Course learning planning system based on computer

Abstract

The invention discloses a course learning planning system based on a computer, and relates to the technical field of course learning planning, and the course learning planning system comprises a learning data acquisition module, a knowledge graph construction module, a learning index scoring module, a multi-index comprehensive evaluation module, a learning plan making module and a real-time progress feedback module. Wherein the modules are connected through electric signals; the learning data acquisition module is used for collecting learning data of students and determining evaluation indexes of the learning data. According to the course learning planning system based on the computer, by monitoring the learning progress and achievement of students, instant learning feedback is provided for the students, so that the students can quickly know the learning state of themselves, related learning resources and exercises are intelligently recommended according to the learning conditions of the students, the students are helped to consolidate knowledge and make up for deficiencies, and the learning efficiency is improved. Students can achieve a higher learning effect in a shorter time, and the learning efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of course learning planning, and in particular to a course learning planning system based on a computer. Background Art

[0002] With the rapid development of information technology and the updating of educational concepts, modern education pays more and more attention to the personalized development and efficient learning of students. However, the traditional education model often adopts a one-size-fits-all teaching method, which is difficult to meet the diverse learning needs of students. Nowadays, computers have become an indispensable tool in people’s daily lives. They can provide strong support for course learning planning, and can integrate various online learning resources, such as video tutorials, online courses, e-books, etc., to provide students with rich and diverse learning options.

[0003] In the existing technology, students' learning situation will change over time, which will lead to a deviation between the predicted course learning progress and the actual learning situation, making it impossible for managers to fully understand the students' learning situation, and then there will be problems with inaccurate learning suggestions and resource recommendations. Therefore, if a comprehensive evaluation based on multiple indicators is carried out to reduce the degree of deviation between the predicted course learning progress and the actual learning situation, this is the problem we want to solve. For this purpose, a computer-based course learning planning system is proposed. Summary of the invention

[0004] To achieve the above objectives, the present invention is implemented through the following technical solutions: a computer-based course learning planning system, the course learning planning system includes a learning data acquisition module, a knowledge graph construction module, a learning indicator scoring module, a multi-indicator comprehensive evaluation module, a learning plan formulation module and a real-time progress feedback module, wherein the modules are connected by electrical signals;

[0005] The learning data acquisition module is used to collect students' learning data and determine the evaluation indicators of the learning data, including learning time, learning progress, learning outcomes, homework completion, and test scores, to provide the system with comprehensive student learning data to ensure the accuracy of subsequent analysis and prediction, and to perform pre-processing operations such as cleaning, sorting, and normalization on the collected data to eliminate noise, outliers, and missing values ​​in the data, improve data quality, and provide a reliable data basis for subsequent analysis and prediction;

[0006] The knowledge graph construction module constructs a course knowledge graph, displays the knowledge system structure of the course, clarifies the connection between knowledge points, helps students clearly understand the knowledge context, reduces cognitive burden, and improves learning efficiency;

[0007] The learning indicator scoring module sets the scoring criteria for each evaluation indicator based on the evaluation indicators of the student learning data and in combination with the course knowledge graph;

[0008] The multi-indicator comprehensive evaluation module combines multiple evaluation indicators in the student's learning data to comprehensively evaluate the student's learning situation, analyze the student's learning progress and development trend, and can more accurately reflect the student's learning status;

[0009] The learning plan formulation module formulates personalized learning plans based on the evaluation and analysis results and the students' learning needs, provides students with tailor-made learning plans, and improves learning efficiency and effectiveness;

[0010] The real-time progress feedback module monitors students' learning progress and achievements in real time, provides real-time learning feedback and suggestions, and helps students understand their learning status in a timely manner, adjust their learning strategies, and improve their learning effects.

[0011] Preferably, in the learning data acquisition module, the process of acquiring and preprocessing student learning data includes:

[0012] Use API interface technology to obtain students' learning data from multiple channels such as online learning platforms, homework submission systems, and test score systems, including learning time, learning progress, learning outcomes, homework completion status, and test scores. Among them, obtain students' learning time, learning progress, and learning outcome data through the API interface provided by the online learning platform, collect students' homework completion status, including submission time and homework scores, through the API interface of the homework submission system, and obtain students' test scores, including scores and ranking information of each subject, through the API interface of the test score system;

[0013] Preprocess the collected learning data, including data cleaning, data organization and data normalization steps;

[0014] Based on the pre-processed student learning data, the evaluation indicators of the learning data are obtained, which are the learning time indicator, the learning progress indicator, the learning outcome indicator, the homework completion indicator and the test score indicator;

[0015] The preprocessed learning data and evaluation indicators are merged into a unified dataset, ensuring that there are no duplicate records in the merged dataset, and a data warehouse is built in the course learning planning system to store the preprocessed learning data.

[0016] Preferably, in the knowledge graph construction module, the construction process of the course knowledge graph includes:

[0017] Collect teaching resources related to student learning data, including textbooks, lesson plans, courseware, exercises, and opinions and suggestions from subject experts, and use natural language processing technology to analyze the text content in teaching resources to extract key information such as concepts, definitions, and examples. Collect official textbooks related to the course, obtain lesson plans written by teachers, understand teaching plans and teaching methods, collect PPTs or other forms of courseware made by teachers, and collect exercises that match the course, including homework and unit tests, to evaluate students' learning outcomes. Collect opinions and suggestions on course content from subject experts through questionnaires;

[0018] According to the chapters and themes of the course, the course content is divided into several logically related sub-knowledge modules. In each sub-knowledge module, key knowledge points are further extracted, including concepts, theorems, formulas, etc., to ensure that the extracted knowledge points can fully cover the core content of the course. Then, the extracted knowledge points are standardized, including unified naming, definition and expression, and the use of standard terms and symbols to ensure the accuracy and consistency of the knowledge points;

[0019] According to the knowledge system structure of the course, design the preliminary framework of the knowledge graph, determine the hierarchical structure and node types of the knowledge graph, take each knowledge point as a node in the knowledge graph, represent it with a graph, and connect the knowledge nodes with arrows according to the teaching semantic relationship (predecessor relationship, successor relationship, related relationship) between knowledge points to form a knowledge graph;

[0020] Classify and organize the collected teaching resources into courseware, exercise, and video categories, formulate unified naming and storage rules for each type of resource, label each teaching resource with the corresponding knowledge point label so as to associate it with the knowledge point in the knowledge graph, and add reference information of the associated resources to each knowledge point in the knowledge graph;

[0021] The knowledge graph is visualized through a graphical interface, which is convenient for students and teachers to browse and query, and the knowledge graph can be updated and revised according to the updates and changes of course content.

[0022] Preferably, in the learning indicator scoring module, the process of setting the scoring criteria for each evaluation indicator includes:

[0023] Based on the pre-processed student learning data, the parameters of each evaluation indicator are determined. Among them, the learning time indicator includes the start time and end time of each learning, and the total learning time is calculated. The learning progress indicator includes the completed course chapters and knowledge point learning ratio. The learning outcome indicator includes the accuracy and participation of answering questions. The homework completion indicator includes the submission time, score, and completion accuracy of the homework. The test score indicator includes the scores of each test, mid-term and final exams, and unit test scores.

[0024] Match the collected learning data with the course knowledge graph to determine the students’ learning status and mastery of each knowledge point, and analyze the students’ related learning status between knowledge points to clarify whether the students have mastered the logical relationship between knowledge points;

[0025] According to the difficulty and importance of the knowledge points in the course knowledge map, set the standard learning time range corresponding to different knowledge points, calculate the ratio of students' actual learning time to the standard learning time, and give a basic score of 60-70 points if the student's learning time is between 80%-120% of the standard time. If it exceeds 120%, points will be deducted, and the total score will not be less than 30 points; if it is less than 80%, points will be added, and the total score will not exceed 90 points; divide the knowledge points in the course knowledge map into different stages according to the learning order, set the standard progress of each stage, compare the actual learning progress of students with the standard progress, and give 70-100 points if the progress meets or exceeds the standard progress, and add points if the progress is ahead of schedule; if the progress lags behind, points will be deducted according to the lag ratio, and the total score will not be less than 30 points; for classroom performance, set a standard score for the accuracy of answering questions, and give a score of 0-30 points according to the accuracy of the answers to the questions, and answers with high accuracy will get higher scores. 20-30 points, 10-20 points for basically correct answers, 0-10 points for incorrect answers; set homework scoring standards based on the difficulty of the homework and the coverage of knowledge points, with a full score of 20 points for simple homework, 30 points for medium-difficulty homework, and 50 points for high-difficulty homework. Give corresponding scores based on the accuracy of the homework. Submit on time with a high accuracy rate to get a score close to the full score. If the submission is delayed, points will be deducted according to the delay time. If the accuracy rate is low, points will be deducted according to the error ratio; analyze the score distribution of each knowledge point in the test paper, combine the importance weight of the knowledge point in the course knowledge map, determine the proportion of different knowledge point scores in the total score, and score according to the score ratio based on the students' actual test scores. Test scores of 90% and above are excellent (90-100 points), 80%-90% are good (80-90 points), 60%-80% are qualified (60-80 points), and less than 60% are unqualified (0-60 points);

[0026] According to the set scoring standards for each evaluation indicator, the student's scores on learning time, learning progress, learning outcomes, homework completion, and test performance indicators are calculated respectively, and the scores are integrated to obtain the student's scoring sequence table.

[0027] Preferably, in the multi-indicator comprehensive evaluation module, the analysis process of students' learning progress and development trend includes:

[0028] Combine the pre-processed student learning data with the set scoring criteria for each evaluation indicator, and score each evaluation indicator separately;

[0029] Based on the determined evaluation indicators of the learning data, a weight is assigned to each evaluation indicator according to its relative importance in the overall evaluation;

[0030] The scores of each individual evaluation indicator and the corresponding weight results are used to calculate the comprehensive progress evaluation coefficient to analyze the degree of deviation of the student's learning progress from the standard progress;

[0031] According to the comprehensive progress evaluation coefficient, compare the student's current learning progress with the standard progress to analyze whether the progress is ahead or behind, and analyze the student's learning trend, including progress, regression or stability, based on the changes in the student's learning data;

[0032] The evaluation results, comprehensive progress evaluation coefficients and learning trend analysis results are organized into an evaluation report, which includes detailed scores for each evaluation indicator, overall scores, progress comparison analysis, learning trend analysis and improvement suggestions. The report is then fed back to students and teachers to help students understand their learning status and guide teachers to adjust their teaching strategies.

[0033] Preferably, the calculation process of the comprehensive progress evaluation coefficient is:

[0034] Determine all evaluation indicators and set a benchmark score value for each evaluation indicator , which is the expected score under the standard progress;

[0035] Collect the actual scores for each evaluation metric , for each evaluation metric, use the formula Calculate its deviation from the benchmark value;

[0036] Based on the weights assigned to each evaluation metric , multiply the deviation degree of each evaluation indicator by its weight to obtain the weighted deviation value ;

[0037] Add the weighted deviation values ​​of all evaluation indicators to get the comprehensive deviation value, and substitute the comprehensive deviation value into the exponential function to get ;

[0038] Substitute the result of the exponential function into the formula with the denominator plus 1 to obtain the comprehensive progress evaluation coefficient , analyze the students' learning progress based on the P value. The closer the P value is to 1, the more the learning progress is in line with or ahead of the standard progress. The smaller the P value is, the more the learning progress lags behind the standard progress.

[0039] Preferably, the calculation formula of the comprehensive progress evaluation coefficient is:

[0040] ;

[0041] ;

[0042] in, is the comprehensive progress evaluation coefficient, is the weighted deviation value, is the number of evaluation indicators, is the weight of the i-th evaluation indicator, is the actual score of the i-th evaluation indicator, is the benchmark score of the ith evaluation indicator, that is, the expected score under the standard progress. Used to calculate the degree of deviation of each evaluation indicator from the benchmark value. The value range is between 0 and 1.

[0043] Preferably, in the learning plan formulation module, the formulation process of the personalized learning plan includes:

[0044] Obtain the student's assessment results from the multi-indicator comprehensive assessment module, including the scores of each assessment indicator, comprehensive progress assessment coefficient, learning progress comparison and learning trend analysis results, and analyze the assessment results to clarify the student's learning status, strengths, weaknesses and potential learning needs;

[0045] Through questionnaire surveys, we deeply analyze students' learning needs, including learning goals, learning styles, interests, and study schedules, and then analyze students' learning needs, set students' short-term and long-term learning goals, and the key skills and knowledge points required to achieve the goals. Specifically, we design questionnaires that include questions about learning goals, learning styles, interests, and study schedules, collect students' questionnaire data online, and conduct statistical analysis on the questionnaire data to understand students' learning needs and preferences;

[0046] Design a learning plan that meets the individual characteristics of students based on the assessment and analysis results and learning needs. The learning plan includes learning objectives, expected outcomes, core skills, and the order in which knowledge points are mastered;

[0047] Based on the established course knowledge map, corresponding learning resources are matched with the learning plan, including textbooks, online courses, exercises and tutoring materials, to ensure that the resources match the students' learning level and needs.

[0048] Preferably, in the real-time progress feedback module, the process of monitoring students' learning progress and achievements includes:

[0049] By recording students' learning behaviors on the system, including online test completion, homework submission time, and discussion participation, students' learning progress and achievements can be obtained. Students' learning achievement data can also be collected through online tests and homework grading.

[0050] The system conducts real-time analysis on the collected learning behavior and learning outcome data, analyzes the students’ learning task completion, compares the students’ current progress with the preset learning goal progress, calculates the task completion evaluation coefficient, and evaluates the students’ learning task completion;

[0051] The system provides instant learning feedback based on students’ learning progress and achievements, including scores, accuracy, and error analysis. Based on students’ learning data and progress comparison results, the system further adjusts learning suggestions, including adjusting learning strategies, strengthening weak links, and participating in relevant discussions.

[0052] After receiving feedback and suggestions, students adjust their learning strategies according to their actual situation and learning goals. The system continues to monitor students' learning progress and outcomes and provides further feedback and suggestions based on new data.

[0053] Preferably, the calculation formula of the task completion evaluation coefficient is:

[0054] ;

[0055] in, is the task completion evaluation coefficient, The percentage of learning content that students actually completed. is the percentage of the preset learning content, is the sum of the student’s scores on all evaluation indicators. is the sum of the benchmark scores of all evaluation indicators, It represents the square root of the ratio of the learning tasks actually completed by students to the preset target tasks, and is used to measure the speed of students' learning progress. This ensures that even if students complete their learning tasks ahead of schedule, the evaluation coefficient will not exceed 1. It represents the logarithm of the difference between the student's score and the benchmark score, and is used to measure the difference between the student's overall performance and expectations. The value range is between 0 and 1, where 0 indicates no progress and 1 indicates that the expected progress is fully met or exceeded.

[0056] The present invention provides a computer-based course learning planning system. It has the following beneficial effects:

[0057] 1. This computer-based course learning planning system provides students with instant learning feedback by monitoring their learning progress and achievements, enabling them to quickly recognize their learning status. It also intelligently recommends relevant learning resources and exercises based on their learning situation, helping them to consolidate their knowledge and make up for their deficiencies, so that they can achieve higher learning results in a shorter time and improve their learning efficiency.

[0058] 2. This computer-based course learning planning system intelligently matches and recommends learning resources according to students' learning needs and progress, which not only improves the efficiency of resource use, but also ensures that resources match students' actual needs, helps teachers allocate teaching resources more effectively, and ensures that every student can obtain learning materials that suit their needs. In addition, the system can provide a variety of learning resources, including videos, audios, and texts, according to students' learning styles and preferences to meet the needs of different learners. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 It is a module diagram of the computer-based course learning planning system of the present invention;

[0060] Figure 2 The analysis flow chart of the student learning progress and development trend of the present invention;

[0061] Figure 3 The present invention is a flow chart for monitoring the learning progress and achievements of students. DETAILED DESCRIPTION

[0062] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The embodiments of the present invention are provided for the purpose of illustration and description, and are not intended to be exhaustive or to limit the present invention to the disclosed forms. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are selected and described in order to better illustrate the principles and practical applications of the present invention, and to enable those of ordinary skill in the art to understand the present invention and thereby design various embodiments with various modifications suitable for specific uses.

[0063] The first embodiment, as Figure 1 , Figure 2 As shown, the present invention provides a technical solution: a computer-based course learning planning system, the course learning planning system includes a learning data acquisition module, a knowledge graph construction module, a learning indicator scoring module, a multi-indicator comprehensive evaluation module, a learning plan formulation module and a real-time progress feedback module, wherein the modules are connected by electrical signals;

[0064] The learning data acquisition module is used to collect students' learning data and determine the evaluation indicators of learning data, including learning time, learning progress, learning results, homework completion, and test scores, to provide the system with comprehensive student learning data to ensure the accuracy of subsequent analysis and prediction, and to clean, organize and standardize the collected data for pre-processing operations to eliminate noise, outliers and missing values ​​in the data, improve data quality, and provide a reliable data basis for subsequent analysis and prediction. The API interface technology is used to obtain students' learning data from multiple channels such as online learning platforms, homework submission systems, and test score systems, including learning time, learning progress, learning results, homework completion, and test scores. Among them, the API interface provided by the online learning platform is used to obtain students' learning time, learning progress, and learning results data. The API interface of the homework submission system is used to collect students' homework completion status, including submission time and homework scores. The API interface of the test score system is used to obtain students' Test scores, including scores and ranking information of each subject, preprocess the collected learning data, including data cleaning, data organization and data normalization steps, wherein data cleaning is used to identify and delete noise in the data, such as irrelevant information and duplicate data, and to check and correct abnormal values ​​in the data, convert time data into a unified format, and convert score data into numerical type to ensure data consistency and comparability, and standardize the data so that data of different indicators have the same dimension, which helps to reduce deviations and errors in the data analysis process and improve the accuracy of the analysis, and obtain evaluation indicators of the learning data based on the preprocessed student learning data, which are learning time indicators, learning progress indicators, learning outcome indicators, homework completion indicators and test score indicators, merge the preprocessed learning data and evaluation indicators into a unified data set, ensure that there are no duplicate records in the merged data set, and build a data warehouse in the course learning planning system to store the preprocessed learning data;

[0065] The knowledge graph construction module constructs a course knowledge graph, displays the knowledge system structure of the course, clarifies the connection between knowledge points, helps students clearly understand the knowledge context, reduces cognitive burden, improves learning efficiency, collects teaching resources related to student learning data, including textbooks, lesson plans, courseware, exercises, and opinions and suggestions from subject experts, and uses natural language processing technology to analyze the text content in teaching resources to extract key information about concepts, definitions, and examples. Among them, official textbooks related to the course are collected, lesson plans written by teachers are obtained, teaching plans and teaching methods are understood, PPTs or other forms of courseware produced by teachers are collected, exercises that match the course are collected, including homework and unit tests, to evaluate students' learning effects, and opinions and suggestions from subject experts on the course content are collected through questionnaires. According to the chapters and themes of the course, the course content is divided into several logically related sub-knowledge modules. In each sub-knowledge module, key knowledge points are further extracted, including concepts, theorems, formulas, etc., to ensure that the extracted knowledge points can cover all aspects. The core content of the course is covered, and then the extracted knowledge points are standardized, including unified naming, definition and expression, using standard terms and symbols to ensure the accuracy and consistency of knowledge points. According to the knowledge system structure of the course, the preliminary framework of the knowledge graph is designed, the hierarchical structure and node type of the knowledge graph are determined, each knowledge point is regarded as a node in the knowledge graph, represented by a graph, and the knowledge nodes are connected with arrows according to the teaching semantic relationship between knowledge points (predecessor relationship, successor relationship, related relationship) to form a knowledge graph. The collected teaching resources are classified and sorted into courseware, exercise and video categories. Unified naming and storage rules are formulated for each type of resource. The corresponding knowledge point label is marked for each teaching resource so as to associate it with the knowledge point in the knowledge graph, and the reference information of the associated resources is added to each knowledge point in the knowledge graph. The knowledge graph is visualized through a graphical interface to facilitate students and teachers to browse and query, and the knowledge graph is updated and revised according to the update and change of the course content;

[0066] The learning indicator scoring module sets the scoring criteria for each evaluation indicator based on the various evaluation indicators of the student learning data and the course knowledge graph. It determines the parameters of each evaluation indicator based on the preprocessed student learning data. Among them, the learning time indicator includes the start time and end time of each learning, and the total learning time is calculated. The learning progress indicator includes the completed course chapters and the proportion of knowledge points learned. The learning outcome indicator includes the accuracy and participation of answering questions. The homework completion indicator includes the submission time, score, and completion accuracy of the homework. The test score indicator includes the scores of each test, mid-term and final exams, and unit test scores. The collected learning data is matched with the course knowledge graph to determine the student's learning status on each knowledge point. The course analyzes the students’ learning situation and mastery level, analyzes the students’ related learning situation between knowledge points, clarifies whether students have mastered the logical relationship between knowledge points, sets standard learning time ranges for different knowledge points according to the difficulty and importance of knowledge points in the course knowledge map, and calculates the ratio of students’ actual learning time to standard learning time. If students’ learning time is between 80%-120% of the standard time, they will be given a basic score of 60-70 points. If it exceeds 120%, points will be deducted, and the total score will not be less than 30 points. If it is less than 80%, points will be added, and the total score will not exceed 90 points. The knowledge points in the course knowledge map are divided into different stages according to the learning order, and the standard progress of each stage is set. The actual learning progress of students is compared with the standard progress. The progress is in line with the standard progress. If the progress is better than the standard, 70-100 points will be given, and extra points will be given for those who are ahead of schedule. If the progress is behind, points will be deducted according to the proportion of the delay, and the total score will not be less than 30 points. According to the classroom performance, a standard score for the accuracy of answering questions is set, and 0-30 points are given according to the accuracy of the answers to the questions. Answers with high accuracy will get 20-30 points, basically correct answers will get 10-20 points, and incorrect answers will get 0-10 points. According to the difficulty of the homework and the coverage of knowledge points, the homework scoring standard is set, with a full score of 20 points for simple homework, 30 points for medium-difficulty homework, and 50 points for high-difficulty homework. The corresponding score is given according to the accuracy of the homework. If the homework is submitted on time and with a high accuracy rate, a score close to the full score will be obtained. If the submission is delayed, points will be deducted according to the delay time. If If the accuracy rate is low, points will be deducted according to the error ratio; analyze the score distribution of each knowledge point in the test paper, combine the importance weight of the knowledge point in the course knowledge map, determine the proportion of different knowledge point scores in the total score, and score according to the score ratio based on the student's actual test score. Test scores of 90% and above are excellent (90-100 points), 80%-90% are good (80-90 points), 60%-80% are qualified (60-80 points), and less than 60% are unqualified (0-60 points). According to the set scoring standards for each evaluation indicator, calculate the student's scores on learning time, learning progress, learning outcomes, homework completion, and test score indicators, and integrate the scores of each item to obtain the student's score sequence table;

[0067] The multi-indicator comprehensive evaluation module combines multiple evaluation indicators in the students' learning data to comprehensively evaluate the students' learning situation, analyze the students' learning progress and development trends, and can more accurately reflect the students' learning status. Combined with the pre-processed student learning data and the set scoring standards for each evaluation indicator, each evaluation indicator is scored separately. Based on the determined learning data and each evaluation indicator, a weight is assigned to each evaluation indicator according to the relative importance of each evaluation indicator in the overall evaluation. The scores of each single evaluation indicator and the corresponding weight results are used to calculate the progress comprehensive evaluation coefficient, analyze the degree of deviation of the students' learning progress from the standard progress, compare the students' current learning progress with the standard progress according to the progress comprehensive evaluation coefficient, analyze whether the progress is ahead or behind, and analyze the students' learning trends according to the changes in the students' learning data, including progress, regression or stability. The evaluation results, progress comprehensive evaluation coefficient and learning trend analysis results are organized into an evaluation report. The report contains detailed scores for each evaluation indicator, overall scores, progress comparison analysis, learning trend analysis and improvement suggestions, and feedback is given to students and teachers to help students understand their own learning status and guide teachers to adjust their teaching strategies;

[0068] Furthermore, the calculation process of the comprehensive progress evaluation coefficient is:

[0069] Determine all evaluation indicators and set a benchmark score value for each evaluation indicator , which is the expected score under the standard progress;

[0070] Collect the actual scores for each evaluation metric , for each evaluation metric, use the formula Calculate its deviation from the benchmark value;

[0071] Based on the weights assigned to each evaluation metric , multiply the deviation degree of each evaluation indicator by its weight to obtain the weighted deviation value ;

[0072] Add the weighted deviation values ​​of all evaluation indicators to get the comprehensive deviation value, and substitute the comprehensive deviation value into the exponential function to get ,

[0073] Substitute the result of the exponential function into the formula with the denominator plus 1 to obtain the comprehensive progress evaluation coefficient , analyze the students’ learning progress according to the value of P. The closer the P value is to 1, the more the learning progress is in line with or ahead of the standard progress. The smaller the P value is, the more the learning progress is behind the standard progress.

[0074] Furthermore, the calculation formula of the comprehensive progress evaluation coefficient is:

[0075] ;

[0076] ;

[0077] in, is the comprehensive progress evaluation coefficient, is the weighted deviation value, is the number of evaluation indicators, is the weight of the i-th evaluation indicator, is the actual score of the i-th evaluation indicator, is the benchmark score of the ith evaluation indicator, that is, the expected score under the standard progress. Used to calculate the degree of deviation of each evaluation indicator from the benchmark value. The value range is between 0 and 1. hour, , indicating no deviation, when When , the logarithmic value increases, indicating that it is ahead; when When the logarithmic value decreases, it indicates that the system is lagging behind. When the actual scores of all evaluation indicators are Equal to the baseline value hour, Taking the maximum value of 1 indicates that the standard progress is fully met. All below the baseline hour, The value of decreases, indicating that it is behind the standard progress. All higher than the baseline hour, The value of is close to 1, indicating that it is ahead of the standard progress;

[0078] The learning plan making module makes personalized learning plans based on the evaluation and analysis results and students’ learning needs, providing students with tailor-made learning plans to improve learning efficiency and effectiveness;

[0079] The real-time progress feedback module monitors students' learning progress and achievements in real time, provides real-time learning feedback and suggestions, and helps students understand their learning status in a timely manner, adjust their learning strategies, and improve learning outcomes.

[0080] The second embodiment is based on the first embodiment. Figure 3 As shown in the figure, in the learning plan making module, the process of making a personalized learning plan includes:

[0081] Obtain the student's assessment results from the multi-indicator comprehensive assessment module, including the scores of each assessment indicator, the comprehensive progress assessment coefficient, the comparison of learning progress and the results of learning trend analysis, and analyze the assessment results to clarify the student's learning status, strengths, weaknesses and potential learning needs. Through questionnaire surveys, deeply analyze the student's learning needs, including learning goals, learning styles, interests, and learning time arrangements, and then analyze the student's learning needs, set students' short-term and long-term learning goals, and the key skills and knowledge points required to achieve the goals. Among them, design a questionnaire containing questions about learning goals, learning styles, interests, and learning time arrangements, collect students' questionnaire data online, and conduct statistical analysis on the questionnaire data to understand students' learning needs and preferences. According to the assessment analysis results and learning needs, design a learning plan that meets the student's personal characteristics. The learning plan includes learning goals, expected results, and the order of mastering core skills and knowledge points. Based on the established course knowledge map, match the corresponding learning resources in combination with the learning plan, including textbooks, online courses, exercises and tutoring materials, to ensure that the resources match the student's learning level and needs;

[0082] In the real-time progress feedback module, the monitoring process of students' learning progress and achievements includes:

[0083] By recording students' learning behaviors on the system, including online test completion, homework submission time, and discussion participation, students' learning progress and achievements are obtained, and students' learning achievement data are collected through online tests and homework correction. The system conducts real-time analysis on the collected learning behaviors and learning achievement data, analyzes students' learning task completion, compares students' current progress with the preset learning goal progress, calculates the task completion evaluation coefficient, and evaluates students' learning task completion. The system provides instant learning feedback based on students' learning progress and achievements, including scores, accuracy, and error analysis. Based on students' learning data and progress comparison results, learning suggestions are further adjusted. Suggestions include adjusting learning strategies, strengthening weak links, and participating in relevant discussions. After receiving feedback and suggestions, students adjust their learning strategies according to their actual situation and learning goals. The system continues to monitor students' learning progress and achievements, and provides further feedback and suggestions based on new data;

[0084] Furthermore, the calculation formula of the task completion evaluation coefficient is:

[0085] ;

[0086] in, is the task completion evaluation coefficient, The percentage of learning content that students actually completed. is the percentage of the preset learning content, is the sum of the student’s scores on all evaluation indicators. is the sum of the benchmark scores of all evaluation indicators, It represents the square root of the ratio of the learning tasks actually completed by students to the preset target tasks, and is used to measure the speed of students' learning progress. This ensures that even if students complete their learning tasks ahead of schedule, the evaluation coefficient will not exceed 1. It represents the logarithm of the difference between the student's score and the benchmark score, and is used to measure the difference between the student's overall performance and expectations. The value range is between 0 and 1, where 0 means no progress and 1 means it fully meets or exceeds the expected progress. Close to or equal to hour, Close to or equal to 1, it means that the student's learning progress meets or exceeds expectations. Much smaller than hour, Close to 0, it means that the student's learning progress is seriously lagging behind. Close to or equal to When the exponential part is close to 1, The value of is mainly determined by the learning progress. Greater than When the exponent part is less than 1, The value of will decrease, indicating that although the student's learning progress is in line with expectations, the overall performance exceeds the benchmark and requires higher learning efficiency.

[0087] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field and related fields without creative work should fall within the scope of protection of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention are implemented according to the conventional means in the field unless otherwise specified and limited.

Claims

1. A computer-based course learning planning system, characterized in that: The course learning planning system includes a learning data acquisition module, a knowledge graph construction module, a learning indicator scoring module, a multi-indicator comprehensive evaluation module, a learning plan formulation module and a real-time progress feedback module, wherein the modules are connected by electrical signals; The learning data acquisition module is used to collect students' learning data, determine the evaluation indicators of the learning data, and pre-process the collected data; The knowledge graph construction module constructs a course knowledge graph to display the knowledge architecture of the course; The learning indicator scoring module sets the scoring criteria for each evaluation indicator based on the evaluation indicators of the student learning data and in combination with the course knowledge graph; The multi-indicator comprehensive evaluation module combines multiple evaluation indicators in the student's learning data to comprehensively evaluate the student's learning situation and analyze the student's learning progress and development trend; The learning plan formulation module formulates a personalized learning plan based on the evaluation and analysis results and the students' learning needs; The real-time progress feedback module monitors students' learning progress and achievements in real time and provides real-time learning feedback and suggestions.

2. The computer-based course learning planning system according to claim 1, characterized in that: In the learning data acquisition module, the acquisition and preprocessing process of student learning data includes: Use API interface technology to obtain students' learning data from multiple channels such as online learning platforms, homework submission systems, and test score systems, including learning time, learning progress, learning outcomes, homework completion status, and test scores; Preprocess the collected learning data, including data cleaning, data organization and data normalization steps; Based on the pre-processed student learning data, the evaluation indicators of the learning data are obtained, which are the learning time indicator, the learning progress indicator, the learning outcome indicator, the homework completion indicator and the test score indicator; The preprocessed learning data and evaluation indicators are merged into a unified dataset, and a data warehouse is built in the course learning planning system to store the preprocessed learning data.

3. The computer-based course learning planning system according to claim 2, characterized in that: In the knowledge graph construction module, the construction process of the course knowledge graph includes: Collect teaching resources related to student learning data, including textbooks, lesson plans, courseware, exercises, and opinions and suggestions from subject experts, and use natural language processing technology to analyze the text content in teaching resources to extract key information such as concepts, definitions, and examples; According to the chapters and topics of the course, the course content is divided into several logically related sub-knowledge modules. In each sub-knowledge module, key knowledge points are further extracted and then standardized. According to the knowledge architecture of the course, design the preliminary framework of the knowledge graph, determine the hierarchical structure and node types of the knowledge graph, take each knowledge point as a node in the knowledge graph, represent it with a graph, and connect the knowledge nodes with arrows according to the teaching semantic relationship between the knowledge points to form a knowledge graph; Classify and organize the collected teaching resources into courseware, exercise, and video categories, formulate unified naming and storage rules for each type of resource, label each teaching resource with the corresponding knowledge point label, and add reference information of related resources to each knowledge point in the knowledge graph; The knowledge graph is visualized through a graphical interface and updated and revised according to updates and changes in course content.

4. The computer-based course learning planning system according to claim 3, characterized in that: In the learning indicator scoring module, the process of setting the scoring criteria for each evaluation indicator includes: Based on the pre-processed student learning data, the parameters of each evaluation indicator are determined. Among them, the learning time indicator includes the start time and end time of each learning, and the total learning time is calculated. The learning progress indicator includes the completed course chapters and knowledge point learning ratio. The learning outcome indicator includes the accuracy and participation of answering questions. The homework completion indicator includes the submission time, score, and completion accuracy of the homework. The test score indicator includes the scores of each test, mid-term and final exams, and unit test scores. Match the collected learning data with the course knowledge graph to determine the students’ learning status and mastery of each knowledge point, and analyze the students’ related learning status between knowledge points to clarify whether the students have mastered the logical relationship between knowledge points; According to the difficulty and importance of the knowledge points in the course knowledge map, set the standard learning time range corresponding to different knowledge points; divide the knowledge points in the course knowledge map into different stages according to the learning order, and set the standard progress for each stage; set the standard score for the accuracy of answering questions based on classroom performance; set the homework scoring standard according to the difficulty of the homework and the coverage of knowledge points; analyze the score distribution of each knowledge point in the test paper, and determine the proportion of different knowledge points in the total score based on the importance weight of the knowledge points in the course knowledge map. According to the actual test scores of students, score according to the score ratio, and the test scores of 90% and above are excellent, 80%-90% are good, 60%-80% are qualified, and less than 60% are unqualified; According to the set scoring standards for each evaluation indicator, the student's scores on learning time, learning progress, learning outcomes, homework completion, and test performance indicators are calculated respectively, and the scores are integrated to obtain the student's scoring sequence table.

5. The computer-based course learning planning system according to claim 4, characterized in that: In the multi-indicator comprehensive evaluation module, the analysis process of students' learning progress and development trend includes: Combine the pre-processed student learning data with the set scoring criteria for each evaluation indicator, and score each evaluation indicator separately; Based on the determined evaluation indicators of the learning data, a weight is assigned to each evaluation indicator according to its relative importance in the overall evaluation; The scores of each individual evaluation indicator and the corresponding weight results are used to calculate the comprehensive progress evaluation coefficient to analyze the degree of deviation of the student's learning progress from the standard progress; Compare the student's current learning progress with the standard progress based on the comprehensive progress evaluation coefficient to analyze whether the progress is ahead or behind, and analyze the student's learning trend based on the changes in the student's learning data; The evaluation results, comprehensive progress evaluation coefficient and learning trend analysis results are organized into an evaluation report, which includes detailed scores for each evaluation indicator, overall scores, progress comparison analysis, learning trend analysis and improvement suggestions, and is fed back to students and teachers.

6. The computer-based course learning planning system according to claim 5, characterized in that: The calculation process of the comprehensive progress evaluation coefficient is as follows: Determine all evaluation indicators and set a benchmark score value for each evaluation indicator , which is the expected score under the standard progress; Collect the actual scores for each evaluation metric , for each evaluation metric, use the formula Calculate its deviation from the benchmark value; Based on the weights assigned to each evaluation metric , multiply the deviation degree of each evaluation indicator by its weight to obtain the weighted deviation value ; Add the weighted deviation values ​​of all evaluation indicators to get the comprehensive deviation value, and substitute the comprehensive deviation value into the exponential function to get , Substitute the result of the exponential function into the formula with the denominator plus 1 to obtain the comprehensive progress evaluation coefficient .

7. The computer-based course learning planning system according to claim 6, characterized in that: The calculation formula of the comprehensive progress evaluation coefficient is: ； ； in, is the comprehensive progress evaluation coefficient, is the weighted deviation value, is the number of evaluation indicators, is the weight of the i-th evaluation indicator, is the actual score of the i-th evaluation indicator, is the benchmark score value of the i-th evaluation indicator, The value range is between 0 and 1.

8. The computer-based course learning planning system according to claim 7, characterized in that: In the learning plan formulation module, the formulation process of the personalized learning plan includes: Obtain the student's assessment results from the multi-indicator comprehensive assessment module, including the scores of each assessment indicator, comprehensive progress assessment coefficient, learning progress comparison and learning trend analysis results, and analyze the assessment results to clarify the student's learning status, strengths, weaknesses and potential learning needs; Through questionnaire surveys, we deeply analyze students' learning needs, including learning goals, learning styles, interests, and study schedules, and then analyze students' learning needs, set students' short-term and long-term learning goals, and the key skills and knowledge points required to achieve the goals. Specifically, we design questionnaires that include questions about learning goals, learning styles, interests, and study schedules, collect students' questionnaire data online, and conduct statistical analysis on the questionnaire data to understand students' learning needs and preferences; Design a learning plan that meets the individual characteristics of students based on the assessment and analysis results and learning needs. The learning plan includes learning objectives, expected outcomes, core skills, and the order in which knowledge points are mastered; Based on the established course knowledge map, corresponding learning resources are matched in combination with the learning plan, including textbooks, online courses, exercises and tutoring materials, to ensure that the resources match the students' learning level and needs.

9. The computer-based course learning planning system according to claim 8, characterized in that: In the real-time progress feedback module, the process of monitoring students' learning progress and achievements includes: By recording students' learning behaviors on the system, including online test completion, homework submission time, and discussion participation, students' learning progress and achievements can be obtained. Students' learning achievement data can also be collected through online tests and homework grading. The system conducts real-time analysis on the collected learning behavior and learning outcome data, analyzes the students’ learning task completion, compares the students’ current progress with the preset learning goal progress, calculates the task completion evaluation coefficient, and evaluates the students’ learning task completion; The system provides instant learning feedback based on students’ learning progress and achievements, including scores, accuracy, and error analysis. Based on students’ learning data and progress comparison results, the system further adjusts learning suggestions, including adjusting learning strategies, strengthening weak links, and participating in relevant discussions. After receiving feedback and suggestions, students adjust their learning strategies according to their actual situation and learning goals. The system continues to monitor students' learning progress and outcomes and provides further feedback and suggestions based on new data.

10. The computer-based course learning planning system according to claim 9, characterized in that: The calculation formula of the task completion evaluation coefficient is: ； in, is the task completion evaluation coefficient, The percentage of learning content that students actually completed. is the percentage of the preset learning content, is the sum of the student’s scores on all evaluation indicators. is the sum of the benchmark scores of all evaluation indicators, The value range is between 0 and 1, where 0 indicates no progress and 1 indicates that the expected progress is fully met or exceeded.

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