CN113535982B - A teaching system based on big data - Google Patents
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Abstract
Description
Translated fromChinese技术领域technical field
本发明涉及大数据技术领域，特别涉及一种基于大数据的教学系统。The invention relates to the technical field of big data, in particular to a teaching system based on big data.
背景技术Background technique
目前，传统的教学方法是老师集体授课，教师在讲台上讲课，学生在台下听讲，但是，由于部分学生学习能力的差距，导致老师无法对所有学生的学习状况进行有效地管理，进而可能导致部分同学学习质量下降，学习效率变低；At present, the traditional teaching method is that teachers teach in groups, teachers give lectures on the podium, and students listen in the audience. However, due to the gap in learning ability of some students, teachers cannot effectively manage the learning status of all students, which may lead to Some students' learning quality has declined, and their learning efficiency has become lower;
因此，本发明提供了一种基于大数据的教学系统，用以对知识数据图谱分析，实现对各个学生制定合适的教学方法，提高学生的学习效率以及学习质量，完善了教学方法中存在的弊端，同时也提高了教学效率。Therefore, the present invention provides a teaching system based on big data, which is used to analyze the knowledge data map, realize the formulation of appropriate teaching methods for each student, improve the learning efficiency and learning quality of students, and improve the shortcomings of the teaching methods. , but also improve the teaching efficiency.
发明内容SUMMARY OF THE INVENTION
本发明提供一种基于大数据的教学系统，用以通过对知识数据图谱分析，实现对各个学生制定合适的教学方法，提高学生的学习效率以及学习质量，完善了教学方法中存在的弊端，同时也提高了教学效率。The invention provides a teaching system based on big data, which is used to formulate appropriate teaching methods for each student by analyzing the knowledge data map, improve the learning efficiency and learning quality of students, improve the shortcomings of the teaching method, and at the same time It also improves teaching efficiency.
本发明提供了一种基于大数据的教学系统，包括：The present invention provides a teaching system based on big data, including:
数据获取模块，用于获取学生的知识数据图谱；The data acquisition module is used to acquire the knowledge data map of students;
数据分析模块，用于基于大数据对所述知识数据图谱进行分析，确定各个学生对应的教学方法；a data analysis module, used for analyzing the knowledge data graph based on big data, and determining the corresponding teaching method for each student;
数据调整模块，用于在预设时间段内检测各个学生在对应的教学方法下的学习质量，并根据所述学习质量对所述教学方法进行调整，完成对各个学生制定合适的目标教学方法。The data adjustment module is used to detect the learning quality of each student under the corresponding teaching method within a preset time period, and adjust the teaching method according to the learning quality, so as to complete the formulation of an appropriate target teaching method for each student.
优选的，一种基于大数据的教学系统，数据获取模块，包括：Preferably, a teaching system based on big data, the data acquisition module includes:
数据获取单元，用于获取学生知识领域的历史学习数据集，其中，所述历史学习数据集中包含训练数据和测试数据；a data acquisition unit for acquiring a historical learning data set in the student's knowledge field, wherein the historical learning data set includes training data and test data;
模型构建单元，用于基于所述训练数据训练深度学习模型，并基于所述测试数据对所述深度学习模型进行测试，并得到测试结果；a model building unit, used for training a deep learning model based on the training data, and testing the deep learning model based on the test data, and obtaining a test result;
第一判断单元，用于将所述测试结果与预设测试结果进行比较；a first judging unit for comparing the test result with a preset test result;
图谱构建单元，用于当所述测试结果满足所述预设测试结果的目标要求时，获取学生知识领域的用于构建知识图谱的目标数据，并基于所述深度学习模型对所述用于构建知识图谱的目标数据进行数据抽取，得到数据抽取结果；A graph construction unit, configured to obtain target data for building a knowledge graph in the student's knowledge field when the test result meets the target requirements of the preset test result, and based on the deep learning model for the target data for building a knowledge graph The target data of the knowledge map is extracted, and the data extraction result is obtained;
所述图谱构建单元，还用于根据所述数据抽取结果，从预设知识数据图谱构建层面对所述数据抽取结果进行知识融合，完成学生的知识数据图谱的构建；The map construction unit is further configured to perform knowledge fusion on the data extraction results from the preset knowledge data map construction level according to the data extraction results, so as to complete the construction of the students' knowledge data map;
所述模型构建单元，还用于当所述测试结果不满足所述预设测试结果的目标要求时，对所述深度学习模型进行再次训练，直至满足所述预设测试结果的目标要求。The model building unit is further configured to retrain the deep learning model when the test result does not meet the target requirement of the preset test result until the target requirement of the preset test result is met.
优选的，一种基于大数据的教学系统，图谱构建单元，还包括：Preferably, a teaching system based on big data, a graph construction unit, further includes:
图谱更新单元，用于获取构建完成的知识数据图谱，同时，基于预设规则确定所述知识数据图谱中各节点对应的数据以及数据的属性值；a graph updating unit, configured to acquire the constructed knowledge data graph, and at the same time, determine the data corresponding to each node in the knowledge data graph and the attribute value of the data based on preset rules;
所述图谱更新单元，还用于在预设时间段内根据所述数据的属性值至少产生一条更新数据，并根据所述更新数据对所述知识数据图谱中各节点对应的数据进行更新，并得到目标更新数据；The graph update unit is further configured to generate at least one piece of update data according to the attribute value of the data within a preset time period, and update the data corresponding to each node in the knowledge data graph according to the update data, and Get target update data;
所述图谱更新单元，还用于根据所述目标更新数据获取预设推理规则，其中，所述预设推理规则是根据目标更新数据生成推理知识图谱普需要使用的规则；The graph updating unit is further configured to obtain a preset inference rule according to the target update data, wherein the preset inference rule is a rule that needs to be used to generate an inference knowledge graph according to the target update data;
所述图谱更新单元，还用于根据所述预设推理规则和目标更新数据，生成推理知识图谱，并将所述推理知识图谱与所述知识数据图谱进行合并，得到最终更新后的知识数据图谱。The graph updating unit is further configured to generate a reasoning knowledge graph according to the preset reasoning rules and target update data, and combine the reasoning knowledge graph and the knowledge data graph to obtain a final updated knowledge data graph .
优选的，一种基于大数据的教学系统，图谱更新单元，还包括：Preferably, a teaching system based on big data, a map update unit, further includes:
第一存储单元，用于获取最终更新后的知识数据图谱，其中，所述最终更新后的知识数据图谱带有数据类型标识；a first storage unit, used to obtain a final updated knowledge data graph, wherein the final updated knowledge data graph has a data type identifier;
所述第一存储单元，用于根据所述数据类型标识判断预设存储区域中是否存在与所述数据类型标识对应的图实例；The first storage unit is used to judge whether there is a graph instance corresponding to the data type identifier in the preset storage area according to the data type identifier;
若不存在，在所述预设存储区域内部创建与所述数据类型标识对应的图实例，并将所述最终更新后的知识数据图谱存储至所述创建所述图实例对应的目标存储区域；If it does not exist, create a graph instance corresponding to the data type identifier in the preset storage area, and store the final updated knowledge data graph in the target storage area corresponding to the creation of the graph instance;
否则，将所述最终更新后的知识数据图谱存储至所述图实例对应的目标存储区域。Otherwise, the final updated knowledge data graph is stored in the target storage area corresponding to the graph instance.
优选的，一种基于大数据的教学系统，数据分析模块，包括：Preferably, a teaching system based on big data, a data analysis module, includes:
学习数据监测单元，用于根据预设频率获取多组学生的学习记录，并调取所述各个学生当前接受的目标教学方案，同时，根据所述多组学生的学习记录以及目标教学方案，确定各个学生的偏离信息；The learning data monitoring unit is used to obtain the learning records of multiple groups of students according to the preset frequency, and retrieve the target teaching plan currently accepted by each student, and at the same time, according to the learning records of the multiple groups of students and the target teaching plan, determine Deviation information for individual students;
所述学习数据监测单元，还用于获取各个学生在当前接受的目标教学方案下产生的生理数据，并根据所述生理数据确定各个学生在所述目标教学方案下的目标反应；The learning data monitoring unit is further configured to acquire physiological data generated by each student under the target teaching scheme currently accepted, and determine the target response of each student under the target teaching scheme according to the physiological data;
所述学习数据监测单元，还用于根据各个学生的目标反应确定当前接受的目标教学方案中教学方式的分类标识，并根据所述分类标识确定各个学生的兴趣点以及非兴趣点；The learning data monitoring unit is also used to determine the classification identification of the teaching method in the currently accepted target teaching scheme according to the target response of each student, and to determine the interest points and non-interest points of each student according to the classification identification;
教学资源整合单元，用于对所述知识数据图谱包含的教学资源进行聚类处理，提取出各个学生对应的学科题目知识点，并构成学科知识点集合，其中，所述知识数据图谱展示了学科知识点集合中元知识点和元知识点之间的关联关系；The teaching resource integration unit is used for clustering the teaching resources included in the knowledge data map, extracting the subject knowledge points corresponding to each student, and forming a subject knowledge point set, wherein the knowledge data map shows the subject The relationship between meta-knowledge points and meta-knowledge points in the knowledge point set;
教学方法确定单元，用于根据各个学生的偏离信息，通过所述知识数据图谱，从所述学科知识点集合中确定目标元知识点以及与所述目标元知识点存在关联关系的元知识点组合；A teaching method determining unit is used to determine a target meta-knowledge point and a meta-knowledge point combination that has an associated relationship with the target meta-knowledge point from the subject knowledge point set through the knowledge data map according to the deviation information of each student ;
所述教学方法确定单元，还用于获取历史试题信息，并基于所述历史试题信息确定目标元知识点以及与所述目标元知识点存在关联关系的元知识点组合各自的教学比重，并根据所述教学比重，确定各个学生对应的最终教学资源；The teaching method determining unit is also used to obtain historical test question information, and based on the historical test question information, determine the respective teaching proportions of the target meta-knowledge point and the meta-knowledge point combination that has an associated relationship with the target meta-knowledge point, and according to the The teaching proportion determines the final teaching resources corresponding to each student;
所述教学方法确定单元，还用于根据各个学生的趣点以及非兴趣点，从预设教学方式库中匹配对应的目标教学方式，并将各个学生对应.的目标教学方式与最终教学资源进行匹配记录，得到各个学生对应的教学方法。The teaching method determining unit is also used to match the corresponding target teaching methods from the preset teaching method library according to the interest points and non-interest points of each student, and compare the target teaching methods corresponding to each student with the final teaching resources. Match the records to get the teaching method corresponding to each student.
优选的，一种基于大数据的教学系统，数据调模块，包括：Preferably, a teaching system based on big data, the data adjustment module, includes:
模型构建单元，用于获取学生学习质量评测的影响因素，并根据所述学生学习质量评测的影响因素建立学生学习质量评测的评价指标体系；a model building unit, used to obtain the influencing factors of student learning quality evaluation, and establish an evaluation index system for student learning quality evaluation according to the influencing factors of student learning quality evaluation;
所述模型构建单元，还用于基于预设方法确定所述评价指标体系的指标权重，并根据所述指标权重构建学生学习质量评价模型；The model construction unit is further configured to determine the index weight of the evaluation index system based on a preset method, and construct a student learning quality evaluation model according to the index weight;
学习数据获取单元，用于基于预设知识点的能力层次，确定各个学生的目标达成度，同时，监控各个学生测评试题、课堂问答和课堂讨论的完成情况，得到各个学生对应的课程参与度；The learning data acquisition unit is used to determine the degree of achievement of each student's goal based on the ability level of the preset knowledge points, and at the same time, monitor the completion of each student's assessment questions, class questions and answers, and class discussion, and obtain each student's corresponding course participation;
学习质量评价单元，用于将各个学生对应的目标达成度以及课程参与度输入所述学习质量评价模型，得到各个学生对应的学习质量评价结果；The learning quality evaluation unit is used to input the target achievement degree and course participation degree corresponding to each student into the learning quality evaluation model, and obtain the learning quality evaluation result corresponding to each student;
所述学习质量评价单元，还用于将所述各个学生对应的学习质量评价结果与预设学习质量评价结果进行比较；The learning quality evaluation unit is further configured to compare the learning quality evaluation result corresponding to each student with the preset learning quality evaluation result;
判断单元，用于当所述各个学生对应的学习质量评价结果高于或等于所述预设评价结果，判定各个学生接受的教学方法合格，否则，判定各个学生接受的教学方法不合格；a judging unit, configured to judge that the teaching method accepted by each student is qualified when the learning quality evaluation result corresponding to each student is higher than or equal to the preset evaluation result, otherwise, judge that the teaching method accepted by each student is unqualified;
教学方法调整单元，用于在判定各个学生接受的教学方法不合格时，基于所述知识数据图谱调取各个知识点的检测数据，并根据所述各个知识点的检测数据确定各个学生对各个知识点的学习能力值；The teaching method adjustment unit is used to retrieve the detection data of each knowledge point based on the knowledge data map when it is determined that the teaching method accepted by each student is unqualified, and determine each student's understanding of each knowledge point according to the detection data of each knowledge point The learning ability value of the point;
所述教学方法调整单元，还用于基于所述各个学生对各个知识点的学习能力值从所述知识数据图谱包含的知识点中筛选学生已掌握的知识点，并根据所述学生已掌握的知识点确定学生的平均学习能力值；The teaching method adjustment unit is further configured to screen the knowledge points that the students have mastered from the knowledge points included in the knowledge data map based on the learning ability values of the students for each knowledge point, and select the knowledge points that the students have mastered according to the knowledge points that the students have mastered. Knowledge points determine the average learning ability value of students;
所述教学方法调整单元，还用于基于所述平均学习能力值对所述教学方法进行调整，完成对各个学生制定合适的目标教学方法。The teaching method adjustment unit is further configured to adjust the teaching method based on the average learning ability value, so as to complete the formulation of an appropriate target teaching method for each student.
优选的，一种基于大数据的教学系统，教学方法调整单元，还包括：Preferably, a teaching system and teaching method adjustment unit based on big data, further comprising:
检测单元，用于获取对各个学生制定的目标教学方法，并基于预设检测方法确定所述目标教学方法是否合理；a detection unit, configured to obtain the target teaching method formulated for each student, and determine whether the target teaching method is reasonable based on the preset detection method;
若不合理，基于大数据对所述知识数据图谱进行分析，重新确定各个学生对应的教学方法，直至判定所述目标教学方法合理；If it is unreasonable, analyze the knowledge data map based on big data, and re-determine the teaching method corresponding to each student until it is determined that the target teaching method is reasonable;
若合理，基于预设网络服务器将所述目标教学方法发送至各个老师以及学生对应的智能终端；If reasonable, send the target teaching method to the corresponding intelligent terminals of each teacher and student based on the preset network server;
反馈单元，用于在老师和学生接收到所述目标教学方法后，执行所述目标教学方法，并实时采集老师和学生的反馈信息，并基于所述反馈信息对所述目标教学方法进行完善。The feedback unit is configured to execute the target teaching method after the teacher and the student receive the target teaching method, collect feedback information of the teacher and the student in real time, and improve the target teaching method based on the feedback information.
优选的，一种基于大数据的教学系统，教学方法调整单元，还包括：Preferably, a teaching system and teaching method adjustment unit based on big data, further comprising:
知识点整合单元，用于基于所述各个学生对各个知识点的学习能力值从所述知识数据图谱包含的知识点中筛选学生未掌握的知识点；a knowledge point integration unit, configured to screen knowledge points that students have not mastered from the knowledge points included in the knowledge data map based on the learning ability value of each student for each knowledge point;
所述知识点整合单元，还用于基于预设规则，确定影响学生掌握的知识点的影响因素，并基于所述影响因素从预设解决方案库中查找对应的目标解决方案，其中，所述预设解决方案库中存储有多种教学问题对应的解决方案；The knowledge point integration unit is further configured to determine the influencing factors that affect the knowledge points mastered by students based on preset rules, and based on the influencing factors to search for a corresponding target solution from a preset solution library, wherein the Solutions corresponding to various teaching problems are stored in the preset solution library;
执行单元，用于根据所述目标解决方案将学生未掌握的知识点进行重新教学，直至学生完全掌握未掌握的知识点。The execution unit is used for re-teaching the unmastered knowledge points according to the target solution until the students completely master the unmastered knowledge points.
本发明的其它特征和优点将在随后的说明书中阐述，并且，部分地从说明书中变得显而易见，或者通过实施本发明而了解。本发明的目的和其他优点可通过在所写的说明书、权利要求书、以及附图中所特别指出的结构来实现和获得。Other features and advantages of the present invention will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description, claims, and drawings.
下面通过附图和实施例，对本发明的技术方案做进一步的详细描述。The technical solutions of the present invention will be further described in detail below through the accompanying drawings and embodiments.
附图说明Description of drawings
附图用来提供对本发明的进一步理解，并且构成说明书的一部分，与本发明的实施例一起用于解释本发明，并不构成对本发明的限制。在附图中：The accompanying drawings are used to provide a further understanding of the present invention, and constitute a part of the specification, and are used to explain the present invention together with the embodiments of the present invention, and do not constitute a limitation to the present invention. In the attached image:
图1为本发明实施例中一种基于大数据的教学系统的结构图；1 is a structural diagram of a teaching system based on big data in an embodiment of the present invention;
图2为本发明实施例中一种基于大数据的教学系统中数据获取模块的内部结构图；2 is an internal structure diagram of a data acquisition module in a teaching system based on big data in an embodiment of the present invention;
图3为本发明实施例中一种基于大数据的教学系统中数据分析模块的内部结构图。FIG. 3 is an internal structure diagram of a data analysis module in a teaching system based on big data according to an embodiment of the present invention.
具体实施方式Detailed ways
以下结合附图对本发明的优选实施例进行说明，应当理解，此处所描述的优选实施例仅用于说明和解释本发明，并不用于限定本发明。The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, but not to limit the present invention.
实施例1：Example 1:
本实施例提供了一种基于大数据的教学系统，如图1所示，包括：This embodiment provides a teaching system based on big data, as shown in Figure 1, including:
数据获取模块，用于获取学生的知识数据图谱；The data acquisition module is used to acquire the knowledge data map of students;
数据分析模块，用于基于大数据对所述知识数据图谱进行分析，确定各个学生对应的教学方法；a data analysis module, used for analyzing the knowledge data graph based on big data, and determining the corresponding teaching method for each student;
数据调整模块，用于在预设时间段内检测各个学生在对应的教学方法下的学习质量，并根据所述学习质量对所述教学方法进行调整，完成对各个学生制定合适的目标教学方法。The data adjustment module is used to detect the learning quality of each student under the corresponding teaching method within a preset time period, and adjust the teaching method according to the learning quality, so as to complete the formulation of an appropriate target teaching method for each student.
该实施例中，知识数据图谱用来表示各个数据之间的关系以及各个元知识点中包含的各个知识点。In this embodiment, the knowledge data graph is used to represent the relationship between various data and each knowledge point contained in each meta-knowledge point.
该实施例中，预设时间段是提前设定好的，例如可以是一周、两周等。In this embodiment, the preset time period is set in advance, for example, it may be one week, two weeks, and the like.
该实施例中，学习质量指的是学生在教学方法下接收知识点以及掌握知识点的程度。In this embodiment, the learning quality refers to the degree to which students receive and master knowledge points under the teaching method.
上述技术方案的有益效果是：通过对知识数据图谱进行分析，确定各个学生对应的教学方案，有利于针对各个学生进行合适的教学，同时对学生质量进行监测，便于对教学方法进行实时调整，提高了对学生教学的有效性，同时也提高了学生的学习质量以及学习效率。The beneficial effects of the above technical solutions are: by analyzing the knowledge data map, the corresponding teaching plan for each student is determined, which is conducive to appropriate teaching for each student, and at the same time, the quality of students is monitored, which is convenient for real-time adjustment of teaching methods. The effectiveness of teaching to students, but also improve the quality of students' learning and learning efficiency.
实施例2:Embodiment 2:
在上述实施例1的基础上，本实施例提供了一种基于大数据的教学系统，如图2所示，数据获取模块，包括：On the basis of the above-mentioned Embodiment 1, this embodiment provides a teaching system based on big data. As shown in FIG. 2 , the data acquisition module includes:
数据获取单元，用于获取学生知识领域的历史学习数据集，其中，所述历史学习数据集中包含训练数据和测试数据；a data acquisition unit for acquiring a historical learning data set in the student's knowledge field, wherein the historical learning data set includes training data and test data;
模型构建单元，用于基于所述训练数据训练深度学习模型，并基于所述测试数据对所述深度学习模型进行测试，并得到测试结果；a model building unit, used for training a deep learning model based on the training data, and testing the deep learning model based on the test data, and obtaining a test result;
第一判断单元，用于将所述测试结果与预设测试结果进行比较；a first judging unit for comparing the test result with a preset test result;
图谱构建单元，用于当所述测试结果满足所述预设测试结果的目标要求时，获取学生知识领域的用于构建知识图谱的目标数据，并基于所述深度学习模型对所述用于构建知识图谱的目标数据进行数据抽取，得到数据抽取结果；A graph construction unit, configured to obtain target data for building a knowledge graph in the student's knowledge field when the test result meets the target requirements of the preset test result, and based on the deep learning model for the target data for building a knowledge graph The target data of the knowledge map is extracted, and the data extraction result is obtained;
所述图谱构建单元，还用于根据所述数据抽取结果，从预设知识数据图谱构建层面对所述数据抽取结果进行知识融合，完成学生的知识数据图谱的构建；The map construction unit is further configured to perform knowledge fusion on the data extraction results from the preset knowledge data map construction level according to the data extraction results, so as to complete the construction of the students' knowledge data map;
所述模型构建单元，还用于当所述测试结果不满足所述预设测试结果的目标要求时，对所述深度学习模型进行再次训练，直至满足所述预设测试结果的目标要求。The model building unit is further configured to retrain the deep learning model when the test result does not meet the target requirement of the preset test result until the target requirement of the preset test result is met.
该实施例中，历史学习数据集指的是学生在以往的学习中对知识点的理解程度。In this embodiment, the historical learning data set refers to the students' understanding of knowledge points in previous learning.
该实施例中，深度学习模型是用来对学生的历史学习数据进行处理的，为构建知识数据图谱提供便利。In this embodiment, the deep learning model is used to process the historical learning data of the students, so as to facilitate the construction of a knowledge data graph.
该实施例中，预设测试结果是提前设定好的，用于衡量对深度学习模型的检测结果是否达标。In this embodiment, the preset test result is set in advance and is used to measure whether the detection result of the deep learning model meets the standard.
该实施例中，构建知识图谱的目标数据指的是学生知识领域中，需要学生进行严格掌握的知识点。In this embodiment, the target data for constructing the knowledge graph refers to the knowledge points in the student's knowledge field that need to be strictly mastered by the student.
该实施例中，预设知识数据图谱构建层面是提前设定好的，例如需构建主知识点，并在主知识点下面进行次知识点的延申。In this embodiment, the preset knowledge data graph construction level is set in advance, for example, the main knowledge point needs to be constructed, and the extension of the secondary knowledge point is performed under the main knowledge point.
上述技术方案的有益效果是：通过构建深度学习模型对学生的历史数据进行分析处理，便于构建准确的知识数据图谱，从而便于根据知识数据图谱制定合适的教学方法，为提高教学质量以及教学效率提供了便利。The beneficial effects of the above technical solutions are: by constructing a deep learning model to analyze and process the historical data of students, it is convenient to construct an accurate knowledge data map, so as to facilitate the formulation of appropriate teaching methods according to the knowledge data map, and to improve teaching quality and teaching efficiency. convenience.
实施例3：Example 3:
在上述实施例2的基础上，本实施例提供了一种基于大数据的教学系统，图谱构建单元，还包括：On the basis of the above-mentioned Embodiment 2, this embodiment provides a teaching system based on big data, a map construction unit, and also includes:
图谱更新单元，用于获取构建完成的知识数据图谱，同时，基于预设规则确定所述知识数据图谱中各节点对应的数据以及数据的属性值；a graph updating unit, configured to acquire the constructed knowledge data graph, and at the same time, determine data corresponding to each node in the knowledge data graph and attribute values of the data based on preset rules;
所述图谱更新单元，还用于在预设时间段内根据所述数据的属性值至少产生一条更新数据，并根据所述更新数据对所述知识数据图谱中各节点对应的数据进行更新，并得到目标更新数据；The graph update unit is further configured to generate at least one piece of update data according to the attribute value of the data within a preset time period, and update the data corresponding to each node in the knowledge data graph according to the update data, and Get target update data;
所述图谱更新单元，还用于根据所述目标更新数据获取预设推理规则，其中，所述预设推理规则是根据目标更新数据生成推理知识图谱普需要使用的规则；The graph updating unit is further configured to obtain a preset inference rule according to the target update data, wherein the preset inference rule is a rule that needs to be used to generate an inference knowledge graph according to the target update data;
所述图谱更新单元，还用于根据所述预设推理规则和目标更新数据，生成推理知识图谱，并将所述推理知识图谱与所述知识数据图谱进行合并，得到最终更新后的知识数据图谱。The graph updating unit is further configured to generate a reasoning knowledge graph according to the preset reasoning rules and target update data, and combine the reasoning knowledge graph and the knowledge data graph to obtain a final updated knowledge data graph .
该实施例中，预设规则是提前设定好的，用于确定知识数据图谱对应的知识点数据。In this embodiment, the preset rules are set in advance and are used to determine knowledge point data corresponding to the knowledge data graph.
该实施例中，各节点对应的数据指的是知识数据图谱中包含的所有知识点。In this embodiment, the data corresponding to each node refers to all knowledge points included in the knowledge data graph.
该实施例中，数据的属性值指的是知识点的数量值以及知识点的难易程度值。In this embodiment, the attribute value of the data refers to the value of the number of knowledge points and the value of the difficulty level of the knowledge point.
该实施例中，预设时间段是提前设定好的，例如可以是两周、一个月等。In this embodiment, the preset time period is set in advance, for example, it may be two weeks, one month, or the like.
该实施例中，更新数据指的是对学生要求掌握的知识点进行更新，即在原有基础上增添的新知识点。In this embodiment, updating the data refers to updating the knowledge points required by the students, that is, new knowledge points added on the original basis.
该实施例中，预设推理规则是提前设定好的，用于确定更新数据和原有数据之间的关联关系的一种规则。In this embodiment, the preset inference rule is a rule set in advance and used to determine the association relationship between the updated data and the original data.
该实施例中，推理知识图谱是用来表示更新数据之间与原有数据之间的关联关系。In this embodiment, the reasoning knowledge graph is used to represent the relationship between the updated data and the original data.
上述技术方案的有益效果是：通过确定更新数据，实现对知识数据图谱的更新，便于完善对学生知识点的教学，有利于提高学生掌握知识点的全面性，提高了学生的学习质量。The beneficial effects of the above technical solutions are: by determining the update data, the update of the knowledge data map is realized, which facilitates the improvement of the teaching of the students' knowledge points, helps to improve the comprehensiveness of the students' mastery of the knowledge points, and improves the students' learning quality.
实施例4：Example 4:
在上述实施例3的基础上，本实施例提供了一种基于大数据的教学系统，图谱更新单元，还包括：On the basis of the above-mentioned Embodiment 3, this embodiment provides a teaching system based on big data, a map updating unit, and also includes:
第一存储单元，用于获取最终更新后的知识数据图谱，其中，所述最终更新后的知识数据图谱带有数据类型标识；a first storage unit, used to obtain a final updated knowledge data graph, wherein the final updated knowledge data graph has a data type identifier;
所述第一存储单元，用于根据所述数据类型标识判断预设存储区域中是否存在与所述数据类型标识对应的图实例；The first storage unit is used to judge whether there is a graph instance corresponding to the data type identifier in the preset storage area according to the data type identifier;
若不存在，在所述预设存储区域内部创建与所述数据类型标识对应的图实例，并将所述最终更新后的知识数据图谱存储至所述创建所述图实例对应的目标存储区域；If it does not exist, create a graph instance corresponding to the data type identifier in the preset storage area, and store the final updated knowledge data graph in the target storage area corresponding to the creation of the graph instance;
否则，将所述最终更新后的知识数据图谱存储至所述图实例对应的目标存储区域。Otherwise, the final updated knowledge data graph is stored in the target storage area corresponding to the graph instance.
该实施例中，数据类型标识是用来区分知识点的类别，起到一种标签的作用。In this embodiment, the data type identifier is used to distinguish the categories of knowledge points, and acts as a kind of label.
该实施例中，图实例指的是存储区域中存储的类似于知识图谱类的图。In this embodiment, the graph instance refers to a graph similar to the knowledge graph class stored in the storage area.
该实施例中，预设存储区域是提前设定好的，例如可以是固态硬盘等。In this embodiment, the preset storage area is set in advance, and may be, for example, a solid-state hard disk or the like.
该实施例中，目标存储区域指的是预设存储区域中能够存储知识数据谱图的存储区域。In this embodiment, the target storage area refers to a storage area in the preset storage area that can store the knowledge data spectrum.
上述技术方案的有益效果是：通过将更新后的知识数据图谱进行存储，便于实时对学生要掌握的知识点进行了解，同时便于将知识点进行全面讲解，提高了学生的学习质量，同时也提高了老师的教学质量，为老师和学生提供了便利。The beneficial effects of the above technical solutions are: by storing the updated knowledge data map, it is convenient to understand the knowledge points to be mastered by students in real time, and at the same time, it is convenient to comprehensively explain the knowledge points, so as to improve the learning quality of students, and at the same time. It improves the quality of teachers' teaching and provides convenience for teachers and students.
实施例5：Example 5:
在上述实施例1的基础上，本实施例提供了一种基于大数据的教学系统，如图3所示，数据分析模块，包括：On the basis of the above-mentioned Embodiment 1, this embodiment provides a teaching system based on big data. As shown in FIG. 3 , the data analysis module includes:
学习数据监测单元，用于根据预设频率获取多组学生的学习记录，并调取所述各个学生当前接受的目标教学方案，同时，根据所述多组学生的学习记录以及目标教学方案，确定各个学生的偏离信息；The learning data monitoring unit is used to obtain the learning records of multiple groups of students according to the preset frequency, and retrieve the target teaching plan currently accepted by each student, and at the same time, according to the learning records of the multiple groups of students and the target teaching plan, determine Deviation information for individual students;
所述学习数据监测单元，还用于获取各个学生在当前接受的目标教学方案下产生的生理数据，并根据所述生理数据确定各个学生在所述目标教学方案下的目标反应；The learning data monitoring unit is further configured to acquire physiological data generated by each student under the target teaching scheme currently accepted, and determine the target response of each student under the target teaching scheme according to the physiological data;
所述学习数据监测单元，还用于根据各个学生的目标反应确定当前接受的目标教学方案中教学方式的分类标识，并根据所述分类标识确定各个学生的兴趣点以及非兴趣点；The learning data monitoring unit is also used to determine the classification identification of the teaching method in the currently accepted target teaching scheme according to the target response of each student, and to determine the interest points and non-interest points of each student according to the classification identification;
教学资源整合单元，用于对所述知识数据图谱包含的教学资源进行聚类处理，提取出各个学生对应的学科题目知识点，并构成学科知识点集合，其中，所述知识数据图谱展示了学科知识点集合中元知识点和元知识点之间的关联关系；The teaching resource integration unit is used for clustering the teaching resources included in the knowledge data map, extracting the subject knowledge points corresponding to each student, and forming a subject knowledge point set, wherein the knowledge data map shows the subject The relationship between meta-knowledge points and meta-knowledge points in the knowledge point set;
教学方法确定单元，用于根据各个学生的偏离信息，通过所述知识数据图谱，从所述学科知识点集合中确定目标元知识点以及与所述目标元知识点存在关联关系的元知识点组合；A teaching method determining unit is used to determine a target meta-knowledge point and a meta-knowledge point combination that has an associated relationship with the target meta-knowledge point from the subject knowledge point set through the knowledge data map according to the deviation information of each student ;
所述教学方法确定单元，还用于获取历史试题信息，并基于所述历史试题信息确定目标元知识点以及与所述目标元知识点存在关联关系的元知识点组合各自的教学比重，并根据所述教学比重，确定各个学生对应的最终教学资源；The teaching method determining unit is also used to obtain historical test question information, and based on the historical test question information, determine the respective teaching proportions of the target meta-knowledge point and the meta-knowledge point combination that has an associated relationship with the target meta-knowledge point, and according to the The teaching proportion determines the final teaching resources corresponding to each student;
所述教学方法确定单元，还用于根据各个学生的趣点以及非兴趣点，从预设教学方式库中匹配对应的目标教学方式，并将各个学生对应.的目标教学方式与最终教学资源进行匹配记录，得到各个学生对应的教学方法。The teaching method determining unit is also used to match the corresponding target teaching methods from the preset teaching method library according to the interest points and non-interest points of each student, and compare the target teaching methods corresponding to each student with the final teaching resources. Match the records to get the teaching method corresponding to each student.
该实施例中，预设频率是提前设定好的，例如可以是一周或两周。In this embodiment, the preset frequency is set in advance, for example, it may be one week or two weeks.
该实施例中，目标教学方案指的是学生当前接受的教学方法或教学计划。In this embodiment, the target teaching plan refers to the teaching method or teaching plan currently accepted by the students.
该实施例中，学生的偏离信息指的是学生在学习过程中出现的偏科或者未掌握的知识点的方向等。In this embodiment, the deviation information of the student refers to the partial subject or the direction of the knowledge point that the student has not mastered during the learning process.
该实施例中，生理数据指的是学生在教学方案下的反应，例如可以是激动、平静、沉寂等。In this embodiment, the physiological data refers to the reaction of the student under the teaching plan, such as excitement, calmness, silence, and the like.
该实施例中，目标反应指的是学生在教学方案下的激动、平静、沉寂中的一种。In this embodiment, the target response refers to one of the students' excitement, calmness, and silence under the teaching plan.
该实施例中，分类标识是用来区分不同教学方式所用的一种标签，例如可以是古板教学的标识是1，有趣教学的标识是2等。In this embodiment, the classification label is a label used to distinguish different teaching methods, for example, the label for old-fashioned teaching is 1, the label for interesting teaching is 2, and so on.
该实施例中，学科题目知识点指的是各个学生在各学科中可能涉及到的知识点。In this embodiment, the subject knowledge points refer to the knowledge points that each student may involve in each subject.
该实施例中，元知识点组合指的是具有关联关系的元知识点构成的数据集合。In this embodiment, the meta-knowledge point combination refers to a data set composed of meta-knowledge points having an associated relationship.
上述技术方案的有益效果是：通过对知识数据图谱分析，确定各个学生的学科知识点集合，同时在学科知识点集合中确定各个知识点之间的关联关系，并根据学生的兴趣点和非兴趣点选择对应的教学方式，并将教学方式与知识点进行结果，完成教学方法的确定，提高了对各个学生制定有效的教学方案，提高了学生的学习质量，同时也提高了老师的教学效率。The beneficial effects of the above technical solution are: through the analysis of the knowledge data map, the subject knowledge point set of each student is determined, and at the same time, the association relationship between the various knowledge points is determined in the subject knowledge point set, and according to the students' interest points and non-interest points. Click to select the corresponding teaching method, and make the results of the teaching method and knowledge points to complete the determination of the teaching method, which improves the formulation of effective teaching plans for each student, improves the learning quality of students, and also improves the teaching efficiency of teachers.
实施例6：Example 6:
在上述实施例1的基础上，本实施例提供了一种基于大数据的教学系统，数据调模块，包括：On the basis of the above-mentioned Embodiment 1, this embodiment provides a teaching system based on big data. The data adjustment module includes:
模型构建单元，用于获取学生学习质量评测的影响因素，并根据所述学生学习质量评测的影响因素建立学生学习质量评测的评价指标体系；a model building unit, used to obtain the influencing factors of student learning quality evaluation, and establish an evaluation index system for student learning quality evaluation according to the influencing factors of student learning quality evaluation;
所述模型构建单元，还用于基于预设方法确定所述评价指标体系的指标权重，并根据所述指标权重构建学生学习质量评价模型；The model construction unit is further configured to determine the index weight of the evaluation index system based on a preset method, and construct a student learning quality evaluation model according to the index weight;
学习数据获取单元，用于基于预设知识点的能力层次，确定各个学生的目标达成度，同时，监控各个学生测评试题、课堂问答和课堂讨论的完成情况，得到各个学生对应的课程参与度；The learning data acquisition unit is used to determine the degree of achievement of each student's goal based on the ability level of the preset knowledge points, and at the same time, monitor the completion of each student's assessment questions, classroom questions and answers, and class discussion, and obtain the corresponding course participation degree of each student;
学习质量评价单元，用于将各个学生对应的目标达成度以及课程参与度输入所述学习质量评价模型，得到各个学生对应的学习质量评价结果；The learning quality evaluation unit is used to input the target achievement degree and course participation degree corresponding to each student into the learning quality evaluation model, and obtain the learning quality evaluation result corresponding to each student;
所述学习质量评价单元，还用于将所述各个学生对应的学习质量评价结果与预设学习质量评价结果进行比较；The learning quality evaluation unit is further configured to compare the learning quality evaluation result corresponding to each student with the preset learning quality evaluation result;
判断单元，用于当所述各个学生对应的学习质量评价结果高于或等于所述预设评价结果，判定各个学生接受的教学方法合格，否则，判定各个学生接受的教学方法不合格；a judging unit, configured to judge that the teaching method accepted by each student is qualified when the learning quality evaluation result corresponding to each student is higher than or equal to the preset evaluation result, otherwise, judge that the teaching method accepted by each student is unqualified;
教学方法调整单元，用于在判定各个学生接受的教学方法不合格时，基于所述知识数据图谱调取各个知识点的检测数据，并根据所述各个知识点的检测数据确定各个学生对各个知识点的学习能力值；The teaching method adjustment unit is used to retrieve the detection data of each knowledge point based on the knowledge data map when it is determined that the teaching method accepted by each student is unqualified, and determine each student's understanding of each knowledge point according to the detection data of each knowledge point The learning ability value of the point;
所述教学方法调整单元，还用于基于所述各个学生对各个知识点的学习能力值从所述知识数据图谱包含的知识点中筛选学生已掌握的知识点，并根据所述学生已掌握的知识点确定学生的平均学习能力值；The teaching method adjustment unit is further configured to screen the knowledge points that the students have mastered from the knowledge points included in the knowledge data map based on the learning ability values of the students for each knowledge point, and select the knowledge points that the students have mastered according to the knowledge points that the students have mastered. Knowledge points determine the average learning ability value of students;
所述教学方法调整单元，还用于基于所述平均学习能力值对所述教学方法进行调整，完成对各个学生制定合适的目标教学方法。The teaching method adjustment unit is further configured to adjust the teaching method based on the average learning ability value, so as to complete the formulation of an appropriate target teaching method for each student.
该实施例中，学生学习质量评测的影响因素可以是学生的学习态度、学生的课程参与度等。In this embodiment, the influencing factors of the student's learning quality evaluation may be the student's learning attitude, the student's course participation, and the like.
该实施例中，学生学习质量评测的评价指标体系可以是根据学生的课程参与度以及掌握知识点的多少程度对学生的学习质量进行评价。In this embodiment, the evaluation index system for evaluating the student's learning quality may be to evaluate the student's learning quality according to the student's degree of participation in the course and the degree of mastery of knowledge points.
该实施例中，预设方法是提前设定好的，是用来确定评价体系中不同评价标准在所有评价标准中的重要程度值。In this embodiment, the preset method is set in advance, and is used to determine the importance value of different evaluation criteria in the evaluation system among all evaluation criteria.
该实施例中，预设知识点的能力层次指的是知识点的难易程度值。In this embodiment, the ability level of the preset knowledge point refers to the difficulty level value of the knowledge point.
该实施例中，目标大程度指的是学生成功掌握知识点的数量值以及掌握的知识点的难易程度值。In this embodiment, the target degree refers to the value of the number of knowledge points successfully mastered by the students and the value of the degree of difficulty of the mastered knowledge points.
该实施例中，预设学习质量评价结果是提前设定好的，是对学生学习质量的要求。In this embodiment, the preset learning quality evaluation result is set in advance, which is a requirement for students' learning quality.
该实施例中，各个知识点的检测数据指的是各个知识点中用来检测学生是否掌握该知识点的数据。In this embodiment, the detection data of each knowledge point refers to data in each knowledge point used to detect whether a student has mastered the knowledge point.
该实施例中，学习能力值指的是学生掌握知识点的能力程度，例如学生掌握知识点所用时间为一个小时，标识学习能力值强，所用时间为一天，标识学习能力值弱。In this embodiment, the learning ability value refers to the degree of students' ability to master knowledge points. For example, it takes one hour for the students to master the knowledge points, indicating that the learning ability value is strong, and the time spent is one day, indicating that the learning ability value is weak.
上述技术方案的有益效果是：通过构建学习质量评价模型，并获取学生在教学方法下的学习数据，实现通过对学生的学习质量进行分析，判断出制定的教学方法是否合理，且在不合理的情况下根据学生的学习能力值对教学方法进行调整，便于针对各个学生制定相应的教学方法，提高了学生学习的质量，同时也不断完善了教学方法，为老师和学生提供了不同方向的便利。The beneficial effects of the above technical solutions are: by constructing a learning quality evaluation model and obtaining students' learning data under the teaching method, it is possible to analyze the students' learning quality to determine whether the formulated teaching method is reasonable, and whether it is unreasonable or not. The teaching method is adjusted according to the learning ability value of the students under different circumstances, so that it is convenient to formulate corresponding teaching methods for each student, improve the quality of students' learning, and continuously improve the teaching methods, providing convenience for teachers and students in different directions.
实施例7：Example 7:
在上述实施例6的基础上，本实施例提供了一种基于大数据的教学系统，教学方法调整单元，还包括：On the basis of the above-mentioned Embodiment 6, this embodiment provides a teaching system based on big data, and a teaching method adjustment unit, further comprising:
检测单元，用于获取对各个学生制定的目标教学方法，并基于预设检测方法确定所述目标教学方法是否合理；a detection unit, configured to obtain the target teaching method formulated for each student, and determine whether the target teaching method is reasonable based on the preset detection method;
若不合理，基于大数据对所述知识数据图谱进行分析，重新确定各个学生对应的教学方法，直至判定所述目标教学方法合理；If it is unreasonable, analyze the knowledge data map based on big data, and re-determine the teaching method corresponding to each student until it is determined that the target teaching method is reasonable;
若合理，基于预设网络服务器将所述目标教学方法发送至各个老师以及学生对应的智能终端；If reasonable, send the target teaching method to the corresponding intelligent terminals of each teacher and student based on the preset network server;
反馈单元，用于在老师和学生接收到所述目标教学方法后，执行所述目标教学方法，并实时采集老师和学生的反馈信息，并基于所述反馈信息对所述目标教学方法进行完善。The feedback unit is configured to execute the target teaching method after the teacher and the student receive the target teaching method, collect feedback information of the teacher and the student in real time, and improve the target teaching method based on the feedback information.
该实施例中，预设检测方法是提前设定好的，例如可以是根据教学大纲对教学方法进行评测，判断教学方法中涉及的知识点是否全面。In this embodiment, the preset detection method is set in advance, for example, the teaching method may be evaluated according to the teaching syllabus to determine whether the knowledge points involved in the teaching method are comprehensive.
该实施例中，智能终端可以是老师和学生的手机或电脑。In this embodiment, the smart terminals may be mobile phones or computers of teachers and students.
该实施例中，反馈信息指的是老师在教学过程中存在的问题以及学生在学习过程中存在的不懂之处。In this embodiment, the feedback information refers to the problems existing in the teaching process of the teacher and the ignorance of the students in the learning process.
上述技术方案的有益效果是：通过实时采集老师和学生的反馈意见，有利于对教学方法进行不断完善，提高了学生的学习质量，同时也便于老师及时调整教学方法。The beneficial effects of the above technical solutions are: by collecting feedbacks from teachers and students in real time, it is conducive to continuous improvement of teaching methods, improves students' learning quality, and facilitates teachers to adjust teaching methods in a timely manner.
实施例8：Example 8:
在上述实施例6的基础上，本实施例提供了一种基于大数据的教学系统，教学方法调整单元，还包括：On the basis of the above-mentioned Embodiment 6, this embodiment provides a teaching system based on big data, and a teaching method adjustment unit, further comprising:
知识点整合单元，用于基于所述各个学生对各个知识点的学习能力值从所述知识数据图谱包含的知识点中筛选学生未掌握的知识点；a knowledge point integration unit, configured to screen knowledge points that students have not mastered from the knowledge points included in the knowledge data map based on the learning ability value of each student for each knowledge point;
所述知识点整合单元，还用于基于预设规则，确定影响学生掌握的知识点的影响因素，并基于所述影响因素从预设解决方案库中查找对应的目标解决方案，其中，所述预设解决方案库中存储有多种教学问题对应的解决方案；The knowledge point integration unit is further configured to determine the influencing factors affecting the knowledge points mastered by students based on preset rules, and based on the influencing factors to search for the corresponding target solution from the preset solution library, wherein the Solutions corresponding to various teaching problems are stored in the preset solution library;
执行单元，用于根据所述目标解决方案将学生未掌握的知识点进行重新教学，直至学生完全掌握未掌握的知识点。The execution unit is used for re-teaching the unmastered knowledge points according to the target solution until the students completely master the unmastered knowledge points.
该实施例中，学习能力值指的是学生掌握知识点的难易程度。In this embodiment, the learning ability value refers to the degree of difficulty for the student to master the knowledge point.
该实施例中，预设规则是提前设定好的。In this embodiment, the preset rule is set in advance.
该实施例中，影响因素可以是知识点过难或者是学生自身因素。In this embodiment, the influencing factor may be that the knowledge point is too difficult or the student's own factor.
该实施例中，目标解决方案是用来解决学生未掌握知识点所用，例如，可以通过多种方法对未掌握的知识点进行多次讲解。In this embodiment, the target solution is used to solve the knowledge points that the students have not mastered. For example, the unmastered knowledge points can be explained multiple times through various methods.
上述技术方案的有益效果是：通过确定学生未掌握的知识点的影响因素，并根据影响因素查找对应额解决方案，便于提高学生对知识点掌握的全面性，提高了学生的学习质量。The beneficial effects of the above technical solutions are: by determining the influencing factors of knowledge points that students have not mastered, and finding corresponding solutions according to the influencing factors, it is convenient to improve the comprehensiveness of students' grasp of knowledge points and improve the quality of students' learning.
显然，本领域的技术人员可以对本发明进行各种改动和变型而不脱离本发明的精神和范围。这样，倘若本发明的这些修改和变型属于本发明权利要求及其等同技术的范围之内，则本发明也意图包含这些改动和变型在内。It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit and scope of the invention. Thus, provided that these 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 these modifications and variations.
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