JP2002230242A - Ability and attitude evaluation system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a performance evaluation system capable of evaluating the personal ability with high objectivity. SOLUTION: This ability and attitude evaluation system is provided with a basic data preparation means for preparing a basic data base based on result evaluation data, process data on a process leading to the result, and other data and a ability and attitude calculation means for calculating personal ability and attitude based on the basic data base prepared by the basic data base preparation means.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION The invention of the present application is used, for example, to evaluate the abilities and attitudes of individuals belonging to an organization such as a company or to determine the abilities and attitudes of students belonging to schools and cram schools. Regarding the ability / attitude evaluation system to evaluate, in particular, individual abilities /
The present invention relates to a device devised so that an attitude can be automatically calculated by numerical values and evaluated.

[0002]

2. Description of the Related Art In recent years, the importance of personnel evaluation systems in companies has been increasing. This is due to the spread of the merit-based personnel system. This type of personnel evaluation is divided into a performance evaluation that measures an employee's ability to perform work and a capability evaluation that measures an employee's ability to perform his or her duties. Of these,
By grasping the ability of employees by ability evaluation,
Empirical analysis of individual and group ability levels, strengths and weaknesses, relative comparisons with others (other groups), changes in ability over time, and the effects of various personnel measures are possible. Therefore, the use of ability evaluation is being attempted in a wide range of personnel measures and human resource development.

[0003]

According to the above-mentioned conventional configuration, there are the following problems. In other words, the conventional personnel evaluation basically has a large influence on the subjectivity of the evaluator, and thus cannot be said to be highly objective. That is,
In order to qualitatively evaluate the ability, it is essential to grasp the indicators (degree of difficulty) that indicate the difficulty of various actions to be performed in the course of business execution, and to grasp the quantitative causal relationship between the actions on performance and performance. . However, in the conventional case, the degree of difficulty in various actions is determined artificially and qualitatively, and the quantitative relations between actions on performance and performance are quantitatively grasped while recognizing the causal relationship. That was not done. That was a major cause of the lack of objectivity of evaluation. It should be noted that this kind of problem is not limited to the ability and attitude evaluation in companies, but also applies to the ability and attitude evaluation of students and students in schools and cram schools, and similarly in the ability and attitude evaluation in various other cases. It can be said.

The present invention has been made on the basis of the above points, and it is an object of the present invention to provide a capability / attitude evaluation system which can automatically evaluate an individual's ability / attitude with high objectivity. To provide.

[0005]

In order to achieve the above object, a capability evaluation system according to claim 1 of the present invention creates a basic database based on result evaluation data, process data relating to a process leading to the result, and other data. And a capacity / attitude calculating means for calculating a personal ability / attitude based on the basic database created by the basic database creating means. The ability / attitude evaluation system according to claim 2 is the ability / attitude evaluation system according to claim 1, wherein the result evaluation data is performance evaluation data, and the process data is behavior questionnaire data regarding an action leading to the performance. It is characterized by having. The ability / attitude evaluation system according to claim 3 is the ability / attitude evaluation system according to claim 1, wherein the result evaluation data is academic achievement evaluation data, and the process data is an action questionnaire regarding an action leading to the academic achievement. It is characterized by being data. The ability / attitude evaluation system according to claim 4 is the ability / attitude evaluation system according to claim 2 or 3, wherein the action questionnaire determines the degree of performance for a plurality of action contents set as questions. It is characterized by being selected and answered separately.
The ability / attitude evaluation system according to claim 5 is characterized in that in the ability / attitude evaluation system according to claim 5, the contents of the behavior questionnaire can be appropriately added or changed. The ability / attitude evaluation system according to claim 6 is the ability / attitude evaluation system according to any one of claims 2 to 4, wherein the behavior questionnaire data is taken out from the basic database to be used as a question of the behavior questionnaire. Behavior difficulty calculation means for calculating the difficulty level of each action content is provided, and the ability / attitude calculation means calculates the difficulty level of each action content calculated by the action difficulty level calculation means and the action questionnaire data. The present invention is characterized in that the ability / attitude of the evaluated person is calculated. The ability / attitude evaluation system according to claim 7 is the ability / attitude evaluation system according to any one of claims 1 to 5, wherein the ability / attitude calculation means extracts result evaluation data from the basic database. The ability and attitude of the evaluated person are calculated in consideration of the result evaluation data. An ability / attitude evaluation system according to claim 8 is the ability evaluation system according to claim 6 or 7, wherein the behavior difficulty calculating means calculates the difficulty of each action using item response theory. It is characterized by being.
According to a ninth aspect of the present invention, in the ability / attitude evaluation system according to any one of the second to eighth aspects, the behavior questionnaire data is taken out from the basic database to determine whether or not it is one-factor. And one factor determining means for determining whether the behavioral questionnaire is appropriate or not based on the determination. or,
The ability / attitude evaluation system according to claim 10 is the same as claim 9.
The described ability / attitude evaluation system is characterized in that a means is provided for prompting restructuring of a behavior questionnaire when the one-factor determining means determines that there is no one-factor. According to an eleventh aspect of the present invention, in the ability / attitude evaluation system according to any one of the second to tenth aspects, the ability / attitude calculation means includes a predetermined arbitrary action intention and action. The present invention is characterized in that the ability and attitude of the evaluated person are calculated by associating with the action contents of the questionnaire. or,
According to the twelfth aspect of the present invention, there is provided a system
1. In the ability / attitude evaluation system described in 1,
The attitude calculating means creates an occupation type ability model from arbitrary action intentions selected according to the occupation type and corresponding action questionnaire data, and evaluates the ability / attitude of the evaluated person along the occupation type ability model. It is characterized by being. According to a thirteenth aspect of the present invention, there is provided the ability / attitude evaluation system according to the eleventh or twelfth aspect, wherein the occupation type is determined based on the action intention of the evaluated person who produces a high result and the action content of the action questionnaire. A feature model is to be created.
The ability / attitude evaluation system according to claim 14 is the ability / attitude evaluation system according to claim 12 or 13, wherein the ability / attitude calculation means uses the covariance structure analysis method to generate a job-specific ability model. It is characterized by being created.

That is, in the ability / attitude evaluation system according to the present invention, first, the basic database creating means creates a basic database based on the input result evaluation data, the process data relating to the process leading to the result, and other data. . Next, the ability / attitude calculating means calculates the ability / attitude of the individual based on the created basic database. At this time, it is conceivable that the result evaluation data is used as performance evaluation data, and the process data is used as behavior questionnaire data relating to an action leading to the performance. Further, it is conceivable that the result evaluation data is used as academic performance evaluation data, and the process data is used as behavioral questionnaire data relating to an action leading to the academic performance. In addition, it is conceivable that the behavioral questionnaire may be such that a degree of performance is selected for each of a plurality of behavioral contents set as a question and answered. At this time, it is conceivable that the contents of the behavior questionnaire can be added or changed as appropriate. Further, there is provided an action difficulty level calculating means for extracting the action questionnaire data from the basic database and calculating the difficulty level of each action content as a question of the action questionnaire. It is conceivable to calculate the ability / attitude of the evaluated person from the difficulty level of each action content calculated by the means and the action questionnaire data. Further, it is conceivable that the ability / attitude calculating means extracts the result evaluation data from the basic database and calculates the ability / attitude of the evaluated person in consideration of the result evaluation data. In addition, as the above-mentioned behavior difficulty calculating means, a means for calculating the difficulty of each behavior using the item response theory can be considered. It is also conceivable to provide a one-factor determining means for extracting behavioral questionnaire data from the basic database and determining whether or not the behavioral questionnaire is one factor, and thereby determining whether or not the behavioral questionnaire is appropriate. At this time, it is conceivable to provide a means for prompting the restructuring of the behavior questionnaire when the one-factor determining means determines that there is no one-factor. In addition, the ability / attitude calculating means may calculate the ability / attitude of the evaluated person by associating a predetermined arbitrary action intention with the action content of the action questionnaire. In addition, as the ability / attitude calculating means, an occupation type ability model is created from an arbitrary action intention selected according to the occupation type and the corresponding behavior questionnaire data, and the ability of the evaluator is evaluated along the occupation type ability model. May be evaluated. In addition, it is conceivable to provide a means for creating a job-specific ability model based on the action intention of the evaluated person who produces a high result and the action content of the action questionnaire. In addition, it is conceivable that the ability / attitude calculation means creates a job-specific ability model using a covariance structure analysis method.

[0007]

DESCRIPTION OF THE PREFERRED EMBODIMENTS One embodiment of the present invention will be described below with reference to FIGS. In this embodiment, the invention of the present application is applied to the evaluation of the ability and attitude of an individual in a company. First, as shown in FIG. 1, behavior questionnaire data (corresponding to process data) 1 collected in advance is input (step S1). Here, the behavior questionnaire data 1 means both a plurality of behavior contents (questionnaire items) set as questions and their results. Further, the performance evaluation data (result evaluation data) 3 that is compiled in advance is input (step S2). Further, the job type, the name of the person to be evaluated, and other personnel data (corresponding to other data) 5 are input (step S3). By inputting these data, a basic database 7 which is the basis of the subsequent information processing is created.

FIG. 8 shows an example of the behavior questionnaire 1. FIG. 8 shows behavior questionnaire 1 used in this embodiment.
And a number 1 to a number 92 in the vertical direction.
The action contents (questionnaire items on the behavior of the evaluator, which are displayed as "contents" in FIG. 8) as the questions up to are described (note that only numbers 1 to 7 are shown in FIG. 8). There is a response column in the horizontal direction. In the above-mentioned action contents, individual actions observed in the course of business execution are described as questions. For example, the number "1" indicates "I work in various ways to fulfill my boss's requirements and internal standards." The action content "" is described, and the number "2" sets "a goal that is higher than the boss's request by himself, instead of being forced by the boss."
Is described. Hereinafter, the action contents are sequentially described as questions up to the number “92”.

On the other hand, the strength (category scale) for the action content set as a question is sequentially described in each step in the answer column. Specifically, "Not at all", "Mostly not applicable", "Rather not applicable", "Neither", "Somewhat applicable", "Most applicable",
It is divided into seven levels according to its strength, such as "Applicable at all". Points are determined for each stage. 1 point for "Not at all applicable", 2 points for "Mostly not applicable", 3 points for "Not applicable", 4 points for "Neither applicable", and "Applicable" 5 points, 6 points for “mostly applicable”, and 7 points for “all applicable”. Then, the evaluator selects one of the intensities for each of the items to be evaluated.

For example, an evaluator responds to a question with a number "1" for a certain evaluator, that is, an action content of "work in various ways to fulfill the demands of the boss and satisfy company standards." But "neither"
Is selected, and as a result, the strength point relating to the action content is “4”. Incidentally, the number of evaluators in this embodiment is 3 in total.
There are 49 evaluators, and any evaluator obtained the data from the behavioral questionnaire 1 for all the evaluators.

Next, the performance evaluation data is 5 data.
It is a graded evaluation, and "1"
"2", "3", "4", and "5". The evaluator determines each evaluator. In this embodiment, only 238 of the 349 evaluators have performance evaluation data, and the remaining 111 have no performance evaluation data. The above-mentioned performance evaluation data, the data of the behavior questionnaire mentioned above,
The basic database 7 as shown in FIG. 9 can be obtained by inputting the evaluated person name and the other personnel data. FIG. 9 shows a part of the basic database 7 displayed on a display (not shown) as it is.

As shown in FIG. 9, the basic database 7 includes “company number”, “occupation type”, “CD”,
"Affiliation", "evaluator", "evaluator", "performance evaluation",
"Item 1", "Item 2", "Item 3" ... "Item 9"
There is a display "2", and data is input for each evaluator. As described above, the five-level evaluation is input to the performance evaluation item as described above, and a point indicating the strength of each action content of the action questionnaire is input to each item. For example, looking at the evaluator “001” in the first row, the “company number” is “1002”
, "Occupation" is "12" and "CD" is "1".
Where "affiliation" is "manufacturing department", "evaluator" is "A", "performance evaluation" is "4", "item 1" is "5 points", and "item “2” is “5 points”, and “item 3” is “5 points”.

Next, the operation of evaluating the ability and attitude of the evaluated person based on the basic database 7 will be sequentially described. First, as shown in FIG. 2, an operation of reading an action evaluation result from the basic database 7 is performed (step S4). Here, the behavior evaluation result means the result of the behavior questionnaire 1, that is, “item 1”, “item 2”, “item 3” in the basic database 7 shown in FIG. -The point of "item 92". Next, the process proceeds to step S5, where factor analysis is performed. Next, the process proceeds to step S6, where it is determined whether or not the result of the factor analysis is “one-factor”. When it is determined by this determination that the behavior questionnaire is not one-factor, a warning or display is given to that effect, and the behavior questionnaire 1 is reconstructed. On the other hand, if it is determined to be one factor, the process proceeds to step S7.

The discrimination of the one-factor property will be further described. The one-factor property means that the quality of each action content in the action questionnaire 1 shown in FIG. 8 is the same. It is to determine whether or not there is.
FIG. 10 shows the result of the factor analysis. FIG. And the eigenvalue, contribution rate (%) and accumulation (%) are taken in the horizontal direction to show the numerical values. This figure 1
As is clear from 0, the eigenvalue ratio between the first factor and the second factor is as large as 8.76, and the value below the second factor is a low value. It can be seen that 1 has a high one-factor property.

Returning to FIG. 2, in step S7,
The difficulty of each action content in the action questionnaire 1 is calculated by the item response theory. First, the behavioral level is scaled by categorical factor analysis of one factor. When measuring characteristics such as ability and attitude by the rating scale method, the item response theory expresses the characteristic value function (item characteristic function) that measures the probability that each item is affirmed, and expresses the characteristics of those items. Is used. The item characteristic function uses a probit model (normal cumulative model) in addition to the logistics model.

[0016] In this case, positive response to be evaluated's ability level f = θ is against the action items u _i of behavior questionnaire (to be evaluated person such action can be seen in the day-to-day operations ) Is referred to as a “one-parameter normal cumulative model” or a “rush model”.

[0017]

(Equation 1)

[0018] To estimate the discriminatory power a and difficulty b _i rush model by covariance structure model, representing a model formula a factor of categorical factor analysis and Equation 2.

[0019]

(Equation 2)

If z _i > τ _il , u _i = 1, z
Assume that u _i = 0 is observed if _i <τ _il . Here, τ _il is a threshold value, and z _i follows a standard normal distribution with an average of 0 and a variance of 1. The probability of a positive response to the causal action (action content) of the action questionnaire 1 in the entire group is as follows. It is expressed as in Equation 3.

[0021]

(Equation 3)

Then, assuming that the factor pattern is common to all the causal action items (that is, placing equalization constraints on the factor patterns), the parameter is estimated. Further, by converting the estimated parameter based on the following Expressions 4 and 5, the item characteristic curve of the rush model can be specified, the level of each causal action can be set, and the distance can be scaled. Then, by such a method, the parameter is estimated on the assumption that the factor pattern is common to all the causal action items (that is, the equalization constraint is placed on the factor pattern).
However, in consideration of a decrease in the result of the fitness, the parameter of the observation variable 10 having a high factor score is estimated as a parameter by narrowing down the behavior. It is shown in FIG. The “item” in FIG. 11 is the action content in the action questionnaire 1, and 10 action contents are selected.

[0023]

(Equation 4)

[0024]

(Equation 5)

[0025] In addition, the evaluation performed on a 7-point scale was evaluated as 1
The parameters are converted to 0 and the evaluations 5 to 7 are converted to 1 to estimate the parameter. Then, the parameter estimation result is as shown in FIG. 12, and the matching degree is as shown in FIG.

In order to estimate the degree of difficulty and the degree of discrimination, the equalization is restricted by assuming that the factor pattern is common to all the contents of the behavior questionnaire 1. As a result, the estimated value (α) was estimated to be 0.248. The fit of this model, chi ² have been rejected at the 5% significance level in the assay, this model looking CFI, the RMR, etc. is adapted to the data. Then, it is possible to obtain the degree of difficulty for each causal action as shown in FIG. The obtained degree of difficulty for each causal action is displayed in step S8. As shown in FIG. 14, the difficulty level is different for each of the 92 action contents set in the action questionnaire 1, and the calculated difficulty level is used for ability / attitude evaluation. For example, even if the result of a certain two action contents is the same, the evaluation is different if the degree of difficulty of the action contents is different, and the points of the action contents having a higher degree of difficulty are higher. In addition, it is displayed on the display in a state as shown in FIG.

Next, in step S9, the action contents of the action questionnaire 1, ie, each question, are read from the basic database 7. Then, a causal action classification and a difficulty / level correspondence table are obtained based on the read data (step S10). That is, a causal behavior classification is created that expresses each behavioral intention (large item, medium item) set on the basis of “intention to achieve high performance”. That is, each action content described in the action questionnaire 1 is classified into each action intention set on the basis of "will" to achieve a result. It is shown in FIG. FIG.
Are shown in the order of "action intention (large item)", "number", "action intention (middle item)", and "definition". For example, the action intention (large item) is “action intention regarding performance”, and the corresponding action intention (middle item) is “efficiency”, “accuracy”, “foresight”, and “information collection”.
Next, as shown in FIG. 16, a level was assigned to the degree of difficulty. Here, the difficulty level is the difficulty level shown in FIG. 14, and is obtained by leveling based on the criteria shown in FIG.

Then, the causal action list database 11 is created based on the data obtained through the above steps, and is displayed (step S11). Specifically, FIG.
As shown in FIG. FIG.
In the causal action list shown in FIG. 7, first, a plurality of action contents as questions of the action questionnaire 1 are classified according to the type of action intention. The difficulty level and the level are calculated and displayed together. As described above, FIG.
The causal action list shown in FIG. 7 is displayed on the display as it is. FIG. 17 is a diagram showing a part of a list of all causal actions.

In addition, for the behaviors and their difficulties in the illustrated causal behavior list, new behaviors and their difficulties may be newly added to the behaviors of various companies using item response theory. That is, depending on the company, the action content as a question of the action questionnaire 1 may be added or changed, and in that case, a part of the causal action list shown in FIGS. 17 to 21 may be added or changed. Will be. For example, 10 new observation variables to be used for estimation are added to 20 items. Then, the same estimation as in the case described above is performed. FIG. 18 shows the result. Assuming that the causal pattern is common to all the action items, the estimated value (α) subjected to the equalization constraint was estimated to be 0.24 as in the case of the ten items shown in FIG. .

Next, shifting to FIG.
In step 12, the evaluation result (points of each item in the basic database shown in FIG. 9) of the causal behavior (action content of the behavior questionnaire 1) of each evaluated person in the basic database 7 is read. In step S13, the causal action (the action content of the action questionnaire 1) and its level in the causal action list database 9 are read. Next, the process proceeds to step S14 to multiply the read causal action evaluation result by the level. That is, the level of the causal action is multiplied by the performance of the evaluator, that is, the result of the behavior questionnaire,
That is the score of causal action. In other words, a higher score will be obtained when a high degree of difficulty (level) exhibits a high degree of performance with respect to the action content.

Next, the process proceeds to step S15, and the scores of each causal action are collected for each action intention. Next, the process proceeds to step S16 to calculate an average score for each action intention by each evaluator. In other words, in order to ensure the stability of the causal behavior score, the causal behavior scores are summarized for each behavioral intention, the average score is calculated, and the causal behavior score for each behavioral intention is calculated. Next, the process proceeds to step S17, and the causal behavior score for each evaluator is displayed.

Next, moving to FIG.
At 18, the causal action score according to the evaluator is determined. Also, in step S19, the basic database 7
Load the performance evaluation result of. Then, in step S20, a correlation analysis is performed between the read causal action score for each action-evaluation for each evaluator and the performance evaluation result. In other words, the correlation analysis between the performance evaluation score and the causal behavior score according to the behavioral intention is divided into job types (for example, manager, current business, planning and development, clerical,
Construction supervisor). As a result, a result as shown in FIG. 19 was obtained. As shown in FIG. 19, the correlation between the performance evaluation score and the score of the causal action according to the behavior intention differs depending on the type of job. FIG. 19 shows the correlation among the manager, the current job, the planning and development job, the clerical job, the manager among the construction supervisors, and the current job.

Next, the process proceeds to step S21 to determine whether the correlation function is 0.5 or more and 1% is significant. As a result of the determination, the correlation function is 0.5 or more and 1%
If it is determined that the result is significant, the process proceeds to step S22, and a causal action display according to the action intention unique to the high-performing person is performed. On the other hand, as a result of the discrimination, the correlation function is 0.5 or more and 1
If it is determined that the percentage is not significant, such display is not performed.

Next, moving to FIG.
At 23, the causal action score for each action evaluator is read. In step S24, the performance evaluation result for each evaluator in the basic database 7 is read.
Next, in step S25, a factor score weight is calculated by covariance structure analysis. Then, step S
The process proceeds to 26 to display factor score weights.

Next, in FIG. 6, first, a causal behavior score for each behavioral intention that is unique to a high-performing person whose performance evaluation is unknown is read (step S27). In step S28, the causal behavior score for each behavior evaluator whose performance evaluation is known and which is unique to the high-performing person is read. Basic database 7
Of the performance evaluation result for each evaluator (step S2
9). Next, the process proceeds to step S30 to calculate a factor score weight by covariance structure analysis. Next, the process proceeds to step S31 to display a factor score weight.

The operation of step S30 will be described in detail. First, performance evaluations and causal actions according to behavioral intentions unique to high-performing persons and ability models as observation variables are created for each job type (for example, management, current, planning and development, clerical, and construction supervisory). In other words, paying attention to the results of the behavior questionnaire of people who have high performance in each occupation type, select an action content item that gives high points, and try to see points for other people with respect to the selected activity content item. Is what you do. At that time, the data obtained by the behavior questionnaire 1 had observation values for all 349 evaluators, whereas the performance evaluation data had only 238 data, and the remaining 111 data had performance evaluations. No missing data. Then, a mean / covariance structure analysis including missing data was performed.

With the above-mentioned ability model, it is possible to quantitatively grasp the causal relationship between the action on the ability and the performance.
In addition, for the statistical instability of the model due to the small number of data, the statistical data of the model is actively used as “missing data” by using the data in which only the same type of activity is observed. Stability can be ensured. As a result of the covariance structure analysis, it was found that the causal relationship between the ability and the performance in each occupation had a causal relationship of about 0.6 to 0.7 in each occupation.

Regarding the causal relationship between the ability and the performance, in the state where the performance is entirely determined by the presence or absence of the ability, since the standardization coefficient between the ability and the performance is "1", the performance in any occupation is other than the ability. It is thought that it is influenced by factors. This is considered to be a middle point between performance and competence (external requirements, internal requirements, personal requirements). FIG. 20 shows the standardization coefficients for the causal relationship between the abilities and the performances, and FIG.

Since the conformity of CFI is good and a high causal relationship between ability and performance is recognized as described above, this ability model is a model imitating the causal relationship between action, ability, and performance. It is something that can be considered to be. Examples of the job-specific ability models are shown in FIGS. FIG. 22 shows a manager's ability model, and FIG. 23 shows a manager's ability model. Similar models are obtained for other occupations. FIG. 24 shows a high-performing person image in each occupation as viewed from the occupation ability model.

For example, FIG. 22 shows a model of managerial abilities. First, look at behavior questionnaire data of persons (or persons) receiving high performance evaluations among a plurality of managers. . Then, the user selects the action intention exhibiting a high point and the action content related thereto, and thereby determines the action intention and action content required for the manager. In this way, the manager's ability model is decided.

Next, referring to FIG. 7, in step S32, a factor score weight is read. In step S33, a causal action score for each action evaluator whose performance evaluation is known and which is unique to the high-performing person is read. In addition, the process shifts to step S34 to read the performance evaluation result for each evaluator in the basic database. Next, the process proceeds to step S35 to multiply the factor score weight, the causal action score by action intention, and the performance evaluation result by evaluator. In other words, by multiplying the value of the performance evaluation result of the evaluator, the value of the causal behavior by behavioral intention by the factor score weight, and adding the values,
Calculate the factor score for each evaluator. By calculating and scoring the factor scores of each of the evaluated persons, it is possible to significantly identify the difference in the ability of each of the evaluated persons based on an objective criterion of a numerical value. Then, the process proceeds to step S36 to display the evaluated factor score. FIG. 25 shows an example of factor scores for each evaluator.

FIG. 25 shows the case of a manager. In the case of a manager, there is an ability model as shown in FIG. 22, which is calculated using data on ten action intentions listed therein and action contents related thereto.

The present invention is not limited to the above embodiment. For example, the content of the behavior as a question in the behavior questionnaire, the number of questions, and the like are not particularly limited. The number of evaluators and evaluators is not particularly limited. Further, in the above-described embodiment, the evaluation of the ability and attitude of an individual in a company has been described as an example, but the present invention is not limited to this. Applicable to ability and attitude evaluation in cases.

[0044]

As described in detail above, the ability according to the present invention
According to the attitude evaluation system, the following effects can be obtained. First, the basic database creation means
Create a basic database based on the input result evaluation data, process data, and other data,
The ability / attitude calculation means is configured to calculate the ability / attitude of the evaluator based on the data stored in the basic database, so if necessary data is collected and input, the ability / attitude of the individual is automatically obtained. The attitude is evaluated, and the ability evaluation with high objectivity becomes possible. In addition, if the contents of the behavior questionnaire can be added or changed as appropriate, it is possible to evaluate individual abilities in various types of organizations. Further, when the difficulty level of each action content is calculated by the action difficulty level calculation means, a more accurate ability evaluation can be performed. In addition, when the ability of the evaluator is calculated in consideration of the performance evaluation data, the accuracy of the evaluation can be improved. In addition, when the behavioral questionnaire data is taken out from the basic database to determine whether or not the behavioral questionnaire is a one-factor property, thereby determining whether or not the behavioral questionnaire is appropriate, a more appropriate behavioral questionnaire is provided. The content can be described, and thereby the evaluation accuracy can be improved. Further, when a means for prompting the restructuring of the behavior questionnaire is provided when it is determined that there is no one factor, the use of an inappropriate behavior questionnaire can be restricted. Further, even when the ability calculating means calculates the ability of the evaluated person by associating a predetermined arbitrary action intention with an action, the evaluation with higher accuracy is possible. In addition, when an occupation-specific ability model is created and the ability of the evaluated person is evaluated along the occupation-specific ability model, high-precision evaluation becomes possible. Further, by performing data processing while focusing on the process of a person who gives a high result for each occupation type, evaluation with higher accuracy can be performed.

[Brief description of the drawings]

FIG. 1 is a diagram showing an embodiment of the present invention, and is a flowchart showing a flow of a capability / attitude evaluation system.

FIG. 2 is a flowchart showing a flow of the ability / attitude evaluation system according to the embodiment of the present invention.

FIG. 3 is a flow chart showing a flow of the ability / attitude evaluation system according to the embodiment of the present invention.

FIG. 4 is a view showing one embodiment of the present invention, and is a flow chart showing a flow of the ability / attitude evaluation system.

FIG. 5 is a view showing one embodiment of the present invention, and is a flow chart showing a flow of the ability / attitude evaluation system.

FIG. 6 is a view showing an embodiment of the present invention, and is a flow chart showing a flow of the ability / attitude evaluation system.

FIG. 7 is a diagram showing an embodiment of the present invention, and is a flowchart showing a flow of a capability / attitude evaluation system.

FIG. 8 is a diagram showing an embodiment of the present invention, and is a diagram showing the contents of a behavior questionnaire.

FIG. 9 is a diagram showing an embodiment of the present invention, and is a diagram showing contents of a basic database.

FIG. 10 is a diagram illustrating an embodiment of the present invention, and is a diagram illustrating a result of factor analysis for an action questionnaire item.

FIG. 11 is a diagram illustrating an embodiment of the present invention, and is a diagram illustrating a path diagram expression related to Expression 2;

FIG. 12 is a diagram illustrating an embodiment of the present invention, and is a diagram illustrating a categorical factor analysis parameter estimation result of a factor.

FIG. 13 is a diagram illustrating an embodiment of the present invention, and is a diagram illustrating a result of categorical factor analysis fitness of a factor.

FIG. 14 is a diagram illustrating an embodiment of the present invention, and is a diagram illustrating an example of a degree of difficulty for each causal action.

FIG. 15 is a diagram illustrating an embodiment of the present invention, and is a diagram illustrating a causal behavior classification.

FIG. 16 is a diagram illustrating an embodiment of the present invention, and is a diagram illustrating a difficulty / level correspondence table of causal behavior.

FIG. 17 is a diagram illustrating an embodiment of the present invention, and is a diagram illustrating an example of a causal action list.

FIG. 18 is a diagram illustrating an embodiment of the present invention, and is a diagram illustrating a result of estimating a categorical factor analysis parameter of a factor.

FIG. 19 is a diagram illustrating an embodiment of the present invention, and is a diagram illustrating a result of a job type correlation analysis.

FIG. 20 is a diagram illustrating an embodiment of the present invention, and is a diagram illustrating a standardization coefficient for a causal relationship between ability and performance.

FIG. 21 is a diagram illustrating an embodiment of the present invention, and is a diagram illustrating a list of degree of conformity of the model of occupational abilities.

FIG. 22 is a diagram illustrating an embodiment of the present invention, and is a diagram illustrating a capability model of a manager;

FIG. 23 is a diagram showing an embodiment of the present invention, and is a diagram showing a model of the abilities of a manager;

FIG. 24 is a diagram illustrating an embodiment of the present invention, and is a diagram illustrating a high-performing person image in each occupation viewed from an occupation-specific ability model.

FIG. 25 is a diagram illustrating an embodiment of the present invention, and is a diagram illustrating an example of factor scores for each evaluated person.

[Explanation of symbols]

 1 Behavioral questionnaire data (process data) 3 Performance evaluation data (result evaluation data) 5 Other personnel data (other data) 7 Basic database

Claims (14)

[Claims] 1. A basic database creating means for creating a basic database based on result evaluation data, process data relating to a process leading to the result, and other data, and an individual based on the basic database created by the basic database creating means. A capacity / attitude calculation means for calculating the capacity / attitude of the user; 2. The ability / attitude evaluation system according to claim 1, wherein the result evaluation data is performance evaluation data, and the process data is behavior questionnaire data on the behavior leading to the performance. Attitude evaluation system. 3. The ability / attitude evaluation system according to claim 1, wherein the result evaluation data is academic performance evaluation data, and the process data is behavior questionnaire data on an action leading to the academic performance. Ability and attitude evaluation system. 4. The ability / attitude evaluation system according to claim 2 or 3, wherein the behavior questionnaire is to answer a plurality of behavior contents set as a question by selecting their degree of performance for each stage. Ability and attitude evaluation system characterized by the following. 5. The ability / attitude evaluation system according to claim 5, wherein the action questionnaire can add or change the content of the action as appropriate. 6. The ability / attitude evaluation system according to claim 2, wherein the behavior questionnaire data is taken out from the basic database and the difficulty of each behavior content as a question of the behavior questionnaire is calculated. The ability / attitude calculation means calculates the ability / attitude of the evaluator from the difficulty level of each action content calculated by the action difficulty level calculation means and the action questionnaire data. An ability / attitude evaluation system characterized by being calculated. 7. The ability / attitude evaluation system according to claim 1, wherein said ability / attitude calculation means takes out result evaluation data from said basic database and considers said result evaluation data. And an ability / attitude evaluation system for calculating the ability / attitude of the evaluated person. 8. The ability evaluation system according to claim 6, wherein the behavior difficulty calculating means calculates the difficulty of each action using an item response theory.・ Attitude evaluation system. 9. The ability / attitude evaluation system according to claim 2, wherein the behavior questionnaire data is taken out from the basic database, and it is determined whether or not the factor is one-factor. A capability / attitude evaluation system characterized by being provided with a one-factor determining means for judging the suitability of a person. 10. The ability / attitude evaluation system according to claim 9, further comprising means for prompting restructuring of a behavior questionnaire when said one-factor determining means determines that there is no one-factor. Ability and attitude evaluation system. 11. The ability / attitude evaluation system according to claim 2, wherein the ability / attitude calculation means associates a predetermined arbitrary action intention with an action content of an action questionnaire. An ability / attitude evaluation system for calculating the ability / attitude of the evaluated person. 12. The ability / attitude evaluation system according to claim 11, wherein said ability / attitude calculation means creates an occupation-specific ability model from an arbitrary action intention selected according to the job type and action questionnaire data corresponding thereto. A capability / attitude evaluation system for evaluating the ability / attitude of the evaluated person according to the job-specific ability model. 13. The ability / attitude evaluation system according to claim 11 or 12, wherein an action intention of the evaluator who produces a high result and an action content of the action questionnaire based on the action content of the action questionnaire. The ability / attitude evaluation system is characterized in that a skill model is created by selecting a job. 14. The ability / attitude evaluation system according to claim 12, wherein said ability / attitude calculation means creates a job-specific ability model using a covariance structure analysis method. Ability and attitude evaluation system.