JP2005352620A - Lesson evaluation system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a lesson evaluation system having highly reliable lesson evaluation capable of improving a system for evaluating lessons, especially contents and quality of lessons, in an educational facilities and improving operation and management of the educational facilities accordingly. <P>SOLUTION: The lesson evaluation system comprises a first determination processing section performing a multivariable analysis on answers to a questionnaire entry obtained from a plurality of students and schoolchildren who have lessons and dividing the plurality of students and schoolchildren into at least three groups on the basis of the results of the multivariable analysis, and a second determination processing section analyzing relationship between the answers of the questionnaire entry for the plurality of students and schoolchildren belonging to one of at least three groups divided by the first determination processing section and each group of at least three groups. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a system for evaluating classes in educational institutions such as secondary schools, high schools, universities, cram schools, prep schools, vocational schools, etc., in particular, improvement / improvement of the contents / quality of classes, and the accompanying The present invention relates to a class evaluation system that provides highly reliable class evaluation that can contribute to improvement and improvement of management and management.

  Traditionally, questionnaires have been sent to teachers who teach classes to students and students, and students and students taking classes, and the results are aggregated and analyzed to provide materials and materials that improve and improve the content and quality of classes. An attempt is being made.

For example, in Japanese Patent Laid-Open No. 11-84998, for the purpose of obtaining accurate and highly reliable teaching materials or teaching materials, both teachers teaching students to students and students receiving the classes There has been proposed a method and system for creating / providing lesson improvement materials for conducting a questionnaire and totalizing and evaluating the questionnaire result data on the teacher side and the questionnaire result data on the student side.
Japanese Patent Laid-Open No. 11-84998

  The attitudes of students and students tackling classes are incredible. For example, there is a natural difference in the attitude of students who want to take classes between subjects that are essential for university entrance examinations and subjects that are not related to university entrance examinations. Also, at university, I was fascinated by the contents of the class, I was fascinated by the teacher in charge, it was a required course, necessary for qualification acquisition, I did not feel particularly attractive, but I took the course because it seems easy to acquire credits, Depending on the situation, there will naturally be a difference in the attitude of the students working on the classes (for example, whether they are positive or negative).

  When a questionnaire survey consisting of questions with the same contents is conducted for multiple students / students with different attitudes to the class, there is a large difference in the response contents depending on the attitude to the class. May occur.

  Conventional questionnaire surveys for teachers, students, and students generally simply aggregate and analyze the results of all respondents. In this case, the general tendency of students and student groups However, as mentioned above, since the answer results obtained from those who have completely different attitudes and enthusiasm for class work are simply tabulated and analyzed, It was inadequate to obtain more accurate and reliable information that could be effectively linked by improving and improving the content and quality.

  For example, in the first place, if you are interested in the teacher in charge of the class and wish to take the class, you are not interested in the students and the teacher or the class. If you get answers to the same questions from multiple students who are taking courses because they are required courses anyway, you can analyze the answer results for each group or answer with each group. By analyzing the relationship of the results, it is possible to analyze more accurately what measures are effective in order to increase students' motivation and motivation for the class, and to obtain highly reliable information It becomes possible.

  Therefore, the present invention is a system for evaluating lessons at educational institutions such as secondary schools, high schools, universities, cram schools, prep schools, vocational schools, etc. The purpose is to propose a class evaluation system that provides highly reliable class evaluation that can contribute to the improvement and improvement of management and management.

  In order to achieve the above object, the class evaluation system proposed by the present invention performs multivariate analysis of answers to questionnaire questions obtained from a plurality of students / students who take classes, and based on the results of the analysis, the plurality of students A first determination processing unit for classifying students into at least three groups, and the questionnaire questions of the plurality of students / students belonging to each group classified into at least three groups by the first determination processing unit A second determination processing unit that analyzes an answer to the matter and a relationship between each of the at least three groups.

  Here, a third determination process for analyzing a distribution tendency and weights of a plurality of students / students belonging to each group divided into at least three groups by the first determination processing unit. It can be set as the structure further provided with the part.

  Further, the multivariate analysis is performed with reference to the processing result of at least one of the first to third determination processing units, and the predetermined class is evaluated for each of the plurality of items. It can be set as the structure provided with the 4th determination process part which derives the numerical lesson evaluation.

  Here, in any of the class evaluation systems according to the present invention, a plurality of students / students are asked about answers to questionnaire questions obtained from a plurality of students / students who take classes, and questionnaire questions related to the questionnaire questions. It is possible to make a configuration further including a fifth determination processing unit that analyzes the answer obtained from the teacher who taught the class and analyzes the relationship between the two.

  The lesson evaluation system of the present invention further includes a sixth determination processing unit that refers to the processing results of the fourth determination processing unit and / or the fifth determination processing unit and derives items to be improved in the class. It can be configured as provided.

  According to this invention, a system for evaluating classes at educational institutions such as secondary schools, high schools, universities, cram schools, prep schools, vocational schools, in particular, improvement / improvement of the contents / quality of classes, and the accompanying It is possible to provide a class evaluation system that provides highly reliable class evaluation that can contribute to improvement and improvement of management and management.

  In other words, the answers to the questionnaire on many items conducted for students / students are analyzed and analyzed by correspondence analysis and cluster analysis, and students / students are divided into at least three levels in the difference in attitude toward classes. By classifying and analyzing the tendency of the students / students included in each level and the relationship with each level further through correspondence analysis, factor analysis, multiple regression analysis, etc. In order to increase motivation, it is possible to analyze more accurately what measures are effective and provide highly reliable information. In addition, improve the content, quality, and improvement of classes, and provide information that clearly identifies the items that should be improved in order to improve the attitude, motivation, and motivation of students and students be able to.

  The class evaluation system of the present invention described above is realized by a computer, and the first determination processing unit to the sixth determination processing unit described above are based on a computer program that causes a computer to perform each operation described above. The computer comprises a processing operation section of a computer that performs each operation of the first determination processing section to the sixth determination processing section.

  The first determination processing unit performs multivariate analysis of responses to questionnaire questions obtained from a plurality of students / students who take classes, and classifies the plurality of students / students into at least three groups based on the results of the analysis. To do.

  The multivariate analysis performed here uses, for example, correspondence analysis or cluster analysis, which is an analysis technique of the “pattern classification / optimum scaling method” type. For example, as shown in FIG. A process of dividing into a plurality of groups including at least three groups, ie, an enthusiastic layer, a normal layer, and an uneasy layer is performed.

  For example, in a questionnaire conducted to students and students to ask for evaluations of classes at educational institutions such as universities, high schools, prep schools, and vocational schools, the willingness to learn (option: good, normal, not good), The attitude toward the class (self-effort) (option: good, normal, not good) and attendance this year (option: good, normal, not good) are included. The student / student who made the answer and the answer items are spatially arranged. From the answer items arranged along the one axis and two axes as shown in FIG. 1 and the characteristics of the students / students, for example, in FIG. , Students / students who will be located on the upper right side divided by one axis and two axes, eager layers, students / students who will be located on the upper left side divided by one axis and two axes, Below one axis Processing for dividing an ordinary layer students and students that will be located in is performed.

  FIG. 2 shows a state in which the processing result of the first determination processing unit is displayed as an image on a CRT which is an information output unit of a computer in which the lesson evaluation system of the present invention is realized. Of course, the processing result in the state shown in FIG. 2 can be printed and output by an output unit including a printing unit such as a printer.

  The second determination processing unit includes answers to questionnaire questions of a plurality of students / students belonging to each group divided into at least three groups by the first determination processing unit, and each of the at least three groups. Analyze the relationship with the group.

  That is, the tendency of the student / student belonging to the hierarchy is analyzed from each group such as the eager class, the normal class, and the uneasy class, that is, the class of the student / student.

  For example, as shown in FIG. 6, what items, indicators, and keywords are common to each group such as the enthusiastic layer, the normal layer, and the uneasy layer, that is, the students / students belonging to each level of the student / student. It is analyzed whether or not.

  In the analysis shown in FIG. 6, the students, students, and students who are enthusiastic, share the same items, indicators, and keywords, such as participation, fulfillment, enthusiasm, teachers, knowledge, and explanations. , Syllabus (lecture outline), quantity, future, qualifications, notes, blackboard, items, indicators, keywords, etc. Is common.

  The third determination processing unit performs a correspondence analysis on the distribution tendency and the weight of each of the plurality of students belonging to each group divided into at least three groups by the first determination processing unit. Analyze by multivariate analysis. That is, the third determination processing unit analyzes how many students / students are in which spatial position of each group (each layer).

  FIG. 3 shows a state in which the result of the processing performed by the processing operation unit of the third determination processing unit is displayed as an image on a CRT which is an information output unit of the computer.

  In FIG. 3, the position where the cylinder is arranged indicates in which spatial position of each group (each level) the student / student exists, and the height of the cylinder indicates the student present at this spatial position.・ Represents the number of students. These are one index to search for students and students who have attended classes and answered questionnaires.

  As shown in FIG. 3, student / student patterns may be concentrated in each group (each layer). For example, in the example shown in FIG. 3, the student patterns of the normal layer and the eager layer are concentrated.

  Therefore, based on the analysis of patterns concentrated in each group (each level), what aspects are needed to move non-easy students / students to the normal class and normal students / students to the keen class? It is possible to obtain clues for deriving specific, more accurate and reliable information on how to change and improve the lesson content, lesson form, and lesson quality.

  The fourth determination processing unit refers to a processing result of at least one of the first to third determination processing units, performs a multivariate analysis, and performs the predetermined class. Derive a quantified class evaluation for each item to be evaluated.

  In this multivariate analysis, for example, factor analysis and multiple regression analysis are adopted. For example, for each of a plurality of items for evaluating the predetermined class such as comprehension, intellectual stimulation, and eagerness Processing to derive a numerical lesson evaluation is performed.

  The Fifth Judgment Processing Department provided lessons to multiple students / students regarding answers to questionnaire questions obtained from multiple students / students taking classes and questionnaire questions related to the questionnaires Analyze answers from teachers and analyze the relationship between them.

  For example, as shown in Fig. 9, "Q16 Overall, do you think the student was satisfied with this class?" In the questionnaire conducted for teachers The questionnaire is related to the question “Q17: Are you satisfied with this lesson?” And the relationship between them, for example, the gap between them is analyzed.

  FIG. 4B shows the answers to the questionnaire questions obtained from a plurality of students / students taking a class analyzed by the fifth determination processing unit and the questionnaire questions related to the questionnaire questions. Analysis of the answers obtained from the teachers who taught the students to the class, and the relationship between the two (here, the gap between the two) displayed on the CRT, which is the information output unit of the computer Is shown.

  The teacher's evaluation is almost the same level as the student / student's evaluation as to whether or not sufficient explanation of specialized knowledge and terminology is provided in the class, but the teacher is high in the progress of the class Students / students are given a lower level of evaluation, but conversely, whether the content is as announced (whether classes are being conducted in accordance with the syllabus) The teacher gives a high level of evaluation while the student gives a low level of evaluation, and it can be understood that there is a gap between them.

  The sixth determination processing unit refers to the processing result of the fourth determination processing unit and / or the processing result of the fifth determination processing unit, and performs processing for deriving items to be improved in the class.

  For example, in order to move non-easy students / students to the normal class and normal students / students to the zeal class, the process of deriving the items to be improved in the above classes, the motivation and motivation of the students / students In order to increase the level, the process for deriving items to be improved in the class is performed.

  The result of processing in the sixth judgment processing section improves the content and quality of the lesson, and consequently contributes to the improvement and improvement of the management and management of the educational institution that provides the lesson. It helps to derive KPI (Key Performance Indicator) in the management and management of the organization.

  In addition to the fifth determination processing unit, a seventh determination processing unit including a computer processing operation unit that analyzes an evaluation gap for each questionnaire response result of each student, student, and teacher is provided. You can also

  For example, FIG. 7 shows a state in which a result of analyzing a questionnaire response result of an enthusiastic student / student for a certain class by a seventh determination processing unit is displayed as an image on a CRT which is an information output unit of a computer. is there.

  In FIG. 7, the positive evaluation is above the level 0, the negative evaluation is below, and a high evaluation is given as to whether or not the content of the lesson has been well understood, but a low evaluation with respect to the progress speed is sufficient for specialized knowledge and terms. As for whether or not the explanation is given in the class, it is understood that there is no excess or deficiency, and that it is given an ordinary level evaluation. As the overall evaluation, a slightly positive evaluation is given.

  In addition, an eighth judgment processing unit consisting of a processing unit of a computer that performs processing for deriving what is regarded as an important item when conducting a comprehensive evaluation from the questionnaire response results of each student / student and teacher It can also be provided.

  FIG. 4 (a) shows the top five items that are regarded as important among the items that the student / student considers as important when analyzed by the processing operation unit of the eighth determination processing unit. The contribution ratio is shown in a table, and the state of image display on a CRT which is an information output unit of the computer is shown. It can be seen that 14.5%, whether or not the contents of the lesson can be understood well, is regarded as the most important.

  FIG. 10 is a conceptual diagram for explaining the schematic configuration of the lesson evaluation system 1 of the present invention together with its processing flow. FIG. 12 shows the schematic configuration of an example of the lesson evaluation system 1 of the present invention realized by a computer. FIG.

  A questionnaire is given to a teacher who teaches students and students, and a questionnaire is sent to students and students who take classes of the teacher, and the results are stored in the questionnaire database 21.

  The first decision processing unit 2 performs correspondence analysis and cluster analysis on the answers to the questionnaire questions obtained from the students and students. Based on the results of these analysis and analysis, the students and students are shown in FIG. As described above, a process of dividing into a plurality of groups including at least three groups, ie, the enthusiastic layer, the normal layer, and the non-corresponding layer, is performed, and the processing result is stored in the stratified database 22.

  The relationship between the answers to the questionnaire questions of a plurality of students / students belonging to each group divided into at least three groups by the first determination processing unit 2 and each of the at least three groups is second. The analysis processing unit 3 analyzes the tendency of students / students belonging to each group (student / student hierarchy) such as the eager layer, the normal layer, and the uneasy layer, What items, indexes, keywords, etc. are common to each group such as the enthusiastic group, that is, students / students belonging to each class of students / students, are analyzed. This analysis result is stored in the questionnaire + stratification database 23.

  The functions performed in the processing operation unit described above should represent the function according to the student group in the class evaluation system of the present invention, and the result is, for example, information as shown in FIG. 2 and FIG. It will be used.

  The third judgment processing unit 4 performs correspondence analysis on the distribution tendency and the weight of each of the plurality of students / students belonging to each group divided into at least three groups by the first judgment processing unit 2. Are analyzed by multivariate analysis, and the result is stored in the laying figure database 24.

  The fourth determination processing unit 5 refers to the processing result of at least one of the first determination processing unit 2 to the third determination processing unit 4 and performs multivariate analysis, A numerical lesson evaluation is derived for each of a plurality of items for evaluating the predetermined lesson.

  In this multivariate analysis, for example, factor analysis and multiple regression analysis are adopted. For example, for each of a plurality of items for evaluating the predetermined class such as comprehension, intellectual stimulation, and eagerness Derive a numerical class evaluation. This analysis result is stored in the analysis database 25.

  On the other hand, in the fifth determination processing unit 6, the plurality of answers to questionnaire questions obtained from a plurality of students / students who take classes stored in the questionnaire database 21 and the questionnaire questions related to the questionnaire questions. Analyzing the answers obtained from the teachers who taught professors to students and analyzing the relationship between them. This analysis result is also stored in the analysis database 25.

  The analysis performed in the third determination processing unit 4, the fourth determination processing unit 5, and the fifth determination processing unit 6 should represent the factor analysis function in the lesson evaluation system of the present invention. Is used as information as shown in FIG. 3, for example.

  The sixth determination processing unit 7 refers to the processing result of the fourth determination processing unit 5 and / or the processing result of the fifth determination processing unit 6 and performs processing for deriving items to be improved in the class.

  The analysis performed in the sixth judgment processing section improves the content and quality of the lesson, and consequently contributes to the improvement and improvement of the management and management of the educational institution that provides the lesson. It helps to derive KPI (Key Performance Indicator) in the management and management of the organization.

  The analysis results of the evaluation gaps for the questionnaire response results of the students / students / teachers conducted in the seventh judgment processing unit 8 are also the results of the students / students / teachers in the eighth judgment processing unit 9 respectively. The results of analyzing what items are regarded as important in the comprehensive evaluation from the questionnaire response results are also stored in the analysis database 25, respectively.

  Processing results in the first determination processing unit 2 to the eighth determination processing unit 9 in the class evaluation system of the present invention, questionnaire database 21, stratified database 22, questionnaire + stratified database 23, laying map database 24, The information in the analysis database 25 is referred to via the network by students / students, teachers, presidents, dean, educational institution management / administrators, etc. who are allowed to access using the class evaluation system of the present invention. It can be used as a reference material for improving class content, quality, motivation for learning, improving motivation, and improving management and management content.

  Hereinafter, with reference to the accompanying drawings, an embodiment in which the lesson evaluation system of the present invention is used for university lesson evaluation will be described.

  The lesson evaluation system 1 of the present invention is realized by a computer. For example, as shown in FIG. 11, the computer performs the processing operations of the first determination processing unit 2 to the eighth determination processing unit 9 described above. And a main storage device storing a computer program necessary for realizing the lesson evaluation system 1 of the present invention, and the first determination processing unit 2 to the eighth determination processing unit 9 described above. The processing operation unit for performing each processing operation, the databases 21 to 25, and the like are arranged and configured. As shown in FIG. 10, a lesson evaluation system of the present invention can be constructed by connecting a plurality of independent computers to a network.

  First, a questionnaire is sent to teachers who give classes to students and students who take classes of the teachers, and the results are stored in the questionnaire database 21.

  FIG. 8 and FIG. 9 each show an example of a questionnaire for teachers and students regarding a certain lecture conducted for a certain period (for example, the half year of the previous period). The questionnaire items randomly include questions about students' attitudes toward class, motivation, motivation, questions about class content, questions about teachers, and so on.

  Also, Q17 of the “Student Questionnaire” “Are you generally satisfied with this class?” And Q16 of the “Questions for Teachers” “Overall, students are satisfied with this class. As you can see, the question related to the question on one side is included in the question on the other side between the question for the student and the question for the teacher. As a result, responses to questionnaire questions obtained from multiple students taking classes and responses obtained from teachers who taught the students to the questionnaire questions related to the questionnaire questions It is possible to analyze and analyze the relationship between the two.

  The first decision processing unit 2 performs correspondence analysis and cluster analysis on the answers to the questionnaire questions obtained from the students. Based on the results of these analysis and analysis, the students are enthusiastic as shown in FIG. A process of dividing into a plurality of groups including at least three groups, ie, a layer, a normal layer, and a non-hearted layer is performed, and the processing result is stored in the stratified database 22.

  This includes, for example, the willingness to learn (choice: good, normal, not good), attitudes toward class (self-effort) (choice: good, normal, bad), and attendance this year ( The answer pattern is “Choice: good, normal, not good”.

  Then, students who make similar answers and their answer items are spatially arranged, and the answer items and student characteristics are spatially arranged along one axis and two axes as shown in FIG.

  In the example of FIG. 1, as shown in FIG. 2, the student who is located on the upper right side defined by one axis and two axes is located on the upper left side divided by the enthusiastic layer, one axis and two axes. The students who will become the uneasy layer, the students who will be located below one axis are the normal layer.

  In the second determination processing unit 3, answers to questionnaire questions of a plurality of students belonging to each group classified into at least three groups in the first determination processing unit 2, and each of the at least three groups The relationship with the group is analyzed and analyzed, that is, the tendency of students belonging to each group (student hierarchy) such as the eager layer, the normal layer, and the uneasy layer is analyzed, and this analysis result is the questionnaire + stratified database 23.

  In this way, the students divided into the above-mentioned layers of the eager, normal, and uneasy tiers will be divided into these groups with an emphasis on what evaluation items, and for students belonging to each tier Such items, indexes, keywords, etc. are analyzed, and the tendency of students belonging to each class such as the enthusiastic, normal, and uneasy classes is analyzed more deeply.

  This result is displayed, for example, arranged in a space as shown in FIG. From the results shown in FIG. 6, it can be seen that students, such as participation, fulfillment, enthusiasm, faculty, knowledge, and explanations, keywords, keywords, etc. are common to eager students. , Difficult, items, indicators, and keywords are common. For ordinary students, items such as syllabus (lecture outline), quantity, future, qualifications, notes, blackboard, items, indicators, and keywords are common. Analyze and understand what is being done.

  The function performed by the first determination processing unit 2 to the second determination processing unit 3 is a so-called student group function in the class evaluation system according to the present invention. This is used as information as shown in FIG.

  The third determination processing unit 4 analyzes the distribution tendency in each group and its weight of a plurality of students belonging to each group classified into at least three groups by the first determination processing unit 2. Again, multivariate analysis such as correspondence analysis is used. Thus, it is analyzed how many students are in which spatial position of each group (each hierarchy). This result is stored in the fabric layout database 24.

  FIG. 3 illustrates an example of a result of processing performed by the processing operation unit of the third determination processing unit 4. In FIG. 3, the position where the cylinder is arranged indicates in which spatial position of each group (each level) the student is present, and the height of the cylinder is the number of students present in this spatial position. It is an index to look for students who have attended classes and answered questionnaires.

  For example, as shown in FIG. 3, student patterns may be concentrated in each group (each level) (in the example shown in FIG. 3, student patterns in the normal layer and the eager layer are concentrated). Based on the analysis of patterns concentrated in each group (each level), the sixth judgment processing part described below will determine which of the following to move the non-easy student to the normal class and the normal student to the keen class. From this aspect, it is possible to obtain a clue to derive a concrete, more accurate and reliable information about whether to change or improve the lesson contents, lesson form, lesson quality.

  The fifth determination processing unit 6 obtains the answers to the questionnaire questions obtained from the students stored in the questionnaire database 21 and the teachers who taught the students about the questionnaire questions related to the questionnaire questions. And the relationship between the two. This analysis result is stored in the analysis database 25.

  For example, as described above, Q17 of “Student Questionnaire”, which is related to each other, “Are you satisfied with this lesson?” Q16 of “Questions for teachers” Students 'and teachers' responses to "Do you think students are satisfied with this class?" Are analyzed, and the relationship between them, for example, the gap between them, is analyzed.

  FIG. 4B is a graphical representation of the analysis result of the fifth determination processing unit 6 (here, the analysis result regarding the gap between the two), and whether the lesson content is well understood. In the syllabus (outline of lectures), whether sufficient explanations of specialized knowledge and terminology are provided in the class, whether the progress of the class is appropriate, whether the teachers are motivated and enthusiastic The gap between the student's answer result and the teacher's answer result is shown as to whether or not the content announced in advance is consistent with the lesson content and whether comprehensive evaluation is performed.

  As shown in Fig. 4 (b), it is thought that the teachers who conduct the classes should improve and improve compared to other teachers by showing the average of universities as a comparison target. Part, the part that the student is taking can improve the attitude toward the class, and can clearly show the part that should be improved in order to improve motivation and motivation.

  The seventh determination processing unit 8 analyzes the evaluation gap for the questionnaire response results of each student and teacher, and the analysis result is stored in the analysis database 25.

  The analysis result by the seventh determination processing unit 8 is, for example, each evaluation item (syllabus (outline of lecture)) as shown in the graph of FIG. 7 showing the analysis result of the questionnaire response for the enthusiastic student about a certain class. Whether the content announced in advance is consistent with the content of the class, whether the teachers are motivated or enthusiastic, whether the class is at an appropriate speed, and sufficient knowledge and terms Positive or negative evaluation for each class), whether the explanation is made in class, whether the contents of the class are well understood, comprehensive evaluation).

  The eighth decision processing unit 9 performs a process of deriving what is regarded as an important item when conducting a comprehensive evaluation of the class to be evaluated from the questionnaire response results of each student and teacher. The result is stored in the analysis database 25.

  The processing result of the eighth determination processing unit 9 is displayed as shown in FIG. 4A, for example. FIG. 4A is a table showing the top five items that are regarded as important when the student makes a comprehensive evaluation, and the contribution rate.

  The fourth determination processing unit 5 refers to the processing results of at least one determination processing unit among the first determination processing unit 2 to the third determination processing unit 4 described above, performs multivariate analysis, Derive a numerical class evaluation for each of multiple items that evaluate a predetermined class.

  In this multivariate analysis, for example, factor analysis and multiple regression analysis are adopted. For example, for each of a plurality of items for evaluating the predetermined class such as comprehension, intellectual stimulation, and eagerness Processing to derive a numerical lesson evaluation is performed. This analysis result is stored in the analysis database 25.

  When the fourth determination processing unit 5 performs such processing, the processing result of at least one determination processing unit among the first determination processing unit 2 to the third determination processing unit 4 is referred to. In addition, referring to the processing result of the seventh determination processing unit 8 and / or the processing result of the eighth determination processing unit 9 described above, a multivariate analysis is performed and a plurality of classes for evaluating a predetermined class are evaluated. It is also possible to derive a numerical lesson evaluation for each item.

  In the example illustrated on the right side of FIG. 10, factor analysis and multiple regression analysis are performed using a plurality of factors (here, 15 factors), and the degree of understanding, the degree of intellectual stimulation, and the degree of eagerness are quantified. Processing to derive class evaluation is performed.

  The analysis performed by the third determination processing unit 4, the fourth determination processing unit 5, the fifth determination processing unit 6, the seventh determination processing unit 8, and the eighth determination processing unit 9 described above is performed according to the present invention. This represents a factor analysis function in the lesson evaluation system, and this result is used as information as shown in FIGS. 3, 4, and 7, for example.

  The sixth determination processing unit 7 refers to the processing result of the fourth determination processing unit 5 and / or the processing result of the fifth determination processing unit 6 and performs processing for deriving items to be improved in the class.

  The processing here is, for example, a numerical evaluation of a class analyzed by the fourth determination processing unit 5 (a plurality of items for evaluating a predetermined class, an understanding level, an intellectual stimulation level, an eagerness level) For example, the class is evaluated by classifying it into a plurality of evaluation patterns (here, 8 patterns) as shown in FIG. In other words, items to be improved can be clearly grasped in order to improve the content, quality, and improvement of the class, and to improve the attitude, motivation, and motivation of the students who are taking the class.

  For example, with the goal of the “balance growth type” shown in FIG. 11, it is possible to balance a part with excess or deficiency, or depending on a specific subject, even if the balance is broken to some extent, Issues such as extending the priority will become clear.

  Also, as shown at the bottom of the example shown on the right side of FIG. 10, the student's motivation and motivation are improved based on the numerical evaluation of the degree of understanding, intellectual stimulation, and eagerness. The sixth determination processing unit 7 can also perform the process of quantifying the degree.

  As a result, students will be able to understand how their motivation and motivation, which should be improved in the class, have changed at the start of the course, at the end of the previous term, at the end of the previous term, and at the end of the year. It is also possible to grasp the items that should be improved in order to improve the attitude, motivation, and motivation of students. In addition, in order to understand the motivation and motivation of the students who take the course, and analyze the changes over time, it is possible to improve the attitude, motivation and motivation of the students. It is also possible to grasp the items to be improved.

  FIG. 5 shows that the sixth judgment processing unit 7 takes a process of quantifying the degree of improvement in motivation and motivation of students based on quantified class evaluations for understanding, intellectual stimulation, and eagerness. This is done by comparing the results at the start and at the end of the course. This comparison can be done to understand how the degree of improvement in student motivation and motivation has changed for each student at the beginning and end of the course. It can also be done to understand how the percentage of motivated and motivated students in a specific class or grade is changing.

  The analysis performed in the sixth judgment processing unit 7 improves the content and quality of the lesson, and thus contributes to the improvement and improvement of the management and management of the educational institution that provides the lesson. It helps to derive KPI (Key Performance Indicator) in the management and management of educational institutions.

  In addition, as described in the lower left of the schematic configuration diagram of FIG. 10, the processing results in the first determination processing unit 2 to the eighth determination processing unit 9 in the class evaluation system 1 of the present invention described above, Students, faculty members who are allowed to access the information in the questionnaire database 21, the stratified database 22, the questionnaire + stratified database 23, the laying table database 24, and the analysis database 25 using the lesson evaluation system 1 of the present invention. , President, Dean, Educational Institution / Management, etc. can be referred to via the network.

  As a result, students, teachers, presidents, dean, educational institution management / managers, etc. can obtain reference materials for improving class content / quality, learning motivation / motivation, and eventually improving management / management content. become.

  As mentioned above, although preferred embodiment and the Example of this invention were described with reference to the accompanying drawing, this invention is not limited to these, In a technical range grasped | ascertained from a claim, it is various forms. It can be changed.

  For example, the class evaluation system of the present invention can be employed not only in universities but also in various educational institutions such as high schools, secondary schools, cram schools, prep schools, and vocational schools.

  In addition, in the sixth determination processing unit 7, referring to the processing result of the fourth determination processing unit 5 and / or the processing result of the fifth determination processing unit 6, performing a process of deriving items to be improved in the class In addition, the evaluations received for the classes conducted at the educational institution from elementary schools, secondary schools, high schools, examination examination schools, preparatory schools, etc. that send new students to the educational institution, graduates of the educational institution, A class that takes into account the information received from the companies that accepted the graduates of the educational institution, etc. regarding the classes conducted at the educational institution, the number of papers published and the number of patents acquired by the teachers conducting the class. It is possible to perform a process for deriving items to be improved in the above.

The figure showing an example of the state which has arrange | positioned the process result in a 1st determination process part to the space coordinate which consists of a uniaxial and two axes which intersect orthogonally. The figure showing another example of the state which has arrange | positioned the process result in a 1st determination process part to the spatial coordinate which consists of 1 axis | shaft and 2 axes which intersect orthogonally. The figure showing an example of the state which has arrange | positioned the process result in a 3rd determination process part to the space coordinate which consists of a perpendicular | vertical 1 axis and 2 axes. (A) The figure showing an example of the process result in the 8th determination process part performed about the questionnaire result with respect to a student, (b) The figure showing an example of the process result in the 5th determination process part. The figure showing an example which performed the process which digitizes the degree to which a student's motivation and motivation are improved by the 6th determination process part at the time of a course start and a course end, and the result was expressed and contrasted. The figure showing an example of the state which has arrange | positioned the process result in a 2nd determination process part to the spatial coordinate which consists of a perpendicular | vertical 1 axis and 2 axes. The figure showing an example of the process result in the 7th determination process part performed about the questionnaire result with respect to a student. The figure which shows an example of the questionnaire performed with respect to a student and a student. The figure which shows an example of the questionnaire performed with respect to a teacher. The conceptual diagram explaining the schematic structure about an example of the lesson evaluation system of this invention with the processing flow. The figure showing an example of each pattern in the case of expressing lesson to evaluate to a plurality of evaluation patterns (here 8 patterns) based on the processing result of the 6th judgment processing part. The figure showing the structure outline | summary of an example of the lesson evaluation system of this invention implement | achieved by the computer.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Class evaluation system 2 1st determination process part 3 2nd determination process part 4 3rd determination process part 5 4th determination process part 6 5th determination process part 7 6th determination process part 8 7th Judgment processor 9 Eighth decision processor 21 Questionnaire DB
22 Stratified DB
23 Questionnaire + DB
24 Cloth layout DB
25 Analysis DB

Claims (5)

A first determination processing unit that performs multivariate analysis of answers to questionnaire questions obtained from a plurality of students / students who take classes, and classifies the plurality of students / students into at least three groups based on the results of the analysis; ,
Analyzing the relationship between answers to the questionnaire questions of the plurality of students / students belonging to each group divided into at least three groups by the first determination processing unit and each group of the at least three groups A class evaluation system comprising a second determination processing unit. A third determination processing unit for analyzing a distribution tendency and a weight of each of the plurality of students belonging to each group divided into at least three groups by the first determination processing unit; The class evaluation system according to claim 1 provided. Multivariate analysis is performed with reference to the processing results of at least one of the first to third determination processing units, and numerical values are set for each of the plurality of items for evaluating the predetermined class. The lesson evaluation system according to claim 2, further comprising a fourth determination processing unit for deriving a normalized lesson evaluation. Analysis of responses to questionnaire questions obtained from multiple students / students taking classes and responses obtained from teachers who taught lessons to multiple students / students related to the questionnaire questions The class evaluation system according to claim 1, further comprising a fifth determination processing unit that analyzes a relationship between the two. 5. The sixth determination processing unit according to claim 3, further comprising a sixth determination processing unit that refers to a processing result of the fourth determination processing unit and / or the fifth determination processing unit and derives an item to be improved in the class. Class evaluation system.

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