技术领域technical field
本发明涉及计算机技术领域，尤其涉及一种基于大数据的易错题库构建管理方法及设备。The invention relates to the field of computer technology, in particular to a method and equipment for building and managing error-prone question banks based on big data.
背景技术Background technique
目前，为了方便学生用户识别易错题，在构建易错题库时通常是由教师以人工方式给习题库中的某一些习题打上“易错”、“易错题”等标识来实现对易错题的定义。然而，在实践中发现，教师以人工方式来定义易错题会存在以下的缺陷：第一、完全凭借教师的个人主观经验，而不同老师的教学经验通常不一样，这就难以客观地定义出易错题；第二、易错题难以实现动态、灵活管理。At present, in order to facilitate students and users to identify error-prone questions, teachers usually mark certain exercises in the exercise bank as "error-prone" and "error-prone questions" manually when constructing error-prone question banks to realize correct and error-prone questions. Definition of the topic. However, in practice, it is found that teachers manually define error-prone questions, which will have the following defects: First, relying entirely on the teacher's personal subjective experience, and the teaching experience of different teachers is usually different, so it is difficult to define objectively. Error-prone questions; Second, error-prone questions are difficult to achieve dynamic and flexible management.
发明内容Contents of the invention
本发明实施例公开了一种基于大数据的易错题库构建管理方法及设备，能够客观地定义出易错题，而且易错题可以实现动态、灵活管理。The embodiment of the present invention discloses a big data-based error-prone question bank construction management method and equipment, which can objectively define error-prone questions, and the error-prone questions can realize dynamic and flexible management.
本发明实施例第一方面公开一种基于大数据的易错题库构建管理方法，包括：The first aspect of the embodiment of the present invention discloses a method for building and managing error-prone question banks based on big data, including:
收集多个学生用户对某一目标习题进行作答的答案数据；Collect the answer data of multiple student users answering a certain target exercise;
判断所述多个学生用户的数量是否超过指定人数，如果超过，以所述多个学生用户对所述目标习题进行作答的答案数据为依据，统计所述目标习题的错题率；Judging whether the number of the plurality of student users exceeds the specified number, if so, counting the error rate of the target exercise based on the answer data of the plurality of student users answering the target exercise;
判断所述错题率是否超过预设阈值，如果超过，在习题库中修改所述目标习题的标签，以使修改后的所述目标习题的标签用于定义所述目标习题为易错题。Judging whether the error rate exceeds a preset threshold, if so, modifying the label of the target exercise in the exercise library, so that the modified label of the target exercise is used to define the target exercise as an error-prone question.
作为一种可选的实施方式，在本发明实施例第一方面中，在习题库中修改所述目标习题的标签，以使修改后的所述目标习题的标签用于定义所述目标习题为易错题之后，所述方法还包括：As an optional implementation, in the first aspect of the embodiment of the present invention, the label of the target exercise is modified in the exercise library, so that the modified label of the target exercise is used to define the target exercise as After error-prone questions, the method also includes:
从所述习题库中获取所述目标习题对应的教师评析信息，所述教师评析信息包括所述目标习题的知识点和习题类型；Acquiring teacher evaluation information corresponding to the target exercise from the exercise library, the teacher evaluation information including knowledge points and exercise types of the target exercise;
以及，从所述多个学生用户对所述目标习题进行作答的答案数据中，确定出错误答案数据，并且从所述多个学生用户中确定出作答了所述错误答案数据的学生用户作为目标学生用户，以形成目标学生用户群；And, determine wrong answer data from the answer data of the plurality of student users answering the target exercise, and determine the student user who answered the wrong answer data from the plurality of student users as the target Student users to form a target student user group;
以及，从所述习题库中查询与所述目标习题的知识点和习题类型同时匹配的除所述目标习题之外的其余习题作为待推荐习题，以形成待推荐习题集；And, query the rest of the exercises except the target exercises that match the knowledge points and exercise types of the target exercises from the exercise library as exercises to be recommended, so as to form an exercise set to be recommended;
以及，从所述待推荐习题集中选取至少一道待推荐习题，并向所述目标学生用户群包含的所述目标学生用户推荐所述至少一道待推荐习题。And, selecting at least one exercise to be recommended from the set of exercises to be recommended, and recommending the at least one exercise to be recommended to the target student users included in the target student user group.
作为一种可选的实施方式，在本发明实施例第一方面中，在向所述目标学生用户群包含的所述目标学生用户推荐所述至少一道待推荐习题之后，所述方法还包括：As an optional implementation manner, in the first aspect of the embodiment of the present invention, after recommending the at least one exercise to be recommended to the target student users included in the target student user group, the method further includes:
获取所述目标学生用户群中的每一个所述目标学生用户的用户属性，所述用户属性包括所述目标学生用户对应的班级标识；Acquiring user attributes of each of the target student users in the target student user group, the user attributes including the class identifier corresponding to the target student user;
以所述目标学生用户群中的每一个所述目标学生用户对应的班级标识为依据，将所述目标学生用户群中的所述目标学生用户按照班级进行分组，获得若干个目标学生用户组；其中，位于同一个目标学生用户组内的所述目标学生用户对应的班级标识相同；Based on the class identification corresponding to each of the target student users in the target student user group, group the target student users in the target student user group according to class to obtain several target student user groups; Wherein, the class identifications corresponding to the target student users located in the same target student user group are the same;
针对每一个所述目标学生用户组，以所述目标学生用户组内的所述目标学生用户对应的班级标识为依据，从预设的班级标识与教学教师的对应关系中确定出所述目标学生用户组对应的目标教学教师；其中，所述目标习题属于所述目标教学教师负责的教学科目的一道习题；For each target student user group, based on the class ID corresponding to the target student user in the target student user group, determine the target student from the preset correspondence between the class ID and the teaching teacher The target teaching teacher corresponding to the user group; wherein, the target exercise belongs to an exercise of the teaching subject that the target teaching teacher is responsible for;
向每一个所述目标学生用户组对应的目标教学教师推荐所述目标习题。The target exercises are recommended to target teaching teachers corresponding to each target student user group.
作为一种可选的实施方式，在本发明实施例第一方面中，在习题库中修改所述目标习题的标签，以使修改后的所述目标习题的标签用于定义所述目标习题为易错题之后，所述方法还包括：As an optional implementation, in the first aspect of the embodiment of the present invention, the label of the target exercise is modified in the exercise library, so that the modified label of the target exercise is used to define the target exercise as After error-prone questions, the method also includes:
从所述多个学生用户对所述目标习题进行作答的答案数据中，确定出错误答案数据，并且从所述多个学生用户中确定出作答了所述错误答案数据的学生用户作为目标学生用户，以形成目标学生用户群；From the answer data of the multiple student users answering the target exercise, determine the wrong answer data, and determine the student user who answered the wrong answer data from the multiple student users as the target student user , to form the target student user group;
获取所述目标学生用户群中的每一个所述目标学生用户的用户属性，所述用户属性包括所述目标学生用户对应的班级标识；Acquiring user attributes of each of the target student users in the target student user group, the user attributes including the class identifier corresponding to the target student user;
以所述目标学生用户群中的每一个所述目标学生用户对应的班级标识为依据，将所述目标学生用户群中的所述目标学生用户按照班级进行分组，获得若干个目标学生用户组；其中，位于同一个目标学生用户组内的所述目标学生用户对应的班级标识相同；Based on the class identification corresponding to each of the target student users in the target student user group, group the target student users in the target student user group according to class to obtain several target student user groups; Wherein, the class identifications corresponding to the target student users located in the same target student user group are the same;
针对每一个所述目标学生用户组，以所述目标学生用户组内的所述目标学生用户对应的班级标识为依据，从预设的班级标识与教学教师的对应关系中确定出所述目标学生用户组对应的目标教学教师；其中，所述目标习题属于所述目标教学教师负责的教学科目的一道习题；For each target student user group, based on the class ID corresponding to the target student user in the target student user group, determine the target student from the preset correspondence between the class ID and the teaching teacher The target teaching teacher corresponding to the user group; wherein, the target exercise belongs to an exercise of the teaching subject that the target teaching teacher is responsible for;
向每一个所述目标学生用户组对应的目标教学教师推荐所述目标习题。The target exercises are recommended to target teaching teachers corresponding to each target student user group.
作为一种可选的实施方式，在本发明实施例第一方面中，以所述多个学生用户对所述目标习题进行作答的答案数据为依据，统计所述目标习题的错题率，包括：As an optional implementation manner, in the first aspect of the embodiment of the present invention, based on the answer data of the multiple student users answering the target exercise, the error rate of the target exercise is counted, including :
从所述多个学生用户对所述目标习题进行作答的答案数据中，统计出错误答案数据的数量；Counting the number of wrong answer data from the answer data of the plurality of student users answering the target exercise;
统计所述错误答案数据的数量占所述答案数据的总数量的比例值，作为所述目标习题的错题率。The ratio of the number of wrong answer data to the total number of answer data is counted as the wrong question rate of the target exercise.
本发明实施例第二方面公开一种基于大数据的易错题库构建管理设备，包括：The second aspect of the embodiment of the present invention discloses an error-prone question bank construction management device based on big data, including:
收集单元，用于收集多个学生用户对某一目标习题进行作答的答案数据；A collection unit, configured to collect answer data of multiple student users answering a certain target exercise;
第一判断单元，用于判断所述多个学生用户的数量是否超过指定人数；A first judging unit, configured to judge whether the number of the plurality of student users exceeds a specified number;
统计单元，用于在所述第一判断单元的判断结果为超过时，以所述多个学生用户对所述目标习题进行作答的答案数据为依据，统计所述目标习题的错题率；A statistical unit, configured to count the error rate of the target exercise based on the answer data of the plurality of student users answering the target exercise when the judgment result of the first judgment unit is exceeded;
第二判断单元，用于判断所述错题率是否超过预设阈值；A second judging unit, configured to judge whether the rate of wrong questions exceeds a preset threshold;
处理单元，用于在所述第二判断单元的判断结果为超过时，在习题库中修改所述目标习题的标签，以使修改后的所述目标习题的标签用于定义所述目标习题为易错题。A processing unit, configured to modify the label of the target exercise in the exercise library when the judgment result of the second judgment unit is over, so that the modified label of the target exercise is used to define the target exercise as Error-prone questions.
作为一种可选的实施方式，在本发明实施例第二方面中，所述易错题库构建管理设备还包括：As an optional implementation manner, in the second aspect of the embodiments of the present invention, the error-prone question bank construction management device further includes:
第一获取单元，用于在所述处理单元在习题库中修改所述目标习题的标签，以使修改后的所述目标习题的标签用于定义所述目标习题为易错题之后，从所述习题库中获取所述目标习题对应的教师评析信息，所述教师评析信息包括所述目标习题的知识点和习题类型；The first acquiring unit is configured to, after the processing unit modifies the label of the target exercise in the exercise library, so that the modified label of the target exercise is used to define the target exercise as an error-prone question, from the Obtain the teacher's evaluation information corresponding to the target exercise in the exercise bank, and the teacher's evaluation information includes knowledge points and exercise types of the target exercise;
第一确定单元，用于从所述多个学生用户对所述目标习题进行作答的答案数据中，确定出错误答案数据，并且从所述多个学生用户中确定出作答了所述错误答案数据的学生用户作为目标学生用户，以形成目标学生用户群；A first determining unit, configured to determine wrong answer data from the answer data of the plurality of student users answering the target exercise, and determine from the plurality of student users that the wrong answer data has been answered student users as target student users to form a target student user group;
查询单元，用于从所述习题库中查询与所述目标习题的知识点和习题类型同时匹配的除所述目标习题之外的其余习题作为待推荐习题，以形成待推荐习题集；a query unit, configured to query from the exercise library other exercises other than the target exercises that match both the knowledge points and the exercise types of the target exercises as exercises to be recommended, so as to form a set of exercises to be recommended;
第一推荐单元，用于从所述待推荐习题集中选取至少一道待推荐习题，并向所述目标学生用户群包含的所述目标学生用户推荐所述至少一道待推荐习题。The first recommending unit is configured to select at least one exercise to be recommended from the set of exercises to be recommended, and recommend the at least one exercise to be recommended to the target student users included in the target student user group.
作为一种可选的实施方式，在本发明实施例第二方面中，所述易错题库构建管理设备还包括：As an optional implementation manner, in the second aspect of the embodiments of the present invention, the error-prone question bank construction management device further includes:
第二获取单元，用于在所述第一推荐单元向所述目标学生用户群包含的所述目标学生用户推荐所述至少一道待推荐习题之后，获取所述目标学生用户群中的每一个所述目标学生用户的用户属性，所述用户属性包括所述目标学生用户对应的班级标识；The second obtaining unit is configured to obtain each of the target student user groups in the target student user group after the first recommending unit recommends the at least one exercise to be recommended to the target student user included in the target student user group. The user attribute of the target student user, the user attribute includes the class identification corresponding to the target student user;
第一分组单元，用于以所述目标学生用户群中的每一个所述目标学生用户对应的班级标识为依据，将所述目标学生用户群中的所述目标学生用户按照班级进行分组，获得若干个目标学生用户组；其中，位于同一个目标学生用户组内的所述目标学生用户对应的班级标识相同；The first grouping unit is configured to group the target student users in the target student user group according to class based on the class identifier corresponding to each target student user in the target student user group, to obtain Several target student user groups; wherein, the class identifications corresponding to the target student users in the same target student user group are the same;
第二确定单元，用于针对每一个所述目标学生用户组，以所述目标学生用户组内的所述目标学生用户对应的班级标识为依据，从预设的班级标识与教学教师的对应关系中确定出所述目标学生用户组对应的目标教学教师；其中，所述目标习题属于所述目标教学教师负责的教学科目的一道习题；The second determining unit is configured to, for each of the target student user groups, based on the class identification corresponding to the target student user in the target student user group, from the preset correspondence between the class identification and the teaching teacher Determine the target teaching teacher corresponding to the target student user group; wherein, the target exercise belongs to an exercise of the teaching subject that the target teaching teacher is responsible for;
所述第一推荐单元，还用于向每一个所述目标学生用户组对应的目标教学教师推荐所述目标习题。The first recommending unit is further configured to recommend the target exercises to the target teaching teachers corresponding to each of the target student user groups.
作为一种可选的实施方式，在本发明实施例第二方面中，所述易错题库构建管理设备还包括：As an optional implementation manner, in the second aspect of the embodiments of the present invention, the error-prone question bank construction management device further includes:
第三确定单元，用于在所述处理单元在习题库中修改所述目标习题的标签，以使修改后的所述目标习题的标签用于定义所述目标习题为易错题之后，从所述多个学生用户对所述目标习题进行作答的答案数据中，确定出错误答案数据，并且从所述多个学生用户中确定出作答了所述错误答案数据的学生用户作为目标学生用户，以形成目标学生用户群；The third determination unit is configured to modify the label of the target exercise in the exercise library by the processing unit, so that the modified label of the target exercise is used to define the target exercise as an error-prone question, from the In the answer data of the plurality of student users answering the target exercise, the wrong answer data is determined, and the student user who has answered the wrong answer data is determined from the plurality of student users as the target student user, so that Form a target student user group;
第三获取单元，用于获取所述目标学生用户群中的每一个所述目标学生用户的用户属性，所述用户属性包括所述目标学生用户对应的班级标识；A third acquiring unit, configured to acquire user attributes of each of the target student users in the target student user group, where the user attributes include a class identifier corresponding to the target student user;
第二分组单元，用于以所述目标学生用户群中的每一个所述目标学生用户对应的班级标识为依据，将所述目标学生用户群中的所述目标学生用户按照班级进行分组，获得若干个目标学生用户组；其中，位于同一个目标学生用户组内的所述目标学生用户对应的班级标识相同；The second grouping unit is configured to group the target student users in the target student user group according to class based on the class identifier corresponding to each target student user in the target student user group, to obtain Several target student user groups; wherein, the class identifications corresponding to the target student users in the same target student user group are the same;
第四确定单元，用于针对每一个所述目标学生用户组，以所述目标学生用户组内的所述目标学生用户对应的班级标识为依据，从预设的班级标识与教学教师的对应关系中确定出所述目标学生用户组对应的目标教学教师；其中，所述目标习题属于所述目标教学教师负责的教学科目的一道习题；The fourth determination unit is configured to, for each of the target student user groups, based on the class identification corresponding to the target student user in the target student user group, from the preset correspondence between the class identification and the teaching teacher Determine the target teaching teacher corresponding to the target student user group; wherein, the target exercise belongs to an exercise of the teaching subject that the target teaching teacher is responsible for;
第二推荐单元，用于向每一个所述目标学生用户组对应的目标教学教师推荐所述目标习题。The second recommending unit is configured to recommend the target exercises to the target teaching teachers corresponding to each of the target student user groups.
作为一种可选的实施方式，在本发明实施例第二方面中，所述统计单元以所述多个学生用户对所述目标习题进行作答的答案数据为依据，统计所述目标习题的错题率的方式具体为：As an optional implementation manner, in the second aspect of the embodiment of the present invention, the statistical unit counts the errors of the target exercise based on the answer data of the multiple student users answering the target exercise. The question rate method is as follows:
所述统计单元从所述多个学生用户对所述目标习题进行作答的答案数据中，统计出错误答案数据的数量，以及统计所述错误答案数据的数量占所述答案数据的总数量的比例值，作为所述目标习题的错题率。The statistical unit counts the number of wrong answer data from the answer data of the plurality of student users answering the target exercise, and counts the ratio of the number of wrong answer data to the total number of answer data value, as the error rate of the target exercises.
与现有技术相比，本发明实施例具备以下有益效果：Compared with the prior art, the embodiments of the present invention have the following beneficial effects:
本发明实施例中，可以收集多个学生用户对某一目标习题进行作答的答案数据，并且在判断该多个学生用户的数量超过指定人数时，以该多个学生用户对该目标习题进行作答的答案数据为依据，统计该目标习题的错题率；当判断该错题率超过预设阈值时，可以在习题库中修改该目标习题的标签，以使修改后的该目标习题的标签用于定义该目标习题为易错题。显然，实施本发明实施例，易错题的定义不再取决于教师的个人主观经验，而是根据收集的多个学生用户对目标习题进行作答的答案数据(即大数据)进行判断和统计后定义出来的，从而可以客观地定义出易错题；此外，易错题的定义无需教师以人工方式来定义，从而可以实现易错题的动态、灵活管理。In the embodiment of the present invention, it is possible to collect the answer data of multiple student users answering a certain target exercise, and when it is judged that the number of the multiple student users exceeds the specified number, use the multiple student users to answer the target exercise Based on the answer data of the target exercise, the error rate of the target exercise is counted; when it is judged that the error rate exceeds the preset threshold, the label of the target exercise can be modified in the exercise library, so that the modified label of the target exercise uses Because the target exercises are defined as error-prone questions. Obviously, implementing the embodiment of the present invention, the definition of error-prone questions no longer depends on the teacher's personal subjective experience, but after judging and counting the answer data (that is, big data) collected by multiple student users to the target exercises. Error-prone questions can be defined objectively; in addition, the definition of error-prone questions does not need to be defined manually by teachers, so that dynamic and flexible management of error-prone questions can be realized.
附图说明Description of drawings
为了更清楚地说明本发明实施例中的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings that need to be used in the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For Those of ordinary skill in the art can also obtain other drawings based on these drawings without making creative efforts.
图1是本发明实施例公开的一种基于大数据的易错题库构建管理方法的流程示意图；Fig. 1 is a schematic flow diagram of a large data-based error-prone question bank construction management method disclosed in an embodiment of the present invention;
图2是本发明实施例公开的另一种基于大数据的易错题库构建管理方法的流程示意图；Fig. 2 is a schematic flow diagram of another big data-based error-prone question bank construction management method disclosed in the embodiment of the present invention;
图3是本发明实施例公开的另一种基于大数据的易错题库构建管理方法的流程示意图；FIG. 3 is a schematic flow diagram of another big data-based error-prone question bank construction management method disclosed in the embodiment of the present invention;
图4是本发明实施例公开的另一种基于大数据的易错题库构建管理方法的流程示意图；FIG. 4 is a schematic flow diagram of another method for building and managing error-prone question banks based on big data disclosed in the embodiment of the present invention;
图5是本发明实施例公开的一种基于大数据的易错题库构建管理装置的结构示意图；5 is a schematic structural diagram of a large data-based error-prone question bank construction management device disclosed in an embodiment of the present invention;
图6是本发明实施例公开的另一种基于大数据的易错题库构建管理装置的结构示意图；6 is a schematic structural diagram of another big data-based error-prone question bank construction management device disclosed in the embodiment of the present invention;
图7是本发明实施例公开的另一种基于大数据的易错题库构建管理装置的结构示意图；7 is a schematic structural diagram of another big data-based error-prone question bank construction management device disclosed in the embodiment of the present invention;
图8是本发明实施例公开的另一种基于大数据的易错题库构建管理装置的结构示意图。Fig. 8 is a schematic structural diagram of another big data-based error-prone question bank construction management device disclosed in the embodiment of the present invention.
具体实施方式detailed description
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
本发明实施例公开了一种基于大数据的易错题库构建管理方法及设备，能够客观地定义出易错题，而且易错题可以实现动态、灵活管理。以下进行结合附图进行详细描述。The embodiment of the present invention discloses a big data-based error-prone question bank construction management method and equipment, which can objectively define error-prone questions, and the error-prone questions can realize dynamic and flexible management. A detailed description will be given below in conjunction with the accompanying drawings.
实施例一Embodiment one
请参阅图1，图1是本发明实施例公开的一种基于大数据的易错题库构建管理方法的流程示意图。如图1所示，该基于大数据的易错题库构建管理方法可以包括以下步骤：Please refer to FIG. 1 . FIG. 1 is a schematic flowchart of a method for building and managing error-prone question banks based on big data disclosed in an embodiment of the present invention. As shown in Figure 1, the error-prone question bank construction and management method based on big data may include the following steps:
101、收集多个学生用户对某一目标习题进行作答的答案数据。101. Collect answer data of multiple student users answering a certain target exercise.
本发明实施例中，可以由服务设备来收集多个学生用户对某一目标习题进行作答的答案数据。其中，服务设备可以是服务器、服务平台、服务主机或者云端平台等能够进行大数据处理的设备，本发明实施例不作限定。In the embodiment of the present invention, the service device may collect the answer data of multiple student users answering a certain target exercise. Wherein, the service device may be a server, a service platform, a service host, or a cloud platform, and other devices capable of processing big data, which is not limited in this embodiment of the present invention.
在一种优选的场景中，服务设备也可以布设在学校内部，进一步地服务设备可以无线网络(如WIFI)与学校内部的各个学生用户的终端设备(如学习平板、学习手机)、教学教师的终端设备(如教学平板、教学电脑)建立数据通讯连接，在此基础上，服务设备可以收集多个学生用户通过各自的终端设备上报的多个学生用户对某一目标习题进行作答的答案数据。其中，该目标习题可以由服务设备事先推荐给该多个学生用户的终端设备。In a preferred scenario, the service device can also be deployed inside the school, and further the service device can communicate with the terminal devices of each student user (such as a learning tablet, a learning mobile phone) and a teaching teacher's computer through a wireless network (such as WIFI) in the school. Terminal equipment (such as teaching tablet, teaching computer) establishes a data communication connection. On this basis, the service equipment can collect multiple student users' answer data for a certain target exercise reported by multiple student users through their respective terminal equipment. Wherein, the target exercise may be recommended by the service device to the terminal devices of the plurality of student users in advance.
需要说明的是，在后续实施例中涉及到的服务设备与目标学生用户的交互均是指服务设备与目标学生用户的终端设备之间的交互，而服务设备与目标教学教师的交互均是指服务设备与目标教学教师的终端设备之间的交互，本发明实施例后续不再复述。It should be noted that the interaction between the service device and the target student user in the subsequent embodiments refers to the interaction between the service device and the terminal device of the target student user, and the interaction between the service device and the target teaching teacher refers to the interaction between the service device and the target student user. The interaction between the service device and the terminal device of the target teaching teacher will not be repeated in the embodiment of the present invention.
102、判断该多个学生用户的数量是否超过指定人数，如果超过，执行步骤103；反之，如果未超过，结束本流程。102. Determine whether the number of the plurality of student users exceeds the specified number, and if so, perform step 103; otherwise, if not, end this process.
本发明实施例中，可以由服务设备来判断该多个学生用户的数量是否超过指定人数，如果超过，执行步骤103；反之，如果未超过，结束本流程。其中，指定人数的取值可以根据需要进行设置，当指定人数的取值越大时，越能准确地、客观地定义出易错题。In the embodiment of the present invention, the service device may determine whether the number of the multiple student users exceeds the specified number, and if so, execute step 103; otherwise, if not, end the process. Wherein, the value of the specified number of people can be set according to needs, and when the value of the specified number of people is larger, the error-prone questions can be defined more accurately and objectively.
103、以该多个学生用户对该目标习题进行作答的答案数据为依据，统计该目标习题的错题率。103. Based on the answer data of the multiple student users answering the target exercise, calculate the error rate of the target exercise.
举例来说，服务设备可以从该多个学生用户对该目标习题进行作答的答案数据中，统计出错误答案数据的数量，以及可以统计错误答案数据的数量与上述答案数据的总数量的比例值，作为该目标习题的错题率n。For example, the service device can count the number of wrong answer data from the answer data of the multiple student users answering the target exercise, and can count the ratio of the number of wrong answer data to the total number of the above-mentioned answer data , as the error rate n of the target exercise.
104、判断该错题率是否超过预设阈值，如果超过，执行步骤105；反之，如果未超过，结束本流程。104. Determine whether the question error rate exceeds a preset threshold, and if so, execute step 105; otherwise, if not, end this process.
举例来说，服务设备可以该错题率n超过40％(即预设阈值)，如果超过，执行步骤105；反之，如果未超过，结束本流程。For example, the service device may allow the error rate n to exceed 40% (ie, a preset threshold), and if so, perform step 105; otherwise, if not, end the process.
105、在习题库中修改该目标习题的标签，以使修改后的该目标习题的标签用于定义该目标习题为易错题。105. Modify the label of the target exercise in the exercise library, so that the modified label of the target exercise is used to define the target exercise as an error-prone question.
作为一种可选的实施方式，服务设备在执行步骤105之后，服务设备可以在习题库中给该目标习题绑定错题率属性，该错题率属性包含该错题率n。As an optional implementation manner, after the service device executes step 105, the service device may bind an error rate attribute to the target exercise in the exercise library, and the error rate attribute includes the error rate n.
作为一种可选的实施方式，服务设备在执行步骤104判断该错题率超过预设阈值之后，以及在执行步骤105之前，服务设备可以先识别出该目标习题的标签是否已用于定义该目标习题为易错题，如果否，服务设备再执行步骤105。As an optional implementation, after the service device performs step 104 to judge that the error rate exceeds the preset threshold, and before performing step 105, the service device can first identify whether the label of the target exercise has been used to define the The target exercise is an error-prone question, if not, the service device performs step 105 again.
作为一种可选的实施方式，服务设备在执行步骤104判断该错题率未超过预设阈值之后，服务设备也可以进一步识别出该目标习题的标签是否已用于定义该目标习题为易错题，如果是，服务设备可以在习题库中修改该目标习题的标签，以使修改后的该目标习题的标签用于定义该目标习题为非易错题，从而可以使得定义的易错题可以随着学生能力的变化而变化，实现对易错题的动态、灵活管理。As an optional implementation, after the service device executes step 104 to judge that the error rate does not exceed the preset threshold, the service device can further identify whether the label of the target exercise has been used to define the target exercise as error-prone If yes, the service device can modify the label of the target exercise in the exercise library, so that the modified label of the target exercise is used to define the target exercise as a non-error-prone question, so that the defined error-prone question can be It changes with the change of students' abilities, and realizes dynamic and flexible management of error-prone questions.
其中，实施图1所描述的方法，易错题的定义不再取决于教师的个人主观经验，而是根据收集的多个学生用户对目标习题进行作答的答案数据(即大数据)进行判断和统计后定义出来的，从而可以客观地定义出易错题；此外，易错题的定义无需教师以人工方式来定义，从而可以实现易错题的动态、灵活管理。Among them, implementing the method described in Figure 1, the definition of error-prone questions no longer depends on the teacher's personal subjective experience, but based on the collected answer data (that is, big data) of multiple student users answering the target exercises. The error-prone questions can be defined objectively after statistics. In addition, the definition of error-prone questions does not need to be defined manually by teachers, so that the dynamic and flexible management of error-prone questions can be realized.
实施例二Embodiment two
请参阅图2，图2是本发明实施例公开的另一种基于大数据的易错题库构建管理方法的流程示意图。如图2所示，该基于大数据的易错题库构建管理方法可以包括以下步骤：Please refer to FIG. 2 . FIG. 2 is a schematic flowchart of another method for building and managing error-prone question banks based on big data disclosed in an embodiment of the present invention. As shown in Figure 2, the error-prone question bank construction management method based on big data may include the following steps:
201、服务设备收集多个学生用户对某一目标习题进行作答的答案数据。201. The service device collects answer data of multiple student users answering a certain target exercise.
202、服务设备判断该多个学生用户的数量是否超过指定人数，如果超过，执行步骤203；反之，如果未超过，结束本流程。202. The service device judges whether the number of the plurality of student users exceeds a specified number, and if so, executes step 203; otherwise, if not, ends this process.
203、服务设备以该多个学生用户对该目标习题进行作答的答案数据为依据，统计该目标习题的错题率。203. The service device calculates the error rate of the target exercise based on the answer data of the multiple student users answering the target exercise.
204、服务设备判断该错题率是否超过预设阈值，如果超过，执行步骤205～209；反之，如果未超过，结束本流程。204. The service device judges whether the question error rate exceeds a preset threshold, and if so, execute steps 205-209; otherwise, if not, end this process.
作为一种可选的实施方式，服务设备在执行步骤204判断该错题率未超过预设阈值之后，服务设备也可以进一步识别出该目标习题的标签是否已用于定义该目标习题为易错题，如果是，服务设备可以在习题库中修改该目标习题的标签，以使修改后的该目标习题的标签用于定义该目标习题为非易错题，并且服务设备可以在习题库中解除该目标习题绑定的错题率属性。从而可以使得定义的易错题可以随着学生能力的变化而变化，实现对易错题的动态、灵活管理。As an optional implementation, after the service device executes step 204 to judge that the error rate does not exceed the preset threshold, the service device can further identify whether the label of the target exercise has been used to define the target exercise as error-prone If yes, the service device can modify the label of the target exercise in the exercise bank, so that the modified label of the target exercise is used to define the target exercise as a non-error-prone question, and the service device can release the label in the exercise bank. The error rate attribute bound to the target exercise. Therefore, the defined error-prone questions can be changed with the change of students' abilities, and the dynamic and flexible management of error-prone questions can be realized.
205、服务设备在习题库中修改该目标习题的标签，以使修改后的该目标习题的标签用于定义该目标习题为易错题。205. The service device modifies the label of the target exercise in the exercise library, so that the modified label of the target exercise is used to define the target exercise as an error-prone question.
作为一种可选的实施方式，服务设备在执行步骤205之后，服务设备可以在习题库中给该目标习题绑定错题率属性，该错题率属性包含该错题率n。As an optional implementation manner, after the service device executes step 205, the service device may bind an error rate attribute to the target exercise in the exercise library, and the error rate attribute includes the error rate n.
206、服务设备从习题库中获取该目标习题对应的教师评析信息，该教师评析信息包括该目标习题的知识点和习题类型。206. The service device acquires the teacher's evaluation information corresponding to the target exercise from the exercise library, and the teacher's evaluation information includes the knowledge points and exercise types of the target exercise.
举例来说，该目标习题的知识点可以是对数，该目标习题的习题类型可以是选择题。For example, the knowledge point of the target exercise may be logarithm, and the exercise type of the target exercise may be multiple choice.
207、服务设备从该多个学生用户对该目标习题进行作答的答案数据中，确定出错误答案数据，并且从该多个学生用户中确定出作答了错误答案数据的学生用户作为目标学生用户，以形成目标学生用户群。207. The service device determines the wrong answer data from the answer data of the multiple student users answering the target exercise, and determines the student user who has answered the wrong answer data from the multiple student users as the target student user, To form the target student user group.
208、服务设备从习题库中查询与该目标习题的知识点和习题类型同时匹配的除该目标习题之外的其余习题作为待推荐习题，以形成待推荐习题集。208. The service device searches the exercise library for other exercises other than the target exercise that match both the knowledge points and the exercise types of the target exercise as exercises to be recommended, so as to form an exercise set to be recommended.
209、服务设备从待推荐习题集中选取至少一道待推荐习题，并向目标学生用户群包含的目标学生用户推荐上述至少一道待推荐习题。209. The service device selects at least one exercise to be recommended from the exercise set to be recommended, and recommends the at least one exercise to be recommended to the target student users included in the target student user group.
其中，实施上述步骤206～步骤209可以向作答了错误答案数据的目标学生用户推荐该目标习题的知识点和习题类型同时匹配的除该目标习题之外的其余习题，从而使得作答了错误答案数据的目标学生用户可以进行针对性的作答练习，提高学习效率。Among them, the implementation of the above steps 206 to 209 can recommend to the target student user who answered the wrong answer data other exercises except the target exercise that the knowledge points and exercise types of the target exercise match at the same time, so that the wrong answer data is answered Target student users can conduct targeted answering exercises to improve learning efficiency.
其中，实施图2所描述的方法，易错题的定义不再取决于教师的个人主观经验，而是根据收集的多个学生用户对目标习题进行作答的答案数据(即大数据)进行判断和统计后定义出来的，从而可以客观地定义出易错题；此外，易错题的定义无需教师以人工方式来定义，从而可以实现易错题的动态、灵活管理。Among them, implementing the method described in Figure 2, the definition of error-prone questions no longer depends on the teacher's personal subjective experience, but based on the collected answer data (that is, big data) of multiple student users answering the target exercises. The error-prone questions can be defined objectively after statistics. In addition, the definition of error-prone questions does not need to be defined manually by teachers, so that the dynamic and flexible management of error-prone questions can be realized.
实施例三Embodiment Three
请参阅图3，图3是本发明实施例公开的另一种基于大数据的易错题库构建管理方法的流程示意图。如图3所示，该基于大数据的易错题库构建管理方法可以包括以下步骤：Please refer to FIG. 3 . FIG. 3 is a schematic flowchart of another big data-based error-prone question bank construction and management method disclosed in the embodiment of the present invention. As shown in Figure 3, the error-prone question bank construction management method based on big data may include the following steps:
301、服务设备收集多个学生用户对某一目标习题进行作答的答案数据。301. The service device collects answer data of multiple student users answering a certain target exercise.
302、服务设备判断该多个学生用户的数量是否超过指定人数，如果超过，执行步骤303；反之，如果未超过，结束本流程。302. The service device judges whether the number of the plurality of student users exceeds a specified number, and if so, executes step 303; otherwise, if not, ends this process.
303、服务设备以该多个学生用户对该目标习题进行作答的答案数据为依据，统计该目标习题的错题率。303. The service device calculates the error rate of the target exercise based on the answer data of the multiple student users answering the target exercise.
304、服务设备判断该错题率是否超过预设阈值，如果超过，执行步骤305～313；反之，如果未超过，结束本流程。304. The service device judges whether the question error rate exceeds a preset threshold, and if so, execute steps 305-313; otherwise, if not, end this process.
作为一种可选的实施方式，服务设备在执行步骤304判断该错题率未超过预设阈值之后，服务设备也可以进一步识别出该目标习题的标签是否已用于定义该目标习题为易错题，如果是，服务设备可以在习题库中修改该目标习题的标签，以使修改后的该目标习题的标签用于定义该目标习题为非易错题，并且服务设备可以在习题库中解除该目标习题绑定的错题率属性。从而可以使得定义的易错题可以随着学生能力的变化而变化，实现对易错题的动态、灵活管理。As an optional implementation, after the service device executes step 304 to judge that the error rate does not exceed the preset threshold, the service device can further identify whether the label of the target exercise has been used to define the target exercise as error-prone If yes, the service device can modify the label of the target exercise in the exercise bank, so that the modified label of the target exercise is used to define the target exercise as a non-error-prone question, and the service device can release the label in the exercise bank. The error rate attribute bound to the target exercise. Therefore, the defined error-prone questions can be changed with the change of students' abilities, and the dynamic and flexible management of error-prone questions can be realized.
305、服务设备在习题库中修改该目标习题的标签，以使修改后的该目标习题的标签用于定义该目标习题为易错题。305. The service device modifies the label of the target exercise in the exercise library, so that the modified label of the target exercise is used to define the target exercise as an error-prone question.
作为一种可选的实施方式，服务设备在执行步骤304判断该错题率超过预设阈值之后，以及在执行步骤305之前，服务设备可以先识别出该目标习题的标签是否已用于定义该目标习题为易错题，如果否，服务设备再执行步骤305。As an optional implementation, after the service device performs step 304 to judge that the error rate exceeds the preset threshold, and before performing step 305, the service device can first identify whether the label of the target exercise has been used to define the The target exercise is an error-prone question, if not, the service device executes step 305 again.
作为一种可选的实施方式，服务设备在执行步骤305之后，服务设备可以在习题库中给该目标习题绑定错题率属性，该错题率属性包含该错题率n。As an optional implementation manner, after the service device executes step 305, the service device may bind an error rate attribute to the target exercise in the exercise library, and the error rate attribute includes the error rate n.
306、服务设备从习题库中获取该目标习题对应的教师评析信息，该教师评析信息包括该目标习题的知识点和习题类型。306. The service device obtains the teacher's evaluation information corresponding to the target exercise from the exercise library, and the teacher's evaluation information includes knowledge points and exercise types of the target exercise.
举例来说，该目标习题的知识点可以是正负数，该目标习题的习题类型可以是选择题。For example, the knowledge points of the target exercise can be positive and negative numbers, and the exercise type of the target exercise can be multiple choice questions.
307、服务设备从该多个学生用户对该目标习题进行作答的答案数据中，确定出错误答案数据，并且从该多个学生用户中确定出作答了错误答案数据的学生用户作为目标学生用户，以形成目标学生用户群。307. The service device determines the wrong answer data from the answer data of the multiple student users answering the target exercise, and determines the student user who has answered the wrong answer data from the multiple student users as the target student user, To form the target student user group.
308、服务设备从习题库中查询与该目标习题的知识点和习题类型同时匹配的除该目标习题之外的其余习题作为待推荐习题，以形成待推荐习题集。308. The service device searches the exercise library for other exercises other than the target exercise that match both the knowledge points and the exercise types of the target exercise as exercises to be recommended, so as to form an exercise set to be recommended.
309、服务设备从待推荐习题集中选取至少一道待推荐习题，并向目标学生用户群包含的目标学生用户推荐上述至少一道待推荐习题。309. The service device selects at least one exercise to be recommended from the exercise set to be recommended, and recommends the at least one exercise to be recommended to the target student users included in the target student user group.
其中，实施上述步骤306～步骤309可以向作答了错误答案数据的目标学生用户推荐该目标习题的知识点和习题类型同时匹配的除该目标习题之外的其余习题，从而使得作答了错误答案数据的目标学生用户可以进行针对性的作答练习，提高学习效率。Among them, the implementation of the above steps 306 to 309 can recommend to the target student user who has answered the wrong answer data other exercises except the target exercise that match the knowledge points and exercise types of the target exercise at the same time, so that the wrong answer data can be answered Target student users can conduct targeted answering exercises to improve learning efficiency.
310、服务设备获取该目标学生用户群中的每一个目标学生用户的用户属性，该用户属性包括该目标学生用户对应的班级标识。310. The service device obtains the user attribute of each target student user in the target student user group, where the user attribute includes a class identifier corresponding to the target student user.
可选的该用户属性还可以包括该目标学生用户对应的性别、年纪等信息。Optionally, the user attribute may also include information such as gender and age corresponding to the target student user.
311、服务设备以目标学生用户群中的每一个目标学生用户对应的班级标识为依据，将目标学生用户群中的目标学生用户按照班级进行分组，获得若干个目标学生用户组；其中，位于同一个目标学生用户组内的目标学生用户对应的班级标识相同。311. Based on the class identification corresponding to each target student user in the target student user group, the service device groups the target student users in the target student user group according to class, and obtains several target student user groups; The class identifiers corresponding to the target student users in a target student user group are the same.
312、服务设备针对每一个目标学生用户组，以该目标学生用户组内的目标学生用户对应的班级标识为依据，从预设的班级标识与教学教师的对应关系中确定出该目标学生用户组对应的目标教学教师；其中，该目标习题属于该目标教学教师负责的教学科目的一道习题。312. For each target student user group, the service device determines the target student user group from the preset correspondence between class IDs and teaching teachers based on the class IDs corresponding to the target student users in the target student user group The corresponding target teaching teacher; wherein, the target exercise belongs to an exercise of the teaching subject that the target teaching teacher is responsible for.
举例来说，该目标教学教师负责的教学科目为数学时，该目标习题属于该目标教学教师负责的数学的一道习题。For example, when the teaching subject that the target teaching teacher is responsible for is mathematics, the target exercise belongs to a mathematics exercise that the target teaching teacher is responsible for.
313、服务设备向每一个目标学生用户组对应的目标教学教师推荐该目标习题。313. The service device recommends the target exercise to the target teaching teacher corresponding to each target student user group.
本发明实施例中，任意两个目标学生用户组对应的目标教学教师可以不同，从而使得服务设备可以并列地向若干个目标学生用户组对应的目标教学教师推荐该目标习题，使得若干个目标学生用户组对应的目标教学教师可以以该目标习题为参考，并列地对各自负责的班级进行针对性的辅导教学，从而可以并行提高各个班级的学生用户的学习效率，降低各个班级的学生用户的学习成绩的差距。In the embodiment of the present invention, the target teaching teachers corresponding to any two target student user groups can be different, so that the service device can recommend the target exercises to the target teaching teachers corresponding to several target student user groups in parallel, so that several target students The target teaching teachers corresponding to the user group can use the target exercises as a reference to carry out targeted tutoring and teaching for the classes they are responsible for side by side, so that the learning efficiency of the student users in each class can be improved in parallel, and the learning efficiency of the student users in each class can be reduced. achievement gap.
其中，实施图3所描述的方法，易错题的定义不再取决于教师的个人主观经验，而是根据收集的多个学生用户对目标习题进行作答的答案数据(即大数据)进行判断和统计后定义出来的，从而可以客观地定义出易错题；此外，易错题的定义无需教师以人工方式来定义，从而可以实现易错题的动态、灵活管理。Among them, implementing the method described in Figure 3, the definition of error-prone questions no longer depends on the teacher's personal subjective experience, but based on the collected answer data (that is, big data) of multiple student users answering the target exercises. The error-prone questions can be defined objectively after statistics. In addition, the definition of error-prone questions does not need to be defined manually by teachers, so that the dynamic and flexible management of error-prone questions can be realized.
实施例四Embodiment Four
请参阅图4，图4是本发明实施例公开的另一种基于大数据的易错题库构建管理方法的流程示意图。如图4所示，该基于大数据的易错题库构建管理方法可以包括以下步骤：Please refer to FIG. 4 . FIG. 4 is a schematic flowchart of another big data-based error-prone question bank construction and management method disclosed in the embodiment of the present invention. As shown in Figure 4, the error-prone question bank construction management method based on big data may include the following steps:
401、服务设备收集多个学生用户对某一目标习题进行作答的答案数据。401. The service device collects answer data of multiple student users answering a certain target exercise.
402、服务设备判断该多个学生用户的数量是否超过指定人数，如果超过，执行步骤403；反之，如果未超过，结束本流程。402. The service device judges whether the number of the plurality of student users exceeds a specified number, and if so, executes step 403; otherwise, if not, ends this process.
403、服务设备以该多个学生用户对该目标习题进行作答的答案数据为依据，统计该目标习题的错题率。403. The service device calculates the error rate of the target exercise based on the answer data of the multiple student users answering the target exercise.
404、服务设备判断该错题率是否超过预设阈值，如果超过，执行步骤405～410；反之，如果未超过，结束本流程。404. The service device judges whether the question error rate exceeds a preset threshold, and if so, execute steps 405-410; otherwise, if not, end this process.
作为一种可选的实施方式，服务设备在执行步骤404判断该错题率未超过预设阈值之后，服务设备也可以进一步识别出该目标习题的标签是否已用于定义该目标习题为易错题，如果是，服务设备可以在习题库中修改该目标习题的标签，以使修改后的该目标习题的标签用于定义该目标习题为非易错题，并且服务设备可以在习题库中解除该目标习题绑定的错题率属性。从而可以使得定义的易错题可以随着学生能力的变化而变化，实现对易错题的动态、灵活管理。As an optional implementation, after the service device executes step 404 to judge that the error rate does not exceed the preset threshold, the service device can further identify whether the label of the target exercise has been used to define the target exercise as error-prone If yes, the service device can modify the label of the target exercise in the exercise bank, so that the modified label of the target exercise is used to define the target exercise as a non-error-prone question, and the service device can release the label in the exercise bank. The error rate attribute bound to the target exercise. In this way, the defined error-prone questions can be changed with the change of students' abilities, and the dynamic and flexible management of error-prone questions can be realized.
405、服务设备在习题库中修改该目标习题的标签，以使修改后的该目标习题的标签用于定义该目标习题为易错题。405. The service device modifies the label of the target exercise in the exercise library, so that the modified label of the target exercise is used to define the target exercise as an error-prone question.
作为一种可选的实施方式，服务设备在执行步骤404判断该错题率超过预设阈值之后，以及在执行步骤405之前，服务设备可以先识别出该目标习题的标签是否已用于定义该目标习题为易错题，如果否，服务设备再执行步骤405。As an optional implementation, after the service device performs step 404 to judge that the error rate exceeds the preset threshold, and before performing step 405, the service device may first identify whether the label of the target exercise has been used to define the The target exercise is an error-prone question, if not, the service device performs step 405 again.
作为一种可选的实施方式，服务设备在执行步骤405之后，服务设备可以在习题库中给该目标习题绑定错题率属性，该错题率属性包含该错题率n。As an optional implementation manner, after the service device executes step 405, the service device may bind an error rate attribute to the target exercise in the exercise library, and the error rate attribute includes the error rate n.
406、服务设备从该多个学生用户对该目标习题进行作答的答案数据中，确定出错误答案数据，并且从该多个学生用户中确定出作答了错误答案数据的学生用户作为目标学生用户，以形成目标学生用户群。406. The service device determines the wrong answer data from the answer data of the multiple student users answering the target exercise, and determines the student user who has answered the wrong answer data from the multiple student users as the target student user, To form the target student user group.
407、服务设备获取该目标学生用户群中的每一个目标学生用户的用户属性，该用户属性包括该目标学生用户对应的班级标识。407. The service device obtains the user attribute of each target student user in the target student user group, where the user attribute includes a class identifier corresponding to the target student user.
408、服务设备以目标学生用户群中的每一个目标学生用户对应的班级标识为依据，将目标学生用户群中的目标学生用户按照班级进行分组，获得若干个目标学生用户组；其中，位于同一个目标学生用户组内的目标学生用户对应的班级标识相同。408. Based on the class identification corresponding to each target student user in the target student user group, the service device groups the target student users in the target student user group according to class, and obtains several target student user groups; The class identifiers corresponding to the target student users in a target student user group are the same.
409、服务设备针对每一个目标学生用户组，以该目标学生用户组内的目标学生用户对应的班级标识为依据，从预设的班级标识与教学教师的对应关系中确定出该目标学生用户组对应的目标教学教师；其中，该目标习题属于该目标教学教师负责的教学科目的一道习题。409. For each target student user group, the service device determines the target student user group from the preset correspondence between class IDs and teaching teachers based on the class identifiers corresponding to the target student users in the target student user group The corresponding target teaching teacher; wherein, the target exercise belongs to an exercise of the teaching subject that the target teaching teacher is responsible for.
410、服务设备向每一个目标学生用户组对应的目标教学教师推荐该目标习题。410. The service device recommends the target exercise to the target teaching teacher corresponding to each target student user group.
本发明实施例中，任意两个目标学生用户组对应的目标教学教师可以不同，从而使得服务设备可以并列地向若干个目标学生用户组对应的目标教学教师推荐该目标习题，使得若干个目标学生用户组对应的目标教学教师可以以该目标习题为参考，并列地对各自负责的班级进行针对性的辅导教学，从而可以并行提高各个班级的学生用户的学习效率，降低各个班级的学生用户的学习成绩的差距。In the embodiment of the present invention, the target teaching teachers corresponding to any two target student user groups can be different, so that the service device can recommend the target exercises to the target teaching teachers corresponding to several target student user groups in parallel, so that several target students The target teaching teachers corresponding to the user group can use the target exercises as a reference to carry out targeted tutoring and teaching for the classes they are responsible for side by side, so that the learning efficiency of the student users in each class can be improved in parallel, and the learning efficiency of the student users in each class can be reduced. achievement gap.
其中，实施图4所描述的方法，易错题的定义不再取决于教师的个人主观经验，而是根据收集的多个学生用户对目标习题进行作答的答案数据(即大数据)进行判断和统计后定义出来的，从而可以客观地定义出易错题；此外，易错题的定义无需教师以人工方式来定义，从而可以实现易错题的动态、灵活管理。Among them, implementing the method described in Figure 4, the definition of error-prone questions no longer depends on the teacher's personal subjective experience, but based on the collected answer data (that is, big data) of multiple student users answering the target exercises to make judgments and conclusions. The error-prone questions can be defined objectively after statistics. In addition, the definition of error-prone questions does not need to be defined manually by teachers, so that the dynamic and flexible management of error-prone questions can be realized.
实施例五Embodiment five
请参阅图5，图5是本发明实施例公开的一种基于大数据的易错题库构建管理设备的结构示意图。其中，图5所示的基于大数据的易错题库构建管理设备可以用于执行上述服务设备的功能。如图5所示，该基于大数据的易错题库构建管理设备可以包括：Please refer to FIG. 5 . FIG. 5 is a schematic structural diagram of an error-prone question bank construction management device based on big data disclosed in an embodiment of the present invention. Wherein, the error-prone question bank construction management device based on big data shown in FIG. 5 can be used to perform the functions of the above-mentioned service device. As shown in Figure 5, the error-prone question bank construction management equipment based on big data may include:
收集单元501，用于收集多个学生用户对某一目标习题进行作答的答案数据；A collection unit 501, configured to collect answer data of multiple student users answering a certain target exercise;
第一判断单元502，用于判断该多个学生用户的数量是否超过指定人数；The first judging unit 502 is configured to judge whether the number of the plurality of student users exceeds a specified number;
统计单元503，用于在第一判断单元503的判断结果为超过时，以该多个学生用户对该目标习题进行作答的答案数据为依据，统计该目标习题的错题率；The statistical unit 503 is used to count the error rate of the target exercise based on the answer data of the plurality of student users answering the target exercise when the judgment result of the first judgment unit 503 is exceeded;
第二判断单元504，用于判断该错题率是否超过预设阈值；The second judging unit 504 is used to judge whether the wrong question rate exceeds a preset threshold;
处理单元505，用于在第二判断单元504的判断结果为超过时，在习题库中修改该目标习题的标签，以使修改后的该目标习题的标签用于定义该目标习题为易错题。The processing unit 505 is configured to modify the label of the target exercise in the exercise library when the judgment result of the second judgment unit 504 is exceeded, so that the modified label of the target exercise is used to define the target exercise as an error-prone question .
本发明实施例中，统计单元503以该多个学生用户对该目标习题进行作答的答案数据为依据，统计该目标习题的错题率的方式可以为：In the embodiment of the present invention, the statistics unit 503 uses the answer data of the multiple student users to answer the target exercise as a basis, and the method of counting the error rate of the target exercise may be:
统计单元503从该多个学生用户对该目标习题进行作答的答案数据中，统计出错误答案数据的数量，以及统计该错误答案数据的数量占该答案数据的总数量的比例值，作为该目标习题的错题率。The statistical unit 503 counts the number of wrong answer data from the answer data of the plurality of student users answering the target exercise, and counts the ratio of the number of wrong answer data to the total number of answer data, as the target The error rate of exercises.
作为一种可选的实施方式，处理单元505在习题库中修改该目标习题的标签，以使修改后的该目标习题的标签用于定义该目标习题为易错题之后，可以在习题库中给该目标习题绑定错题率属性，该错题率属性包含该错题率n。As an optional implementation, the processing unit 505 modifies the label of the target exercise in the exercise bank, so that after the modified label of the target exercise is used to define the target exercise as an error-prone question, it can Bind the wrong question rate attribute to the target exercise, and the wrong question rate attribute includes the wrong question rate n.
作为一种可选的实施方式，处理单元505在第二判断单元504的判断结果为超过时，可以先识别出该目标习题的标签是否已用于定义该目标习题为易错题，如果否，才在习题库中修改该目标习题的标签，以使修改后的该目标习题的标签用于定义该目标习题为易错题。As an optional implementation manner, when the judgment result of the second judging unit 504 is exceeded, the processing unit 505 can first identify whether the label of the target exercise has been used to define the target exercise as an error-prone question, if not, Then the label of the target exercise is modified in the exercise bank, so that the modified label of the target exercise is used to define the target exercise as error-prone.
作为一种可选的实施方式，处理单元505在第二判断单元504的判断结果为未超过时，也可以进一步识别出该目标习题的标签是否已用于定义该目标习题为易错题，如果是，可以在习题库中修改该目标习题的标签，以使修改后的该目标习题的标签用于定义该目标习题为非易错题，从而可以使得定义的易错题可以随着学生能力的变化而变化，实现对易错题的动态、灵活管理。As an optional implementation manner, when the judgment result of the second judging unit 504 is not exceeded, the processing unit 505 may further identify whether the label of the target exercise has been used to define the target exercise as an error-prone question, if Yes, the label of the target exercise can be modified in the exercise bank, so that the modified label of the target exercise can be used to define the target exercise as a non-error-prone question, so that the defined error-prone question can be adjusted as the student's ability improves. Changes and changes to achieve dynamic and flexible management of error-prone questions.
其中，实施图5所描述的基于大数据的易错题库构建管理设备，易错题的定义不再取决于教师的个人主观经验，而是根据收集的多个学生用户对目标习题进行作答的答案数据(即大数据)进行判断和统计后定义出来的，从而可以客观地定义出易错题；此外，易错题的定义无需教师以人工方式来定义，从而可以实现易错题的动态、灵活管理。Among them, implementing the big data-based error-prone question library construction management equipment described in Figure 5, the definition of error-prone questions no longer depends on the teacher's personal subjective experience, but based on the answers collected by multiple student users to the target exercises Data (that is, big data) is defined after judgment and statistics, so that error-prone questions can be defined objectively; in addition, the definition of error-prone questions does not need to be defined manually by teachers, so that the dynamic and flexible error-prone questions can be realized manage.
实施例六Embodiment six
请参阅图6，图6是本发明实施例公开的另一种基于大数据的易错题库构建管理设备的结构示意图。其中，图6所示的基于大数据的易错题库构建管理设备是由图5所示的基于大数据的易错题库构建管理设备进行优化得到的。与图5所示的基于大数据的易错题库构建管理设备相比，图6所示的基于大数据的易错题库构建管理设备还可以包括：Please refer to FIG. 6 . FIG. 6 is a schematic structural diagram of another big data-based error-prone question bank construction management device disclosed in an embodiment of the present invention. Wherein, the big data-based error-prone question bank construction management device shown in FIG. 6 is obtained by optimizing the big data-based error-prone question bank construction management device shown in FIG. 5 . Compared with the big data-based error-prone question bank construction management device shown in Figure 5, the big data-based error-prone question bank construction management device shown in Figure 6 may further include:
第一获取单元506，用于在处理单元505在习题库中修改该目标习题的标签，以使修改后的该目标习题的标签用于定义该目标习题为易错题之后，从习题库中获取该目标习题对应的教师评析信息，其中，教师评析信息包括该目标习题的知识点和习题类型；The first acquisition unit 506 is configured to obtain from the exercise library after the processing unit 505 modifies the label of the target exercise in the exercise library, so that the modified label of the target exercise is used to define the target exercise as an error-prone question The teacher's evaluation information corresponding to the target exercise, where the teacher's evaluation information includes the knowledge points and exercise types of the target exercise;
第一确定单元507，用于从该多个学生用户对该目标习题进行作答的答案数据中，确定出错误答案数据，并且从该多个学生用户中确定出作答了错误答案数据的学生用户作为目标学生用户，以形成目标学生用户群；The first determining unit 507 is configured to determine the wrong answer data from the answer data of the multiple student users answering the target exercise, and determine the student user who has answered the wrong answer data from the multiple student users as target student users to form a target student user group;
查询单元508，用于从习题库中查询与该目标习题的知识点和习题类型同时匹配的除该目标习题之外的其余习题作为待推荐习题，以形成待推荐习题集；A query unit 508, configured to query from the exercise library other exercises except the target exercise that match the knowledge points and exercise types of the target exercise as exercises to be recommended, so as to form a set of exercises to be recommended;
第一推荐单元509，用于从待推荐习题集中选取至少一道待推荐习题，并向目标学生用户群包含的目标学生用户推荐上述至少一道待推荐习题。The first recommending unit 509 is configured to select at least one exercise to be recommended from the exercise set to be recommended, and recommend the at least one exercise to be recommended to the target student users included in the target student user group.
其中，本发明实施例可以向作答了错误答案数据的目标学生用户推荐该目标习题的知识点和习题类型同时匹配的除该目标习题之外的其余习题，从而使得作答了错误答案数据的目标学生用户可以进行针对性的作答练习，提高学习效率。Among them, the embodiment of the present invention can recommend to the target student user who has answered the wrong answer data other exercises except the target exercise that the knowledge points of the target exercise and the type of the exercise match at the same time, so that the target student who has answered the wrong answer data Users can conduct targeted answering exercises to improve learning efficiency.
实施例七Embodiment seven
请参阅图7，图7是本发明实施例公开的另一种基于大数据的易错题库构建管理设备的结构示意图。其中，图7所示的基于大数据的易错题库构建管理设备是由图6所示的基于大数据的易错题库构建管理设备进行优化得到的。与图6所示的基于大数据的易错题库构建管理设备相比，图7所示的基于大数据的易错题库构建管理设备还可以包括：Please refer to FIG. 7 . FIG. 7 is a schematic structural diagram of another big data-based error-prone question bank construction management device disclosed in an embodiment of the present invention. Wherein, the big data-based error-prone question bank construction management device shown in FIG. 7 is obtained by optimizing the big data-based error-prone question bank construction management device shown in FIG. 6 . Compared with the big data-based error-prone question bank construction management device shown in Figure 6, the big data-based error-prone question bank construction management device shown in Figure 7 may further include:
第二获取单元510，用于在第一推荐单元509向目标学生用户群包含的目标学生用户推荐上述至少一道待推荐习题之后，获取目标学生用户群中的每一个目标学生用户的用户属性，用户属性包括目标学生用户对应的班级标识；The second acquisition unit 510 is configured to acquire the user attributes of each target student user in the target student user group after the first recommendation unit 509 recommends the above-mentioned at least one exercise to be recommended to the target student users contained in the target student user group, the user The attribute includes the class ID corresponding to the target student user;
第一分组单元511，用于以目标学生用户群中的每一个目标学生用户对应的班级标识为依据，将目标学生用户群中的目标学生用户按照班级进行分组，获得若干个目标学生用户组；其中，位于同一个目标学生用户组内的目标学生用户对应的班级标识相同；The first grouping unit 511 is used to group the target student users in the target student user group according to class based on the class identification corresponding to each target student user in the target student user group, and obtain several target student user groups; Among them, the class identifiers corresponding to the target student users in the same target student user group are the same;
第二确定单元512，用于针对每一个目标学生用户组，以该目标学生用户组内的目标学生用户对应的班级标识为依据，从预设的班级标识与教学教师的对应关系中确定出该目标学生用户组对应的目标教学教师；其中，该目标习题属于该目标教学教师负责的教学科目的一道习题；The second determining unit 512 is configured to, for each target student user group, determine the class ID corresponding to the target student user in the target student user group from the preset correspondence between the class ID and the teaching teacher. The target teaching teacher corresponding to the target student user group; wherein, the target exercise belongs to an exercise of the teaching subject that the target teaching teacher is responsible for;
第一推荐单元509，还用于向每一个目标学生用户组对应的目标教学教师推荐所述目标习题。The first recommending unit 509 is further configured to recommend the target exercises to the target teaching teachers corresponding to each target student user group.
本发明实施例中，任意两个目标学生用户组对应的目标教学教师可以不同，从而使得服务设备可以并列地向若干个目标学生用户组对应的目标教学教师推荐该目标习题，使得若干个目标学生用户组对应的目标教学教师可以以该目标习题为参考，并列地对各自负责的班级进行针对性的辅导教学，从而可以并行提高各个班级的学生用户的学习效率，降低各个班级的学生用户的学习成绩的差距。In the embodiment of the present invention, the target teaching teachers corresponding to any two target student user groups can be different, so that the service device can recommend the target exercises to the target teaching teachers corresponding to several target student user groups in parallel, so that several target students The target teaching teachers corresponding to the user group can use the target exercises as a reference to carry out targeted tutoring and teaching for the classes they are responsible for side by side, so that the learning efficiency of the student users in each class can be improved in parallel, and the learning efficiency of the student users in each class can be reduced. achievement gap.
实施例八Embodiment eight
请参阅图8，图8是本发明实施例公开的另一种基于大数据的易错题库构建管理设备的结构示意图。其中，图8所示的基于大数据的易错题库构建管理设备是由图5所示的基于大数据的易错题库构建管理设备进行优化得到的。与图5所示的基于大数据的易错题库构建管理设备相比，图8所示的基于大数据的易错题库构建管理设备还可以包括：Please refer to FIG. 8 . FIG. 8 is a schematic structural diagram of another large data-based error-prone question bank construction management device disclosed in an embodiment of the present invention. Wherein, the big data-based error-prone question bank construction management device shown in FIG. 8 is obtained by optimizing the big data-based error-prone question bank construction management device shown in FIG. 5 . Compared with the big data-based error-prone question bank construction management device shown in Figure 5, the big data-based error-prone question bank construction management device shown in Figure 8 may further include:
第三确定单元513，用于在处理单元505在习题库中修改该目标习题的标签，以使修改后的该目标习题的标签用于定义该目标习题为易错题之后，从该多个学生用户对该目标习题进行作答的答案数据中，确定出错误答案数据，并且从该多个学生用户中确定出作答了错误答案数据的学生用户作为目标学生用户，以形成目标学生用户群；The third determining unit 513 is configured to, after the processing unit 505 modifies the label of the target exercise in the exercise library, so that the modified label of the target exercise is used to define the target exercise as an error-prone question, from the plurality of students Determining wrong answer data from the answer data of the user's answer to the target exercise, and determining the student user who answered the wrong answer data from the plurality of student users as the target student user, so as to form a target student user group;
第三获取单元514，用于获取目标学生用户群中的每一个目标学生用户的用户属性，用户属性包括该目标学生用户对应的班级标识；The third acquiring unit 514 is configured to acquire the user attributes of each target student user in the target student user group, where the user attributes include the class identifier corresponding to the target student user;
第二分组单元515，用于以目标学生用户群中的每一个目标学生用户对应的班级标识为依据，将目标学生用户群中的目标学生用户按照班级进行分组，获得若干个目标学生用户组；其中，位于同一个目标学生用户组内的目标学生用户对应的班级标识相同；The second grouping unit 515 is used to group the target student users in the target student user group according to class based on the class identification corresponding to each target student user in the target student user group, and obtain several target student user groups; Among them, the class identifiers corresponding to the target student users in the same target student user group are the same;
第四确定单元516，用于针对每一个目标学生用户组，以该目标学生用户组内的目标学生用户对应的班级标识为依据，从预设的班级标识与教学教师的对应关系中确定出该目标学生用户组对应的目标教学教师；其中，该目标习题属于该目标教学教师负责的教学科目的一道习题；The fourth determining unit 516 is configured to, for each target student user group, determine the class ID corresponding to the target student user in the target student user group from the preset corresponding relationship between the class ID and the teaching teacher. The target teaching teacher corresponding to the target student user group; wherein, the target exercise belongs to an exercise of the teaching subject that the target teaching teacher is responsible for;
第二推荐单元517，用于向每一个目标学生用户组对应的目标教学教师推荐目标习题。The second recommending unit 517 is configured to recommend target exercises to target teaching teachers corresponding to each target student user group.
本发明实施例中，任意两个目标学生用户组对应的目标教学教师可以不同，从而使得服务设备可以并列地向若干个目标学生用户组对应的目标教学教师推荐该目标习题，使得若干个目标学生用户组对应的目标教学教师可以以该目标习题为参考，并列地对各自负责的班级进行针对性的辅导教学，从而可以并行提高各个班级的学生用户的学习效率，降低各个班级的学生用户的学习成绩的差距。In the embodiment of the present invention, the target teaching teachers corresponding to any two target student user groups can be different, so that the service device can recommend the target exercises to the target teaching teachers corresponding to several target student user groups in parallel, so that several target students The target teaching teachers corresponding to the user group can use the target exercises as a reference to carry out targeted tutoring and teaching for the classes they are responsible for side by side, so that the learning efficiency of the student users in each class can be improved in parallel, and the learning efficiency of the student users in each class can be reduced. achievement gap.
本领域普通技术人员可以理解上述实施例的各种方法中的全部或部分步骤是可以通过程序来指令相关的硬件来完成，该程序可以存储于一计算机可读存储介质中，存储介质包括只读存储器(Read-Only Memory，ROM)、随机存储器(Random Access Memory，RAM)、可编程只读存储器(Programmable Read-only Memory，PROM)、可擦除可编程只读存储器(Erasable Programmable Read Only Memory，EPROM)、一次可编程只读存储器(One-time Programmable Read-Only Memory，OTPROM)、电子抹除式可复写只读存储器(Electrically-Erasable Programmable Read-Only Memory，EEPROM)、只读光盘(CompactDisc Read-Only Memory，CD-ROM)或其他光盘存储器、磁盘存储器、磁带存储器、或者能够用于携带或存储数据的计算机可读的任何其他介质。Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above-mentioned embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium includes read-only Memory (Read-Only Memory, ROM), Random Access Memory (Random Access Memory, RAM), Programmable Read-Only Memory (Programmable Read-only Memory, PROM), Erasable Programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), One-time Programmable Read-Only Memory (OTPROM), Electronically Erasable Programmable Read-Only Memory (EEPROM), Compact Disc Read-Only Memory (CompactDisc Read -Only Memory, CD-ROM) or other optical disk storage, magnetic disk storage, tape storage, or any other computer-readable medium that can be used to carry or store data.
以上对本发明实施例公开的一种基于大数据的易错题库构建管理方法及设备进行了详细介绍，本文中应用了具体个例对本发明的原理及实施方式进行了阐述，以上实施例的说明只是用于帮助理解本发明的方法及其核心思想；同时，对于本领域的一般技术人员，依据本发明的思想，在具体实施方式及应用范围上均会有改变之处，综上所述，本说明书内容不应理解为对本发明的限制。The method and equipment for building and managing error-prone question banks based on big data disclosed in the embodiments of the present invention have been introduced in detail above. In this paper, specific examples have been used to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only It is used to help understand the method of the present invention and its core idea; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation and scope of application. In summary, this The content of the description should not be construed as limiting the present invention.
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611051877.9ACN106547909A (en) | 2016-11-23 | 2016-11-23 | Error-prone question bank construction management method and device based on big data |
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611051877.9ACN106547909A (en) | 2016-11-23 | 2016-11-23 | Error-prone question bank construction management method and device based on big data |
| Publication Number | Publication Date |
|---|---|
| CN106547909Atrue CN106547909A (en) | 2017-03-29 |
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611051877.9APendingCN106547909A (en) | 2016-11-23 | 2016-11-23 | Error-prone question bank construction management method and device based on big data |
| Country | Link |
|---|---|
| CN (1) | CN106547909A (en) |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107274738A (en)* | 2017-06-23 | 2017-10-20 | 广东外语外贸大学 | Chinese-English translation teaching points-scoring system based on mobile Internet |
| CN107633721A (en)* | 2017-08-25 | 2018-01-26 | 刘宸瑜 | A kind of error analysis method, apparatus and system for language learning |
| CN108446401A (en)* | 2018-03-29 | 2018-08-24 | 上海乂学教育科技有限公司 | Problem database system |
| CN109255019A (en)* | 2018-09-07 | 2019-01-22 | 广州爱易学智能信息科技有限公司 | A kind of online exam pool and its application method based on artificial intelligence |
| CN109635259A (en)* | 2018-11-05 | 2019-04-16 | 广东共升教育科技有限公司 | A kind of electronic test paper generation method, device, equipment and storage medium |
| CN110211007A (en)* | 2019-04-30 | 2019-09-06 | 宜春宜联科技有限公司 | Job analysis method, system, mobile terminal and storage medium |
| CN110349061A (en)* | 2019-07-15 | 2019-10-18 | 联想(北京)有限公司 | Processing method, processing unit and electronic equipment |
| CN110414837A (en)* | 2019-07-29 | 2019-11-05 | 上海乂学教育科技有限公司 | Based on mistake because of the man-machine interactive system of analysis |
| CN110599840A (en)* | 2019-08-06 | 2019-12-20 | 安徽学云教育科技有限公司 | Personalized self-adaptive online learning method based on big data |
| CN111753153A (en)* | 2019-11-25 | 2020-10-09 | 广东小天才科技有限公司 | Error information collection method, electronic device, storage medium and program product |
| CN112506855A (en)* | 2020-12-24 | 2021-03-16 | 贵州树精英教育科技有限责任公司 | Question bank construction method based on cognitive hierarchy |
| CN113688301A (en)* | 2021-08-24 | 2021-11-23 | 杨成兴 | Online accurate teaching tutoring method and system based on artificial intelligence and big data |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101477755A (en)* | 2009-01-06 | 2009-07-08 | 陈诗周 | Error problem database system for student |
| KR20110078073A (en)* | 2009-12-30 | 2011-07-07 | 동국대학교 산학협력단 | Method and device for problem selection and achievement assessment |
| CN103971553A (en)* | 2014-05-29 | 2014-08-06 | 深圳图瑞交互信息技术有限公司 | Feedback teaching system and feedback teaching method |
| CN105931513A (en)* | 2016-06-21 | 2016-09-07 | 广州伟度计算机科技有限公司 | Class test realizing system applied to teaching process and realizing method thereof |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101477755A (en)* | 2009-01-06 | 2009-07-08 | 陈诗周 | Error problem database system for student |
| KR20110078073A (en)* | 2009-12-30 | 2011-07-07 | 동국대학교 산학협력단 | Method and device for problem selection and achievement assessment |
| CN103971553A (en)* | 2014-05-29 | 2014-08-06 | 深圳图瑞交互信息技术有限公司 | Feedback teaching system and feedback teaching method |
| CN105931513A (en)* | 2016-06-21 | 2016-09-07 | 广州伟度计算机科技有限公司 | Class test realizing system applied to teaching process and realizing method thereof |
| Title |
|---|
| 赵翠娟: ""教育家成长丛书 赵翠娟与学习型学校"", 《教育家成长丛书》* |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107274738A (en)* | 2017-06-23 | 2017-10-20 | 广东外语外贸大学 | Chinese-English translation teaching points-scoring system based on mobile Internet |
| CN107633721A (en)* | 2017-08-25 | 2018-01-26 | 刘宸瑜 | A kind of error analysis method, apparatus and system for language learning |
| CN108446401B (en)* | 2018-03-29 | 2021-06-01 | 上海松鼠课堂人工智能科技有限公司 | Question bank system |
| CN108446401A (en)* | 2018-03-29 | 2018-08-24 | 上海乂学教育科技有限公司 | Problem database system |
| CN109255019A (en)* | 2018-09-07 | 2019-01-22 | 广州爱易学智能信息科技有限公司 | A kind of online exam pool and its application method based on artificial intelligence |
| CN109255019B (en)* | 2018-09-07 | 2021-06-08 | 广州爱易学智能信息科技有限公司 | On-line question bank query and application method thereof |
| CN109635259A (en)* | 2018-11-05 | 2019-04-16 | 广东共升教育科技有限公司 | A kind of electronic test paper generation method, device, equipment and storage medium |
| CN110211007A (en)* | 2019-04-30 | 2019-09-06 | 宜春宜联科技有限公司 | Job analysis method, system, mobile terminal and storage medium |
| CN110349061A (en)* | 2019-07-15 | 2019-10-18 | 联想(北京)有限公司 | Processing method, processing unit and electronic equipment |
| CN110414837A (en)* | 2019-07-29 | 2019-11-05 | 上海乂学教育科技有限公司 | Based on mistake because of the man-machine interactive system of analysis |
| CN110599840A (en)* | 2019-08-06 | 2019-12-20 | 安徽学云教育科技有限公司 | Personalized self-adaptive online learning method based on big data |
| CN111753153A (en)* | 2019-11-25 | 2020-10-09 | 广东小天才科技有限公司 | Error information collection method, electronic device, storage medium and program product |
| CN112506855A (en)* | 2020-12-24 | 2021-03-16 | 贵州树精英教育科技有限责任公司 | Question bank construction method based on cognitive hierarchy |
| CN113688301A (en)* | 2021-08-24 | 2021-11-23 | 杨成兴 | Online accurate teaching tutoring method and system based on artificial intelligence and big data |
| Publication | Publication Date | Title |
|---|---|---|
| CN106547909A (en) | Error-prone question bank construction management method and device based on big data | |
| CN106781785B (en) | A Big Data-Based Question Difficulty Construction Method, Device, and Service Equipment | |
| CN108550292B (en) | A multi-layer organization and representation method of learning resources in an online education system | |
| CN107563924A (en) | Test paper generation method, medium and electronic equipment | |
| CN106156354B (en) | A learning resource recommendation system | |
| CN106157204A (en) | A kind of Forecasting The Scores method and system based on BP neural network model | |
| KR20170100265A (en) | Method, apparatus and computer program for providing personalized educateionl contents | |
| CN106251261B (en) | Training scheme generation method and device | |
| WO2016090774A1 (en) | Online examination management method, apparatus and system | |
| CN106127634A (en) | A kind of Forecasting The Scores method and system based on model-naive Bayesian | |
| CN110097482A (en) | Study plan creation method and device, storage medium and electronic device | |
| CN107886451A (en) | Exercise individualized fit method in the Teaching System of mobile terminal | |
| CN110245207A (en) | A kind of exam pool construction method, exam pool construction device and electronic equipment | |
| CN106844384A (en) | Examination question indexing method and device | |
| CN118537176A (en) | Remote interactive education method and system | |
| KR20150116157A (en) | method of learning service in on-line and service system thereof | |
| CN108066990A (en) | The method, apparatus and server of user is selected in a kind of list from candidate user | |
| CN111444244A (en) | A big data information management system | |
| CN115050039A (en) | Automatic test paper analysis method, system, electronic device and storage medium | |
| CN114971974A (en) | Teaching processing method, device, equipment and medium | |
| CN118733955A (en) | A review content generation method, device, storage medium and electronic device | |
| KR101241273B1 (en) | Method of creating new test paper by using teat structure | |
| CN113313470A (en) | Employment type evaluation method and system based on big data | |
| CA2561698A1 (en) | Method to assess a person's knowledge of a subject area | |
| CN108764481A (en) | A kind of information security ability evaluating method and system based on mobile terminal behavior |
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | Application publication date:20170329 | |
| RJ01 | Rejection of invention patent application after publication |