CN114510600A - Learning system and method based on human-computer interaction - Google Patents
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Abstract
The invention provides a learning system and method based on human-computer interaction. The method comprises the steps of setting a test exercise answer sheet according to pre-learning contents and learning targets input by a user and currently mastered learning information input by the user in an exercise type proportion setting mode; according to the answer results, a learning plan is made by combining the learning content, the learning target and the like; extracting course videos from the course video database according to a learning plan, and integrating the course videos to set daily learning time, learning video courses and exercise plans; the method comprises the steps that a user learns courses and supports the user to carry out video-in skip and video-in note generation in the course video process; and determining the grasping condition of the user on the content corresponding to the current course video according to the answering condition of the exercise of the user after the course video, and determining whether the content corresponding to the current course video is learnt again in the subsequent learning plan according to the grasping condition. The system comprises a module corresponding to the method.
Description
Technical Field
The invention provides a learning system and method based on human-computer interaction, and belongs to the technical field of learning systems.
Background
With the continuous development of internet technology and the continuous diversification of student's learning mode, online education learning system has been the indispensable learning tool of student's web course study at present, however, most current online education learning systems all only provide simple teaching course and teaching video for the student, can't carry out the setting of study plan according to student's actual learning condition and have reached the purpose that the system carries out effective interaction with the student.
Disclosure of Invention
The invention provides a learning system and a method based on human-computer interaction, which are used for solving the problem that the existing on-line learning education system of students can not adjust the learning cycle and the learning plan according to the actual learning mastering conditions of the students, and adopt the following technical scheme:
a learning method based on human-computer interaction, the learning method comprising:
setting a test exercise answer sheet in an exercise type proportion setting mode according to pre-learning content and a learning target input by a user and currently mastered learning information input by the user;
making a learning plan according to the answer result of the test exercise answer sheet by the user and by combining the learning content, the learning target and the learning period input by the user;
extracting course videos from the course video database according to a learning plan, and integrating the course videos to set daily learning time, learning video courses and exercise plans;
the user learns courses according to the learning plan and supports the user to carry out video-in skip and video-in note generation in the course video process;
and determining the grasping condition of the user on the content corresponding to the current course video according to the answering condition of the exercise of the user after the course video, and determining whether the content corresponding to the current course video is learnt again in the subsequent learning plan according to the grasping condition.
Further, according to the pre-learning content and the learning objective input by the user and the currently mastered learning information input by the user, the test exercise answer sheet is set in an exercise type proportion setting mode, which comprises the following steps:
judging whether the mastered learning information input by the user contains learning information belonging to pre-learned contents or not according to the mastered learning information input by the user at present;
and setting the test exercise answer sheet in an exercise type proportion setting mode according to a judgment result corresponding to whether the mastered learning information input by the user contains the learning information belonging to the pre-learning content.
Further, the setting module includes:
when the judgment result is that the mastered learning information input by the user contains learning information belonging to the pre-learning content, setting a first-level exercise content in the mastered learning information; setting second-level exercise content in a learning content range which is in line with the pre-learning content and the learning target range but does not belong to the mastered learning information; wherein, the proportion relation between the first level exercise content and the second level exercise content is as follows: the content proportion of the first-level exercises is 85% -95%; the content proportion of the second-level exercises is 5% -15%;
when the judgment result is that the mastered learning information input by the user does not contain the learning information belonging to the pre-learning content, setting a first level exercise content in the mastered learning information and the learning information belonging to the pre-learning content; setting second-level exercise content in a learning content range which accords with the pre-learning content and the learning target range; at this time, the knowledge content related to the second-level exercises is the knowledge content with a low difficulty in the preliminary range of the pre-learning content, and the proportion relationship between the first-level exercises and the second-level exercises is as follows: the content proportion of the first-level exercises is 90% -95%; the content proportion of the second-level exercises is 5% -10%;
and combining the first-level exercise question content and the second-level exercise question content to form a test exercise question answer sheet.
Furthermore, according to the answer result of the test question answer sheet by the user, a learning plan is made by combining the learning content, the learning target and the learning cycle input by the user, which comprises the following steps:
acquiring answer scores of the test exercise answer sheet;
judging the current mastering condition of the user aiming at the pre-learning content according to the answer score;
judging whether the learning period set by the user is reasonable or not according to the grasping condition;
when the learning period set by the user is in a reasonable range, making a learning plan according to the learning period set by the user;
and when the learning period set by the user is unreasonable, adjusting the learning period set by the user to obtain an adjusted learning period, and making a learning plan according to the adjusted learning period.
Further, when the learning period set by the user is not reasonable, adjusting the learning period set by the user to obtain an adjusted learning period, including:
when the learning period set by the user exceeds the reasonable learning period, acquiring the time difference between the learning period set by the user and the reasonable period, and adjusting the learning period by using the time difference between the learning period set by the user and the reasonable period; specifically, a first adjustment model is used to adjust the learning period, where the first adjustment model is as follows:
wherein the content of the first and second substances,T 1representing a learning period after the learning period is adjusted by using the first adjustment model;T h representing the reasonable period;T z representing the self-set learning period of the user;nrepresenting the total number of chapters contained in the current user pre-learning content;Wrepresenting a total score of the test question answer sheet;W 1representing the answer scores of the user to the test question answer sheet;
when the learning period set by the user is smaller than the reasonable learning period, acquiring the time difference between the learning period set by the user and the reasonable period and the score difference between the answer score obtained by the user and the standard score corresponding to the reasonable period, and adjusting the learning period by using the time difference between the learning period set by the user and the reasonable period and the score difference between the answer score obtained by the user and the standard score corresponding to the reasonable period; specifically, a second adjustment model is used to adjust the learning period, where the second adjustment model is as follows:
wherein the content of the first and second substances,T 2representing a learning period after the learning period is adjusted by using the second adjustment model;T h representing the reasonable period;T z representing the self-set learning period of the user;nrepresenting the total number of chapters contained in the current user pre-learning content;Wrepresenting a total score of the test question answer sheet;W 1representing the answer scores of the user to the test question answer sheet;W 0expressing the answer score obtained by the user and the standard score corresponding to the reasonable period;
the reasonable period is set according to the answer scores of the test exercise answer paper of the user and comprises a first-level reasonable period, a second-level reasonable period and a third-level reasonable period; when the score is lower than the passing score line (60% of full score corresponds to the score), setting a first-level reasonable period; when the score is higher than the passing score line but lower than the excellent score line (80% of full score corresponds to score), setting a second level reasonable period; when the score is higher than the excellent score line (80% of full score corresponds to score), setting a third-level reasonable period; and the specific time lengths of the first-level reasonable period, the second-level reasonable period and the third-level reasonable period are set according to chapters and contents of the learning target.
A human-computer interaction based learning system, the learning system comprising:
the answer sheet setting module is used for setting a test exercise answer sheet according to pre-learning content and a learning target input by a user and currently mastered learning information input by the user in an exercise type proportion setting mode;
the plan making module is used for making a learning plan according to the answer result of the test exercise answer sheet by the user and by combining the learning content, the learning target and the learning period input by the user;
the course setting module is used for extracting course videos from the course video database according to a learning plan and integrating and setting daily learning time, learning video courses and exercise plans for the course videos;
the note generation module is used for a user to carry out course learning according to the learning plan and supporting the user to carry out video-in skip and video-in note generation in the course video process;
and the relearning module is used for determining the mastering condition of the user on the content corresponding to the current course video according to the answering condition of the exercise of the user after the course video, and determining whether the content corresponding to the current course video is relearned in the subsequent learning plan according to the mastering condition.
Further, the answer sheet setting module comprises:
the judging module is used for judging whether the grasped learning information input by the user contains the learning information belonging to the pre-learning content or not according to the grasped learning information input by the user at present;
and the setting module is used for setting the test exercise answer sheet in an exercise type proportion setting mode according to a judgment result of whether the grasped learning information input by the user contains the learning information corresponding to the pre-learning content.
Further, the setting module includes:
the answer sheet setting module I is used for setting first-level exercise contents in the grasped learning information when the judgment result is that the grasped learning information input by the user contains the learning information belonging to the pre-learning contents; setting second-level exercise content in a learning content range which is in line with the pre-learning content and the learning target range but does not belong to the mastered learning information; wherein, the proportion relation between the first level exercise content and the second level exercise content is as follows: the content proportion of the first-level exercises is 85% -95%; the content proportion of the second-level exercises is 5% -15%;
the answer sheet setting module II is used for setting first-level exercise contents in the grasped learning information and the learning information associated with the pre-learning content when the judgment result is that the grasped learning information input by the user does not contain the learning information belonging to the pre-learning content; setting second-level exercise content in a learning content range which accords with the pre-learning content and the learning target range; at this time, the knowledge content related to the second-level exercises is the knowledge content with a low difficulty in the preliminary range of the pre-learning content, and the proportion relationship between the first-level exercises and the second-level exercises is as follows: the content proportion of the first-level exercises is 90% -95%; the content proportion of the second-level exercises is 5% -10%;
and the synthesis module is used for combining the first-level exercise content and the second-level exercise content to form a test exercise answer sheet.
Further, the planning module includes:
the acquisition module is used for acquiring the answer scores of the test exercise answer sheet;
the situation judging module is used for judging the current mastering situation of the user aiming at the pre-learning content according to the answer score;
the reasonable judgment module is used for judging whether the learning period set by the user is reasonable or not according to the grasping condition;
the plan generating module is used for making a learning plan according to the learning cycle set by the user when the learning cycle set by the user is in a reasonable range;
and the period adjusting module is used for adjusting the learning period set by the user when the learning period set by the user is unreasonable to obtain the adjusted learning period, and formulating a learning plan according to the adjusted learning period.
Further, the period adjustment module includes:
the first adjusting module is used for acquiring the time difference between the learning period and the reasonable period set by the user when the learning period set by the user exceeds the reasonable period for learning, and adjusting the learning period by using the time difference between the learning period and the reasonable period set by the user; specifically, a first adjustment model is used to adjust the learning period, where the first adjustment model is as follows:
wherein the content of the first and second substances,T 1representing a learning period after the learning period is adjusted by using the first adjustment model;T h representing the reasonable period;T z representing the self-set learning period of the user;nrepresenting the total number of chapters contained in the current user pre-learning content;Wrepresenting a total score of the test question answer sheet;W 1representing the answer scores of the user to the test question answer sheet;
the second adjusting module is used for acquiring the time difference between the learning period and the reasonable period set by the user and the score difference between the answer score obtained by the user and the standard score corresponding to the reasonable period when the learning period set by the user is smaller than the reasonable period for learning, and adjusting the learning period by utilizing the time difference between the learning period and the reasonable period set by the user and the score difference between the answer score obtained by the user and the standard score corresponding to the reasonable period; specifically, a second adjustment model is used to adjust the learning period, where the second adjustment model is as follows:
wherein the content of the first and second substances,T 2representing a learning period after the learning period is adjusted by using the second adjustment model;T h representing the reasonable period;T z representing the self-set learning period of the user;nrepresenting the total number of chapters contained in the current user pre-learning content;Wrepresenting a total score of the test question answer sheet;W 1representing the answer scores of the user to the test question answer sheet;W 0expressing the answer score obtained by the user and the standard score corresponding to the reasonable period;
the reasonable period is set according to the answer scores of the test exercise answer paper of the user and comprises a first-level reasonable period, a second-level reasonable period and a third-level reasonable period; when the score is lower than the passing score line (60% of full score corresponds to the score), setting a first-level reasonable period; when the score is higher than the passing score line but lower than the excellent score line (80% of full score corresponds to score), setting a second level reasonable period; when the score is higher than the excellent score line (80% of full score corresponds to score), setting a third-level reasonable period; and the specific time lengths of the first-level reasonable period, the second-level reasonable period and the third-level reasonable period are set according to chapters and contents of the learning target.
The invention has the beneficial effects that:
the learning system and the method based on the man-machine interaction can adjust the learning cycle and the learning plan according to the actual learning grasping condition of the student, and effectively improve the reasonability of the learning plan setting aiming at the pre-learning content of the student. Effectively improving the learning efficiency and the mastering degree of learning contents. Meanwhile, according to the input condition and the test of the mastered knowledge of the student user, the proficiency degree of the student aiming at the mastered knowledge points and the potential capability of deducing and processing the knowledge content which is not mastered and learned based on the mastered knowledge content can be effectively discovered, and the mastering speed of the student user aiming at the pre-learning content and the rationality of the learning plan making can be further improved by setting the learning plan through the mining quantity degree and the potential capability.
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FIG. 1 is a first flow chart of the method of the present invention;
FIG. 2 is a second flow chart of the method of the present invention;
fig. 3 is a system block diagram of the system of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
The embodiment of the invention provides a learning method based on human-computer interaction, which comprises the following steps of:
s1, setting a test exercise answer sheet according to the pre-learning content and the learning target input by the user and the currently mastered learning information input by the user in an exercise type proportion setting mode;
s2, making a learning plan according to the answer result of the test question answer sheet by the user and by combining the learning content, the learning target and the learning period input by the user;
s3, extracting course videos from the course video database according to a learning plan, and integrating the course videos to set daily learning time, learning video courses and exercise plans;
s4, the user learns courses according to the learning plan and supports the user to skip in the videos and generate notes in the videos in the course video process;
s5, determining the mastering condition of the user for the content corresponding to the current course video according to the answering condition of the exercise of the user after the course video, and determining whether the content corresponding to the current course video is learnt again in the subsequent learning plan according to the mastering condition.
As shown in fig. 2, the method for setting test exercise answer sheets according to the pre-learning content and the learning objective inputted by the user and the currently mastered learning information inputted by the user via the exercise type ratio setting mode includes:
s101, judging whether the mastered learning information input by the user contains learning information belonging to pre-learning content or not according to the mastered learning information input by the user at present;
and S102, setting the test exercise answer sheet in an exercise type proportion setting mode according to a judgment result corresponding to whether the mastered learning information input by the user contains the learning information belonging to the pre-learning content.
The working principle of the technical scheme is as follows: firstly, setting a test exercise answer sheet in an exercise type proportion setting mode according to pre-learning content and a learning target input by a user and currently mastered learning information input by the user; then, according to the answer result of the test exercise answer sheet by the user, a learning plan is made by combining the learning content, the learning target and the learning period input by the user; then, extracting a course video from the course video database according to a learning plan, and integrating the course video to set daily learning time, learning video courses and exercise plans; then, the user learns courses according to the learning plan and supports the user to carry out video-in skip and video-in note generation in the course video process; and finally, determining the grasping condition of the user on the content corresponding to the current course video according to the answering condition of the user after the course video, and determining whether the content corresponding to the current course video is learnt again in a subsequent learning plan according to the grasping condition.
The effect of the above technical scheme is as follows: the learning method based on the man-machine interaction can adjust the learning cycle and the learning plan according to the actual learning grasping condition of the student, and effectively improves the reasonability of the setting of the learning plan aiming at the pre-learning content of the student. The learning efficiency and the mastering degree of learning contents are effectively improved. Meanwhile, according to the input condition and the test of the mastered knowledge of the student user, the proficiency degree of the student aiming at the mastered knowledge points and the potential capability of deducing and processing the knowledge content which is not mastered and learned based on the mastered knowledge content can be effectively discovered, and the mastering speed of the student user aiming at the pre-learning content and the rationality of the learning plan making can be further improved by setting the learning plan through the mining quantity degree and the potential capability.
In one embodiment of the present invention, the setting module includes:
s1021, when the judgment result is that the mastered learning information input by the user contains learning information belonging to pre-learning content, setting first-level exercise content in the mastered learning information; setting second-level exercise content in a learning content range which is in line with the pre-learning content and the learning target range but does not belong to the mastered learning information; wherein, the proportion relation between the first level exercise content and the second level exercise content is as follows: the content proportion of the first-level exercises is 85% -95%; the content proportion of the second-level exercises is 5% -15%;
s1022, when the judgment result is that the mastered learning information input by the user does not contain the learning information belonging to the pre-learning content, setting a first level exercise content in the mastered learning information and the learning information belonging to the pre-learning content; setting second-level exercise content in a learning content range which accords with the pre-learning content and the learning target range; at this time, the knowledge content related to the second-level exercises is the knowledge content with a low difficulty in the preliminary range of the pre-learning content, and the proportion relationship between the first-level exercises and the second-level exercises is as follows: the content proportion of the first-level exercises is 90% -95%; the content proportion of the second-level exercises is 5% -10%;
and S1023, combining the first-level exercise content and the second-level exercise content to form a test exercise answer sheet.
The working principle of the technical scheme is as follows: firstly, when the judgment result is that the mastered learning information input by the user contains learning information belonging to the pre-learning content, setting a first-level exercise content in the mastered learning information; setting second-level exercise content in a learning content range which is in line with the pre-learning content and the learning target range but does not belong to the mastered learning information; wherein, the proportion relation between the first level exercise content and the second level exercise content is as follows: the content proportion of the first-level exercises is 85% -95%; the content proportion of the second-level exercises is 5% -15%; then, when the judgment result is that the grasped learning information input by the user does not contain the learning information belonging to the pre-learning content, setting first-level exercise content in the grasped learning information and the learning information associated with the pre-learning content; setting second-level exercise content in a learning content range which accords with the pre-learning content and the learning target range; at this time, the knowledge content related to the second-level exercises is the knowledge content with a small difficulty in the preliminary learning content range, and the proportional relationship between the first-level exercises and the second-level exercises is as follows: the content proportion of the first-level exercises is 90% -95%; the content proportion of the second-level exercises is 5% -10%; and combining the first-level exercise question content and the second-level exercise question content to form a test exercise question answer sheet.
The effect of the above technical scheme is as follows: according to the input condition and the test of the mastered knowledge of the student user, the proficiency degree of the student aiming at the mastered knowledge points and the potential capability of deducing and processing the knowledge content which is not mastered and learned based on the mastered knowledge content can be effectively discovered, and the mastering speed of the student user aiming at the pre-learning content and the rationality of the learning plan making can be further improved by setting the learning plan through the mining quantity degree and the potential capability. Meanwhile, the test paper obtained according to the proportion can furthest investigate and mine the mastering conditions of the student users on the learned contents and the unlearned contents, and further furthest improves the reasonability of subsequent learning plan setting.
In one embodiment of the present invention, the step of making a learning plan according to the answer result of the test question answer sheet input by the user and by combining the learning content, the learning objective and the learning cycle input by the user comprises:
s301, acquiring answer scores of the user to the test exercise answer sheet;
s302, judging the current mastering condition of the user aiming at the pre-learning content according to the answer score;
s303, judging whether the learning period set by the user is reasonable or not according to the grasping condition;
s304, when the learning period set by the user is in a reasonable range, making a learning plan according to the learning period set by the user;
s305, when the learning period set by the user is unreasonable, adjusting the learning period set by the user to obtain an adjusted learning period, and making a learning plan according to the adjusted learning period.
When the learning period set by the user is unreasonable, the learning period set by the user is adjusted to obtain the adjusted learning period, and the method comprises the following steps:
s3051, when the learning period set by the user exceeds the reasonable learning period, acquiring the time difference between the learning period set by the user and the reasonable learning period, and adjusting the learning period by using the time difference between the learning period set by the user and the reasonable learning period; specifically, a first adjustment model is used to adjust the learning period, where the first adjustment model is as follows:
wherein the content of the first and second substances,T 1representing a learning period after the learning period is adjusted by using the first adjustment model;T h representing the reasonable period;T z representing the self-set learning period of the user;nrepresenting the total number of chapters contained in the current user pre-learning content;Wrepresenting a total score of the test question answer sheet;W 1representing the answer scores of the user to the test question answer sheet;
s3052, when the learning period set by the user is smaller than the reasonable learning period, acquiring the time difference between the learning period set by the user and the reasonable period and the score difference between the answer score obtained by the user and the standard score corresponding to the reasonable period, and adjusting the learning period by using the time difference between the learning period set by the user and the reasonable period and the score difference between the answer score obtained by the user and the standard score corresponding to the reasonable period; specifically, a second adjustment model is used to adjust the learning period, where the second adjustment model is as follows:
wherein the content of the first and second substances,T 2representing a learning period after the learning period is adjusted by using the second adjustment model;T h representing the reasonable period;T z representing the self-set learning period of the user;nrepresenting the total number of chapters contained in the current user pre-learning content;Wrepresenting a total score of the test question answer sheet;W 1representing the answer scores of the user to the test question answer sheet;W 0expressing the answer score obtained by the user and the standard score corresponding to the reasonable period;
the reasonable period is set according to the answer scores of the test exercise answer paper of the user and comprises a first-level reasonable period, a second-level reasonable period and a third-level reasonable period; when the score is lower than the passing score line (60% of full score corresponds to the score), setting a first-level reasonable period; when the score is higher than the passing score line but lower than the excellent score line (80% of full score corresponds to score), setting a second level reasonable period; when the score is higher than the excellent score line (80% of full score corresponds to score), setting a third-level reasonable period; and the specific time lengths of the first-level reasonable period, the second-level reasonable period and the third-level reasonable period are set according to chapters and contents of the learning target.
The working principle of the technical scheme is as follows: firstly, acquiring the answer score of a user to the test exercise answer sheet; judging the current mastering condition of the user aiming at the pre-learning content according to the answer score; then, judging whether the learning period set by the user is reasonable or not according to the grasping condition; when the learning period set by the user is in a reasonable range, making a learning plan according to the learning period set by the user; and when the learning period set by the user is unreasonable, adjusting the learning period set by the user to obtain an adjusted learning period, and making a learning plan according to the adjusted learning period.
The effect of the above technical scheme is as follows: by means of the mode, a learning cycle which is more balanced and effective relative to objective and reasonable learning cycle requirements and student self-set learning cycle requirements can be set for students, so that the mastering degree of the students for learning contents is improved, and the balance between learning efficiency and knowledge point mastering is improved. Meanwhile, the reasonable period is a period time length with range, although the method of the embodiment can provide an objective and reasonable learning period according to the test request of the student, the student learns the learning habit of the student and the mastering habit of receiving a new knowledge point most, in order to avoid neglect the self-set learning period set by the student aiming at the self-learning, the reasonable period obtained by the objective data and the learning period set by the student aiming at the self-learning are considered through the formula to carry out the learning period adjustment, so that the effective balance between the learning speed of the student aiming at new learning content and the learning knowledge mastering degree can be further improved, and the proficiency of the student aiming at the pre-learning content can be ensured to the maximum degree in the least time period. The problems that the learning efficiency is low due to overlong learning time and the knowledge mastering proficiency is low due to an overlong time period are solved.
An embodiment of the present invention provides a learning system based on human-computer interaction, as shown in fig. 3, the learning system includes:
the answer sheet setting module is used for setting a test exercise answer sheet according to pre-learning content and a learning target input by a user and currently mastered learning information input by the user in an exercise type proportion setting mode;
the plan making module is used for making a learning plan according to the answer result of the test exercise answer sheet by the user and by combining the learning content, the learning target and the learning period input by the user;
the course setting module is used for extracting course videos from the course video database according to a learning plan and integrating and setting daily learning time, learning video courses and exercise plans for the course videos;
the note generation module is used for a user to carry out course learning according to the learning plan and supporting the user to carry out video-in skip and video-in note generation in the course video process;
and the relearning module is used for determining the mastering condition of the user on the content corresponding to the current course video according to the answering condition of the exercise of the user after the course video, and determining whether the content corresponding to the current course video is relearned in the subsequent learning plan according to the mastering condition.
Wherein, answer sheet sets up the module and includes:
the judging module is used for judging whether the mastered learning information input by the user contains the learning information belonging to the pre-learning content or not according to the mastered learning information input by the user at present;
and the setting module is used for setting the test exercise answer sheet in an exercise type proportion setting mode according to a judgment result whether the mastered learning information input by the user contains the learning information corresponding to the pre-learning content.
The effect of the above technical scheme is as follows: the learning system based on human-computer interaction provided by the embodiment can adjust the learning cycle and the learning plan according to the actual learning grasping condition of the student, and effectively improves the reasonability of the setting of the learning plan aiming at the pre-learning content of the student. Effectively improving the learning efficiency and the mastering degree of learning contents. Meanwhile, according to the input condition and the test of the mastered knowledge of the student user, the proficiency degree of the student aiming at the mastered knowledge points and the potential capability of deducing and processing the knowledge content which is not mastered and learned based on the mastered knowledge content can be effectively discovered, and the mastering speed of the student user aiming at the pre-learning content and the rationality of the learning plan making can be further improved by setting the learning plan through the mining quantity degree and the potential capability.
In one embodiment of the present invention, the setting module includes:
the answer sheet setting module I is used for setting first-level exercise contents in the grasped learning information when the judgment result is that the grasped learning information input by the user contains the learning information belonging to the pre-learning contents; setting second-level exercise content in a learning content range which is in line with the pre-learning content and the learning target range but does not belong to the mastered learning information; wherein, the proportion relation between the first level exercise content and the second level exercise content is as follows: the content proportion of the first-level exercises is 85% -95%; the content proportion of the second-level exercises is 5% -15%;
the answer sheet setting module II is used for setting first-level exercise contents in the grasped learning information and the learning information associated with the pre-learning content when the judgment result is that the grasped learning information input by the user does not contain the learning information belonging to the pre-learning content; setting second-level exercise content in a learning content range which accords with the pre-learning content and the learning target range; at this time, the knowledge content related to the second-level exercises is the knowledge content with a low difficulty in the preliminary range of the pre-learning content, and the proportion relationship between the first-level exercises and the second-level exercises is as follows: the content proportion of the first-level exercises is 90% -95%; the content proportion of the second-level exercises is 5% -10%;
and the synthesis module is used for combining the first-level exercise content and the second-level exercise content to form a test exercise answer sheet.
The effect of the above technical scheme is as follows: according to the input condition and the test of the mastered knowledge of the student user, the proficiency degree of the student aiming at the mastered knowledge points and the potential capability of deducing and processing the knowledge content which is not mastered and learned based on the mastered knowledge content can be effectively discovered, and the mastering speed of the student user aiming at the pre-learning content and the rationality of the learning plan making can be further improved by setting the learning plan through the mining quantity degree and the potential capability. Meanwhile, the test paper obtained according to the proportion can furthest investigate and mine the mastering conditions of the student users on the learned contents and the unlearned contents, and further furthest improves the reasonability of subsequent learning plan setting.
In one embodiment of the invention, the planning module comprises:
the acquisition module is used for acquiring the answer scores of the test exercise answer sheet;
the situation judging module is used for judging the current mastering situation of the user aiming at the pre-learning content according to the answer score;
the reasonable judgment module is used for judging whether the learning period set by the user is reasonable or not according to the grasping condition;
the plan generating module is used for making a learning plan according to the learning cycle set by the user when the learning cycle set by the user is in a reasonable range;
and the period adjusting module is used for adjusting the learning period set by the user when the learning period set by the user is unreasonable to obtain the adjusted learning period, and formulating a learning plan according to the adjusted learning period.
Wherein the period adjustment module comprises:
the first adjusting module is used for acquiring the time difference between the learning period and the reasonable period set by the user when the learning period set by the user exceeds the reasonable period for learning, and adjusting the learning period by using the time difference between the learning period and the reasonable period set by the user; specifically, a first adjustment model is used to adjust the learning period, where the first adjustment model is as follows:
wherein the content of the first and second substances,T 1representing a learning period after the learning period is adjusted by using the first adjustment model;T h representing the reasonable period;T z representing the self-set learning period of the user;nrepresenting the total number of chapters contained in the current user pre-learning content;Wrepresenting a total score of the test question answer sheet;W 1representing the answer scores of the user to the test question answer sheet;
the second adjusting module is used for acquiring the time difference between the learning period and the reasonable period set by the user and the score difference between the answer score obtained by the user and the standard score corresponding to the reasonable period when the learning period set by the user is smaller than the reasonable period for learning, and adjusting the learning period by utilizing the time difference between the learning period and the reasonable period set by the user and the score difference between the answer score obtained by the user and the standard score corresponding to the reasonable period; specifically, a second adjustment model is used to adjust the learning period, where the second adjustment model is as follows:
wherein the content of the first and second substances,T 2representing a learning period after the learning period is adjusted by using the second adjustment model;T h representing the reasonable period;T z representing the self-set learning period of the user;nthe total number of chapters contained in the current user pre-learning content is represented;Wrepresenting a total score of the test question answer sheet;W 1represent user pairsThe answer scores of the test exercise answer sheet;W 0expressing the answer score obtained by the user and the standard score corresponding to the reasonable period;
the reasonable period is set according to the answer scores of the test exercise answer paper of the user and comprises a first-level reasonable period, a second-level reasonable period and a third-level reasonable period; when the score is lower than the passing score line (60% of full score corresponds to the score), setting a first-level reasonable period; when the score is higher than the passing score line but lower than the excellent score line (80% of full score corresponds to score), setting a second level reasonable period; when the score is higher than the excellent score line (80% of full score corresponds to score), setting a third-level reasonable period; and the specific time lengths of the first-level reasonable period, the second-level reasonable period and the third-level reasonable period are set according to chapters and contents of the learning target.
The effect of the above technical scheme is as follows: by means of the method, a learning cycle which is more balanced and effective relative to objective and reasonable learning cycle requirements and student self-determined learning cycle requirements can be set for students, the mastering degree of the students for learning contents is further improved, and the balance between learning efficiency and knowledge point mastering is improved. Meanwhile, the reasonable period is a period time length with range, although the method of the embodiment can provide an objective and reasonable learning period according to the test request of the student, the student learns the learning habit of the student and the mastering habit of receiving a new knowledge point most, in order to avoid neglect the self-set learning period set by the student aiming at the self-learning, the reasonable period obtained by the objective data and the learning period set by the student aiming at the self-learning are considered through the formula to carry out the learning period adjustment, so that the effective balance between the learning speed of the student aiming at new learning content and the learning knowledge mastering degree can be further improved, and the proficiency of the student aiming at the pre-learning content can be ensured to the maximum degree in the least time period. The problems that the learning efficiency is low due to overlong learning time and the knowledge mastering proficiency is low due to an overlong time period are solved.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A learning method based on human-computer interaction is characterized in that the learning method comprises the following steps:
setting a test exercise answer sheet in an exercise type proportion setting mode according to pre-learning content and a learning target input by a user and currently mastered learning information input by the user;
making a learning plan according to the answer result of the test exercise answer sheet by the user and by combining the learning content, the learning target and the learning period input by the user;
extracting a course video from a course video database according to a learning plan, and integrating the course video to set daily learning time, learning video courses and exercise plans;
the user learns courses according to the learning plan and supports the user to carry out video-in skip and video-in note generation in the course video process;
and determining the grasping condition of the user on the content corresponding to the current course video according to the answering condition of the exercise of the user after the course video, and determining whether the content corresponding to the current course video is learnt again in the subsequent learning plan according to the grasping condition.
2. The learning method of claim 1, wherein the setting of the test question answer sheet by the question type proportion setting mode according to the pre-learning content and the learning objective input by the user and the currently mastered learning information input by the user comprises:
judging whether the mastered learning information input by the user contains learning information belonging to pre-learned contents or not according to the mastered learning information input by the user at present;
and setting the test exercise answer sheet in an exercise type proportion setting mode according to a judgment result corresponding to whether the mastered learning information input by the user contains the learning information belonging to the pre-learning content.
3. The learning method of claim 2, wherein the setting of the test question answer sheet in a question type proportion setting manner according to a determination result corresponding to whether the learned learning information input by the user includes learning information belonging to pre-learned contents comprises:
when the judgment result is that the mastered learning information input by the user contains learning information belonging to the pre-learning content, setting a first-level exercise content in the mastered learning information; setting second-level exercise content in a learning content range which is in line with the pre-learning content and the learning target range but does not belong to the mastered learning information; wherein, the proportion relation between the first level exercise content and the second level exercise content is as follows: the content proportion of the first-level exercises is 85% -95%; the content proportion of the second-level exercises is 5% -15%;
when the judgment result is that the grasped learning information input by the user does not contain the learning information belonging to the pre-learning content, setting first-level exercise content in the grasped learning information and the learning information associated with the pre-learning content; setting second-level exercise content in a learning content range which accords with the pre-learning content and the learning target range; wherein, the proportion relation between the first level exercise content and the second level exercise content is as follows: the content proportion of the first-level exercises is 90% -95%; the content proportion of the second-level exercises is 5% -10%;
and combining the first-level exercise question content and the second-level exercise question content to form a test exercise question answer sheet.
4. The learning method of claim 1, wherein the step of making a learning plan according to the answer results of the test exercise paper and the learning content, the learning goal and the learning period input by the user comprises:
acquiring answer scores of the test exercise answer sheet;
judging the current mastering condition of the user aiming at the pre-learning content according to the answer score;
judging whether the learning period set by the user is reasonable or not according to the mastering condition;
when the learning period set by the user is in a reasonable range, making a learning plan according to the learning period set by the user;
and when the learning period set by the user is unreasonable, adjusting the learning period set by the user to obtain an adjusted learning period, and making a learning plan according to the adjusted learning period.
5. The learning method according to claim 4, wherein when the learning period set by the user is unreasonable, adjusting the learning period set by the user to obtain an adjusted learning period comprises:
when the learning period set by the user exceeds the reasonable learning period, acquiring the time difference between the learning period set by the user and the reasonable period, and adjusting the learning period by using the time difference between the learning period set by the user and the reasonable period;
when the learning period set by the user is smaller than the reasonable learning period, acquiring the time difference between the learning period set by the user and the reasonable period and the score difference between the answer score obtained by the user and the standard score corresponding to the reasonable period, and adjusting the learning period by using the time difference between the learning period set by the user and the reasonable period and the score difference between the answer score obtained by the user and the standard score corresponding to the reasonable period.
6. A human-computer interaction based learning system, the learning system comprising:
the answer sheet setting module is used for setting a test exercise answer sheet according to pre-learning content and a learning target input by a user and currently mastered learning information input by the user in an exercise type proportion setting mode;
the plan making module is used for making a learning plan according to the answer result of the test exercise answer sheet by the user and by combining the learning content, the learning target and the learning period input by the user;
the course setting module is used for extracting course videos from the course video database according to a learning plan and integrating and setting daily learning time, learning video courses and exercise plans for the course videos;
the note generation module is used for a user to carry out course learning according to the learning plan and supporting the user to carry out video-in skip and video-in note generation in the course video process;
and the relearning module is used for determining the mastering condition of the user on the content corresponding to the current course video according to the answering condition of the exercise of the user after the course video, and determining whether the content corresponding to the current course video is relearned in the subsequent learning plan according to the mastering condition.
7. The learning system of claim 6, wherein the answer sheet setting module comprises:
the judging module is used for judging whether the mastered learning information input by the user contains the learning information belonging to the pre-learning content or not according to the mastered learning information input by the user at present;
and the setting module is used for setting the test exercise answer sheet in an exercise type proportion setting mode according to a judgment result whether the mastered learning information input by the user contains the learning information corresponding to the pre-learning content.
8. The learning system of claim 6, wherein the setup module comprises:
the answer sheet setting module I is used for setting first-level exercise contents in the grasped learning information when the judgment result is that the grasped learning information input by the user contains the learning information belonging to the pre-learning contents; setting second-level exercise content in a learning content range which is in line with the pre-learning content and the learning target range but does not belong to the mastered learning information; wherein, the proportion relation between the first level exercise content and the second level exercise content is as follows: the content proportion of the first-level exercises is 85% -95%; the content proportion of the second-level exercises is 5% -15%;
the answer sheet setting module II is used for setting first-level exercise contents in the grasped learning information and the learning information associated with the pre-learning content when the judgment result is that the grasped learning information input by the user does not contain the learning information belonging to the pre-learning content; setting second-level exercise content in a learning content range which accords with the pre-learning content and the learning target range; wherein, the proportion relation between the first level exercise content and the second level exercise content is as follows: the content proportion of the first-level exercises is 90% -95%; the content proportion of the second-level exercises is 5% -10%;
and the synthesis module is used for combining the first-level exercise content and the second-level exercise content to form a test exercise answer sheet.
9. The learning system of claim 6, wherein the planning module comprises:
the acquisition module is used for acquiring the answer scores of the test exercise answer sheet;
the situation judging module is used for judging the current mastering situation of the user aiming at the pre-learning content according to the answer score;
the reasonable judgment module is used for judging whether the learning period set by the user is reasonable or not according to the grasping condition;
the plan generating module is used for making a learning plan according to the learning cycle set by the user when the learning cycle set by the user is in a reasonable range;
and the period adjusting module is used for adjusting the learning period set by the user when the learning period set by the user is unreasonable to obtain the adjusted learning period, and formulating a learning plan according to the adjusted learning period.
10. The learning system of claim 9, wherein the period adjustment module comprises:
the first adjusting module is used for acquiring the time difference between the learning period and the reasonable period set by the user when the learning period set by the user exceeds the reasonable period for learning, and adjusting the learning period by using the time difference between the learning period and the reasonable period set by the user;
and the second adjusting module is used for acquiring the time difference between the learning period set by the user and the reasonable period and the score difference between the answer score obtained by the user and the standard score corresponding to the reasonable period when the learning period set by the user is smaller than the reasonable period of learning, and adjusting the learning period by utilizing the time difference between the learning period set by the user and the reasonable period and the score difference between the answer score obtained by the user and the standard score corresponding to the reasonable period.
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