CN112182343A - Online learning interaction method, device, equipment and storage medium - Google Patents

Online learning interaction method, device, equipment and storage medium Download PDF

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CN112182343A
CN112182343A CN202010996240.7A CN202010996240A CN112182343A CN 112182343 A CN112182343 A CN 112182343A CN 202010996240 A CN202010996240 A CN 202010996240A CN 112182343 A CN112182343 A CN 112182343A
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content
interaction
feedback
user
interactive
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侯在鹏
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Beijing Baidu Netcom Science and Technology Co Ltd
Shanghai Xiaodu Technology Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/048—Interaction techniques based on graphical user interfaces [GUI]
    • G06F3/0481—Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/048—Interaction techniques based on graphical user interfaces [GUI]
    • G06F3/0487—Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser
    • G06F3/0488—Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures
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    • G06Q50/10—Services
    • G06Q50/20—Education
    • G06Q50/205—Education administration or guidance
    • 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
    • G09B5/08—Electrically-operated educational appliances providing for individual presentation of information to a plurality of student stations
    • 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
    • G09B7/00—Electrically-operated teaching apparatus or devices working with questions and answers

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Abstract

The application discloses an online learning interaction method, an online learning interaction device, an online learning interaction equipment and a storage medium, and relates to the technical field of artificial intelligence such as data processing, natural language processing and voice interaction. The specific implementation scheme is as follows: responding to an online interaction request initiated by a current user, and acquiring the interaction content of the current user; and processing the learning attribute information and/or the interactive content of the current user, and determining feedback content according to a processing result. The method and the device can improve the online learning efficiency of the user to a certain extent and enrich the online learning experience of the user.

Description

Online learning interaction method, device, equipment and storage medium
Technical Field
The application relates to the technical field of computers, in particular to the technical field of artificial intelligence such as data processing, natural language processing, voice interaction and the like, and particularly relates to an online learning interaction method, device, equipment and storage medium.
Background
With the development of computer technology, users can learn through the internet in an electronic environment formed by communication technology, microcomputer technology, computer technology, artificial intelligence, network technology, multimedia technology and the like, and with the development of intelligent electronic equipment and the spread of global epidemic situations, offline learning is greatly influenced, and online learning gradually becomes an important way for students to acquire knowledge.
Since the development of offline learning is easily affected in some emergency situations, online learning is the mainstream of current learning in view of the characteristic that online learning is not limited by time, place and space.
Disclosure of Invention
The present disclosure provides a method, apparatus, device, and storage medium for online learning interaction.
According to an aspect of the present disclosure, there is provided an online learning interaction method, including:
responding to an online interaction request initiated by a current user, and acquiring the interaction content of the current user;
and processing the learning attribute information and/or the interactive content of the current user, and determining feedback content according to a processing result.
According to another aspect of the present disclosure, there is provided an online learning interaction apparatus, including:
the interactive content acquisition module is used for responding to an online interactive request initiated by a current user and acquiring the interactive content of the current user;
and the feedback content determining module is used for processing the learning attribute information of the current user and/or the interactive content and determining feedback content according to a processing result.
According to a third aspect, there is provided an electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform an online learning interaction method as described in any one of the embodiments of the present application.
According to a fourth aspect, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the online learning interaction method according to any one of the embodiments of the present application.
According to the technology of the application, the online learning efficiency of the user is improved, and the online learning experience of the user is enriched.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not intended to limit the present application. Wherein:
FIG. 1 is a schematic flow chart diagram illustrating a method for online learning interaction according to an embodiment of the present disclosure;
FIG. 2 is a flow chart diagram illustrating another online learning interaction method provided in accordance with an embodiment of the present application;
FIG. 3 is a schematic structural diagram of an online learning interaction device according to an embodiment of the present application;
fig. 4 is a block diagram of an electronic device for implementing an online learning interaction method according to an embodiment of the present application.
Detailed Description
The following description of the exemplary embodiments of the present application, taken in conjunction with the accompanying drawings, includes various details of the embodiments of the application for the understanding of the same, which are to be considered exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Fig. 1 is a schematic flow chart of an online learning interaction method disclosed in an embodiment of the present application, which may be applied to a user online learning situation, and typically, may be applied to a situation where corresponding interaction is performed according to an online learning situation of the user. The method of the embodiment may be executed by an online learning interaction device, which may be implemented in software and/or hardware, and may be integrated in an electronic device. Referring to fig. 1, the online learning interaction method disclosed in this embodiment may include:
s101, responding to an online interaction request initiated by a current user, and collecting the interaction content of the current user.
The online interaction request is a request sent by a current user for online interaction with other users, and can be initiated by clicking an appointed key by the current user or an online interaction voice instruction of the current user and the like.
And after the current user initiates an online interaction request, acquiring the interaction content corresponding to the current user and the online interaction request. The interactive content can be specific content generated in interactive behaviors such as job consultation, problem complaint, invitation online communication and the like. The interactive content and the feedback content may be at least one of voice, video and text, which is not limited by the embodiment.
Optionally, the online interaction request may be to click a head portrait of the target user, initiate an interaction invitation to the target user through options such as online interaction, and if the target user responds to the invitation, the target user may enter a virtual learning room exclusive to the current user to learn or communicate with the current user together.
And S102, processing the learning attribute information of the current user and/or the interactive content, and determining feedback content according to a processing result.
Wherein, the learning attribute information is user attribute user information related to learning.
The learning attribute information of the current user who initiates the request can be obtained through the online interaction request initiated by the current user. The obtaining mode may be to directly obtain the learning attribute information provided by the current user during registration, or may be to prompt the current user to perform corresponding learning attribute information filling when the current user initiates a request, which is not limited in this embodiment.
The learning attribute information may include grade, region, subject to be learned, historical learning habit job completion time, learning planning, concentration learning time, dominant learning subject, vulnerable learning subject, and the like.
And processing the learning attribute information of the current user, and determining feedback content according to a processing result. The object for feeding back the interactive content of the current user may be determined according to the learning attribute information of the current user, and for example, the current user is a student in the beijing area at the grade of one school, and the interactive content may be preferentially sent to other users in the beijing area at the grade of one school, so that other users meeting the standard feed back the interactive content.
The form of the feedback content can be determined according to the learning attribute information, for example, when the current user is a pupil of a lower grade, pinyin can be automatically marked for the text when the feedback content is the text content, so that the current user can conveniently read the text.
And processing the interactive content of the current user, and determining feedback content according to the processing result. For example, when the interactive content is a question query, the feedback content should be an answer to the question, and technologies such as natural language processing may be adopted to filter the feedback content that is not related to the interactive content, or prompt the current user that the feedback content may not be related to the interactive content, and the like.
And processing the learning attribute information and the interactive content of the current user, determining feedback content according to a processing result, and determining the feedback content for a common processing result combining the learning attribute information and the interactive content.
Optionally, the processing the learning attribute information of the current user and/or the interactive content, and determining the feedback content according to the processing result includes:
determining an interaction type according to the interaction content of the current user; the interaction type is experience interaction type or problem consultation type;
determining a feedback template according to the learning attribute information of the current user;
and determining feedback content according to the interaction type based on the feedback template.
The experience traffic interactive content is content which is expected to be fed back by objects with the same experience and is obtained by sharing experience generated when a current user handles a certain problem. Illustratively, how well mathematics are learned for communication, etc.
The problem consultation interactive content is the content that the current user can not solve the problem and expects other objects to solve the problem. For example, the current user may encounter an unsolvable problem in the course of the job.
The provider of the feedback content may be a user with the same experience or a user who can solve the problem, or a system that determines the feedback content after analyzing the interactive content by using technologies such as big data analysis, which is not limited in this embodiment.
When the interactive object is a system, the interactive content of the current user can be identified through technologies such as voice recognition, natural language processing and the like, feedback is given, and whether the feedback content is displayed to the public can be determined according to the setting of the user.
And determining a feedback template according to the learning attribute information of the current user, wherein the feedback template is a template determined according to the learning attribute information of the user, for example, the feedback template is determined to be a template with a more lover decoration style and language style for a user with a smaller age, and the like.
And jointly determining feedback content according to the interaction type based on the feedback template. Illustratively, when the user is an elderly user and the interactive content is a question consulting class, the feedback content is the question consulting class with more lovely decorative style and language style.
The learning attribute information and the interactive content of the current user are processed together, and the feedback content is determined according to the feedback template and the interaction type, so that the pertinence and the effectiveness of the feedback content are improved, and the enthusiasm of online learning interaction of the user is improved.
According to the technical scheme, the learning attribute information and/or the interactive content of the current user are/is processed by collecting the interactive content of the current user, and the feedback content is determined according to the processing result, so that the online learning efficiency of the user is improved, and the online learning experience of the user is enriched.
Fig. 2 is a schematic flowchart of another online learning interaction method provided in an embodiment of the present application. The present embodiment is an alternative proposed on the basis of the above-described embodiments. Referring to fig. 2, the online learning interaction method provided in this embodiment includes:
s201, responding to an online interaction request initiated by a current user, and collecting the interaction content of the current user.
S202, processing the learning attribute information of the user and/or the interactive content.
S203, obtaining the interactive mode selected by the user.
The form of the interaction mode may be at least one of a voice mode, a video mode and a text mode, which is not limited in this embodiment.
The interaction modes can be further divided into different types so as to realize different interaction purposes. For example, the interaction mode may be interaction with other users or interaction with the system, when interacting with other users, the interaction mode may be a drift bottle or encouragement, and when interacting with the system, the interaction mode may be a tree hole, which is not limited in this embodiment.
And determining a sending object of the interactive content according to the interactive mode selected and determined by the user.
And S204, determining feedback content according to the processing result and the interactive mode.
The feedback content is determined by learning the attribute information and/or the processing content and the interaction mode of the interaction content.
Optionally, the determining the feedback content according to the processing result and the interaction manner includes:
if the interaction mode is a drift bottle, selecting a target user from candidate users for online learning according to a processing result;
sending the interactive content to the target user;
and acquiring feedback content of the target user to the interactive content.
Wherein the contents of the drift bottle are pre-recorded or written by the user. The candidate users are users who are or have been in an online learning state except the current user. One or more target users are jointly determined according to the drift bottle and the processing result, and the target users can be users related to learning attribute information and/or interactive content with the drift bottle function opened.
Optionally, before sending the drift bottles, the current user may determine labels for the drift bottles, for example, the current user may determine target users according to the labels of the drift bottles, and for example, when the candidate user only accepts the drift bottles of the experience traffic category, the candidate user does not receive the drift bottles of the problem consultation category.
And sending the interactive content to the target user, and acquiring feedback content of the target user on the interactive content, wherein the feedback content can be presented in the form of a drift bottle.
Interaction is carried out on the target user through the drift bottle form, feedback content is obtained, the requirement of light social contact of the user is met, the online learning experience of the user is enhanced, and therefore the online learning efficiency and the enthusiasm of the user are improved.
Optionally, the determining the feedback content according to the processing result and the interaction manner includes:
if the interaction mode is encouraging, selecting a target release position for the current user from candidate release positions of the learning square according to a processing result;
publishing the interactive content at the target publishing location;
and acquiring feedback content of other users to the interactive content.
Wherein the request issued by the current user for encouraging other users to perform the desired action on the specified content is encouraged. Illustratively, the motivational content is the first 5 years of the end-of-term test.
The learning square is a public area, and the content published in the learning square can be displayed to all users in an online learning state in the corresponding area. The candidate publication location may be a location in the learning square where the user has the right to publish the interactive content. Each candidate publishing position may correspond to different types of publishing contents, for example, the candidate publishing positions include an experience communication type block, a problem consultation type block, and an encouragement type block, where the experience communication type block is used to publish the experience communication type contents, the problem consultation type block is used to publish the problem consultation type contents, and the encouragement type block is used to publish the encouragement type contents. A place where the encouragement content can be released is selected for the current user from the candidate release places of the learning square according to the processing result.
And publishing the interactive content at the target publishing position, and acquiring the feedback content of other users to the interactive content. The feedback content can approve the encouraging content issued by the user or reply to the corresponding encouraging content. Alternatively, the user providing the encouragement may obtain the corresponding points according to different forms of feedback. For example, a user who releases the motivational content receives a higher credit score than a user who likes the motivational content. The points can be exchanged for virtual or physical articles in a points mall, and exemplarily can be decoration of a user virtual image, a user virtual medal, ornaments capable of being placed in a virtual learning room, a drawing book, a learning card, toys and the like, so that the enthusiasm of user interaction is improved.
Through the encouraging mode, interaction with the users in the learning square is achieved, feedback content is obtained, the requirement of the users on social contact is met, the online learning experience of the users is enhanced, the confidence of learning targets is achieved, and therefore the online learning efficiency and the enthusiasm of the users are improved.
According to the technical scheme of the embodiment of the application, the interaction mode selected by the user is obtained, the feedback content is determined according to the processing result and the interaction mode, the pertinence of online learning interaction is improved, and the online learning experience of the user is enriched.
Fig. 3 is a schematic structural diagram of an online learning interaction device according to an embodiment of the present application. Referring to fig. 3, an online learning interaction apparatus 300 provided in an embodiment of the present application may include:
an interactive content acquisition module 301, configured to respond to an online interaction request initiated by a current user, and acquire interactive content of the current user;
a feedback content determining module 302, configured to process the learning attribute information of the current user and/or the interactive content, and determine a feedback content according to a processing result.
According to the technical scheme, the learning attribute information and/or the interactive content of the current user are/is processed by collecting the interactive content of the current user, and the feedback content is determined according to the processing result, so that the online learning efficiency of the user is improved, and the online learning experience of the user is enriched.
Optionally, the feedback content determining module includes:
the interaction type determining unit is used for determining an interaction type according to the interaction content of the current user; the interaction type is experience interaction type or problem consultation type;
a feedback template determining unit, configured to determine a feedback template according to the learning attribute information of the current user;
and the first feedback content determining unit is used for determining feedback content according to the interaction type based on the feedback template.
Optionally, the feedback content determining module includes:
the information content processing unit is used for processing the learning attribute information of the user and/or the interactive content;
the interactive mode determining unit is used for acquiring the interactive mode selected by the user;
and the second feedback content determining unit is used for determining the feedback content according to the processing result and the interactive mode.
Optionally, the second feedback content determining unit includes:
the target user selection subunit is used for selecting a target user from candidate users for online learning according to a processing result if the interaction mode is a drift bottle;
the interactive content sending subunit is used for sending the interactive content to the target user;
and the first feedback content acquisition subunit is used for acquiring the feedback content of the target user on the interactive content.
Optionally, the second feedback content determining unit includes:
the target issuing position selecting subunit is used for selecting a target issuing position for the current user from the candidate issuing position of the learning square according to the processing result if the interaction mode is encouraging;
the interactive content publishing subunit is used for publishing the interactive content at the target publishing position;
and the second feedback content acquisition subunit is used for acquiring the feedback content of other users to the interactive content.
According to an embodiment of the present application, an electronic device and a readable storage medium are also provided.
As shown in fig. 4, fig. 4 is a block diagram of an electronic device for implementing an online learning interaction method according to an embodiment of the present application. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present application that are described and/or claimed herein.
As shown in fig. 4, the electronic apparatus includes: one or more processors 401, memory 402, and interfaces for connecting the various components, including high-speed interfaces and low-speed interfaces. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions for execution within the electronic device, including instructions stored in or on the memory to display graphical information of a GUI on an external input/output apparatus (such as a display device coupled to the interface). In other embodiments, multiple processors and/or multiple buses may be used, along with multiple memories and multiple memories, as desired. Also, multiple electronic devices may be connected, with each device providing portions of the necessary operations (e.g., as a server array, a group of blade servers, or a multi-processor system). In fig. 4, one processor 401 is taken as an example.
Memory 402 is a non-transitory computer readable storage medium as provided herein. Wherein the memory stores instructions executable by at least one processor to cause the at least one processor to perform the method of online learning interaction provided herein. The non-transitory computer readable storage medium of the present application stores computer instructions for causing a computer to perform the method of online learning interaction provided herein.
The memory 402, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the method for online learning interaction in the embodiments of the present application (e.g., the interaction content acquisition module 301 and the feedback content determination module 302 shown in fig. 3). The processor 401 executes various functional applications of the server and data processing by running non-transitory software programs, instructions and modules stored in the memory 402, that is, implements the method of online learning interaction in the above-described method embodiments.
The memory 402 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created from use of the electronic device for online learning interaction, and the like. Further, the memory 402 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, memory 402 optionally includes memory located remotely from processor 401, which may be connected to an online learning interactive electronic device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The electronic device of the method of online learning interaction may further include: an input device 403 and an output device 404. The processor 401, the memory 402, the input device 403 and the output device 404 may be connected by a bus or other means, and fig. 4 illustrates an example of a connection by a bus.
The input device 403 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic device interacting with online learning, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, a pointing stick, one or more mouse buttons, a track ball, a joystick, or other input devices. The output devices 404 may include a display device, auxiliary lighting devices (e.g., LEDs), and haptic feedback devices (e.g., vibrating motors), among others. The display device may include, but is not limited to, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display, and a plasma display. In some implementations, the display device can be a touch screen.
Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, application specific ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
These computer programs (also known as programs, software applications, or code) include machine instructions for a programmable processor, and may be implemented using high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), the internet, and blockchain networks.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service are overcome.
According to the technical scheme of the embodiment of the application, the online learning efficiency of the user is improved, and the online learning experience of the user is enriched.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present application may be executed in parallel, sequentially, or in different orders, and the present invention is not limited thereto as long as the desired results of the technical solutions disclosed in the present application can be achieved.
The above-described embodiments should not be construed as limiting the scope of the present application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims (12)

1. An online learning interaction method, comprising:
responding to an online interaction request initiated by a current user, and acquiring the interaction content of the current user;
and processing the learning attribute information and/or the interactive content of the current user, and determining feedback content according to a processing result.
2. The method of claim 1, wherein the processing the learning attribute information of the current user and/or the interactive content and determining feedback content according to the processing result comprises:
determining an interaction type according to the interaction content of the current user; the interaction type is experience interaction type or problem consultation type;
determining a feedback template according to the learning attribute information of the current user;
and determining feedback content according to the interaction type based on the feedback template.
3. The method of claim 1, wherein the processing the learning attribute information of the user and/or the interactive content and determining feedback content according to the processing result comprises:
processing the learning attribute information and/or the interactive content of the user;
acquiring the interactive mode selected by the user;
and determining feedback content according to the processing result and the interaction mode.
4. The method of claim 3, wherein the determining feedback content according to the processing result and the interaction mode comprises:
if the interaction mode is a drift bottle, selecting a target user from candidate users for online learning according to a processing result;
sending the interactive content to the target user;
and acquiring feedback content of the target user to the interactive content.
5. The method of claim 3, wherein the determining feedback content according to the processing result and the interaction mode comprises:
if the interaction mode is encouraging, selecting a target release position for the current user from candidate release positions of the learning square according to a processing result;
publishing the interactive content at the target publishing location;
and acquiring feedback content of other users to the interactive content.
6. An online learning interaction device, comprising:
the interactive content acquisition module is used for responding to an online interactive request initiated by a current user and acquiring the interactive content of the current user;
and the feedback content determining module is used for processing the learning attribute information of the current user and/or the interactive content and determining feedback content according to a processing result.
7. The apparatus of claim 6, wherein the feedback content determination module comprises:
the interaction type determining unit is used for determining an interaction type according to the interaction content of the current user; the interaction type is experience interaction type or problem consultation type;
a feedback template determining unit, configured to determine a feedback template according to the learning attribute information of the current user;
and the first feedback content determining unit is used for determining feedback content according to the interaction type based on the feedback template.
8. The apparatus of claim 6, wherein the feedback content determination module comprises:
the information content processing unit is used for processing the learning attribute information of the user and/or the interactive content;
the interactive mode determining unit is used for acquiring the interactive mode selected by the user;
and the second feedback content determining unit is used for determining the feedback content according to the processing result and the interactive mode.
9. The apparatus of claim 8, wherein the second feedback content determining unit comprises:
the target user selection subunit is used for selecting a target user from candidate users for online learning according to a processing result if the interaction mode is a drift bottle;
the interactive content sending subunit is used for sending the interactive content to the target user;
and the first feedback content acquisition subunit is used for acquiring the feedback content of the target user on the interactive content.
10. The apparatus of claim 8, wherein the second feedback content determining unit comprises:
the target issuing position selecting subunit is used for selecting a target issuing position for the current user from the candidate issuing position of the learning square according to the processing result if the interaction mode is encouraging;
the interactive content publishing subunit is used for publishing the interactive content at the target publishing position;
and the second feedback content acquisition subunit is used for acquiring the feedback content of other users to the interactive content.
11. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.
12. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-5.
CN202010996240.7A 2020-09-21 2020-09-21 Online learning interaction method, device, equipment and storage medium Pending CN112182343A (en)

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