference) between this answer and the answer pattern related to the selected set is calculated. Based on this difference amount, for example, At least one set, such as a set having the smallest difference between the learner's answer and the answer pattern, is selected. A learning strategy to be presented to the learner is generated based on the answer pattern corresponding to the selected set.

  According to the present invention, it is possible to analyze the answers and test results of questionnaires conducted on a plurality of people by a statistical method, and objectively according to the analysis results and the answers of questionnaires of each learner. Appropriate learning strategies can be presented.

  The first set selection means may select a set of people having a common answer pattern to the questionnaire among the plurality of people so as to reduce variation in test results of the people belonging to each set. In this way, not only the questionnaire response pattern is common among the people belonging to each set, but also the test results are close to some extent.

  The first set selection means may select a plurality of sets of people who share a common answer pattern to the questionnaire by a regression binary tree method. In the regression binary tree method, test results (score etc.) are adopted as target variables, and questionnaire responses are adopted as explanatory variables. At this time, the learning strategy generation means stores in advance a partial learning strategy in association with some or all of a plurality of nodes of the regression binary tree and also belongs to a set selected by the third set selection means. A partial learning strategy associated with one or a plurality of nodes corresponding to an answer pattern to the questionnaire common to the questionnaire, and generating a learning strategy to be presented to the learner based on the read partial learning strategy It's okay. In addition, the learning strategy generation means provides the learner with the read partial learning strategy to be presented to the learner in order from a partial learning strategy associated with a node close to the root node of the regression binary tree. A presented learning strategy may be generated. According to the regression binary tree method, it is possible to search for differences in questionnaire responses between those who have excellent test results and those who do not. It can be presented in order from the difference.

  Moreover, you may further contain the learner test result acquisition means which acquires the test result of the said learner. In this case, if the learning strategy generation means generates a learning strategy to be presented to the learner based further on the test result acquired by the learner test result acquisition means, according to the test result of each learner Can present an appropriate learning strategy.

  Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings.

  In this embodiment, a questionnaire regarding learning strategies is conducted for a large number of people, a test is conducted on those people, and the answer pattern of the questionnaire by the superior is determined based on the answers and results of the questionnaire. At the same time, the same questionnaire is conducted to the learner, and the learning strategy is provided to the learner according to the answer pattern of the excellent person who is closest to the answer.

  FIG. 1 is a configuration diagram of a learning strategy generation system according to the present embodiment. The learning strategy generation system 10 shown in FIG. 1 includes a questionnaire response and test result database 12, a regression binary tree processing unit 14, a superior group selection / storage unit 16, a guidance target set selection unit 18, a learning strategy generation unit 20, and a communication. The unit 22 is configured to be connected to a learner terminal 26 used by a learner via a communication network 24 such as the Internet. The learning strategy system and the learner terminal 26 are configured by a computer and software, for example.

  In the present embodiment, for example, a questionnaire regarding a learning strategy of n cases (here, n = 5) as shown in FIG. This questionnaire is an answer to n of the degree to which a questionnaire respondent applies to each of a predetermined number (here, 5) of learning attitudes. The questionnaire response and test result database 12 stores the questionnaire responses and test results of each person. That is, in the questionnaire response and test result database 12, for each learning attitude (questionnaire item (question)), numerical values of 1 to 5 indicating the degree of application are stored, and the score of the test is stored.

  The regression binary tree processing unit 14 selects a plurality of groups of people who share the same answer pattern with respect to the questionnaire among the questionnaire respondents based on the questionnaire responses and the stored contents of the test result database 12. Specifically, among the questionnaire respondents, a set of people who share the same answer pattern to the questionnaire is selected so as to reduce the variation in test results of the people belonging to each set. Here, in order to select such a set, a regression binary tree method is used. In other words, the test results (points) are adopted as the target variables, and the answers (numbers 1 to 5) of each questionnaire item are adopted as the explanatory variables. Then, the method of answering the questionnaire that minimizes each variation (dispersion) of the test results of the persons belonging to both sets is specified (branching process). This branching process is repeated until the variation in the test results of the persons belonging to the final set falls below a predetermined reference value. Select one that is below the reference value.

  FIG. 3 shows an example of a regression binary tree generated according to the contents of the questionnaire response and test result database 12. In the figure, Zn is a standardized branch point for the question n and is calculated by the following equation (n = 1 to 5). Here, the branch point is a boundary value (natural number of 1 to 5) when the questionnaire respondent is divided by the answer of the question n before standardization, and equal (=) is given to the person who reaches the excellent person's node. It is designed to be attached.

  Zn = (branch point of question n−average point of question n) / standard deviation of question n

  The excellent person set selection / storage unit 16 calculates an average value (statistic) of the test results of the persons belonging to the set for each of a plurality of sets selected by the regression binary tree processing unit 14, and calculates the average Based on the values, a plurality of sets (here, a set having an average value equal to or greater than a predetermined value) is selected. And the answer pattern of the person who belongs to those sets is memorized. The answer pattern may be stored in the form of a question (questionnaire item) and a branch point in each branch on the route from the route node corresponding to the set, for example.

  The guidance target set selection unit 18 performs data communication with the learner terminal 26 to obtain an answer to the questionnaire having the same content as the above-described questionnaire from the learner, and the answer and the excellent set selection / storage The difference between each answer pattern stored in the unit 16 is calculated. Then, a set corresponding to the answer pattern having the smallest difference from the learner's answer is selected. Further, the learning strategy generation unit 20 generates display data of a learning strategy for a learner who uses the learner terminal 26 based on the answer pattern corresponding to the set selected by the guidance target set selection unit 18. This is transmitted to the learner terminal 26 by the communication unit 22 via the communication network 24. The learner terminal 26 receives the display data and displays the learning strategy on the monitor.

  Here, the processing of the guidance target set selection unit 18 and the learning strategy generation unit 20 will be described in more detail. First, as shown in FIG. 4, questionnaire data is first obtained by the communication unit 22 via the communication network 24 as a learner terminal. 26 and receives an answer An (n = 1 to 5; An = 1 to 5) for the question n. These answers are standardized by the following formula (S101).

  ZAn = (An−average point of question n) / standard deviation of question n

  Next, the difference amount between each answer pattern related to the group of excellent persons stored in the excellent person group selection / storage unit 16 and the learner's answers is calculated (S102). Specifically, the cumulative L of the distance ln in the question n between the answer pattern of the excellent person and the user's answer is calculated according to the following formula, and this is set as the difference amount. Here, the distance ln takes 0 when the learner's answer ZAn matches the answer pattern related to the group of excellent students, and takes | ZAn−Zn | Also, Σ is the sum for n.

  L = Σln

  Thereafter, an answer pattern having the smallest difference amount (cumulative L) is selected (S103), and the learning strategy generation unit 20 sets a learning strategy for a learner who uses the learner terminal 26 based on the answer pattern. Display data is generated (S104). For example, the learning strategy generation unit 20 stores in advance data (partial learning strategy) for guiding a learning strategy in association with some or all of the nodes of the regression binary tree, and selects a guidance target set. The data associated with the node corresponding to the answer pattern corresponding to the set selected by the unit 18 may be read out, and the learning strategy data for the learner may be created by combining these data. At this time, a plurality of data may be associated with each node in association with the condition of the test result of the learner. In this way, the test result of the learner is received by receiving the test result of the learner from the learner terminal 26, and the data corresponding to the condition satisfying the test result is read out and used to create the learning strategy data. When the condition is good or bad, a message of a learning strategy corresponding to that can be transmitted to the learner terminal 26. In addition, the data associated with the node closer to the root node of the regression binary tree is learned by combining the data of each node in the order according to the distance to the root node so that it can be noticed first by the learner. Strategy data may be created. In this way, it is possible to present to the learner in order from the important items that separate the superior from those who are not.

  According to the embodiment described above, it is possible to analyze the answers and test results of questionnaires conducted on a large number of people by statistical methods, and according to the analysis results and the answers to the questionnaires of each learner, Objective learning strategies can be presented.

It is a block diagram of the learning strategy production | generation system which concerns on embodiment of this invention. It is a figure which shows an example of a questionnaire. It is a figure which shows an example of a regression binary tree. It is a processing flow of a guidance object set selection part and a learning strategy production | generation part.

Explanation of symbols

  10 Learning Strategy Generation System, 12 Questionnaire Response and Test Result Database, 14 Regression Binary Tree Processing Unit, 16 Excellent Person Set Selection / Storage Unit, 18 Guidance Target Set Selection Unit, 20 Learning Strategy Generation Unit, 22 Communication Unit, 24 Communication Network, 26 learner terminals.

Claims (6)

Questionnaire answers and test result storage means for storing questionnaire responses regarding learning strategies for each of a plurality of people and test results of those people,
Based on answers of the questionnaire for each of the plurality of persons stored in the test result storage means and the test results of those persons, a group of persons having a common answer pattern for the questionnaire among the plurality of persons. A first set selection means for selecting a plurality by a regression binary tree method ;
A statistic calculating means for calculating a statistic related to a test result of a person belonging to the set for each of the plurality of sets selected by the first set selecting means;
Second set selection means for selecting a plurality of the plurality of sets selected by the first set selection means based on the statistics calculated by the statistics calculation means;
Learner response acquisition means for acquiring responses of the questionnaire to the learner;
A difference amount calculating means for calculating a difference amount between the answer acquired by the learner answer acquiring means and the answer pattern for the questionnaire common to the persons belonging to the plurality of sets selected by the second set selecting means When,
Third set selection means for selecting at least one of the plurality of sets selected by the second set selection means based on the difference amount calculated by the difference amount calculation means;
Answers to the questionnaire common to people belonging to the set selected by the third set selection means among the partial learning strategies stored in advance in association with some or all of the plurality of nodes of the regression binary tree Learning strategy generation means for reading a partial learning strategy associated with one or a plurality of nodes corresponding to a pattern and generating a learning strategy presented to the learner based on the read partial learning strategies ;
A learning strategy generation system characterized by including: The learning strategy generation system according to claim 1,
The first set selection means selects a set of people having a common answer pattern to the questionnaire among the plurality of people so as to reduce variation in test results of people belonging to each set.
A learning strategy generation system characterized by that. In the learning strategy generation system according to claim 1 or 2 ,
The learning strategy generation means is presented to the learner to present the read partial learning strategy to the learner in order from a partial learning strategy associated with a node close to a root node of the regression binary tree. Generate learning strategies,
A learning strategy generation system characterized by that. The learning strategy generation system according to any one of claims 1 to 3 ,
Learner test result acquisition means for acquiring the learner's test result,
The learning strategy generation means generates a learning strategy to be presented to the learner based further on the test result acquired by the learner test result acquisition means.
A learning strategy generation system characterized by that. The learning strategy generation system according to claim 4,
A plurality of partial learning strategies are stored in association with some or all of the plurality of nodes of the regression binary tree and associated with the test result condition of the learner,
The learning strategy generating means includes
A partial learning strategy associated with one or a plurality of nodes corresponding to an answer pattern to the questionnaire common to people belonging to the set selected by the third set selection means, and obtaining the learner test result Reading a partial learning strategy associated with the condition that satisfies the learner's test result obtained by means, and generating a learning strategy to be presented to the learner based on the read partial learning strategy thing,
A learning strategy generation system characterized by Questionnaire answers and test result acquisition steps for obtaining answers to questionnaires about learning strategies for each of a plurality of people and test results of those people,
Based on the questionnaire responses for each of the plurality of persons acquired in the test result acquisition step and the test results of those persons, a group of persons having a common answer pattern for the questionnaire among the plurality of persons. A first set selection step of selecting a plurality by a regression binary tree method ;
For each of the plurality of sets selected in the first set selection step, a statistic calculation step for calculating a statistic related to a test result of a person belonging to the set;
A second set selection step of selecting a plurality of the plurality of sets selected in the first set selection step based on the statistics in the statistics calculation step;
A learner response acquisition step of acquiring an answer of the questionnaire to the learner;
A difference amount calculating step for calculating a difference amount between the answer acquired in the learner answer acquiring step and the answer pattern for the questionnaire common to people belonging to the plurality of sets selected in the second set selecting step When,
A third set selection step of selecting at least one of the plurality of sets selected in the second set selection step based on the difference amount calculated in the difference amount calculation step;
Answers to the questionnaire common to those belonging to the set selected in the third set selection step among partial learning strategies stored in advance in association with some or all of the plurality of nodes of the regression binary tree A learning strategy generation step of reading a partial learning strategy associated with one or a plurality of nodes corresponding to a pattern , and generating a learning strategy to be presented to the learner based on the read partial learning strategies ;
A learning strategy generation method characterized by comprising:

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