BACKGROUND

FIELD OF THE DISCLOSURE

Various embodiments of the disclosure relate generally to e-learning platforms. More specifically, various embodiments of the disclosure relate to methods and systems for immersive and interactive approach for facilitating e-learning.

DESCRIPTION OF THE RELATED ART

Technical advancement has enabled availability of various online learning platforms that facilitate virtual education. A known approach for facilitating virtual education includes a virtual classroom setup. The virtual classroom setup includes a plurality of participants including a teacher and multiple students. The teacher is available for teaching the students participating in the virtual classroom. Teaching in the virtual classroom generally progresses based on an average understanding of the students participating in the virtual classroom. However, this approach may not be effective and efficient for every student as each student may have different intelligence level and attitude towards learning.

For example, a student may be a quick learner and may grasp things in less time and with less effort in the virtual classroom. Therefore, the student may get bored with the pace of teaching and may find it not interesting, and hence may lose interest in the classroom. Thus, such approach of teaching may not be optimal for the student and may hinder his/her progress and development. In another exemplary scenario, a student may have below average intelligence and may require additional time to understand and grasp things. Therefore, the student may sometimes lag behind or get confused during the virtual classroom teaching. Consequently, the student may not be able to understand further related topics being taught in the virtual classroom. Hence, the student may lose interest in study and his/her academic performance may deteriorate. Also, the student may need extra help (such as personal tuitions) with studies which may not be affordable to the student. Moreover, such an approach for learning necessitates presence of a trained teacher participating in the virtual classroom to teach the students. However, availability of the teacher may not be possible at all times and also may not be affordable to all which may put barriers in the path of learning.

Another known solution for providing virtual education includes online modules that can be open sourced or may be subscription based. Such online modules may be used by the students to leam various concepts. Such an approach does not require presence of a teacher for teaching the concepts. However, use of such online modules may not be optimal as each student may perceive a notion of the module in accordance with his/her own understandability. Hence, the students may end up taking too long to learn the concepts or may have an incorrect understanding of the concepts.

Thus, the existing online learning platforms do not allow students to participate in the classroom or collaborate in various group activities such as projects, discussions, or the like. Such inability of the online learning platforms to provide participatory and collaborative learning prevents the students from practicing most efficient and effective ways of learning.

In light of the foregoing, there exists a need for a technical and reliable solution that overcomes the abovementioned problems, and ensures a seamless and efficient approach for facilitating online learning.

SUMMARY

Systems for facilitating interactive e-learning are provided substantially as shown in, and described in connection with, at least one of the figures, as set forth more completely in the claims.

These and other features and advantages of the present disclosure may be appreciated from a review of the following detailed description of the present disclosure, along with the accompanying figures in which like reference numerals refer to like parts throughout.

BRIEF DESCRIPTION OF DRAWINGS FIG. 1 is a block diagram that illustrates a system environment for an e-learning system, in accordance with an exemplary embodiment of the disclosure;

FIG. 2 is a block diagram that illustrates an application server of FIG. 1, in accordance with an exemplary embodiment of the disclosure;

FIGS. 3A-3C are schematic diagrams that collectively illustrate an exemplary scenario for facilitating interactive e-leaming, in accordance with an exemplary embodiment of the disclosure;

FIGS. 4A-4C are schematic diagrams that collectively illustrate implementation of a supplementary memory, in accordance with an exemplary embodiment of the disclosure; and

FIG. 5 is a block diagram that illustrates a system architecture of a computer system for facilitating e-learning, in accordance with an exemplary embodiment of the disclosure.

DETAILED DESCRIPTION OF EMBODIMENTS

Certain embodiments of the disclosure may be found in disclosed systems and methods for facilitating interactive e-learning. Exemplary aspects of the disclosure provide systems for facilitating e-learning as well as online teaching. The systems include a server (for example, an application server) that executes various operations to facilitate e-learning and e-teaching. In an embodiment, an e-learning system (also referred to as “online learning system”) includes a data storage, a search engine, and a processor. The data storage is configured to store a knowledgebase including a collection of a plurality of lessons. The plurality of lessons exhibit a uniform format each including a plurality of sections. The search engine is configured to search in the knowledgebase for one or more lessons of the plurality of lessons that correlate to a context of a first user query. The processor is configured to render, via a user device of a first user, a first interactive graphical user interface (GUI) that displays a list of the one or more lessons for user selection. The processor is further configured to render, via the user device, a second interactive GUI that displays a transitive view of a first lesson selected from the list. The transitive view transitions between the plurality of sections of the first lesson as per a progress of the first user in the first lesson. The plurality of sections of the first lesson includes a first section that includes an introduction to the first lesson. The plurality of sections of the first lesson further includes a second section that includes a cognitive map that illustrates one or more concepts encompassed by the first lesson. The plurality of sections of the first lesson further includes a third section that includes a description of each concept of the one or more concepts. The plurality of sections of the first lesson further includes a fourth section that enables revision of the first lesson by way of participation in one or more virtual group discussions. The plurality of sections of the first lesson further includes a fifth section that enables execution of the first lesson. The execution of the first lesson includes creation of a new lesson by the first user on a same topic as the first lesson. The new lesson is a learning result of the first user and is stored in the knowledgebase for a future reference by the first user or one or more second users.

In an embodiment, the search engine is further configured to rank the one or more lessons in an order based on one of a feedback associated with each of the one or more lessons, a category associated with an author of each lesson, a count of views on each lesson, and a user profile of the first user. The one or more lessons in the list are displayed in the order of ranking.

In an embodiment, the introduction to the first lesson includes one of a context of the first lesson, a narrative of the first lesson, and a conclusion of the first lesson.

In an embodiment, the cognitive map is a graphical structure that summarizes the first lesson and is indicative of multi-level associations between the one or more concepts encompassed by the first lesson.

In an embodiment, the description of each concept of the one or more concepts includes at least one of a definition of each concept, one or more practical applications of each concept, and a correlation of each concept with remaining concepts of the one or more concepts.

In an embodiment, the processor is further configured to receive a feedback of the first user on the first lesson. The feedback is one of a textual comment, a score, and a graphical character. The ranking of the first lesson in response to a second user query is based on the feedback of the first user.

In an embodiment, the processor is further configured to control creation and management of one or more virtual discussion rooms for the one or more virtual group discussions. In an embodiment, the execution of the first lesson further includes simulation of one or more experiments pertaining to the one or more concepts encompassed by the first lesson and a creation of a new virtual discussion room for the first lesson. The first user is a host of the new virtual discussion room and one or more second users interested in the first lesson join the new virtual discussion room for a group discussion on the first lesson.

In an embodiment, the processor is further configured to store, in the data storage, one of experimental data, a set of audio notes, a set of video notes, a set of textual notes, data associated with the one or more virtual group discussions participated by the first user, and the first lesson, for future reference by the first user.

In an embodiment, the processor is further configured to recommend to the first user, a second lesson of the plurality of lessons that is to be accessed in a sequence with the first lesson.

The methods and systems of the disclosure provide a solution for independent learning of an individual. The disclosed methods and systems provide for an efficient approach for online education that allows for persistent learning. Further, the disclosed methods and systems allow an individual to adapt to a personalized pace and approach for learning. The disclosed methods and systems also provide the individual with a ranked list of lessons that is relevant to the individual. Therefore, the individual does not require to make efforts for searching the relevant lesson. The disclosed methods and systems also allow the individual to create a new lesson for future reference. The disclosed methods and systems also allow the individual to keep the new lesson for personal use or share the new lesson with others, thereby allowing the individual to follow “learn by teaching” approach for learning which makes the learning persistent and long lasting. Moreover, the disclosed methods and systems allow the individual to perform one or more experiments associated with the lesson. Therefore, the individual may gain practical knowledge of the lesson while learning the lesson online. Moreover, the disclosed methods and systems allow the individual to participate in virtual group discussions associated with the lesson. Therefore, the individual may get clarity regarding the lesson as well as the individual may learn and share his/her knowledge with participants of the group discussion. Hence, the disclosed methods and systems allow for participatory and collaborative learning approach that efficient and effective for facilitating independent learning. FIG. 1 is a block diagram that illustrates a system environment 100 for an online learning system 102, in accordance with an exemplary embodiment of the disclosure. The system environment 100 includes a database server 104 and an application server 106 that constitute the online-learning system 102. The system environment 100 further includes a communication network 108, first through third user devices 110-114, and first through third users 116-120 associated with corresponding first through third user devices 110-114. Hereinafter, the terms “online learning system 102” and “e-learning system 102” are interchangeably used.

The database server 104 may include suitable logic, circuitry, interfaces, and/or code, executable by the circuitry, that may be configured to perform one or more operations for collecting and storing a plurality of lessons that form a knowledgebase 122. In an embodiment, the plurality of lessons may be created by the first through third users 116-120. In another embodiment, the plurality of lessons may be created by one or more experts of a domain associated with each of the plurality of lessons. Examples of the database server 104 may include a cloud-based database, a local database, a distributed database, a database management system (DBMS), or the like. The database server 104 may be used as data storage for the online learning system 102.

The knowledgebase 122 refers to a collection of the plurality of lessons that may be used by the first through third users 116-120 for e-learning. Further, each lesson of the plurality of lessons may encompass one or more concepts and may include a plurality of sections pertaining to the one or more concepts of the corresponding lesson. The plurality of sections may be used by the first through third users 116-120 for e-learning. The plurality of lessons in the knowledgebase 122 may have a uniform format i.e., all the lessons have an identical layout for describing the corresponding concepts. Further, each lesson may have an identical sequence for transitioning among the plurality of sections of the corresponding lesson. A lesson refers to a collection of information associated with a domain, a topic, or a concept. The lesson is created with an objective of knowledge transfer among users of the e-learning system 102. The lesson may include the information in form of video, audio, text, images, or the like.

The database server 104 may be communicatively coupled to the application server 106 via the communication network 108. Examples of the communication network 108 may include, but are not limited to, a wireless fidelity (Wi-Fi) network, a light fidelity (Li-Fi) network, a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a satellite network, the Internet, a fiber optic network, a coaxial cable network, an infrared (IR) network, a radio frequency (RF) network, and a combination thereof. Various entities (such as the first through third user devices 110-114, the database server 104, and the application server 106) in the system environment 100 may be coupled to the communication network 108 in accordance with various wired and wireless communication protocols, such as Transmission Control Protocol and Internet Protocol (TCP/IP), User Datagram Protocol (UDP), Long Term Evolution (LTE) communication protocols, or any combination thereof.

The first through third user devices 110-114 may include suitable logic, circuitry, interfaces, and/or code, executable by the circuitry, that may be configured to perform one or more operations for using various services offered by the e-learning learning system 102. In one embodiment, the first through third user devices 110-114 may be exclusive to respective first through third users 116- 120. In another embodiment, each of the first through third user devices 110-114 may be shared among the first through third users 116-120. Examples of the first through third user devices 110- 114 may include a cell-phone, a laptop, a tablet, a phablet, a desktop, a computer, or the like. It will be apparent to a person skilled in the art that the e-learning system 102 may be used with a plurality of device. For sake of brevity, three user devices i.e., a cellphone 110, a laptop 112, and a tablet 114 are shown as the first through third user devices 110-114. However, in other embodiments, the first through third user devices 110-114 may be other devices such as a personal computer, a phablet, or the like.

The first through third user devices 110-114 may be configured to be controlled by the application server 106. The first through third user devices 110-114 may be controlled by the application server 106 to present various graphical user interfaces (GUI) to the respective first through third users 116-120 for facilitating e-learning. In one example, the first through third user devices 110-114 may be configured to present a GUI of a search engine to the respective first through third users 116-120. The GUI of the search engine may allow the respective first through third users 116-120 to submit (or provide) a user query including keyword(s). The keyword(s) of the user query may refer to a domain, a lesson, a concept, or the like. Based on the user query submitted via the presented GUI, the search engine may be configured to search in the knowledgebase 122 for various lessons of the plurality of lessons that correlate to a context of the user query. In an embodiment, the user query may be a textual input. In another embodiment, the user query may be received in form of speech data (i.e., audio data) including words uttered by the corresponding first through third users 116-120.

For sake of brevity, the ongoing description is described from perspective of the first user device 110. However, in other embodiments, the e-learning system 102 may be accessed on other devices (e.g., the second and third user devices 112 and 114) in a similar manner as described for the first user device 110.

The application server 106 may include suitable logic, circuitry, interfaces, and/or code, executable by the circuitry, that may be configured to perform one or more operations for realizing the e- learning system 102. The application server 106 may act as a processor that performs one or more operations for realizing the e-learning system 102. In another embodiment, the application server 106 may include a processor (shown in FIG. 2) that performs the one or more operations for realizing the e-learning system 102. The application server 106 may be a cloud-based server or a local processor. Upon receiving a first user query via the first user device 110 associated with the first user 116, the application server 106 processes the first user query to determine a context of the first user query. The application server 106 may be configured to render, via the first user device 110, a first interactive GUI that displays a list of lessons that correlate with the context of the first user query, for user selection. The application server 106 may be configured to rank the lessons that correlate with the context of the first user query in an order based on one of a feedback associated with each of the one or more lessons, a category associated with an author of each lesson, a count of views on each lesson, and a user profile of the first user 116. The one or more lessons in the list are displayed in the order of ranking.

The application server 106 may further render, via the first user device 110, a second interactive GUI that displays a transitive view of a first lesson selected from the list. The transitive view transitions between the plurality of sections of the first lesson as per a progress of the first user 116 in the first lesson. The plurality of sections of the first lesson include a first section, a second section, a third section, a fourth section, and a fifth section. The first section includes an introduction to the first lesson. The introduction to the first lesson includes one of a context of the first lesson, a narrative of the first lesson, and a conclusion of the first lesson. The second section includes a cognitive map that illustrates one or more concepts encompassed by the first lesson. The cognitive map is a graphical structure that summarizes the first lesson and is indicative of multi-level associations between the one or more concepts encompassed by the first lesson. The third section includes a description of each concept of the one or more concepts. The description of each concept of the one or more concepts includes one of a definition of each concept, one or more practical applications of each concept, and a correlation of each concept with remaining concepts of the one or more concepts. The fourth section enables revision of the first lesson by way of participation in one or more virtual group discussions. The fifth section enables execution of the first lesson. The execution of the first lesson includes creation of a new lesson by the first user 116 on a same topic as the first lesson. The new lesson is a learning result of the first user 116 and is stored in the knowledgebase 122 for a future reference by the first user 116 or one or more second users (such as second user 118 and third user 120). In an embodiment, the new lesson may act as a supplementary memory for the first user 116. For a new lesson to be used as the supplementary memory, the new lesson may include user derived correlations among two or more concepts, two or more lessons, and/or a concept and a lesson during the learning. The execution of the first lesson further includes simulation of one or more experiments pertaining to the one or more concepts encompassed by the first lesson and a creation of a new virtual discussion room for the first lesson. The first user 116 is a host (or a teacher) of the new virtual discussion room and the one or more second users interested in the first lesson join the new virtual discussion room for a group discussion on the first lesson.

The application server 106 is further configured to receive a feedback of the first user 116 on the first lesson. The feedback is one of a textual comment, a score, and a graphical character. The ranking of the first lesson in response to a second user query is based on the feedback of the first user 116. The application server 106 is further configured to control creation and management of one or more virtual discussion rooms for the one or more virtual group discussions. The application server 106 is further configured to store, in the data storage i.e., the database server 104, one of experimental data, a set of audio notes, a set of video notes, a set of textual notes, data associated with the one or more virtual group discussions participated by the first user 116, and the first lesson, for future reference by the first user 116. The application server 106 is further configured to recommend to the first user 116, a second lesson of the plurality of lessons that is to be accessed in a sequence with the first lesson. The e-learning system 102 may be accessed by the first user 116 via a web-application or a mobile- application running on the first user device 110. The web-application or a mobile-application may be hosted and controlled by the application server 106. In one embodiment, the first user 116 may be required to register with the application server 106 for accessing the e-learning system 102. For registration, the first user 116 may be required to create a user profile and provide his/her user preferences when the e-learning system 102 is accessed for the first time on the first user device 110 via the web-application or the mobile-application.

FIG. 2 is a block diagram that illustrates the application server 106 of FIG. 1, in accordance with an exemplary embodiment of the disclosure. The application server 106 includes the search engine (hereinafter, referred to and designated as “the search engine 202”), the processor (hereinafter, referred to and designated as “the processor 204”), a retainer tool 206, a simulation tool 208, a renderer tool 210, and a recommendation tool 212. The application server 106 further includes a collaboration tool 214, a video processor 216, a natural language processor 218, a memory 220, an audio processor 222, a network interface 224, a machine learning engine 226, and a feedback tool 228.

The search engine 202 may include suitable logic, circuitry, interfaces, and/or code, executable by the circuitry, that may be configured to perform one or more operations for facilitating e-learning. The search engine 202 may be configured to receive various inputs from user devices, for example, the first user query from the first user device 110. The search engine 202 may be further configured to analyze the received user query to determine a domain and a context associated therewith. Based on the determined domain and context of the user query, the search engine 202 may be configured to access the knowledgebase 122 to retrieve the lessons that correlate to the determined domain and context of the user query. Further, the search engine 202 may be configured to rank the retrieved lessons based on one of the feedback associated with each of the retrieved lessons, a category associated with an author of each retrieved lesson, a count of views on each retrieved lesson, and a user profile of the first user 116. In one embodiment, the retrieved lessons are ranked based on the feedback associated therewith. In such embodiment, the feedback may be provided in form of a rating (such as a numerical rating, an alphabetical rating, a symbolical rating, and/or the like). Further, a lesson having a higher rating may be ranked higher than another lesson having a lower rating. In another embodiment, the retrieved lessons may be ranked based on the category associated with the author of each retrieved lesson. The category associated with the author of each lesson may be one of a poet, a novelist, a satirist, a short story writer, a librettist, a lyricist, a playwright, a screenwriter, a student, a researcher, a domain expert, a teacher, and/or the like. In such an embodiment, a lesson authored by a student may be ranked higher that another lesson authored by a researcher as the lesson authored by the researcher may be of higher learning value than another lesson authored by the student. In another embodiment, the retrieved lessons may be ranked based on a count of views on each lesson. In such an embodiment, a lesson having a greater count of views may be ranked higher than another lesson having a lower count of views. In another embodiment, the retrieved lessons may be ranked based on the user profile of the first user 116 who had submitted the user query. In such an embodiment, a lesson having a context similar to a user preference of the first user 116 may be ranked higher than another lesson that has a context that is different from the user preference. In an embodiment, the retrieved lessons may be ranked based on neural coupling of the lesson with the first user 116. The neural coupling of a lesson with a user (for example, the first user 116) may be indicative of suitability and efficiency of the lesson for learning of the first user 116. The neural coupling of the retrieved lessons with the first user 116 may be determined based on one of a feedback received from the first user 116, a survey filled by the first user 116, and a new lesson created by the first user 116. In an embodiment, the neural coupling of each retrieved lesson with the first user 116 may be determined based on one or more artificial intelligence techniques, neural network algorithms, or the like. The search engine 202 may be further configured to display, via the first user device 110, list of the retrieved lessons in the order of ranking. Beneficially, such ranking of the retrieved lessons makes it convenient for the first user 116 to identify most relevant lessons. Hence, the search engine 202 enables the first user 116 to find relevant lessons by spending significantly less time and effort and without going through each lesson in the knowledgebase 122 to determine relevance thereof.

The processor 204 may include suitable logic, circuitry, interfaces, and/or code, executable by the circuitry, that may be configured to execute the instructions stored in the memory 220 to perform various operations for facilitating the e-learning. The processor 204 may be configured to perform various operations associated with data collection, data processing, data retrieval, and data presentation. It will be apparent to a person of ordinary skill in the art that the processor 204 may be compatible with multiple operating systems. The processor 204 may be configured to render, via the first user device 110, the first interactive GUI that displays the ranked list of the retrieved lessons for user selection. The processor 204 may further render, via the first user device 110, the second interactive GUI that displays a transitive view of a first lesson selected from the ranked list. The transitive view transitions between the plurality of sections of the first lesson as per a progress of the first user 116 in the first lesson. The plurality of sections of the first lesson include the first section, the second section, the third section, the fourth section, and the fifth section.

In one embodiment, a transitive view of a lesson refers to a progressive view which progresses based on a learning of a user (e.g., the first user 116). The transitive view transitions among the first through fifth sections of a lesson as per the progress. For example, the transitive view transitions from the first section to the second section when the first user 116 finishes understanding and learning of the first section. In one embodiment, the transitive view transitions among sections based on a command or an instruction received from the first user 116. In an embodiment, the transitive view may transition between the first through fifth sections based on a time threshold defined by the first user 116. In one example, a user may have allocated “48 hours” for each section of a lesson. Therefore, a transitive view of the lesson may transition from one section to another every “48 hours”. In an embodiment, the processor 204 may be configured to record and analyze a time spent by the first user 116 on each section of the lesson. Based on such analysis, the processor 204 may be configured to interpret understanding and grasping ability of the first user 116. Based on such interpretation, the processor 204 may be configured to maintain a statistical report of the progress of the first user 116.

The retainer tool 206 may include suitable logic, circuitry, interfaces, and/or code, executable by the circuitry, that may be configured to store data, a link, or an address associated with various lessons stored by a user (e.g., the first user 116) for future reference. In one embodiment, the retainer tool 206 may be configured to store data, a link, or an address associated with one or more new lessons created by a user (e.g., the first user 116). In an embodiment, the retainer tool 206 may be further configured to obtain user information for creating a user profile of the first user 116. The retainer tool 206 may be configured to store the user information, organized to form the user profile of the first user 116, in the data storage i. e. , the database server 104. In an embodiment, the retainer tool 206 may be configured to implement the supplementary memory for the first through third users 116-120 that is persistent and accessible. The supplementary memory for the first user 116 may refer to a collection of audio, video, and textual notes, lessons learnt by the first user 116, and one or more new lessons created by the first user 116. The supplementary memory for the first user 116 may be further configured to store a correlation and additional derivations observed by the first user 116 between the learnt lessons, the created lessons, the audio, video, and textual notes. In one example, the first user 116 may have learnt a lesson “Cellular structure of humans”. The first user 116 may have also leamt another lesson “Animal cell”. The first user 116, based on his/her learning experience of both the lessons, may establish a correlation therebetween. The first user 116 may also store a set of notes (audio, video, or textual notes) associated with the correlation between both the lessons in the supplementary memory. The supplementary memory may be included in the memory 220 or the database server 104. The first user 116 may access the supplementary memory periodically in order make modifications therein to reflect his/her recent learnings. In other words, the supplementary memory may serve as a second brain of the first user 116 that continues to evolve and grow as per the learning of the first user 116 on the e-learning system 102.

The simulation tool 208 may include suitable logic, circuitry, interfaces, and/or code, executable by the circuitry, that may be configured to imitate a practical experiment or application of one or more concepts associated with a corresponding lesson. The simulation tool 208 may be configured to create a simulation environment which facilitate execution of one or more scientific and/or practical applications associated with the one or more concepts. In one example, a lesson may include a concept associated with a chemical reaction between “hydrochloric acid” and “sulfuric acid”. Therefore, the simulation tool 208 may be configured to create a simulation environment for imitating execution of the chemical reaction between “hydrochloric acid” and “sulfuric acid”.

The Tenderer tool 210 may include suitable logic, circuitry, interfaces, and/or code, executable by the circuitry, that may be configured to present, via the first user device 110, a user interface for presenting the first interactive GUI and the second interactive GUI, and a user selected lesson e.g., the first lesson. The Tenderer tool 210 may be configured to facilitate and control transitive views of lessons being displayed on the first user device 110. The Tenderer tool 210 may be further configured to present the simulation environment, generated by the simulation tool 208, to the first user 116 via the first user device 110. The recommendation tool 212 may include suitable logic, circuitry, interfaces, and/or code, executable by the circuitry, that may be configured to provide one or more lessons as recommendation to the first user 116 prior to or after completing a selected lesson. The recommendation tool 212 may be configured to provide the recommendation based on a correlation between the selected lesson and the recommended lessons. In one embodiment, the recommendation tool 212 may be configured to recommend the lessons based on a learning pattern of the first user 116. In one embodiment, the recommendation tool 212 may be further configured to recommend a sequence in which the recommended lessons are to be learned. For example, the recommendation tool 212 may be configured to recommend a lesson that is to learned in a sequence with a current lesson (for example, the first lesson).

The collaboration tool 214 may include suitable logic, circuitry, interfaces, and/or code, executable by the circuitry, that may be configured to facilitate a collaborative learning (i.e., participatory learning) among the first through third users 116-120. The collaboration tool 214 may allow the first through third users 116-120 to collaborate with each other to improve their learning. The collaboration tool 214 may be further configured to facilitate a workspace where each of the first through third users 116-120 may contribute and create a new lesson. The collaboration tool 214 may further allow each of the first through third users 116-120 to create new virtual discussion rooms for virtual group discussion on a lesson or to join existing virtual discussion rooms for group discussion. Each virtual discussion room may be associated with a concept or a lesson, such that the associated concept or lesson is the subject of a virtual group discussion in the corresponding virtual discussion room. In an embodiment, an invitation to join a virtual discussion room created by the first user 116 may be sent by the first user 116 to the second and third users 118 and 120, who may be learning a concept or lesson similar to the first user 116.

The video processor 216 may include suitable logic, circuitry, interfaces, and/or code, executable by the circuitry, that may be configured to process an image or video to obtain filtered and optimized version of the image or video. The video processor 216 may be configured to process images and videos in the plurality of lessons to obtain an optimized version of each of the plurality of lessons. The video processor 216 may be further configured to facilitate a video presentation of a group discussion being participated by the first through third users 116-120. The video processor 216 may be further configured to present, via the first through third user devices 110-114, a live stream of various virtual group discussions. The video processor 216 may be further configured to compress image data and video data of the virtual group discussions.

The natural language processor 218 may include suitable logic, circuitry, interfaces, and/or code, executable by the circuitry, that may be configured to process speech data associated with the user query (i.e., audio user query). The natural language processor 218 may be further configured to identify one or more keywords from the speech data associated with the user query. The identified one or more keywords and their corresponding context is communicated to the search engine 202. Based on the identified one or more keywords, the search engine 202 may retrieve the one or more lessons that are relevant and have a context that correlates with the identified keywords of the user query. In one embodiment, the natural language processor 218 may be configured to process audio data associated with the virtual group discussion. Based on the processed audio data, the natural language processor 218 may be configured to create a set of notes associated with lesson or concept discussed during the virtual group discussion. In an embodiment, the natural language processor 218 may be configured to process the audio data that has already been processed by the audio processor 222. Hence, the natural language processor 218 may receive unambiguous and noiseless data.

The memory 220 may include suitable logic, circuitry, and interfaces that may be configured to store one or more instructions which when executed by the processor 204 cause the processor 204 to perform various operations for facilitating e-learning. The memory 220 may also be referred act as the data storage of the e-learning system 102. In such an embodiment, the memory 220 may be configured to store the knowledgebase 122. The memory 220 may be accessible by the search engine 202, the processor 204, the retainer tool 206, the simulation tool 208, the Tenderer tool 210, the recommendation tool 212, the collaboration tool 214, the video processor 216, the natural language processor 218, the audio processor 222, the network interface 224, the machine learning engine 226, and the feedback tool 228. Examples of the memory 220 may include, but are not limited to, a random-access memory (RAM), a read only memory (ROM), a removable storage drive, a hard disk drive (HDD), a flash memory, a solid-state memory, or the like. It will be apparent to a person skilled in the art that the scope of the disclosure is not limited to realizing the memory 220 in the application server 106, as described herein. In some embodiments, the memory 220 may be realized in form of a database or a cloud storage working in conjunction with the application server 106, without departing from the scope of the disclosure.

The audio processor 222 may include suitable logic, circuitry, interfaces, and/or code, executable by the circuitry, that may be configured to perform one or more operations for processing the speech data received as the user query. The output of the audio processor 222 may be used to optimize and enhance working of the natural language processor 218. The audio processor 222 may further process speech data associated with the virtual group discussion to eliminate noise present therein. Therefore, the first through third users 116-120 are presented with clear and unambiguous audio. The audio processor 222 may apply one or more audio processing algorithms on the audio data. Examples of the audio processing algorithm may include, but is not limited, digital signal processing (DSP) technique. It will be apparent to a person skilled in the art that the speech data may be processed by applying any audio processing technique known in the art.

The network interface 224 may include suitable logic, circuitry, interfaces, and/or code, executable by the circuitry, that may be configured to enable the application server 106 to communicate with the database server 104, and user devices (for example, first through third user devices 110-114). The network interface 224 may be implemented as a hardware, software, firmware, or a combination thereof. Examples of the network interface 224 may include a network interface card, a physical port, a network interface device, an antenna, a radio frequency transceiver, a wireless transceiver, an Ethernet port, a universal serial bus (USB) port, or the like.

The machine learning engine 226 may include suitable logic, circuitry, interfaces, and/or code, executable by the circuitry, that may be configured to perform one or more operations for facilitating e-learning. The machine learning engine 226 may be further configured to identify a trend or pattern in learning of the first through third users 116-120. The machine learning engine 226 may provide user information to the recommendation tool 212 based on which the recommendation tool 212 may recommend the one or more lessons to the first through third users 116-120. In an embodiment, the machine learning tool 226 may be further configured to customize a format (i.e. , a layout) of lessons based on a requirement and habits of the first through third users 116-120. The machine learning engine 226 may apply one or more machine learning algorithms and/or techniques for operations thereof. Examples of the machine learning algorithms and/or techniques may include, but are not limited to, Linear Regression, Logistic Regression, k-nearest neighbors algorithm, neural networks, and the like.

The feedback tool 228 may include suitable logic, circuitry, interfaces, and/or code, executable by the circuitry, that may be configured to perform one or more operations for facilitating e-learning. The feedback tool 228 may be configured to receive user experience associated with one or more lessons that the first through third users 116-120 have leamt. The feedback tool 228 may be configured to communicate information, based on the user experience, to the recommendation tool 212, regarding a preference and interest of the first through third users 116-120.

The search engine 202, the processor 204, the retainer tool 206, the simulation tool 208, the render er tool 210, the recommendation tool 212, the collaboration tool 214, the video processor 216, the natural language processor 218, the audio processor 222, the machine learning engine 226, and the feedback tool 228 may be implemented by one or more processors, such as, but not limited to, an application-specific integrated circuit (ASIC) processor, a reduced instruction set computing (RISC) processor, a complex instruction set computing (CISC) processor, and a field- programmable gate array (FPGA) processor. The one or more processors may also correspond to central processing units (CPUs), graphics processing units (GPUs), network processing units (NPUs), digital signal processors (DSPs), or the like.

FIGS. 3A-3C are schematic diagrams that collectively illustrate an exemplary scenario 300 for facilitating e-learning on a user device using the e-leaning system 102, in accordance with an exemplary embodiment of the disclosure.

For sake of brevity, FIGS. 3A-3C are described with respect to the first user device 110 and the first user 116. It will be apparent to a person of ordinary skill in the art that the e-leaning system 102 may enable e-learning on the second and third user devices 112 and 114 in a similar manner as described for the first user device 110.

Referring to FIG. 3 A, at 302, a search GUI rendered on a display of the first user device 110 is illustrated. The rendering of the search GUI is controlled by the search engine 202 of the application server 106. The search GUI facilitates receiving of the first user query of the first user 116. The search GUI includes a text box 302a and an audio input button 302b that enables the first user 116 to submit the first user query. The text box 302a may act as a search field, where a textual input including one or more keywords, a topic, a domain, and/or a concept may be submitted for searching. Examples of the keywords may include “coagulation”, “blood”, or the like. Examples of a topic may include “coagulation of blood”, or the like. Examples of a domain may include “biology”, or the like. Examples of a concept may include “coagulation”, or the like. The audio input button 302b upon selection may activate a microphone of the first user device 110 and enable the first user 116 to submit the first user query in form of speech data (i.e., audio data) captured by the microphone. In a non-limiting example, it is assumed that the first user query “SOIL” is received in the text box 302a.

At 304, the first GUI rendered on a display of the first user device 110 is illustrated. The first interactive GUI may present various search results retrieved by the search engine 202 based on the first user query “SOIL”. The search engine 202 may be configured to search in the knowledgebase 122 (shown in FIG. 1) for various lessons that correlate with the context of the first user query. For example, the search engine 202 may search among the plurality of lessons stored in the knowledgebase 122 to identify those lessons that correlate with the context of the keyword “SOIL”. Based on the search, the search engine 202 may identify that three lessons (“Introduction to soil”, “Soil and its types”, and “Soil explained”) stored in the knowledgebase 122 correlate with the keyword “SOIL”. The processor 204, in conjunction with the Tenderer tool 210, may be configured to display the first interactive GUI, via the first user device 110, to display the list of the identified lessons (search results) for user selection.

In an embodiment, the search engine 202 may rank the identified lessons (i.e., relevant lessons or search results) based on one of the feedback associated with each of the identified lessons, the category associated with the author of each identified lesson, the count of views on each identified lesson, and the user profile of the first user 116 (as described in FIG. 2). Thus, the identified lessons in the list are displayed in the order of raking. As shown at 304 in FIG. 3 A, the first interactive GUI displays the list of lessons “Introduction to soil”, “Soil explained”, and “Soil and its types” in the order of ranking. Upon displaying the search results via the first interactive GUI, the processor 204 receives a user selection (as shown with a rectangular box 304a) of the lesson “Soil and its types”. The user selection may be performed on the first user device 110 by the first user 116. At 306, the second GUI rendered on the display of the first user device 110 is illustrated. The processor 204, in conjunction with the Tenderer tool 210, may be configured to render the second interactive GUI based on the received user selection. The second interactive GUI displays the transitive view of a first lesson (i.e., “Soil and its types”) selected from the list by the first user 116. The second interactive GUI may have a vertical scrollbar 306a which facilitates a top-to bottom and a bottom-to-top scrolling of the first lesson to view its content. The second interactive GUI may further have a horizontal scrollbar 306b which facilitates a left-to right and a right-to- left scrolling of the first lesson to view its content. At 306, the second interactive GUI is shown to display, in the transitive view, the first section of the first lesson “Soil and its types”. The first section includes an introduction to the first lesson “Soil and its types”. The first section may include general introduction to various concepts and definitions included in the first lesson “Soil and its types”. As shown at 306, the first section of the first lesson includes an introduction to “soil”. The introduction of the first lesson includes one of a context of the first lesson, a narrative of the first lesson, and a conclusion of the first lesson. The first section serves as an anchor to the purpose and context of the first lesson in cognition with the first user 116.

At 308, the second interactive GUI, displaying the second section of the first lesson, is illustrated. The transitive view of the first lesson “Soil and its types” transitions from the first section to the second section, when the first section is finished or completed by the first user 116. In other words, the transitive view of the first lesson “Soil and its types” transitions from the first section to the second section based on the progress of the first user 116 in the first section. In an embodiment, the first section is assumed to be finished after a specific time threshold set by the first user 116. In another embodiment, the first section is assumed to be finished when the first user 116 scrolls to the bottom of the first section using the vertical scrollbar 306a. In another embodiment, the first section is assumed to be finished when the first user 116 selects a finish button or a next section button (not shown) present at the bottom of the first section to indicate a completion of the first section. The second section may include a cognitive map 308a that illustrates the concepts encompassed by the first lesson “Soil and its types”. The cognitive map 308a may also be referred to as a mind map. The cognitive map 308a may refer to a graphical representation of the concepts included in the first lesson “Soil and its types”. Beneficially, the cognitive map 308a including figures, symbols, graphs, tables, and/or the like may significantly increase persistence of learning for the first user 116. The cognitive map 308a may significantly increase a pace of learning for the first user 116. The cognitive map 308a significantly increases clarity with regard to the concepts included in the first lesson. The cognitive map 308a may present multi-level relations between the concepts of the first lesson in a simple and understandable fashion. The multi-level relationship between the concepts refers to direct and indirect relationships of each concept with other concepts included in the first lesson. In other words, the cognitive map 308a is a graphical structure that summarizes the first lesson and is indicative of multi-level associations between the concepts (e.g., soil types and particle size) encompassed by the first lesson.

In a non-limiting example, as shown at 308, the cognitive map 308a indicates various concepts associated with soil such as “Soil Types”, “Composition of soil”, “Residual Soil”, “Particle Size”, “Soil Erosion”, and “Percolation”. The cognitive map 308a further indicates that “Soil Types” include “Chalk”, “Silt”, “Sandy”, “Clay”, and “Peat”. The cognitive map 308a also indicates the “Particle Size” of “Soil” may be “Fine”, “Medium”, and “Coarse”. The cognitive map 308a further indicates that the particle size of “clay” soil is “fine” and the particle size of “sandy” soil may be “fine”, “medium”, or “coarse”, thereby indicating a multi-level relationship among the concepts.

At 310, the second interactive GUI, displaying the third section of the first lesson, is illustrated. The transitive view of the first lesson “Soil and its types” transitions from the second section to the third section, when the second section is finished or completed by the first user 116. In other words, the transitive view of the first lesson “Soil and its types” transitions from the second section to the third section based on the progress of the first user 116 in the second section. In an embodiment, the second section is assumed to be finished after a specific time threshold set by the first user 116. In another embodiment, the second section is assumed to be finished when the first user 116 scrolls to the bottom of the second section. In another embodiment, the second section is assumed to be finished when the first user 116 selects a finish button or a next section button (not shown) present at the bottom of the second section to indicate a completion of the second section. The third section includes the description of the first lesson. The description includes a detailed and understandable explanation of the concepts included in the first lesson. The third section may include a vertical scrollbar 310a to navigate top-to-bottom and bottom -to-top of the third section. The third section may further include a horizontal scrollbar 310b to navigate right- to-left and left- to-right of the third section. The description of each concept of the first lesson includes a definition of each concept, one or more practical applications of each concept, and a correlation of each concept with remaining concepts of the first lesson. In a non-limiting example, as shown at 310, the description includes information describing various “Components of soil” and “Types of soil”.

At 312, the second interactive GUI, displaying the fourth section of the first lesson, is illustrated. The transitive view of the first lesson “Soil and its types” transitions from the third section to the fourth section, when the third section is finished or completed by the first user 116. In other words, the transitive view of the first lesson “Soil and its types” transitions from the third section to the fourth section based on the progress of the first user 116 in the third section. In an embodiment, the third section is assumed to be finished after a specific time threshold set by the first user 116. In another embodiment, the third section is assumed to be finished when the first user 116 scrolls to the bottom of the second section. In another embodiment, the third section is assumed to be finished when the first user 116 selects a finish button or a next section button (not shown) present at the bottom of the third section to indicate a completion of the third section. The fourth section, in the transitive view of the first lesson, displays a summary (or crux) of the first lesson. The fourth section enables revision of the first lesson by way of a brief description of keywords and the concepts included in the first lesson. The summary presented in the fourth section allows the first user 116 to brush up his/her learning from the previous sections. The summary presented in the fourth section may include highlights of the previous sections which may help the first user 116 by providing crisp and effective notes.

At 314, the second interactive GUI, displaying the fourth section of the first lesson, is illustrated. The transitive view of the first lesson “Soil and its types” transitions from the summary to virtual discussion, when the summary is finished or completed by the first user 116. The collaboration/parti cipation options enable the first user 116 to join virtual group discussions rooms or create virtual discussion room. When the first user 116 selects to join a virtual discussion room or create a new virtual discussion room, the transitive view of the first lesson remains in the fourth section. The “Join virtual discussion room” option upon selection enables the first user 116 to join an existing virtual discussion room. The “Create virtual discussion room” upon selection enables the first user 116 to create a new virtual discussion room where the first user 116 may be the host of the new virtual discussion room and other users (e.g., the second and third users 118 and 120) interested in the first lesson may join the new virtual discussion room for a virtual group discussion on the first lesson. In an embodiment, the virtual discussion room may be created for a parent’ s/guardian’s meeting with one or more experts. In another embodiment, the virtual discussion room may be created for the first user 116 to interact with the one or more experts for doubt solving and concept clarification or to get tips and suggestions for improving the learning experience and output.

At 316, based on the user selection of the “Join virtual discussion room” option, the collaboration tool 214 enables the first user 116 to join as participant, an existing virtual discussion room “XYZ” associated with the first lesson “Soil and its types”. The second interactive GUI may present various details of the existing virtual discussion room “XYZ” to the first user 116 via the first user device 110. In an exemplary scenario, the details of the virtual discussion room “XYZ” may include admin name “Jack”, number of participants “4”, an agenda of discussion “Discussion on Soil”, list of participants “Jack, Lisa, Mark, and Andrew”, duration of the virtual group discussion “90 minutes”, and a date of the virtual group discussion “10 March, 2018”. Beneficially, virtual group discussion based on the first lesson enables the first user 116 to get clarity on the concepts of the first lesson. The virtual group discussion also enables the first user 116 to have a long-lasting memory of the concepts of the first lesson. The processor 204, in conjunction with the collaboration tool 214, may be configured to control the creation and management of various virtual discussion rooms for group discussions.

In an embodiment, the fourth section may include various other mechanisms to enable revision of the first lesson along with the summary and the virtual group discussions. For example, the fourth section may further include audio visual aids for revision, question and answer tests, or the like.

At 318, the second interactive GUI, displaying the fifth section of the first lesson, is illustrated. The transitive view of the first lesson “Soil and its types” transitions from the fourth section to the fifth section, when the fourth section is finished or completed by the first user 116. In other words, the transitive view of the first lesson “Soil and its types” transitions from the fourth section to the fifth section based on the progress of the first user 116 in the fourth section. In an embodiment, the fourth section is assumed to be finished after a specific time threshold set by the first user 116. In another embodiment, the fourth section is assumed to be finished when the virtual group discussion on the first lesson ends. The fifth section enables the execution of the first lesson. The execution of the first lesson includes execution of the concepts of the first lesson based on simulation of experiments pertaining to the concepts encompassed by the first lesson. In a nonlimiting example, at 318, a simulation environment is shown that enables the first user 116 to identify soil types based on soil samples. The soil types may be selected based on selection of answer from a given list of options (shown with dotted rectangular boxes). The execution of the first lesson enables the first user 116 to test his/her learnings from the first lesson and determine if he/she requires to redo the first lesson. The fifth section may include a vertical scrollbar 318a to navigate top-to-bottom and bottom-to-top of the fifth section. The fifth section may further include a horizontal scrollbar 318b to navigate right-to-left and left-to-right of the fifth section.

At 320, the second interactive GUI, displaying the fifth section of the first lesson, is illustrated. The fifth section further includes various options to execute (or implement) learnings from the first lesson by way of creating a new lesson or by making changes (i.e., edit) in an existing lesson created by the corresponding user (for example, the first user 116).

At 322, based on a user selection of “create new lesson”, a workspace is presented to the first user 116. In other words, based on the user selection to “create new lesson”, the transitive view displays the workspace where a new lesson may be created by the first user 116 based on his/her learnings from the first lesson. In other words, the new lesson may correspond to a learning result of the first user 116. The new lesson may be personalized to understanding of the first user 116. The new lesson may be stored in the knowledgebase 122 for future reference of the first user 116. In an embodiment, the first user 116 may share the new lesson with other users, for example, the second and third users 118 and 120. The new lesson created by the first user 116 may have a format identical to the first lesson, i. e. , the new lesson may also have the first through fifth sections created by the first user 116 as per the learning. In an embodiment, the first user 116 may choose to make changes in an existing lesson created in past by him/her. The first user 116 may make changes in the previously created lessons to include additional information learnt from the first lesson. The first user 116 may also make changes in the previously created lessons to reflect correlations between the first lesson and the previously created lessons. The changes may include addition of references, links, or hyperlinks in the previously created lessons as per the correlation and additional derivations observed by the first user 116 between the previously created/learnt lessons and new lesson. The workspace may include a vertical scrollbar 322a to navigate top-to-bottom and bottom-to-top of the fifth section. The workspace may further include a horizontal scrollbar 322b to navigate right-to-left and left-to-right of the fifth section.

At 324, a retainer GUI displayed via the first user device 110 is illustrated. The retainer GUI displays options for retaining (i.e., storing for future reference) data associated with the first lesson. The retainer GUI enables the first user 116 to store the first lesson “Soil and its types”, group discussion data (for example, audio/video recording, date, and time of the group discussion, textual notes taken during the group discussion, and the like), audio/video textual notes of the first user 116, and the new lesson “Basics of soil” created by the first user 116 in the user profile of the first user 116. The processor 204 may be configured to store, in the memory 220 or the database server 104, experimental data associated with execution of the first lesson, a set of audio notes, a set of video notes, a set of textual notes, data associated with the group discussions participated by the first user 116, and the first lesson, as the supplementary memory for future reference by the first user 116.

At 326, a feedback GUI displayed via the first user device 110 illustrated. The feedback user interface enables reception of user’s experience and views regarding the first lesson. The first user 116 may provide his/her opinion regarding the first lesson via the feedback GUI. The feedback may be received on the first user device 110 from the first user 116 in form of a score, a grade, a rating, a textual comment, and a graphical character. A ranking of the first lesson in response to a second user query, having a similar or dissimilar context, later in time is based on the feedback of the first user 116. For example, a bad feedback may lead to low ranking of the first lesson while presenting ranked list of one or more lessons for the second user query. As shown, the first lesson may be rated in form of stars for example, “one star” may be indicative of poor quality of the first lesson, “four stars” may be indicative of good quality of the first lesson, and “five stars” may be indicative of excellent quality of the first lesson. The first lesson may be rated based on a score out of ten. Feedback regarding the first lesson may also be provided by selection of options such as “Understood” and “Had fun” which may be indicative of a good quality and understandability of the first lesson. In an embodiment, the first user 116 may receive a feedback from other users on the new lesson created based on learnings from the first lesson. The processor 204 may be configured to enable the first user 116 to modify i.e., make changes, in the new lesson based on the received feedback.

At 328, a recommendation GUI, presented via the first user device 110, is illustrated. The recommendation tool 212 presents a list of recommended lessons that have a similar context as the first lesson as recommendations. As shown, the recommended lessons include “All about soil”, “Why is soil important”, “layers of soil”, and “Soil formation”. The processor 204 may be configured to recommend to the first user 116, a second lesson of the plurality of lessons that is to be accessed in a sequence with the first lesson. Beneficially, such recommendation increases convenience of the first user 116 while learning and also provides a smooth and seamless learning experience.

FIG. 4 is a schematic diagram 400 that illustrate implementation of the supplementary memory for the first user 116 on the e-learning system 102, in accordance with an exemplary embodiment of the disclosure.

With reference to FIG. 4, a second interactive GUI 402, presenting a previous lesson learnt and created by the first user 116, is displayed. The previous lesson relates to geography of India and includes a list of Indian states such as Odisha, Bihar, Gujarat, or the like and their corresponding soil types.

A second interactive GUI 404, presenting the first lesson being leamt by the first user 116, is also displayed. The first lesson, as described in the foregoing description of FIGS. 3A-3C, includes the first through fifth sections describing various components of soil, types of soil, particle size of soil, agriculture pattern on each soil, or the like.

The new lesson 406 created by the first user 116 based on learnings from the first lesson and the previous lesson, is illustrated. The new lesson 406 includes information pertaining to “soil” leamt by the first user 116 from the first lesson. The new lesson further includes a reference to agriculture pattern in each Indian state as per their soil type. Such reference is created by the first user 116 based on the correlation observed by the first user 116 in the previously learnt lesson and the first lesson. The new lesson also includes a cognitive map that reflects derivations and correlations made by the first user 116 based on the first lesson and the previous lesson. The new lesson may further include audio, video, symbolic, and textual notes created by the first user 116 based on his/her understanding of the first lesson and the previous lesson and one or more correlations therebetween. The new lesson is stored in the memory 220 or the database server 104 to be used as the supplementary memory. Beneficially, such supplementary memory provides the first user 116 with assurance that his/her learnings are safe and can be retrieved as per his/her requirement. Further, as the time progresses, the supplementary memory created by the first user 116 till that time may be utilized for easy reference and quick understanding of previously leamt lessons.

FIG. 5 is a block diagram that illustrates a system architecture of a computer system 500 for implementing the e-learning system 102, in accordance with an exemplary embodiment of the disclosure. An embodiment of the disclosure, or portions thereof, may be implemented as computer readable code on the computer system 500. In one example, the application server 106 or the database server 104 of FIG. 1 may be implemented in the computer system 500 using hardware, software, firmware, non-transitory computer readable media having instructions stored thereon, or a combination thereof and may be implemented in one or more computer systems or other processing systems. Hardware, software, or any combination thereof may embody modules and components used to implement the online learning system 102.

The computer system 500 may include a processor 502 that may be a special purpose or a general- purpose processing device. The processor 502 may be a single processor or multiple processors. The processor 502 may have one or more processor “cores.” Further, the processor 502 may be coupled to a communication infrastructure 504, such as a bus, a bridge, a message queue, the communication network 108, multi-core message-passing scheme, or the like. The computer system 500 may further include a main memory 506 and a secondary memory 508. Examples of the main memory 506 may include RAM, ROM, and the like. The secondary memory 508 may include a hard disk drive or a removable storage drive (not shown), such as a floppy disk drive, a magnetic tape drive, a compact disc, an optical disk drive, a flash memory, or the like. Further, the removable storage drive may read from and/or write to a removable storage device in a manner known in the art. In an embodiment, the removable storage unit may be a non-transitory computer readable recording media. The computer system 500 may further include an input/output (I/O) port 510 and a communication interface 512. The I/O port 510 may include various input and output devices that are configured to communicate with the processor 502. Examples of the input devices may include a keyboard, a mouse, a joystick, a touchscreen, a microphone, and the like. Examples of the output devices may include a display screen, a speaker, headphones, and the like. The communication interface 512 may be configured to allow data to be transferred between the computer system 500 and various devices that are communicatively coupled to the computer system 500. Examples of the communication interface 512 may include a modem, a network interface, i.e., an Ethernet card, a communication port, and the like. Data transferred via the communication interface 512 may be signals, such as electronic, electromagnetic, optical, or other signals as will be apparent to a person skilled in the art. The signals may travel via a communications channel, such as the communication network 108, which may be configured to transmit the signals to the various devices that are communicatively coupled to the computer system 500. Examples of the communication channel may include a wired, wireless, and/or optical medium such as cable, fiber optics, a phone line, a cellular phone link, a radio frequency link, and the like. The main memory 506 and the secondary memory 508 may refer to non-transitory computer readable mediums that may provide data that enables the computer system 500 to implement the online learning system 102.

Various embodiments of the disclosure provide an online learning system 102 that includes a data storage (e.g., the database server 104 or the memory 220) configured to store the knowledgebase 122 including the collection of a plurality of lessons. The plurality of lessons have a uniform format each including the plurality of sections. Various embodiments of the disclosure provide the search engine 202 configured to search in the knowledgebase 122 for one or more lessons of the plurality of lessons that correlate to a context of the first user query. Various embodiments of the disclosure provide the processor 204 configured to render, via the first user device 110 of the first user 116, the first interactive GUI that displays the list of the one or more lessons for user selection. The processor 204 may be configured to render, via the user device 110, the second interactive GUI that displays the transitive view of the first lesson selected from the list. The transitive view transitions between the plurality of sections of the first lesson as per the progress of the first user 116 in the first lesson. The plurality of sections of the first lesson include the first section, the second section, the third section, the fourth section, and the fifth section. The first section includes the introduction to the first lesson. The second section that includes the cognitive map that illustrates one or more concepts encompassed by the first lesson. The third section that includes the description of each concept of the one or more concepts. The fourth section enables revision of the first lesson by way of participation in one or more virtual group discussions. The fifth section that enables execution of the first lesson. The execution of the first lesson includes creation of the new lesson by the first user 116 on the same topic as the first lesson. The new lesson is the learning result of the first user 116 and is stored in the knowledgebase 122 for the future reference by the first user 116 or one or more second users for example, second and third users 118 and 120.

The disclosed embodiments encompass numerous advantages. Exemplary advantages of the disclosed methods include, but are not limited to, providing an independent and interactive learning platform offering equal learning and teaching opportunity to everyone. Technological improvements in the disclosed e-learning system 102 is configured to implement collaborative and participatory learning methods that significantly improve persistence of learning. Further, the technological improvements in the disclosed e-learning system 102 facilitate learning by using cognitive maps associated with one or more concepts. Such use of cognitive maps enables the first through third users 116-120 to remember various concepts in form of images which is easier and persistent than learning and remembering textual information associated with the one or more concepts. The disclosed e-learning system 102 further enables the first through third users 116- 120 to participate in the group discussions to discuss their learnings. Such discussions provide clarity and persistence to learnings associated with the one or more concepts. Further, the disclosed e-learning system 102 also allows practice of “learning by teaching” approach for learning. The disclosed e-learning system 102 allows the first through third users 116-120 to create new lessons based on their learnings and correlations observed across various learnt lessons. Such created lessons serve as the supplementary memory of the first through third users 116-120 and can be used anytime and anywhere for reference. The first through third users 116-120 are allowed to keep the new lessons for personal use or share the new lessons with everyone to learn from them. Further, the disclosed e-learning system 102 allows the first through third users 116-120 to provide feedback associated with learnt lessons. The feedback may act as a guide to improve a quality of the lessons as well as is indicative of user preferences. Further, the e-learning system 102 disclosed herein allows for providing recommendations based on a learning history and pattern of the first through third users 116-120. Therefore, the disclosed e-leaming system 102 enables for a hassle- free and seamless way of progress in learning of the first through third users 116-120. The disclosed methods and systems work on existing infrastructure and does not require any specialized resources. Therefore, the disclosed e-learning system 102 allows for an inexpensive, simple, and efficient approach for facilitating learning. The disclosed methods and systems do not require traveling to reach any institute or school hence enabling the first through third users 116- 120 to leam in comfort of own space and at desired time. Hence, the disclosed methods and systems allow the first through third users 116-120 to adjust learning in respective lifestyles without making any compromise. Therefore, the first through third users 116-120 may manage time for other activities such as part- time/fulltime jobs, sports, hobbies, and the like.

The disclosed e-learning system 102 presents the plurality of lessons via the first through third user devices 110-114 in a format that is easily understandable by a user (e.g., the first through third users 116-120). The first section of each of the plurality of sections is an introduction section that enables the user to understand a context of the lesson. Based on the context of the lesson, one or more concepts of the lesson may be anchored to the user’s understanding. The second section of each of the plurality of lessons is a cognitive map that describes multi-level correlations between concepts included in the ongoing lesson. The cognitive map enables the user to maintain a photographic memory of the concepts, keywords, and correlations included in the ongoing lesson. The cognitive map acts as crisp effective notes for the user for a quick revision. The third section of each of the plurality of lessons includes a description of the concepts included in the corresponding lesson. The third section enables the user to have a deep understanding of the concepts and their correlations. The third section makes the corresponding lesson practical and engaging. The fourth section enables revision of the lesson and prepares the user for execution (such as, teaching, examination, research, or the like) of the learnt lesson. The fifth section allows the user to execute the leamt lesson. Such execution of the lesson builds confidence of the user on the concepts included in the lesson. The fifth section enables the user to gain expertise (to teach/ to execute) over the concepts included in the leamt lesson.

A person of ordinary skill in the art will appreciate that embodiments and exemplary scenarios of the disclosed subject matter may be practiced with various computer system configurations, including multi-core multiprocessor systems, minicomputers, mainframe computers, computers linked or clustered with distributed functions, as well as pervasive or miniature computers that may be embedded into virtually any device. Further, the operations may be described as a sequential process, however some of the operations may in fact be performed in parallel, concurrently, and/or in a distributed environment, and with program code stored locally or remotely for access by single or multiprocessor machines. In addition, in some embodiments, the order of operations may be rearranged without departing from the spirit of the disclosed subject matter.

Techniques consistent with the disclosure provide, among other features, systems and methods for facilitating online learning. While various exemplary embodiments of the disclosed systems and methods have been described above, it should be understood that they have been presented for purposes of example only, and not limitations. It is not exhaustive and does not limit the disclosure to the precise form disclosed. Modifications and variations are possible in light of the above teachings or may be acquired from practicing of the disclosure, without departing from the breadth or scope.

While various embodiments of the disclosure have been illustrated and described, it will be clear that the disclosure is not limited to these embodiments only. Numerous modifications, changes, variations, substitutions, and equivalents will be apparent to those skilled in the art, without departing from the spirit and scope of the disclosure, as described in the claims.