DETAILED ACTION
This action is in response to communication filed on 21 August 2026. Claims 1, 9 and 15 are amended. Claims 4 and 17 were canceled before. No claim is added. Claims 1-3, 5-16 and 18-22 are pending in the application and have been considered below.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 21 August 2026 has been entered.
Response to Arguments
Applicant argues that [“In contrast, the cited portion of Bilic at best discloses that the back-computing servers can be computing devices such as laptops or PCs, not that front-end resources of client devices execute the recited functions. Applicant respectfully submits that claim 1 should be allowable for at least the foregoing reasons.” (Page 12 )].
The argument described above has been considered and is persuasive. Therefore, rejection has been withdrawn. However, upon further search and consideration, a new ground of rejection is made, citing the new reference NEDIVI (US20180301046A1) (see claims 1 and 9 rejections below).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-3, 5-8, 15-16 and 18-22 are rejected under 35 U.S.C. 103 as being unpatentable over NEDIVI et al. (US20180301046A1) in view of KANE et al. (US20210141616A1) and further view of SUBRAMANYAN et al. (US20020178181A1) and further in view of BILIC et al. (US20160358494A1).
As to claim 1, NEDIVI teaches:
digital learning system comprising: one or more front-end processing resources operative to execute, on one or more client devices, machine-readable instructions (see fig. 1, par. 0020, wherein the system 100 can each be implemented as a single system, multiple systems, distributed systems, or in any other form. In one implementation, the system 100 includes a digital learning platform (hereinafter “learning platform”) having a frontend system (e.g., presentation layer) 102 and a backend system 104 (e.g., data access layer) in communication with the frontend system 102. The frontend system, for example, runs on client device 110. The client device 110 illustrated in FIG. 1 is a representative of a large number of client devices that can be included in the system 100; as taught by NEDIVI)
to: receive, via an author-side graphical user interface (GUI) executed by the one or more front-end processing resources on the one or more client devices (see figs. 1-3d, par. 0042, wherein the course builder accounts 206 are each associated with a particular type of user 180 who is designated to create (e.g., design and build) one or more courses implemented within the system 100. A course may be built by creating a sequence of course segments corresponding to a predetermined course structure. Users 180 associated to course builder accounts may be referred to as “course builders”. Course builders may be given access to create and store learning objects associated with the courses implemented within the system 100; see also par. 0025, wherein in one implementation, when the App is running on the client device 110, the interface module 118 will display the App as a full screen application and provide access to the learning activities, learning objects, information and functionalities implemented in the system 100. The interface module 118 presents information output for display on the screen of the client device 110, which allows the user 180 to navigate the system 100 and interact with the components, modules, layers or digital content therein. For example, the interface module 118 allows a user 180 to select or browse through learning objects stored in the backend system 104, and participate in live events hosted by the backend system 104; see also pars. 0023-0024, 0027 and 0049; as taught by NEDIVI),
provide, via a learner-side GUI, the created digital learning course (see figs. 1-2, par. 0049, wherein the course module 224 facilitates implementation, delivery and management of a catalogue of courses (e.g., educational programs, training programs) maintained in the system 100. Each course includes one or more course segments and a collection of information and learning objects relating to one or more courses. The courses may be created by a course builder who is associated with one of the course builder accounts 206. Course builders can utilize the course module 224 to create and store information associated with a particular course, such as a course identifier (e.g., course name, course code), a course description, course structure (e.g., course format, organization of course segments), and links to the course-related learning objects. The learning objects may be in the form of text documents, video files, digital images, or the like. In one implementation, learners may receive notification of new information (relating to the courses in which the learners are enrolled) made available in the system 100. For example, when new learning objects relating to Course A, or a course segment of Course A, are created and stored in the learning content repository, electronic notifications are delivered online from the backend system 104 to the frontend system 102 on the client device 110 associated to learners enrolled into Course A; as taught by NEDIVI);
and responsive to the learner's inputs and using the one or more front-end processing resources, compute, on the one or more client devices, for the learner's progress towards the first terminal objective (see par. 0043, wherein the administrator accounts 208 are each associated with a particular type of user 180 who is designated to monitor and administer the services and functionalities of the system 100 through a computer or computing device. Users 180 associated to administrator accounts may be referred to as “administrator”. An administrator may be given authority to perform a range of administrative functions in the system 100 such as, but not limited to, creating learner accounts for association with particular users 180; adding (or enrolling) learners to, and removing learners from, one or more courses implemented in the system 100; assigning learning activities to learners; and generating performance-related reports of one or more learners; as taught by NEDIVI).
NEDIVI does not expressly teach low code inputs defining terminal objectives and enabling objectives for a digital learning course; receive, via the author-side GUI, low code inputs defining weighted associations between a first terminal objective and a first subset of enabling objectives that guide learners toward the first terminal objective; based on the received low code inputs, create the digital learning course comprising the defined terminal objectives and the defined enabling objectives; receive, via the learner-side GUI, inputs from a learner as the learner engages with the created digital learning course; compute a progress score and a performance score.
In similar field of endeavor, KANE teaches:
receive low code inputs, receive, via the author-side GUI, low code inputs (see figs. 2-4, par. 0019, wherein the disclosed LCNC framework provides a distributed software development environment that enables the creation of software (e.g., applications) through graphical user interfaces and configurations instead of traditional hand-coded programming. A low code (LC) model enables developers of varied experience levels to create applications using a visual user interface in combination with model-driven logic as taught by KANE)
based on the received low code inputs (see fig. 12, par. 0123, wherein Process 1200 details some embodiments of the LCNC framework that enables the creation of software (e.g., applications) through graphical user interfaces and configurations instead of traditional hand-coded programming. The LCNC engine 400 enables developers of varied experience levels to create applications using a visual user interface in combination with model-driven logic (as provided by the UI/IOs discussed below); as taught by KANE).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the NEDIVI apparatus to include the teachings of KANE to receive low code inputs, receive, via the author-side GUI, low code inputs, based on the received low code inputs. Such a person would have been motivated to make this combination as LCNC framework is beneficial for reducing the amount of traditional hand coding and enabling accelerated delivery of business applications. The LCNC framework also lowers the initial cost of setup, training, deployment and maintenance of applications and services (see par. 0019, KANE).
NEDIVI and KANE do not expressly teach defining terminal objectives and enabling objectives for a digital learning course; defining weighted associations between a first terminal objective and a first subset of enabling objectives that guide learners toward the first terminal objective; create the digital learning course comprising the defined terminal objectives and the defined enabling objectives; receive, via the learner-side GUI, inputs from a learner as the learner engages with the created digital learning course; compute a progress score and a performance score.
In similar field of endeavor, SUBRAMANYAN teaches:
defining terminal objectives and enabling objectives for a digital learning course (see fig. 1, par. 0043, wherein the subject matter expert may categorize or characterize the raw content uploaded to the storyboard server by designating the material as, for example, write-ups, manuals, audio, video, or graphics. The subject matter expert may enter or characterize the main or terminal objective of the material and the more specific or enabling objectives, and information on the user environment and audience demographics; as taught by SUBRAMANYAN);
create the digital learning course comprising the defined terminal objectives and the defined enabling objectives (see fig. 2, par. 0048, wherein as templates, learning objects, and frames are modified, a history of these items is stored in the storyboard server. Users can revert back to previous versions. When the users and developers sign off on the content, the content is ready to go 24; see also fig. 3, par. 0050, wherein content developers create the relevant media for the storyboard pages, incorporate it into the network or webpages of the storyboard and receive feedback from other users and developers, such as the instructional designer and subject matter experts 38, and collaborate further with the users and developers until the final content 39 is achieved; as taught by SUBRAMANYAN).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the NEDIVI and KANE apparatus to include the teachings of SUBRAMANYAN for defining terminal objectives and enabling objectives for a digital learning course; create the digital learning course comprising the defined terminal objectives and the defined enabling objectives. Such a person would have been motivated to make this combination as what is desired, therefore, is a method and system collecting, creating, and developing content for eLearning, which will simplify and improve the process of storyboarding by enabling team members to communicate and develop storyboards more efficiently and definitively. Preferably, this system and method would exist in a network or world wide web setting, more preferably in a setting which allows team members to collaborate, communicate, and interact with a multitude of media files, information, and presentations online simultaneously. A method and system for integrating knowledge management and content development, including collecting and assembling various types of information, knowledge, or both, developing a storyboard based upon such knowledge and information, and managing the user and workflow through and within the storyboard via a storyboard server is also desired. A method and system which is relatively inexpensive, cost-effective, and user-friendly is also desired (see par. 0007, SUBRAMANYAN).
NEDIVI, KANE and SUBRAMANYAN do not expressly teach defining weighted associations between a first terminal objective and a first subset of enabling objectives that guide learners toward the first terminal objective; receive, via the learner-side GUI, inputs from a learner as the learner engages with the created digital learning course; compute a progress score and a performance score.
In similar field of endeavor, BILIC teaches:
defining weighted associations between a first terminal objective and a first subset of enabling objectives that guide learners toward the first terminal objective (see par. 0006, wherein for each learning objective of the set of learning objectives, selecting, from a plurality of resources accessible to the electronic learning system, one or more resources assigned a relevance score at least satisfying a relevance threshold for that learning objective, the relevance score representing an estimated degree of correlation between that learning objective and a content of the respective resource, and the relevance threshold indicating a minimum relevance score required for a resource to be selected for a learning objective; see also fig. 4, par. 00017; see also par. 0180, wherein the learning path component 114 can generate the combined score by applying a first weight to the relevance score and a second weight to the system learn value. The combined score may be a sum of the weighted relevance score and the weighted system learn value. The first weight and the second weight may, in some embodiments, each be numerical values that, together, sum to one; see also par. 0181, wherein described with reference to FIGS. 8A to 11, the electronic learning system 30 can generate the initial learning path 512 based on estimated correlations between the received learning objectives 320, 330; as taught by BILIC)
receive, via the learner-side GUI, inputs from a learner as the learner engages with the created digital learning course (see par. 0095, wherein The system processor 110 may also, based on user response inputs received via the interface component 116, initiate the evaluation component 118 to determine a competence level of the user in respect of at least one learning objective; see also figs. 7-8B, pars. 0155-0156, wherein at 750, the system processor 110 monitors a feedback usage indicator for each evaluation resource; The feedback usage indicator can generally represent an amount of user interaction with that evaluation resource; as taught by BILIC);
compute a progress score and a performance score (see par. 0081, wherein the computing servers 32 may be a computing device 20 (e.g. a laptop or personal computer); see also figs. 8A-8B, par. 0157, wherein with each use of the evaluation resource in the learning path 512, the corresponding feedback usage indicator increases in value and the electronic learning system 30 can also collect usage data related to those interactions by the users with the evaluation resources; see par. 0160, wherein the electronic learning system 30 can assign a system learn value to each resource selected at 720 in response to each time a user completes a corresponding evaluation resource; as taught by BILIC).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the NEDIVI, KANE and SUBRAMANYAN apparatus to include the teachings of BILIC for defining weighted associations between a first terminal objective and a first subset of enabling objectives that guide learners toward the first terminal objective; receive, via the learner-side GUI, inputs from a learner as the learner engages with the created digital learning course; and compute a progress score and a performance score. Such a person would have been motivated to make this combination as it is beneficial for the author and the user to know the correlation between objectives and achievements, and providing a way to measure the success of the training course afterwards. It is also more flexible to be able to run the whole system on a laptop or a PC for testing or debugging purposes (see also BILIC, pars. 0002-0004).
As to claim 2, NEDIVI, KANE, SUBRAMANYAN and BILIC teach the limitations of claim 1. KANE further teaches:
wherein the low code inputs comprise at least one of drag-and-drop-related inputs, pull-down-menu-related inputs, and point- and-click-related inputs (see figs. 1-4, par. 0011, wherein the LCNC framework can comprise a development platform that can be a visually integrated development environment that allows citizen developers to drag-and-drop application components, connect them together, and create an application; as taught by KANE).
As to claim 3, NEDIVI, KANE, SUBRAMANYAN and BILIC teach the limitations of claim 1. SUBRAMANYAN further teaches:
the terminal objectives comprise desired outcomes for learners engaging with the digital learning course; and the enabling objectives comprise learning experiences that guide learners towards the terminal objectives (see par. 0044, wherein creating content for eLearning wherein the storyboarding process comprises collaboratively deciding the objectives of the eLearning program, defining the audience for the same and, based on the objectives and audience, to collect information that goes into making the program, structuring it, breaking it in modules of the appropriate sizes, and defining the look and feel of the program; as taught by SUBRAMANYAN).
As to claim 5, NEDIVI, KANE, SUBRAMANYAN and BILIC teach the limitations of claim 1. BILIC further teaches:
wherein computing the progress score and the performance score for the first terminal objective comprises: computing, for enabling objectives of the first subset of enabling objectives, a progress score and a performance score for the learner's progress towards the enabling objective
(see par. 0016, wherein generate the learning path based on (i) the relevance score assigned to each resource of the one or more resources and (ii) a system learn value assigned to each resource selected for the subset of learning objectives associated with that evaluation type resource; see also par. 0157, wherein with each use of the evaluation resource in the learning path 512, the corresponding feedback usage indicator increases in value and the electronic learning system 30 can also collect usage data related to those interactions by the users with the evaluation resources; see par. 0160, wherein the electronic learning system 30 can assign a system learn value to each resource selected at 720 in response to each time a user completes a corresponding evaluation resource; as taught by BILIC); based on the weighted associations between the first terminal objective and the first subset of enabling objectives, computing the progress score for the learner's progress towards the first terminal objective as a weighted sum of the computed progress scores for the learner's progress towards the first subset of enabling objectives; and based on the weighted associations between the first terminal objective and the first subset of enabling objectives, computing the performance score for the learner's progress towards the first terminal objective as a weighted sum of the computed performance scores for the learner's progress towards the first subset of enabling objectives (see par. 0006, wherein one or more resources assigned a relevance score at least satisfying a relevance threshold for that learning objective, the relevance score representing an estimated degree of correlation between that learning objective and a content of the respective resource; see also par. 0008, wherein generating the learning path based on the relevance score assigned to each resource and the system learn value assigned to each resource includes: applying a first weight to the relevance score and a second weight to the system learn value; and generating a combined score based on the weighted relevance score and the weighted system learn value; as taught by BILIC).
As to claim 6, NEDIVI, KANE, SUBRAMANYAN and BILIC teach the limitations of claim 1. BILIC further teaches:
wherein the one or more front-end processing resources are further operative to execute machine-readable instructions to: transmit, to a back-end learning management system, records related to the computed progress score and the computed performance score for the learner's progress towards the first terminal objective (see fig. 2, par. 0155, wherein at 750, the system processor 110 monitors a feedback usage indicator for each evaluation resource ... The feedback usage indicator can be stored in the learning path database 146; see also par. 0087, wherein the data storage components 34 can store various data associated with the operation of the electronic learning system 30. For example, course data 35, such as data related to a course's framework, educational content, and/or records of assessments, may be stored at the data storage components 34. The data storage components 34 may also store user data, which includes information associated with the users 12, 14. The user data may include a user profile for each user 12, 14, for example …The data storage components 34 may also store data associated with the learning path, such as learning objectives and learning path data associated with the learning path; see also par. 0081, wherein the computing servers 32 may be a computing device 20 (e.g. a laptop or personal computer); as taught by BILIC).
As to claim 7, NEDIVI, KANE, SUBRAMANYAN and BILIC teach the limitations of claim 1. BILIC further teaches:
wherein the one or more front-end processing resources are further operative to execute machine-readable instructions to: responsive to at least one of the computed progress score and the computed performance score for the learner's progress towards the first terminal objective, modify content of the digital learning course provided to the learner via the learner-side GUI (see par. 0058, wherein learning paths can be generated based on an estimated degree of correlation between the learning objectives and the one or more resources. In some embodiments, the electronic learning systems described herein can update the learning path based on usage data associated with certain types of resources, such as evaluation resources. An evaluation resource is a resource that involves some degree of interaction between the user and the electronic learning system in order to evaluate a proficiency of the user with one or more learning objectives. When a usage amount of the evaluation resource at least satisfies a predefined threshold, the systems described herein can determine that the collected usage data is sufficient and can then proceed to update the learning path based, at least partially, on that collected usage data; see also par. 0081, wherein the computing servers 32 may be a computing device 20 (e.g. a laptop or personal computer); as taught by BILIC).
As to claim 8, NEDIVI, KANE, SUBRAMANYAN and BILIC teach the limitations of claim 1.
BILIC further teaches wherein:
the one or more front-end processing resources are further operative to execute machine-readable instructions to receive, via the author-side GUI, defining content pages that arrange digital learning content for the enabling objectives (see figs. 3-17, par. 0101, wherein reference is now made to FIG. 3, which is a screenshot 200 of an example user interface 210 for receiving example learning objectives 220, 230 by the electronic learning system 30. The user interface 210 is provided via a browser application 202 in this example; see also par. 0081, wherein the computing servers 32 may be a computing device 20 (e.g. a laptop or personal computer); as taught by BILIC);
and creating the digital learning course comprises implementing the content pages as web pages or segments of web pages provided via the learner-side GUI (see figs. 3-17, par. 0111, wherein FIG. 5 is a screenshot of an example user interface 400 showing an example learning path generated based on the example learning objectives 220, 230 received via the user interface 210 in FIG. 3; see also par. 0074, wherein the connection request initiated from the computing devices 20 a, 20 b may be initiated from a web browser and directed at the browser-based communications application on the electronic learning system 30; as taught by BILIC).
KANE further teaches:
low code inputs (see figs. 2-4, par. 0019, wherein the disclosed LCNC framework provides a distributed software development environment that enables the creation of software (e.g., applications) through graphical user interfaces and configurations instead of traditional hand-coded programming. A low code (LC) model enables developers of varied experience levels to create applications using a visual user interface in combination with model-driven logic as taught by KANE),
based on the received low code inputs (see fig. 12, par. 0123, wherein Process 1200 details some embodiments of the LCNC framework that enables the creation of software (e.g., applications) through graphical user interfaces and configurations instead of traditional hand-coded programming. The LCNC engine 400 enables developers of varied experience levels to create applications using a visual user interface in combination with model-driven logic (as provided by the UI/IOs discussed below); as taught by KANE).
As to claim 22, NEDIVI, KANE, SUBRAMANYAN and BILIC teach the limitations of claim 1.
NEDIVI further teaches:
the digital learning system of claim 1, further comprising a client device that includes the one or more front-end processing resources (see fig. 1, par. 0043, wherein the administrator accounts 208 are each associated with a particular type of user 180 who is designated to monitor and administer the services and functionalities of the system 100 through a computer or computing device. Users 180 associated to administrator accounts may be referred to as “administrator”. An administrator may be given authority to perform a range of administrative functions in the system 100 such as, but not limited to, creating learner accounts for association with particular users 180; adding (or enrolling) learners to, and removing learners from, one or more courses implemented in the system 100; assigning learning activities to learners; and generating performance-related reports of one or more learners; as taught by NEDIVI)
BILIC further teaches:
to compute the progress score and the performance score (see par. 0081, wherein the computing servers 32 may be a computing device 20 (e.g. a laptop or personal computer); see also figs. 8A-8B, par. 0157, wherein with each use of the evaluation resource in the learning path 512, the corresponding feedback usage indicator increases in value and the electronic learning system 30 can also collect usage data related to those interactions by the users with the evaluation resources; see par. 0160, wherein the electronic learning system 30 can assign a system learn value to each resource selected at 720 in response to each time a user completes a corresponding evaluation resource; as taught by BILIC).
Claim 15 amounts to the method performed by the system of claim 1. Accordingly, claim 15 is rejected for substantially the same reasons as presented above for claim 1 and based on the references’ disclosure of the necessary supporting hardware and software.
Claim 16 amounts to the method performed by the system of claim 3. Accordingly, claim 16 is rejected for substantially the same reasons as presented above for claim 3 and based on the references’ disclosure of the necessary supporting hardware and software.
Claim 18 amounts to the method performed by the system of claim 5. Accordingly, claim 18 is rejected for substantially the same reasons as presented above for claim 5 and based on the references’ disclosure of the necessary supporting hardware and software.
Claim 19 amounts to the method performed by the system of claim 7. Accordingly, claim 19 is rejected for substantially the same reasons as presented above for claim 7 and based on the references’ disclosure of the necessary supporting hardware and software.
Claim 20 amounts to the method performed by the system of claim 6. Accordingly, claim 20 is rejected for substantially the same reasons as presented above for claim 6 and based on the references’ disclosure of the necessary supporting hardware and software.
Claim 21 amounts to the method performed by the system of claim 22. Accordingly, claim 21 is rejected for substantially the same reasons as presented above for claim 22 and based on the references’ disclosure of the necessary supporting hardware and software.
Claims 9-14 are rejected under 35 U.S.C. 103 as being unpatentable over BILIC et al. (US20160358494A1) in view of NEDIVI et al. (US20180301046A1) and further view of KANE et al. (US20210141616A1) and further view of SUBRAMANYAN et al. (US20020178181A1).
As to claim 9, BILIC teaches
a digital learning system (see fig. 1, par. 0001, wherein the described embodiments relate to methods and systems associated with providing a learning path for an electronic learning system; as taught by BILIC)
comprising: an author-side graphical user interface (GUI) comprising: a terminal objective field (see par. 0028, wherein FIG. 4 is a screenshot of an example user interface for receiving example learning objectives by the electronic learning system; as taught by BILIC),
an enabling objective field (see par. 0030, wherein FIG. 6 is a screenshot of an example user interface showing an example learning path generated based on the example learning objectives received via the user interface in FIG. 4; as taught by BILIC),
and a content page field arranging digital learning content for the enabling objectives (see fig. 12, par. 0209, wherein one or more learning objectives 320, 330 can be assigned a mandatory status. The mandatory status can indicate that the actions in the learning path 512 associated with that learning objective are required for the user, and cannot be removed from the learning path 512 despite the electronic learning system 30 determining that the user has reached the mastery level in respect of that learning objective. That is, the mandatory status can override the effects of the mastery status 1240, 1242; see also par. 0210, wherein in FIG. 12, the subject specific learning objective 1230 a, which corresponds to the subject specific learning objective 330 a, is assigned the mandatory status 1250; as taught by BILIC);
one or more front-end processing resources operative to execute machine-readable instructions to: via the author-side GUI create the digital learning course having the defined terminal objectives, the defined enabling objectives, and the arranged digital learning content (see par. 0038, wherein FIG. 13 is a screenshot of an example user interface showing an example learning path generated based on the learning objectives in FIG. 12; see also par. 0081, wherein the computing servers 32 may be a computing device 20 (e.g. a laptop or personal computer); as taught by BILIC);
and provide the created digital learning course to learners via a learner-side GUI; and the learner-side GUI configured to display the created digital learning course and receive inputs from learners as the learners engage with the created digital learning course (see figs 12-13, par. 0214, wherein An example learning path 1312 will now be described with reference to FIG. 13, which is a screenshot 1300 of an example user interface 1310 showing the learning path 1312 generated based on the learning objectives 1220, 1230 in FIG. 12; see also par. 0215, wherein the learning path 1312 includes a first series of actions 1330 associated with the second group 520 b of the learning path 512, a second series of actions 1340 associated with the third group 520 c of the learning path 512 and a third series of actions 1350 associated with a new group 1320 (“Promotion of Products and Services”); as taught by BILIC);
wherein the one or more front-end processing resources (see par. 0081, wherein the computing servers 32 may be a computing device 20 (e.g. a laptop or personal computer); as taught by BILIC),
responsive to a learner's inputs received via the learner-side GUI (see par. 0095, wherein the system processor 110 may also, based on user response inputs received via the interface component 116, initiate the evaluation component 118 to determine a competence level of the user in respect of at least one learning objective; see also figs. 7-8B, pars. 0155-0156, wherein at 750, the system processor 110 monitors a feedback usage indicator for each evaluation resource; The feedback usage indicator can generally represent an amount of user interaction with that evaluation resource; as taught by BILIC),
compute a progress score and a performance score for the learner's progress towards the defined terminal objectives (see figs. 8A-8B, par. 0157, wherein with each use of the evaluation resource in the learning path 512, the corresponding feedback usage indicator increases in value and the electronic learning system 30 can also collect usage data related to those interactions by the users with the evaluation resources; see par. 0160, wherein the electronic learning system 30 can assign a system learn value to each resource selected at 720 in response to each time a user completes a corresponding evaluation resource; as taught by BILIC).
BILIC does not expressly teach executed on one or more client devices, the author-side GUI, configured to receive low code inputs, defining terminal objectives for a digital learning course, configured to receive low code inputs, defining enabling objectives for the digital learning course, configured to receive low code inputs, to execute, on the one or more client devices, based on low code inputs received, on the one or more client devices.
In similar field of endeavor, NEDIVI teaches:
executed on one or more client devices, the author-side GUI, to execute, on the one or more client devices, on the one or more client devices (see fig. 1, par. 0020, wherein the system 100 can each be implemented as a single system, multiple systems, distributed systems, or in any other form. In one implementation, the system 100 includes a digital learning platform (hereinafter “learning platform”) having a frontend system (e.g., presentation layer) 102 and a backend system 104 (e.g., data access layer) in communication with the frontend system 102. The frontend system, for example, runs on client device 110. The client device 110 illustrated in FIG. 1 is a representative of a large number of client devices that can be included in the system 100; see also figs. 1-3d, par. 0042, wherein the course builder accounts 206 are each associated with a particular type of user 180 who is designated to create (e.g., design and build) one or more courses implemented within the system 100. A course may be built by creating a sequence of course segments corresponding to a predetermined course structure. Users 180 associated to course builder accounts may be referred to as “course builders”. Course builders may be given access to create and store learning objects associated with the courses implemented within the system 100; see also par. 0025, wherein in one implementation, when the App is running on the client device 110, the interface module 118 will display the App as a full screen application and provide access to the learning activities, learning objects, information and functionalities implemented in the system 100. The interface module 118 presents information output for display on the screen of the client device 110, which allows the user 180 to navigate the system 100 and interact with the components, modules, layers or digital content therein. For example, the interface module 118 allows a user 180 to select or browse through learning objects stored in the backend system 104, and participate in live events hosted by the backend system 104; see also pars. 0023-0024, 0027 and 0049; as taught by NEDIVI).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the BILIC apparatus to include the teachings of NEDIVI executed on one or more client devices, the author-side GUI, to execute, on the one or more client devices, on the one or more client devices. Such a person would have been motivated to make this combination as there is a need for a computer implemented method and system that provides a learning experience through combining interactive learning opportunities with social interaction to provide the learner with higher levels of interest and involvement during learning activities (see par. 0004, NEDIVI).
BILIC and NEDIVI do not expressly teach configured to receive low code inputs, defining terminal objectives for a digital learning course, configured to receive low code inputs, defining enabling objectives for the digital learning course, configured to receive low code inputs, based on low code inputs received.
In similar field of endeavor, KANE teaches:
configured to receive low code inputs, configured to receive low code inputs, configured to receive low code inputs (see figs. 2-4, par. 0019, wherein the disclosed LCNC framework provides a distributed software development environment that enables the creation of software (e.g., applications) through graphical user interfaces and configurations instead of traditional hand-coded programming. A low code (LC) model enables developers of varied experience levels to create applications using a visual user interface in combination with model-driven logic as taught by KANE),
based on low code inputs received (see fig. 12, par. 0123, wherein Process 1200 details some embodiments of the LCNC framework that enables the creation of software (e.g., applications) through graphical user interfaces and configurations instead of traditional hand-coded programming. The LCNC engine 400 enables developers of varied experience levels to create applications using a visual user interface in combination with model-driven logic (as provided by the UI/IOs discussed below); as taught by KANE).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the BILIC apparatus to include the teachings of KANE configured to receive low code inputs, configured to receive low code inputs, configured to receive low code inputs, based on low code inputs received. Such a person would have been motivated to make this combination as LCNC framework is beneficial for reducing the amount of traditional hand coding and enabling accelerated delivery of business applications. The LCNC framework also lowers the initial cost of setup, training, deployment and maintenance of applications and services (see par. 0019, KANE).
BILIC, NEDIVI and KANE do not expressly teach defining terminal objectives for a digital learning course, defining enabling objectives for the digital learning course.
In similar field of endeavor, SUBRAMANYAN teaches defining terminal objectives for a digital learning course, defining enabling objectives for the digital learning course (see fig. 1, par. 0043, wherein the subject matter expert may categorize or characterize the raw content uploaded to the storyboard server by designating the material as, for example, write-ups, manuals, audio, video, or graphics. The subject matter expert may enter or characterize the main or terminal objective of the material and the more specific or enabling objectives, and information on the user environment and audience demographics; as taught by SUBRAMANYAN).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the BILIC, NEDIVI and KANE apparatus to include the teachings of SUBRAMANYAN defining terminal objectives for a digital learning course, defining enabling objectives for the digital learning course. Such a person would have been motivated to make this combination as what is desired, therefore, is a method and system collecting, creating, and developing content for eLearning, which will simplify and improve the process of storyboarding by enabling team members to communicate and develop storyboards more efficiently and definitively (see par. 0007, SUBRAMANYAN).
Claim 10 amounts to the system that is analogous to a system with a combination of limitations from the system of claim 1 and claim 3. Accordingly, claim 10 is rejected for substantially the same reasons as presented above for combination of limitations from 1 and claim 3, and based on the references’ disclosure of the necessary supporting hardware and software.
Claim 11 amounts to the system that is analogous to the system of claim 4. Accordingly, claim 11 is rejected for substantially the same reasons as presented above for claim 4 and based on the references’ disclosure of the necessary supporting hardware and software.
Claim 12 amounts to the system that is analogous to the system of claim 5. Accordingly, claim 12 is rejected for substantially the same reasons as presented above for claim 5 and based on the references’ disclosure of the necessary supporting hardware and software.
Claim 13 amounts to the system that is analogous to the system of claim 6. Accordingly, claim 13 is rejected for substantially the same reasons as presented above for claim 6 and based on the references’ disclosure of the necessary supporting hardware and software.
Claim 14 amounts to the system that is analogous to the system of claim 7. Accordingly, claim 14 is rejected for substantially the same reasons as presented above for claim 7 and based on the references’ disclosure of the necessary supporting hardware and software.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Publication Number
Filing Date
Title
US11694564B2
2021-07-18
Maze training platform
US20140227675A1
2014-02-13
Knowledge evaluation system
US20080014569A1
2007-04-06
Teacher Assisted Internet Learning
US20150199910A1
2015-01-12
Systems and methods for an educational platform providing a multi faceted learning environment
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/KOOROSH NEHCHIRI/Examiner, Art Unit 2174
/WILLIAM L BASHORE/ Supervisory Patent Examiner, Art Unit 2174
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