Patent Application
20160086502
This application claims priority to Taiwan Application Serial Number 103132290, filed Sep. 18, 2014, which is herein incorporated by reference.
1. Field of Invention
The present invention relates to a skill evaluation method. More particularly, the present invention relates to a skill evaluation method of an online learning system.
2. Description of Related Art
With the development of network performance and website technology, the online learning course is a major trend in the field of education. The online learning course may be provided to learn and evaluate through a remote device and a network and without limited time.
For example, in Taiwan patent of publication No. 201027477, an online learning system is disclosed. The interactive online learning system may be provided to switch the remote online tutors arbitrarily according to user's learning result. It makes the learning system more flexible and optional. For instance, in Taiwan patent of publication No. 200847081, an online learning method is disclosed. During the learning course, the relative basic data and the statistic capacity and skill are provided to the remote device to assist learning. However, the information above may be not sufficient for the remote device to analyze user's skill thoroughly. The thorough performance of the remote device may not be reflected effectively, either. Accordingly, the issues may arise because of the inaccurate data.
For the forgoing reasons, there is a need for improving the defects and inconvenience of the technology above. Therefore, to solve the problems above is not only one important subject matter of development, but also an urgent need for the relative fields.
One aspect of this disclosure is providing a skill evaluation method of an online learning system to solve the defects and inconvenience of the prior art. The skill evaluation method of the online learning system may be implemented by a program and stored in a computer readable recording medium. Accordingly, after a computer accesses the computer readable recording medium above, the skill evaluation method of the online learning system may be executed. The skill evaluation method of the online learning system includes the steps as follows. Providing at least one remote device to log in an online learning platform; quantifying a learning result of the online learning process executed by the remote device on the online learning platform to obtain a professional skill data; quantifying an online community interaction of the remote device on the online learning platform to obtain a soft skill data; and utilizing the professional skill data and the soft skill data.
According to one or more embodiments of this disclosure, the step of quantifying the online community interaction of the remote device on the online learning platform to obtain the soft skill data further includes the following steps. When the remote device receives/transmits plural community interaction messages through the online learning platform, the messages are respectively quantified to first points, and the first points are calculated to be the first soft skill data of the remote device.
According to one or more embodiments of his disclosure, the skill evaluation method further includes the following steps. In the online learning process is executed by the remote device, the accomplishment of plural subsidiary subjects of at least one parent subject is quantified as a second soft skill data. Then, the second soft skill data is utilized.
According to one or more embodiments of this disclosure, the step of quantifying the accomplishment of plural subsidiary subjects of at least one parent subject further includes the following steps. A determination that whether at least one subsidiary subject is completed by the remote device is made. When the determination that the subsidiary subject being completed by the remote device is made, a second point is obtained by quantification according to a level of the subsidiary subject, and the second point is calculated to be a second soft skill data of the remote device.
According to one or more embodiments of this disclosure, the skill evaluation method further includes the following steps. The accomplishment efficiency executed by the remote device in the online learning process is quantified respectively to obtain a third soft skill data. Then, the third soft skill data is utilized.
According to one or more embodiments of this disclosure, the step of quantifying the accomplishment efficiency to obtain the third soft skill data further includes the following steps. A ratio of the actual spending time and the suggested accomplishment time of at least one subsidiary subject being accomplished by the remote device is calculated. The third point is obtained by quantification according to the ratio. The third point is then calculated to be the third soft skill data of the remote device.
According to one or more embodiments of this disclosure, the step of quantifying the accomplishment efficiency to obtain the third soft skill data further includes the following steps. A ratio of the actual spending time and the suggested accomplishment time of at least one parent subject being accomplished is calculated. The third point is obtained by quantification according to the ratio. The third point is calculated as the third soft skill data of the remote device.
According to one or more embodiments of this disclosure, the step of quantifying the learning result of the online learning process executed by the remote device on the online learning platform to obtain a professional skill data further includes the following steps. The remote device is provided to utilize at least one learning element of at least one of subsidiary subjects on the online learning platform. The learning result is quantified as a fourth point, and the fourth point is calculated to be the professional skill data of the remote device.
According to one or more embodiments of this disclosure, the step of quantifying the learning result as the fourth point further includes the following steps. When the online learning platform is utilized by the remote device, a reading time of the learning element is transformed into the fourth point when the online learning platform is utilized by the remote device, and the reading time of the learning element is proportional to the fourth point.
According to one or more embodiments of this disclosure, the step of quantifying the learning result as the fourth point further includes the following steps. A question correct rate of the learning element is transformed into the fourth point when the online learning platform is utilized by the remote device, and the question correct rate of the learning element is proportional to the fourth point.
According to one or more embodiments of this disclosure, the step of quantifying the learning result as the fourth point further includes the following steps. A game score of the learning element is transformed into the fourth point when the online learning platform is utilized by the remote device, and the game score is proportional to the fourth point.
According to one or more embodiments of this disclosure, the step of quantifying the learning result as the fourth point further includes the following step. The learning result is transformed into the fourth point according to a predetermined weight setting.
According to one or more embodiments of this disclosure, the step of utilizing the professional skill data and from the first to the third soft skill data further includes the following step. At least one of the professional skill data, and the first to the third soft skill data is graphed.
According to one or more embodiments of this disclosure, the step of utilizing the professional skill data and from the first to the third soft skill data further includes the following step. A percentile rank of the remote device with respect to other remote devices is provided in calculation according to at least one of the professional skill data and from the first to the third soft skill data for this remote device.
According to one or more embodiments of this disclosure, the step of utilizing the professional skill data and from the first to the third soft skill data further includes the following step. At least one of the professional skill data and from the first to the third soft skill data for this remote device is matched with a demand standard of at least one matching demand, and a matching result is generated.
Another aspect of this disclosure is providing an online learning system. The online learning system includes a server, and the server includes a network transmission device, a professional skill acquiring device, a soft skill acquiring device, a community interaction database, and a learner database. The network transmission device provides at least one remote device to log in the online learning system. The professional skill acquiring device quantifies the learning result of the online learning process executed by the remote device on the online learning platform to obtain a professional skill data. The soft skill acquiring device quantifies an online community interaction of the remote device on the online learning platform to obtain a first soft skill data. The learner database stores the professional skill data and the first soft skill data.
According to one or more embodiments of this disclosure, the soft skill acquiring device includes a community interaction database, a community interaction recording device, and a soft skill analyzing device. The community interaction recording device records the community interaction message which is transmitted/received from the online learning system by the remote device into the community interaction database. The community interaction messages are respectively quantified as first points. The soft skill analyzing device calculates the first points as the first soft skill data of the remote device.
According to one or more embodiments of this disclosure, the professional skill acquiring device includes a learning content database, a learning device and a professional skill analyzing device. The learning content database stores at least one parent subject having plural subsidiary subjects, and each of the subsidiary subjects includes at least one learning element. The learning device provides the remote device to use at least one learning element, records the learning result that the remote device using the learning element, and quantifies the learning result as a fourth point. The professional skill analyzing device calculates the forth point to be the professional skill data of the remote device.
According to one or more embodiments of this disclosure, the learning content database is provided with a checking table. The learning device refers to the checking table and quantifies the learning result as the fourth point according to the learning result.
According to one or more embodiments of this disclosure, the learning content database is provided with a weight setting table. The learning device refers to the weight setting table and quantifies the learning result as the fourth point according to the sort of one of the subsidiary subjects or the parent subject.
According to one or more embodiments of this disclosure, the professional skill acquiring device further quantifies the accomplishment of the subsidiary subjects of the parent subject executed by the remote device in the online learning process to obtain a second soft skill data.
According to one or more embodiments of this disclosure, the learning device further determines whether the remote device completes at least one of the subsidiary subjects, and quantifies to obtain a second point according to a level of the subsidiary subject when the remote device completing the subsidiary subject is determined, and also, the professional skill analyzing device calculates the second point as the second soft skill data of the remote device.
According to one or more embodiments of this disclosure, the learning device further determines whether the remote device completes all subsidiary subjects, and quantifies to obtain a second point according to the level of the parent subject when the remote device completing the subsidiary subject is determined, also, the professional skill analyzing device calculates the second point to be the second soft skill data of the remote device.
According to one or more embodiments of this disclosure, the professional skill acquiring device quantifies the accomplishment efficiency respectively of the online learning process executed by the remote device to obtain a third soft skill data.
According to one or more embodiments of this disclosure, the learning device calculates a ratio of the actual spending time and the suggested accomplishment time of each of the subsidiary subjects being accomplished by the remote device, and the learning device quantifies to obtain a third point respectively according to the ratio thereof, and the professional skill analyzing device calculates the third point to be the third soft skill data of the remote device.
According to one or more embodiments of this disclosure, the learning device further calculates the ratio of the actual spending time and the suggested accomplishment time for the parent subject being accomplished by the remote device. Then, the learning device quantifies to obtain the third point respectively according to the ratio, and the professional skill analyzing device calculates the third point to be the third soft skill data of the remote device.
According to one or more embodiments of this disclosure, the server further includes a graphing device. The graphing device graphs charts according to the professional skill data and from the first to the third soft skill data.
According to one or more embodiments of this disclosure, the server further includes a sorting device. The sorting device calculates the percentile rank of this remote device according to the professional skill data for this remote device and the other remote devices. The sorting device also calculates the percentile rank of this remote device according to one of the first to the third soft skill data for this remote device and for other remote devices.
According to one or more embodiments of this disclosure, the server further includes a matching device. The matching device matches at least one of the professional skill data and from the first to the third soft skill data for this remote device with a demand standard of at least one matching demand to generate a matching result.
To sum up, according to the skill evaluation method of this disclosure, not only the professional skill of a learner is analyzed during the online learning process, but also the soft skill of the learner is analyzed from his community interaction with others online. This method provides the learner with self-skill analysis and benefits his future application.
It is to be understood that both the foregoing general description and the following detailed description are by examples, and are intended to provide further explanation of the invention as claimed.
The accompanying drawings are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification. The drawings illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention. In the drawings,
Reference will now be made in detail to the present embodiments of the invention, examples of which are illustrated in the accompanying drawings. Wherever possible, the same reference numbers are used in the drawings and the description to refer to the same or like parts. According to the embodiments, it will be apparent to those skilled in the art that various modifications and variations can be made to the structure of the present invention without departing from the scope or spirit of the invention.
Referring to
The skill evaluation method includes the following steps. In Step 110, a remote device that is, a learner) is provided to log in an online learning platform. In Step 120, a learning result of the online learning process executed by the remote device on the online learning platform is quantified to obtain a professional skill data. In Step 130, an online community interaction of the remote device on the online learning platform is quantified to obtain a soft skill data. In Step 140, the professional skill data and the soft skill data are utilized.
As shown in
For example, the platform entrance may be a homepage of the learning website, or a learning-used application for smart phones in the remote device. However, the platform entrance of this invention is not limited to those above, it also may be a USB device connected to the remote device 300 directly.
The network transmission device 410 provides the aforementioned remote devices 300 (i.e., learners) for logging in the online learning platform through networks. The learner information recording device 420 is connected to the network transmission device 410, the soft skill acquiring device 440, the learner database 450 and the professional skill acquiring device 430. The learner information recording device 420 provides the remote devices (i.e., learners) with recording or registering learner information. The learner information can be basic information, professional certification license information and/or result work(s), however, the disclosure is not limited thereto.
The learner database 450 is connected to the professional skill acquiring device 430, the soft skill acquiring device 440, and the learner information recording device 420. The professional skill acquiring device 430 is connected to the soft skill acquiring device 440, and quantifies a learning result of the online learning process executed by one of the remote devices 300 (i.e., a learner) on the online learning platform to obtain a professional skill data. The professional skill data is stored in the learner database for sequent utilizations. The soft skill acquiring device 440 quantifies an online community interaction of the remote device 300 (i.e. the learner) on the online learning platform to obtain a first soft skill data. The first soft skill data is stored in the learner database 450 for sequent utilizations.
The soft skill acquiring device 440 includes a community interaction database 441, a community interaction recording device 442, and a soft skill analyzing device 443. The community interaction database 441 is connected to the community interaction recording device 442 and the soft skill analyzing device 443. When the remote device 300 receives and/or transmits plural community interaction messages through the online learning platform, the community interaction recording device 442 records the community interaction messages into the community interaction database 441 and quantifies the community interaction messages as one first point, respectively. In practice, one way to quantify one of the message as the first point is to use a checking table for recognizing the kinds of the message and the corresponding first point thereof. However, this invention is not limited to the usage of the checking table, for example, it may be accomplished only by calculating. The soft skill analyzing device 443 is connected to the learner database 450, and calculates (e.g., sum up or average) the first points to be the first soft skill data of the remote device 300 (i.e., the learner). Then, the first soft skill data is stored into the learner database 450.
The professional skill acquiring device 430 includes a learning content database 431, a learning device 432 and a professional skill analyzing device 433. The learning content database 431 stores at least one parent subject (i.e., program, course or subsidiary course). The parent subject includes plural subsidiary subjects (i.e., hurdles) and each of the subsidiary subjects includes at least one learning element. For example, each program includes plural courses or subsidiary courses, and each of the courses or subsidiary courses includes plural hurdles. Therefore, when the hurdles are defined as the subsidiary subject, the program, course or subsidiary course is defined as the parent subject of the hurdles.
The learning device 432 is connected to the professional skill analyzing device 433, learning content database 431, the community interaction recording device 442 and learner information recording device 420. The learning device 432 provides the remote device 300 with at least one learning element for using, records the learning results of the remote device 300 (i.e., the learner), and respectively quantifies the learning results as fourth points. The professional skill analyzing device 433 is connected to the learner database 450, and calculates (e.g., sum up or average) the forth points to be the professional skill data of the remote device 300 (i.e., the learner).
Specifically, a checking table is provided and stored in the learning content database 431. The checking table records the relationship between the levels of the learning results and the fourth points corresponding to the levels of the learning results. Therefore, when the learning device 432 refers to the checking table, the learning result may be quantified as the forth point according to the level of the learning result. However, this invention is not limited to the usage of the checking table, for example, it may be accomplished only by calculating. For instance, in other embodiment, a weight setting table is provided and stored in the learning content database 431. The weight setting table records the relationship between the levels of the learning results and the corresponding setting weights. The learning device 432 refers to the weight setting table and quantifies the learning results as the fourth points according to the sorts of the subsidiary subjects or the parent subject. However, this invention is not limited to the usage of the weight setting table, for example, it may be accomplished only by calculating.
The professional skill acquiring device 430 respectively quantifies the accomplishments of the subsidiary subjects of at least one parent subject being executed by the remote device in the online learning process so as to obtain a second soft skill data. Then, the second soft skill data is stored in the learner database 450 for sequent utilizations. In practice, for this embodiment, the learning device 432 is utilized to determine whether the remote device 300 completes to utilize one of the subsidiary subjects. When the remote device 300 completing to utilize the subsidiary subject is determined by the learning device 432, the learning device 432 quantifies to obtain a second point according to the level of the subsidiary subject. Besides, the learning device 432 is further utilized to determine whether the remote device 300 completes to utilize all subsidiary subjects. When the remote device 300 completing to utilize all subsidiary subjects is determined by the learning device 432, the learning device 432 of the professional skill acquiring device 430 quantifies a second point according to the level of the parent subject. In practice, one way to quantify for the second point is to use a checking table in which the second point is checked out in accordance with the level of the subsidiary subject being filled in the checking table. However, this invention is not limited to the usage of the checking table, for example, it may be accomplished only by calculating. The professional skill analyzing device 433 of the professional skill acquiring device 430 is utilized to calculate (e.g., sum up or average) the second point as the second soft skill data of the remote device 300.
Besides, the professional skill acquiring device 430 is further utilized to quantify the accomplishment efficiency respectively in the online learning process being executed by the remote device 300, so as to obtain a third soft skill data. Then, the third soft skill data is stored in the learner database 450 for sequent utilizations. In practice, the learning device 432 of the professional skill acquiring device 430 is further utilized to calculate the ratio of the actual spending time and the suggested accomplishment time for the accomplished subsidiary subject or the accomplished parent subject. Then, the learning device 432 respectively quantifies to obtain the third point according to the ratio. In practice, one way to quantify for the third point is to use a checking table in which the third point is checked out in accordance with the ratio filled in the checking table. However, this invention is not limited to the usage of the checking table, for example, it may be accomplished only by calculating. The professional skill analyzing device 433 of the professional skill acquiring device 430 is utilized to calculate (e.g., sum up or average) the third point to be the third soft skill data of the remote device 300.
Accordingly, as shown in
The professional skill and the soft skill for the learner analyzed previously may be displayed in the “professional skill” field 650 and the “soft skill” field 660 in a chart form. However, in other embodiments, the professional skill and the soft skill for the learner analyzed previously may be shown in the “professional skill” field 650 and the “soft skill” field 660 in other way (e.g., digitalization).
Further, in order to realize the learning performance of the remote device (i.e., the learner), each of the subsidiary subjects 720 (e.g., hurdles) has learning elements 730. The learning elements are, but not limited to, films, articles, questions and or games. For instance, in the course plan 700 in
As shown in
For example, when the learning element 730 is a film, the learning device 432 may calculate the fourth point according to the watching time for the remote device (i.e., the learner). Accordingly, the professional skill analyzing device 433 may calculate the professional skill data for the remote device (i.e., the learner). The professional skill data is stored at the corresponding address for the remote device (i.e., the learner) in the learner database 450. The length of watching time for the film is proportional to the fourth point. Besides, when the learning device 432 detects that the time length that the film being watched is longer than a predetermined ratio of the full length of the film, the learning device 432 determines that the remote device (i.e., the learner) has completed this subsidiary subject 720 (i.e., hurdle) and vice versa.
For another example, when the learning elements 730 are questions, the learning device may transform question correct rate of the remote device e., the learner) to the fourth point. Accordingly, the professional skill analyzing device 433 may calculate the professional skill data of the remote device (i.e., the learner). The professional skill data is stored at the corresponding address for the remote device (i.e.; the learner) in the learner database 450. The question correct rate for the questions is proportional to the fourth point. practice, if the remote device (i.e., the learner) correctly answers the question till the second time, the learning device 432 may discount the fourth point.
For another example, when the learning element 730 is an interaction game, the learning device 432 may calculate to get the fourth point according to the game score granted by the remote device (i.e., the learner). Accordingly, the professional skill analyzing device 433 may calculate the professional skill data of the remote device (i e., the learner). The professional skill data is stored at the corresponding address for the remote device (i.e., the learner) in the learner database 450. The game score is proportional to the fourth point.
However, it should be understood that the quantifications of the learning result above are merely examples and those should not limit this invention. The person with ordinary knowledge in the art may select other implementing method as required.
It should be understood that under the same or different parent subjects (e.g., courses), the difficulties of the learning elements for all subsidiary subjects (e.g., hurdles) are various. Therefore, it may set different weights corresponding to the different learning elements to generate respective fourth points as required.
In addition to utilizing the content of the online learning platform, the remote device (i.e., the learner) may execute community interactions with other remote devices (i.e., other learners) on the online learning platform. The interactions may be, for example, question & answer, discussion, sharing and replying the learning elements above (including courses, films, articles and so on), and recommending or encouraging other learners. However, this invention is not limited to those above, the remote device (i.e., the learner) may execute course learning and community interaction independently.
As shown in
Finally, the professional skill analyzing device 433 may calculate (e.g., sum up or average) all the second points granted by the remote device (i.e., the learner) as the second soft skill data for Initiative 810 category. The second soft skill data is stored at the corresponding address for the remote device (i.e., the learner) in the learner database 450.
In Interactive expression 820 and Trouble shooting 830 categories, when the remote device (i.e., the learner) releases a community interaction message to other remote devices (specific learners or nonspecific learners) or receives a community interaction message from other remote devices (specific learners or nonspecific learners), the community interaction recording device 442 quantities the community interaction message as the first point according to the kind of the community interaction record. The first point is stored in the community interaction database 441 and is accumulated into the first soft skill data of the remote device (i.e., the learner). For example, the community interaction message may be an article publishing message, an article replying message, an article recommending message, a thumbs up message, a subject approximation message, a best solution message or/and a virtual gift giving message. However, this invention is not limited to those above. For example, whenever an article is published by the learner, the community interaction recording device 422 records that the remote device (i.e., the learner) grants ten points for the first point. For another example, whenever an article is replied by the learner, the community interaction recording device 422 records that the remote device (i.e., the learner) grants five points for the first point. For yet another example, the community interaction recording device 422 counts the number of thumbs up message received from other remote devices (specific learners or nonspecific learners) as the first point granted. Because the online learning platform 500 has a clear operation interface, the community interaction recording device 422 may obtain the article publishing message, the article replying message, the article recommending message, the thumbs up message, the subject approximation message, the best solution message and the virtual gift giving message clearly. Finally, the soft skill analyzing device 443 may calculate (e.g. sum up or average) the first point in the community interaction database 441 as the second soft skill data for Interactive expression 820 and Trouble shooting 830 categories. The first soft skill data is stored at the corresponding address for the remote device (i.e., the learner) in the learner database 450.
It should be understood that the Interactive expression 820 category is related to that the remote device (i.e., the learner) releases the community interaction message to other remote devices (specific learners or nonspecific learners), and the Trouble shooting 830 category is related to that the remote device (i.e., the learner) receives the community interaction message from other remote devices (specific learners or nonspecific learners). Therefore, the person with ordinary knowledge in this art may easily distinguish or combine Interactive expression 820 and Trouble shooting 830 categories in the first soft skill data.
In learning efficiency 840 category, when the learning device 432 calculates the ratio of the actual spending time and the suggested accomplishment time for the accomplished subsidiary subject respectively. Then, the learning device 432 quantifies the third point respectively according to the ratio. Finally, the professional skill analyzing device 433 may calculate (e.g., sum up or average) the third point granted by the remote device (i.e.; the learner) as the third soft skill data for learning efficiency 840 category. The third soft skill data is stored at the corresponding address for the remote device (i.e., the learner) in the learner database 450.
It should be understood that the features of the soft skill categories are not invariant, those may be amended by verification to satisfy the requirement. For example, first, the platform is configured to acquire and analyze the skill according to the function definition and the market demand. Then, said community interaction is recorded and analyzed to obtain the skill data. Finally, the analysis result of the platform is verified by questionnaire and evaluation.
In practice, for the skill evaluation method of this invention, the professional skill and the soft skill may be charted, especially for the professional skill data, and from the first to the third soft skill data. However, this invention is not limited to those above.
In practice, for the skill evaluation method of this invention, the professional skill and the soft skill may be sorted in percentile ranking. However, this invention is not limited to those above.
However, this invention is not limited to those above. The sorting device 470 may sort the percentile rank of the remote device according to the professional′ skill data for this remote device and for other remote devices.
In practice, for the skill evaluation method of this invention, the professional′ skill and the soft skill may be matched with job vacancy. However, this invention is not limited to those above.
The matching device 560 matches at least one of the professional skill data and from the first to the third soft skill data for this remote device with a demand standard of at least one matching demand (e.g., job vacancy, school integration). In this embodiment, the matching device 560 matches at least one of the professional skill data and from the first to the third soft skill data for this remote device (i.e., the learner) with a demand standard of at least one job vacancy in the job vacancy database, and to generate a matching result., and to generate a matching result. The matching result is displayed in a human resource list 570 on the enterprise end, and in a job vacancy list 540 on the learner end partially or thoroughly. The job vacancy list 540 on the learner end may be responded in field 670 for “matching result for job vacancy” at the lower part of the webpage 600 in
It should be understood that the learner information recording device, the professional skill acquiring device, the soft skill acquiring device, the graphing device and the sorting device may be a software/a firmware, or an integration of a processor (e.g., CPU, CPU or single chip) and a software/a firmware executed thereby. The database mentioned above may be a storage device or a portion storing space in a storage device.
To sum up, according to the skill evaluation method of this disclosure, not only the professional skill of a learner is analyzed during the online learning process, but also the soft skill of the learner is analyzed from his community interaction with others online. This method provides the learner with self-skill analysis and benefits his future application.
Although the present invention has been described in considerable detail with reference to certain embodiments thereof, other embodiments are possible. Therefore, the spirit and scope of the appended claims should not be limited to the description of the embodiments contained herein.
It will be apparent to those skilled in the art that various modifications and variations can be made to the structure of the present invention without departing from the scope or spirit of the invention. In view of the foregoing, it is intended that the present invention cover modifications and variations of this invention provided they fall within the scope of the following claims and their equivalents.
| Number | Date | Country | Kind |
|---|---|---|---|
| 103132290 | Sep 2014 | TW | national |
