WO2015192530A1 - 在线教育中课程的推荐方法及装置 - Google Patents
在线教育中课程的推荐方法及装置 Download PDFInfo
- Publication number
- WO2015192530A1 WO2015192530A1 PCT/CN2014/087615 CN2014087615W WO2015192530A1 WO 2015192530 A1 WO2015192530 A1 WO 2015192530A1 CN 2014087615 W CN2014087615 W CN 2014087615W WO 2015192530 A1 WO2015192530 A1 WO 2015192530A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- user
- course
- server
- learning
- ability
- Prior art date
Links
Images
Classifications
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B5/00—Electrically-operated educational appliances
Definitions
- the present invention relates to the field of online education, and in particular to a method and apparatus for recommending courses in online education.
- Online education also known as online education or distance education, e-Learning or online-learning
- e-Learning is a network-based teaching method. Through the network, students and teachers can carry out distance learning activities. In addition, by using online courseware, students You can also learn anywhere, anytime, breaking the limits of time and space.
- a common form of online education is that an online education provider provides a website or a client, a website and a client display a course content that can be learned, and a student browses a website or a client to find a course of interest on the website. When you find a course that is of interest to the student, the student can study the course.
- the course is usually in the form of a lecture slide, video recording, live video, and so on.
- the above-mentioned online education method requires the user to select a course independently, and cannot implement a personalized service for the student.
- courses recommended in the related art these programs are based on the courses that the students have watched, recommending similar courses to the students, most of which are based on the interests of the students. For example, if the students have watched the calculus, they recommend linear algebra to the students. Students who have spoken in English will recommend English listening to the students. This type of recommendation is too simple and it is difficult to provide personalized services for students.
- the present invention provides a method and a device for recommending a course in online education to solve at least the above problems.
- a method for recommending a course in online education including: a server acquiring capability data of a user; and the server according to the capability data of the user, according to a corresponding relationship between the preset capability and the course, The above user selects a course; the above server sends the course selected for the above user.
- the method further includes: the server acquiring a plurality of pieces of teaching data, wherein the plurality of pieces of teaching data include: a score obtained by a plurality of users who have completed the course learning, and capability data of the plurality of users; and the server is configured according to The plurality of pieces of teaching data analyze the ability of the user with high scores; the server obtains the ability of the user who has obtained the high score as the ability condition for the recommended user to learn the corresponding course, and obtains the correspondence between the above ability and the course.
- the correspondence between the above-mentioned ability and the course is determined by the ability of the user who has achieved high scores in the course of study.
- the foregoing capability data includes at least one of the following: a score obtained by the other courses that the user has learned, an educational institution that the user has attended, other courses that the user has studied, and teaching materials purchased or browsed by the user. , the user's education, the user's working time, the user's professional background.
- the server sending the course selected by the user includes: the server sending the course selected by the user to the user; or the server sending the course selected by the user to the device requesting the course selection for the user.
- the server sends the course selected by the user to the user, where the server sends the link of the course selected by the user to the user, or the description information of the course selected by the user.
- the method further includes: the server formulating a learning plan according to the relationship of the courses selected by the user, where the learning plan includes a course selected for the user and learning an arrangement of each course in the course selected by the user; the server Send the above study plan.
- the method further includes: the server acquiring the situation that the learning is the course selected by the user; and the server is adjusted to the course selected by the user according to the above situation, or is adjusted to the learning plan specified by the user.
- a device for recommending a course in online education includes: a first obtaining module configured to acquire capability data of a user; and a selection module configured to follow the capability data of the user according to the pre-preparation The corresponding relationship between the ability and the course is selected for the above-mentioned user; the sending module is set to send the course selected by the above user.
- the device further includes: a second acquiring module, configured to acquire a plurality of pieces of teaching data, wherein the plurality of pieces of teaching data include: a score obtained by a plurality of users who have completed the course learning, and the capabilities of the plurality of users Data; an analysis module, configured to analyze the performance of a user with high scores based on the above plurality of teaching data analysis
- the determination module is configured to take the ability of the user who has achieved the above-mentioned high score as the ability condition for the recommended user to learn the corresponding course, and obtain the correspondence between the above-mentioned ability and the course.
- the correspondence between the above-mentioned ability and the course is determined by the ability of the user who has achieved high scores in the course of study.
- the apparatus further includes: a formulating module configured to formulate a learning plan according to the relationship of the course selected for the user, the learning plan including a course selected for the user and learning an arrangement of each course in the course selected by the user
- the above sending module is configured to send the above learning plan.
- the device further includes: a third obtaining module, configured to acquire the case of learning the course selected by the user; the adjusting module is configured to adjust to the course selected by the user according to the foregoing situation, or adjust to the user specified Learning plan.
- a third obtaining module configured to acquire the case of learning the course selected by the user
- the adjusting module is configured to adjust to the course selected by the user according to the foregoing situation, or adjust to the user specified Learning plan.
- a course is recommended for a user according to the user's ability, and a personalized service for the user is provided.
- FIG. 1 is a flow chart of a method of recommending a course in online education according to an embodiment of the present invention
- FIG. 2 is a structural block diagram of a recommendation device for a course in online education according to an embodiment of the present invention
- FIG. 3 is a flow chart of a preferred method of recommending a course in online education in accordance with an embodiment of the present invention.
- FIG. 1 is a flow chart of a method for recommending a course in online education according to an embodiment of the present invention. As shown in FIG. 1, the method includes steps S102 to S106.
- step S102 the server acquires capability data of the user.
- Step S104 The server selects a course for the user according to the user's capability data according to the corresponding relationship between the preset ability and the course.
- step S106 the server sends the course selected for the above user.
- the course is recommended for the user according to the user's ability, and a personalized service for the user is provided.
- the user's capability data is various, as long as the ability of the user can be characterized, for example, the degree of the user, and the higher the degree of education, the stronger the learning ability is represented by a certain probability.
- the user's capability data may include at least one of the following: scores obtained by other courses that the user has learned, educational institutions that the user has attended, other courses that the user has studied, and user purchases. Or browse the teaching materials, the user's education, the user's working hours, and the user's professional background.
- the correspondence between the above capabilities and the course can be determined based on big data analysis.
- the server may further acquire a plurality of pieces of teaching data, where the plurality of pieces of teaching data include: a score obtained by a plurality of users who have completed the course learning, and capability data of the plurality of users. .
- the server analyzes the capabilities of the users with high scores based on the above plurality of teaching data.
- the server takes the ability of the user who has achieved the above-mentioned high score as the ability condition for the recommended user to learn the corresponding course, and obtains the correspondence between the ability and the course.
- the correspondence between the above-mentioned ability and the course is determined by the ability of the user who has obtained a high score in the course of study.
- the user's capability data includes multiple capability parameters, and the course can be recommended for the user by considering various capability parameters. For example, the course can be selected according to the importance of each capability parameter.
- the server may send the course selected by the user to the user; or the server may send the course selected by the user to the device requesting the course selection for the user.
- the above-mentioned course for sending the user to the user may be to send the course selected by the user to the account registered by the user, or to send the course selected for the user to the device dedicated to the user.
- the above request is a device for selecting a course for the user, and may be a user device, or may be another server or the like.
- the server may send a link for the course selected by the user to the user, or description information of the course selected by the user.
- the user can click on the link to learn the course, or judge whether to take the course according to the description of the course.
- the user is often self-learning, on the one hand, the learning time limit can be broken, and on the other hand, the learning effect is not good.
- the server may further formulate a learning plan according to the relationship of the course selected for the user, where the learning plan includes a course selected for the user and a course selected for the user selected by the user.
- Course arrangement The server can send a defined learning plan.
- the above learning plan can be derived from big data analysis. For example, analyzing the teaching data and finding that users who have learned according to a certain schedule or course order have achieved higher results, then the learning plan can be formulated for the user according to the plan.
- the server may further acquire the case of learning the course selected by the user, adjust the course selected by the user according to the above situation, or adjust to the learning plan specified by the user.
- the device includes: a first obtaining module 10 configured to acquire capability data of a user; and a selection module 20, An obtaining module 10 is connected, and is configured to select a course for the user according to the capability data of the user according to the corresponding relationship between the preset capability and the course; the sending module 30 is connected to the selecting module 20 and configured to be sent as the user. Selected course.
- the course is recommended for the user according to the user's ability, and a personalized service for the user is provided.
- the capability data of the user is various, as long as the ability of the user can be characterized, for example, the degree of the user, and the higher the degree of education, the stronger the learning ability is expressed by a certain probability.
- the user's capability data may include at least one of the following: scores obtained by other courses that the user has learned, educational institutions that the user has attended, other courses that the user has studied, and user purchases. Or browse the teaching materials, the user's education, the user's working hours, and the user's professional background.
- the correspondence between the above capabilities and the course can be determined based on big data analysis.
- the apparatus further includes: a second acquiring module, configured to acquire a plurality of pieces of teaching data, wherein the plurality of pieces of teaching data include: scores obtained by a plurality of users who have completed the course learning And the capability data of the plurality of users; the analysis module is configured to analyze the capability of the user having high scores according to the plurality of pieces of teaching data; and the determining module is configured to use the capability of the user with high achievement as the recommended user Learn the competency conditions of the corresponding courses and get the corresponding relationship between the above abilities and the courses.
- a second acquiring module configured to acquire a plurality of pieces of teaching data, wherein the plurality of pieces of teaching data include: scores obtained by a plurality of users who have completed the course learning And the capability data of the plurality of users
- the analysis module is configured to analyze the capability of the user having high scores according to the plurality of pieces of teaching data
- the determining module is configured to use the capability of the user with high achievement as the recommended user Learn the competency conditions of the corresponding courses and get the corresponding
- the correspondence between the above-mentioned ability and the course is determined by the ability of the user who has obtained a high score in the course of study.
- the user's capability data includes multiple capability parameters, and the course can be recommended for the user by considering various capability parameters. For example, the course can be selected according to the importance of each capability parameter.
- the server may send the course selected by the user to the user; or the server may send the course selected by the user to the device requesting the course selection for the user.
- the above-mentioned course for sending the user to the user may be to send the course selected by the user to the account registered by the user, or to send the course selected for the user to the device dedicated to the user.
- the above request is a device for selecting a course for the user, and may be a user device, or may be another server or the like.
- the step sending module 30 may send a link for the course selected by the user to the user, or description information of the course selected by the user. The user can click on the link to learn the course, or judge whether to take the course according to the description of the course.
- the user is often self-learning, on the one hand, the learning time limit can be broken, and on the other hand, the learning effect is not good.
- the apparatus further includes: a setting module configured to formulate a learning plan according to a relationship selected for the user, wherein the learning plan includes a course selected for the user and learning is The arrangement of each course in the course selected by the user; the above sending module is set to send the above learning plan.
- the above learning plan can be derived from big data analysis. For example, analyzing the teaching data and finding that users who have learned according to a certain schedule or course order have achieved higher results, then the learning plan can be formulated for the user according to the plan.
- the device further includes: a third obtaining module, configured to acquire the case of learning the course selected by the user; and an adjusting module, configured to adjust to the course selected by the user according to the foregoing situation , or adjust to the learning plan specified by the above user.
- FIG. 3 is a flow chart of a preferred method for recommending a course in online education according to an embodiment of the present invention. As shown in FIG. 3, the method mainly includes the following steps:
- Step S302 collecting and storing big data. Can be divided into two parts: First, the data generated by its own system. 2. Data provided by other partners.
- Step S304 Perform data analysis and mining on the big data for the education industry for the algorithm preset by the system, and store the result as a “base of experience”. For example, the correspondence between capabilities and courses, etc.
- Step S306 generating one or more customized educational programs for selection according to the historical data of the specific individual and the experience base library.
- Step S308 when the individual implements according to the selected educational program, new data will be generated, and the system will repeatedly combine the experience base database with the newly generated data, and timely correct the existing educational program to complete the educational program. To achieve the desired results.
- the embodiment of the present invention achieves the following technical effects: using collection and analysis of big data, a series of education-related "experiences” are obtained, and then the "experience” is combined with the need for personalized service.
- modules or steps of the present invention described above can be implemented by a general-purpose computing device that can be centralized on a single computing device or distributed across a network of multiple computing devices. Alternatively, they may be implemented by program code executable by the computing device such that they may be stored in the storage device by the computing device and, in some cases, may be different from the order herein.
- the steps shown or described are performed, or they are separately fabricated into individual integrated circuit modules, or a plurality of modules or steps thereof are fabricated as a single integrated circuit module.
- the invention is not limited to any specific combination of hardware and software.
- a course may be recommended for a user according to the capabilities of the user, and a personalized service for the user is provided.
Abstract
一种在线教育中课程的推荐方法包括：服务器获取用户的能力数据；所述服务器根据所述用户的能力数据，按照预设的能力与课程的对应关系，为所述用户选择课程；所述服务器发送为所述用户选择的课程。还公开了一种在线教育中课程的推荐装置。通过本发明，实现了针对用户的个性化服务。
Description
本发明涉及在线教育领域，具体而言，涉及一种在线教育中课程的推荐方法及装置。
在线教育(又称为网络教育或远程教育，e-Learning或online-learning)，是以网络为介质的教学方式，通过网络，学员与教师可以展开远程教学活动；此外，借组网络课件，学员还可以随时随地进行学习，打破时间和空间的限制。
相关技术中，常见的在线教育形式是，在线教育提供商提供网站或客户端，网站和客户端上展示可供学习的课程内容，学员浏览网站或客户端，查找感兴趣的课程，在网站上找到学员感兴趣的课程时，学员可以学习该课程，课程的形式常见的有课程讲义幻灯片、视频录像、视频直播等。
上述的在线教育方式，需要用户自主选择课程，不能实现针对学员的个性化服务。相关技术中虽然也有课程推荐的方案，但是这些方案基于学员观看过的课程，向学员推荐类似的课程，大多数是基于学员的兴趣，例如，学员观看过微积分，则向学员推荐线性代数，学员观看过英语口语，则向学员推荐英语听力。这样的推荐方式过于简单，难以针对学员提供个性化服务。
针对相关技术中在线教育的课程推荐简单、无法实现针对学员的个性化服务的问题，目前尚未提出有效的解决方案。
发明内容
针对在线教育的课程推荐简单、无法实现针对学员的个性化服务的问题，本发明提供了一种在线教育中课程的推荐方法及装置，以至少解决上述问题。
根据本发明的一个实施例，提供了一种在线教育中课程的推荐方法，包括：服务器获取用户的能力数据；上述服务器根据上述用户的能力数据，按照预设的能力与课程的对应关系，为上述用户选择课程；上述服务器发送为上述用户选择的课程。
可选地，上述方法还包括：上述服务器获取多条教学数据，其中，上述多条教学数据包括：已完成课程学习的多个用户所取得的成绩、上述多个用户的能力数据；上述服务器根据上述多条教学数据分析取得成绩高的用户所具备的能力；上述服务器将上述取得成绩高的用户所具备的能力作为推荐用户学习对应课程的能力条件，得到上述能力与课程的对应关系。
可选地，上述能力与课程的对应关系由学习课程取得成绩高的用户具备的能力确定。
可选地，上述能力数据包括以下至少之一：上述用户曾学习的其他课程所取得的成绩、上述用户曾就读的教育机构、上述用户曾学习过的其他课程、上述用户购买或浏览的教学资料、用户的学历、用户的工作时间、用户的职业背景。
可选地，上述服务器发送为上述用户选择的课程，包括：上述服务器向上述用户发送为上述用户选择的课程；或者上述服务器向请求为上述用户选择课程的设备发送为上述用户选择的课程。
可选地，上述服务器向上述用户发送为上述用户选择的课程，包括：上述服务器向上述用户发送为上述用户选择的课程的链接，或为上述用户选择的课程的描述信息。
可选地，上述方法还包括：上述服务器根据为上述用户选择的课程的关系制定学习计划，上述学习计划包括为上述用户选择的课程和学习为上述用户选择的课程中各个课程的安排；上述服务器发送上述学习计划。
可选地，上述方法还包括：上述服务器获取上述学习为上述用户选择的课程的情况；上述服务器根据上述情况调整为上述用户选择的课程，或者调整为上述用户指定的学习计划。
根据本发明的另一个实施例，提供了一种在线教育中课程的推荐装置，包括：第一获取模块，设置为获取用户的能力数据；选择模块，设置为根据上述用户的能力数据，按照预设的能力与课程的对应关系，为上述用户选择课程；发送模块，设置为发送为上述用户选择的课程。
可选地，上述装置还包括：第二获取模块，设置为获取多条教学数据，其中，上述多条教学数据包括：已完成课程学习的多个用户所取得的成绩、上述多个用户的能力数据；分析模块，设置为根据上述多条教学数据分析取得成绩高的用户所具备的能
力；确定模块，设置为将上述取得成绩高的用户所具备的能力作为推荐用户学习对应课程的能力条件，得到上述能力与课程的对应关系。
可选地，上述能力与课程的对应关系由学习课程取得成绩高的用户具备的能力确定。
可选地，上述装置还包括：制定模块，设置为根据为上述用户选择的课程的关系制定学习计划，上述学习计划包括为上述用户选择的课程和学习为上述用户选择的课程中各个课程的安排；上述发送模块，设置为发送上述学习计划。
可选地，上述装置还包括：第三获取模块，设置为获取上述学习为上述用户选择的课程的情况；调整模块，设置为根据上述情况调整为上述用户选择的课程，或者调整为上述用户指定的学习计划。
通过本发明，根据用户的能力为用户推荐课程，提供了针对用户的个性化服务。
此处所说明的附图用来提供对本发明的进一步理解，构成本申请的一部分，本发明的示意性实施例及其说明用于解释本发明，并不构成对本发明的不当限定。在附图中：
图1是根据本发明实施例的在线教育中课程的推荐方法的流程图；
图2是根据本发明实施例的在线教育中课程的推荐装置的结构框图；以及
图3是根据本发明实施例优选的在线教育中课程的推荐方法的流程图。
下文中将参考附图并结合实施例来详细说明本发明。需要说明的是，在不冲突的情况下，本申请中的实施例及实施例中的特征可以相互组合。
在以下实施例中，可以预料的是，以下方法及装置可以通过计算机程序单元实现。
图1是根据本发明实施例的在线教育中课程的推荐方法的流程图，如图1所示，该方法包括步骤S102至步骤S106。
步骤S102，服务器获取用户的能力数据。
步骤S104，服务器根据用户的能力数据，按照预设的能力与课程的对应关系，为上述用户选择课程。
步骤S106，服务器发送为上述用户选择的课程。
通过本发明实施例，根据用户的能力为用户推荐课程，提供了针对用户的个性化服务。
上述步骤S102中，用户的能力数据多种多样，只要能够表征用户的能力即可，例如，用户的学历，学历越高则在一定概率上表示学习能力越强。
在本发明实施例的一个实施方式中，用户的能力数据可以包括以下至少之一：用户曾学习的其他课程所取得的成绩、用户曾就读的教育机构、用户曾学习过的其他课程、用户购买或浏览的教学资料、用户的学历、用户的工作时间、用户的职业背景。
在本发明实施例中，可以基于大数据分析确定上述能力与课程的对应关系。
在本发明实施例的一个可选实施方式中，服务器还可以获取多条教学数据，其中，多条教学数据包括：已完成课程学习的多个用户所取得的成绩、上述多个用户的能力数据。服务器根据上述多条教学数据分析取得成绩高的用户所具备的能力。服务器将上述取得成绩高的用户所具备的能力作为推荐用户学习对应课程的能力条件，得到能力与课程的对应关系。
在本发明实施例的一个实施方式中，上述能力与课程的对应关系由学习课程取得成绩高的用户具备的能力确定。
例如，通过对教学数据进行大数据分析，确定数学成绩较好的用户在计算机学习方面取得的成绩较高，或者分析计算机课程成绩较高的用户，发现这些用户的数学成绩较高。从上述的分析，得出数学成绩与计算机课程的对应关系，即为数学成绩较好的用户推荐计算机课程。
此外，用户的能力数据包含多个能力参数，可以综合考虑各个能力参数为用户推荐课程。例如，可以按照各个能力参数的重要程度选择课程。
在根据能力数据选择课程时，还可以参考用户的兴趣，选择用户感兴趣且与用户能力相匹配的课程。
在本发明实施例的一个实施方式中，上述步骤S106，服务器可以向上述用户发送为上述用户选择的课程；或者，服务器可以向请求为上述用户选择课程的设备发送为上述用户选择的课程。
上述的向用户发送为用户选择的课程，可以是向用户注册的账号发送为用户选择的课程，也可以是向用户专用的设备发送为用户选择的课程。
上述的请求为上述用户选择课程的设备，可以是用户设备，也可以是其他服务器等。
在本发明实施例的一个实施方式中，上述步骤S106中，服务器可以向上述用户发送为上述用户选择的课程的链接，或为上述用户选择的课程的描述信息。用户可以点击链接进行课程的学习，或者根据课程的描述信息判断是否学习课程。
相关技术中，对于非直播课程的学习，往往是用户自主学习，一方面可以突破学习时间的限制，另一方面也存在学习效果不佳的问题。
为此，在本发明实施例的一个实施方式中，服务器还可以根据为上述用户选择的课程的关系制定学习计划，上述学习计划包括为上述用户选择的课程和学习为上述用户选择的课程中各个课程的安排。服务器可发送制定的学习计划。
上述的学习计划可以根据大数据分析得出，例如，分析教学数据，发现按照某一进度或课程先后顺序学习的用户取得了较高的成绩，则可以按照这用计划为用户制定学习计划。
在本发明实施例的一个实施方式中，服务器还可以获取上述学习为上述用户选择的课程的情况，根据上述情况调整为上述用户选择的课程，或者调整为上述用户指定的学习计划。
图2是根据本发明实施例的在线教育中课程的推荐装置的结构框图，如图2所示，该装置包括：第一获取模块10，设置为获取用户的能力数据；选择模块20，与第一获取模块10相连接，设置为根据上述用户的能力数据，按照预设的能力与课程的对应关系，为上述用户选择课程；发送模块30，与选择模块20相连接，设置为发送为上述用户选择的课程。
通过本发明实施例，根据用户的能力为用户推荐课程，提供了针对用户的个性化服务。
在本发明实施例中，用户的能力数据多种多样，只要能够表征用户的能力即可，例如，用户的学历，学历越高则在一定概率上表示学习能力越强。
在本发明实施例的一个实施方式中，用户的能力数据可以包括以下至少之一：用户曾学习的其他课程所取得的成绩、用户曾就读的教育机构、用户曾学习过的其他课程、用户购买或浏览的教学资料、用户的学历、用户的工作时间、用户的职业背景。
在本发明实施例中，可以基于大数据分析确定上述能力与课程的对应关系。
在本发明实施例的一个实施方式中，上述装置还包括：第二获取模块，设置为获取多条教学数据，其中，上述多条教学数据包括：已完成课程学习的多个用户所取得的成绩、上述多个用户的能力数据；分析模块，设置为根据上述多条教学数据分析取得成绩高的用户所具备的能力；确定模块，设置为将上述取得成绩高的用户所具备的能力作为推荐用户学习对应课程的能力条件，得到上述能力与课程的对应关系。
在本发明实施例的一个实施方式中，上述能力与课程的对应关系由学习课程取得成绩高的用户具备的能力确定。
例如，通过对教学数据进行大数据分析，确定数学成绩较好的用户在计算机学习方面取得的成绩较高，或者分析计算机课程成绩较高的用户，发现这些用户的数学成绩较高。从上述的分析，得出数学成绩与计算机课程的对应关系，即为数学成绩较好的用户推荐计算机课程。
此外，用户的能力数据包含多个能力参数，可以综合考虑各个能力参数为用户推荐课程。例如，可以按照各个能力参数的重要程度选择课程。
在根据能力数据选择课程时，还可以参考用户的兴趣，选择用户感兴趣且与用户能力相匹配的课程。
在本发明实施例的一个实施方式中，上述步骤S106，服务器可以向上述用户发送为上述用户选择的课程；或者，服务器可以向请求为上述用户选择课程的设备发送为上述用户选择的课程。
上述的向用户发送为用户选择的课程，可以是向用户注册的账号发送为用户选择的课程，也可以是向用户专用的设备发送为用户选择的课程。
上述的请求为上述用户选择课程的设备，可以是用户设备，也可以是其他服务器等。
在本发明实施例的一个实施方式中，上述步骤发送模块30可以向上述用户发送为上述用户选择的课程的链接，或为上述用户选择的课程的描述信息。用户可以点击链接进行课程的学习，或者根据课程的描述信息判断是否学习课程。
相关技术中，对于非直播课程的学习，往往是用户自主学习，一方面可以突破学习时间的限制，另一方面也存在学习效果不佳的问题。
为此，在本发明实施例的一个实施方式中，上述装置还包括：制定模块，设置为根据为上述用户选择的课程的关系制定学习计划，上述学习计划包括为上述用户选择的课程和学习为上述用户选择的课程中各个课程的安排；上述发送模块，设置为发送上述学习计划。
上述的学习计划可以根据大数据分析得出，例如，分析教学数据，发现按照某一进度或课程先后顺序学习的用户取得了较高的成绩，则可以按照这用计划为用户制定学习计划。
在本发明实施例的一个实施方式中，上述装置还包括：第三获取模块，设置为获取上述学习为上述用户选择的课程的情况；调整模块，设置为根据上述情况调整为上述用户选择的课程，或者调整为上述用户指定的学习计划。
下面结合一个具体实例对本发明实施例进行详细描述。
在本发明实施例中，结合个人数据(如从出生到现在就读过的教育机构，各学科的考试成绩、排名，家庭信息、购买记录、听课记录、爱好等等)和其它大数据产生的大概率事件(如数学和物理好的人如果再进修汽车专业会比其他人更加容易在这个领域取得成绩)，针对个人推荐的多套教育方案，以便个人根据这些推荐进行选择参考，实现互联网时代下真正的“因材施教”。
图3是根据本发明实施例优选的在线教育中课程的推荐方法的流程图，如图3所示，该方法主要包括以下几个步骤：
步骤S302，大数据的采集和存储。可分为两个部分：一，自身系统产生的数据。二、其它合作方提供的数据。
步骤S304，针对系统预置的算法，对大数据进行教育行业的数据分析和挖掘，将结果作为“经验”存为基础库。例如，能力与课程的对应关系等。
步骤S306，针对特定个人的历史数据，结合经验基础库，生成一套或多套定制化的教育方案供选择。
步骤S308，在个人按选择的教育方案进行实施时，会有新的数据产生，系统会针对这些新产生的数据反复结合经验基础库，对现有的教育方案及时进行修正，以此完成教育方案，从而达到预期效果。
从以上的描述中，可以看出，本发明实施例实现了如下技术效果：利用采集、分析大数据，得到了一系列和教育相关的“经验”，然后利用这些“经验”结合需要个性化服务的对象，给出一些具有前瞻性的教育方案推荐，从而达到真正的“因材施教”。
显然，本领域的技术人员应该明白，上述的本发明的各模块或各步骤可以用通用的计算装置来实现，它们可以集中在单个的计算装置上，或者分布在多个计算装置所组成的网络上，可选地，它们可以用计算装置可执行的程序代码来实现，从而，可以将它们存储在存储装置中由计算装置来执行，并且在某些情况下，可以以不同于此处的顺序执行所示出或描述的步骤，或者将它们分别制作成各个集成电路模块，或者将它们中的多个模块或步骤制作成单个集成电路模块来实现。这样，本发明不限制于任何特定的硬件和软件结合。
以上所述仅为本发明的优选实施例而已，并不用于限制本发明，对于本领域的技术人员来说，本发明可以有各种更改和变化。凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。
基于本发明实施例提供的上述技术方案，可以根据用户的能力为用户推荐课程，提供了针对用户的个性化服务。
Claims (13)
- 一种在线教育中课程的推荐方法，包括：服务器获取用户的能力数据；所述服务器根据所述用户的能力数据，按照预设的能力与课程的对应关系，为所述用户选择课程；所述服务器发送为所述用户选择的课程。
- 根据权利要求1所述的方法，其中，还包括：所述服务器获取多条教学数据，其中，所述多条教学数据包括：已完成课程学习的多个用户所取得的成绩、所述多个用户的能力数据；所述服务器根据所述多条教学数据分析取得成绩高的用户所具备的能力；所述服务器将所述取得成绩高的用户所具备的能力作为推荐用户学习对应课程的能力条件，得到所述能力与课程的对应关系。
- 根据权利要求1所述的方法，其中，所述能力与课程的对应关系由学习课程取得成绩高的用户具备的能力确定。
- 根据权利要求1所述的方法，其中，所述能力数据包括以下至少之一：所述用户曾学习的其他课程所取得的成绩、所述用户曾就读的教育机构、所述用户曾学习过的其他课程、所述用户购买或浏览的教学资料、所述用户的学历、所述用户的工作时间、所述用户的职业背景。
- 根据权利要求1所述的方法，其中，所述服务器发送为所述用户选择的课程，包括：所述服务器向所述用户发送为所述用户选择的课程；或者所述服务器向请求为所述用户选择课程的设备发送为所述用户选择的课程。
- 根据权利要求5所述的方法，其中，所述服务器向所述用户发送为所述用户选择的课程，包括：所述服务器向所述用户发送为所述用户选择的课程的链接，或为所述用户选择的课程的描述信息。
- 根据权利要求1所述的方法，其中，还包括：所述服务器根据为所述用户选择的课程的关系制定学习计划，所述学习计划包括为所述用户选择的课程和学习为所述用户选择的课程中各个课程的安排；所述服务器发送所述学习计划。
- 根据权利要求1至7中任一项所述的方法，其中，还包括：所述服务器获取所述学习为所述用户选择的课程的情况；所述服务器根据所述情况调整为所述用户选择的课程，或者调整为所述用户指定的学习计划。
- 一种在线教育中课程的推荐装置，包括：第一获取模块，设置为获取用户的能力数据；选择模块，设置为根据所述用户的能力数据，按照预设的能力与课程的对应关系，为所述用户选择课程；发送模块，设置为发送为所述用户选择的课程。
- 根据权利要求9所述的装置，其中，还包括：第二获取模块，设置为获取多条教学数据，其中，所述多条教学数据包括：已完成课程学习的多个用户所取得的成绩、所述多个用户的能力数据；分析模块，设置为根据所述多条教学数据分析取得成绩高的用户所具备的能力；确定模块，设置为将所述取得成绩高的用户所具备的能力作为推荐用户学习对应课程的能力条件，得到所述能力与课程的对应关系。
- 根据权利要求9所述的装置，其中，所述能力与课程的对应关系由学习课程取得成绩高的用户具备的能力确定。
- 根据权利要求9所述的装置，其中，所述装置还包括：制定模块，设置为根据为所述用户选择的课程的关系制定学习计划，所述学习计划包括为所述用户选择的课程和学习为所述用户选择的课程中各个课程的安排；所述发送模块，设置为发送所述学习计划。
- 根据权利要求9至12中任一项所述的装置，其中，还包括：第三获取模块，设置为获取所述学习为所述用户选择的课程的情况；调整模块，设置为根据所述情况调整为所述用户选择的课程，或者调整为所述用户指定的学习计划。
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410270931.3 | 2014-06-17 | ||
| CN201410270931.3A CN105225553B (zh) | 2014-06-17 | 2014-06-17 | 在线教育中课程的推荐方法及装置 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2015192530A1 true WO2015192530A1 (zh) | 2015-12-23 |
Family
ID=54934780
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/CN2014/087615 WO2015192530A1 (zh) | 2014-06-17 | 2014-09-26 | 在线教育中课程的推荐方法及装置 |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN105225553B (zh) |
| WO (1) | WO2015192530A1 (zh) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110188266A (zh) * | 2019-05-10 | 2019-08-30 | 广州职赢未来信息科技有限公司 | 课程信息推送方法、系统、可读存储介质及终端设备 |
| CN111223015A (zh) * | 2018-11-27 | 2020-06-02 | 阿里巴巴集团控股有限公司 | 课程推荐方法、装置及终端设备 |
| CN112232921A (zh) * | 2020-10-27 | 2021-01-15 | 北京聚通达科技股份有限公司 | 一种在线教育运营系统 |
| CN112804342A (zh) * | 2021-01-27 | 2021-05-14 | 上海向心云网络科技有限公司 | 一种基于用户学习行为的个性化推荐系统和方法 |
| CN114066695A (zh) * | 2022-01-18 | 2022-02-18 | 广东数业智能科技有限公司 | 一种基于劳动项目的教育内容分析方法、系统和存储介质 |
| CN115098790A (zh) * | 2022-08-24 | 2022-09-23 | 北京英华在线科技有限公司 | 在线教育平台用的课程管理方法及系统 |
Families Citing this family (23)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106251723A (zh) * | 2016-09-09 | 2016-12-21 | 深圳市企鹅网络科技有限公司 | 一种移动互联网的在线教育系统及方法 |
| CN106408475B (zh) * | 2016-09-30 | 2017-12-26 | 中国地质大学（北京） | 一种在线课程适用性评价方法 |
| CN108809675A (zh) * | 2017-04-28 | 2018-11-13 | 北京嘀嘀无限科技发展有限公司 | 信息推送方法及装置 |
| CN107122488A (zh) * | 2017-05-11 | 2017-09-01 | 安徽谦通信息科技有限公司 | 一种基于消息推送的考试管理方法 |
| CN109035079B (zh) * | 2017-06-08 | 2021-10-15 | 深圳市鹰硕技术有限公司 | 一种基于互联网的录播课程跟随学习系统和方法 |
| CN109040797B (zh) * | 2017-06-08 | 2020-06-02 | 深圳市鹰硕技术有限公司 | 一种互联网教学的录播系统和方法 |
| CN109086563A (zh) * | 2017-06-14 | 2018-12-25 | 达易特基因科技股份有限公司 | 应用基因检测的适性教育分析方法 |
| CN107864383A (zh) * | 2017-11-09 | 2018-03-30 | 北京市农林科学院 | 一种远程教育终端 |
| CN107731034A (zh) * | 2017-11-09 | 2018-02-23 | 北京市农林科学院 | 一种远程教育终端、服务端和远程教育资源推荐方法 |
| CN107909438B (zh) * | 2017-11-15 | 2021-04-27 | 河南工学院 | 管理课程的推送方法及推送系统 |
| CN108010405A (zh) * | 2017-11-28 | 2018-05-08 | 苏州云创宝网络科技股份有限公司 | 基于互联网的在线视频教学互动移动终端、介质及方法 |
| CN108664539A (zh) * | 2018-01-15 | 2018-10-16 | 福建中科多特教育投资有限公司 | 一种课程项目匹配方法和系统 |
| CN110136497B (zh) * | 2018-02-02 | 2022-04-22 | 上海流利说信息技术有限公司 | 用于口语学习的数据处理方法及装置 |
| CN108711319A (zh) * | 2018-05-24 | 2018-10-26 | 李炜 | 一种国际职业汉语教学方法及系统 |
| CN108596808A (zh) * | 2018-06-08 | 2018-09-28 | 天柱县白市镇双河村峰晶种植专业合作社 | 一种葡萄加工培训系统 |
| CN109035937A (zh) * | 2018-08-29 | 2018-12-18 | 芜湖新使命教育科技有限公司 | 授权共享网络教育系统 |
| CN109447869A (zh) * | 2018-12-06 | 2019-03-08 | 安徽教育网络出版有限公司 | 一种在线教育中课程的推荐方法 |
| CN109637233B (zh) * | 2019-02-12 | 2021-04-02 | 湖南文动力教育科技有限公司 | 一种智能教学的方法及系统 |
| CN110163514A (zh) * | 2019-05-25 | 2019-08-23 | 上海乂学教育科技有限公司 | 智能课表安排方法 |
| CN110930790A (zh) * | 2019-12-03 | 2020-03-27 | 广州三人行壹佰教育科技有限公司 | 自适应课程推荐的方法和装置 |
| CN111222792B (zh) * | 2020-01-08 | 2022-04-05 | 中国建设银行股份有限公司 | 混合式培训的实现方法及装置 |
| CN113053188A (zh) * | 2021-03-11 | 2021-06-29 | 中山大学 | 一种安卓多语言学习系统 |
| CN116541432B (zh) * | 2023-05-22 | 2023-10-17 | 杭州精英在线教育科技股份有限公司 | 一种基于教育机器人的在线课堂智能推荐方法 |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101064069A (zh) * | 2006-04-25 | 2007-10-31 | 杭州草莓资讯有限公司 | 反向学习历程与鼓励教学之方法与系统 |
| CN101582101A (zh) * | 2008-05-15 | 2009-11-18 | 梁昌年 | 利用计算机系统为用户提供个性化学习的方法及其装置 |
| CN102822882A (zh) * | 2010-01-15 | 2012-12-12 | 阿波洛集团公司 | 动态推荐学习内容 |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1831866A (zh) * | 2005-03-08 | 2006-09-13 | 株式会社新星 | 外语教学经营管理系统及外语教学经营管理方法 |
| CN101436277A (zh) * | 2008-12-04 | 2009-05-20 | 北京安博在线软件有限公司 | 提供测评、培训、求职及招聘的系统 |
| CN101650809A (zh) * | 2009-09-10 | 2010-02-17 | 上海一佳一网络科技有限公司 | 岗位能力培训管理方法和系统 |
| CN102136106A (zh) * | 2011-03-23 | 2011-07-27 | 镇江睿泰信息科技有限公司 | 一种全程人才成长培养系统 |
| CN102508846A (zh) * | 2011-09-26 | 2012-06-20 | 深圳中兴网信科技有限公司 | 一种基于网络的媒体课件的推荐方法和系统 |
| CN102855542A (zh) * | 2012-07-19 | 2013-01-02 | 周宇 | “学习基因”个体学习能力测评方法 |
| CN103578310A (zh) * | 2012-08-08 | 2014-02-12 | 袁正华 | 可依程度或能力补强的云端学习系统 |
-
2014
- 2014-06-17 CN CN201410270931.3A patent/CN105225553B/zh active Active
- 2014-09-26 WO PCT/CN2014/087615 patent/WO2015192530A1/zh active Application Filing
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101064069A (zh) * | 2006-04-25 | 2007-10-31 | 杭州草莓资讯有限公司 | 反向学习历程与鼓励教学之方法与系统 |
| CN101582101A (zh) * | 2008-05-15 | 2009-11-18 | 梁昌年 | 利用计算机系统为用户提供个性化学习的方法及其装置 |
| CN102822882A (zh) * | 2010-01-15 | 2012-12-12 | 阿波洛集团公司 | 动态推荐学习内容 |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111223015A (zh) * | 2018-11-27 | 2020-06-02 | 阿里巴巴集团控股有限公司 | 课程推荐方法、装置及终端设备 |
| CN111223015B (zh) * | 2018-11-27 | 2024-04-12 | 阿里巴巴集团控股有限公司 | 课程推荐方法、装置及终端设备 |
| CN110188266A (zh) * | 2019-05-10 | 2019-08-30 | 广州职赢未来信息科技有限公司 | 课程信息推送方法、系统、可读存储介质及终端设备 |
| CN112232921A (zh) * | 2020-10-27 | 2021-01-15 | 北京聚通达科技股份有限公司 | 一种在线教育运营系统 |
| CN112804342A (zh) * | 2021-01-27 | 2021-05-14 | 上海向心云网络科技有限公司 | 一种基于用户学习行为的个性化推荐系统和方法 |
| CN114066695A (zh) * | 2022-01-18 | 2022-02-18 | 广东数业智能科技有限公司 | 一种基于劳动项目的教育内容分析方法、系统和存储介质 |
| CN115098790A (zh) * | 2022-08-24 | 2022-09-23 | 北京英华在线科技有限公司 | 在线教育平台用的课程管理方法及系统 |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105225553A (zh) | 2016-01-06 |
| CN105225553B (zh) | 2018-06-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| WO2015192530A1 (zh) | 在线教育中课程的推荐方法及装置 | |
| Cathcart et al. | Learner-focused evaluation cycles: Facilitating learning using feedforward, concurrent and feedback evaluation | |
| US9349298B2 (en) | System and method for on-line interactive learning and feedback | |
| Sahu et al. | Medical students’ perceptions of small group teaching effectiveness in hybrid curriculum | |
| van Dijk et al. | The relation between classroom management and mathematics achievement: A multilevel structural equation model | |
| Çakıroğlu et al. | Understanding community in synchronous online learning: do perceptions match behaviours? | |
| Ní Fhloinn et al. | Student perception of the impact of mathematics support in higher education | |
| Samala et al. | Online learning applications for students: Opportunities & challenges | |
| Yan et al. | Comparing digital libraries with virtual communities from the perspective of e-quality | |
| Khee et al. | Students’ perception towards lecture capture based on the Technology Acceptance Model | |
| Göktürk Saglam et al. | Evaluating an online professional learning community as a context for professional development in classroom-based research | |
| Storie et al. | Determining the information literacy needs of a medical and dental faculty | |
| Lantzy | Health literacy education: the impact of synchronous instruction | |
| Schwarzhaupt et al. | Teachers’ engagement and self-efficacy in a PK–12 computer science teacher virtual community of practice | |
| KR20150139395A (ko) | 온라인 화상 교육서비스 제공방법 및 이를 수행하는 온라인 화상교육을 위한 서비스 제공서버 | |
| Pinnegar et al. | Self-study inquiry practices: Introduction to self-study inquiry practices and scholarly activity | |
| Newhouse | Using digital technologies to improve the authenticity of performance assessment for high-stakes purposes | |
| Stjernquist et al. | Problem based learning and the case method–medical students change preferences during clerkship | |
| Isenberg-Grzeda et al. | A survey of American and Canadian psychiatry residents on their training, teaching practices, and attitudes toward teaching | |
| TWI696386B (zh) | 多媒體資料推薦系統及多媒體資料推薦方法 | |
| Pan et al. | Exploring the impact of intelligent learning tools on students’ independent learning abilities: a PLS-SEM analysis of grade 6 students in China | |
| Nongkhai et al. | Framework for e-Leaming recommendation based on index of learning styles model | |
| Kranz et al. | Mobile and contextual learning: a case study on mobile didactics in teaching and education | |
| US20160111013A1 (en) | Learning content management methods for generating optimal test content | |
| Durodolu et al. | The perception of information literacy skill among the Librarians: A survey of University of Lagos Library |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| 121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 14894839 Country of ref document: EP Kind code of ref document: A1 |
|
| NENP | Non-entry into the national phase |
Ref country code: DE |
|
| 122 | Ep: pct application non-entry in european phase |
Ref document number: 14894839 Country of ref document: EP Kind code of ref document: A1 |