DETAILED ACTION
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 .
Response to Amendment
The amendment filed May 15, 2026 has been entered. Claims 1, 5-8, 10-12, and 15-20 remain pending in the application. Claims 1, 8, 11, and 18 are noted as amended. Applicant’s amendments to the claims have overcome all previous objections and 35 U.S.C. 112(b) and 112(d) rejections set forth in the Non-Final Office Action mailed December 16, 2025 and all objections and 112(b) and 112(d) rejections therein have been withdrawn.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 5-8, 10-12, and 15-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claims 1 and 11 recite a process and a computer system for performing the process, the process including the steps of associating a user with a student account, the student account including at least user information; assigning a plurality of educational jobs to the student account; scoring each of the at least one educational jobs completed by the user; triggering/sending a reward to the student account based on the completion of the at least one educational job and the external performance data, the reward comprising at least one digital badge associated with a career or skill; prompting the user to take out a virtual loan; searching the user content database for saved user data comprising user actions, engagements, performances, and preferences tied to the student account; analyze the saved user data; and generating, based on a comparison of the saved user data against a plurality of age milestones associated with a goal system, a virtual credit score associated with the user. The recited steps, under their broadest reasonable interpretation, are associating a user with an account with user information, assigning a plurality of jobs/tasks to the student account, scoring each of the jobs/tasks completed by the user, triggering a reward to the student account based on the completion of at least one job/task, prompting the user to take out a virtual loan, searching a user database for user data, analyzing the user data, and generating a virtual credit score associated with the user based on a comparison of saved data against age milestones. The recited steps, as drafted, are a process that is a method of applying an abstract idea, specifically mental processes (evaluation (scoring each of the completed jobs/tasks; analyzing the user data; generating a virtual credit score; comparing saved user data against a plurality of age milestones), judgement (assigning a plurality of educational jobs; triggering a reward based on the completion; prompting the user to take out a virtual loan), observation (associating a user with a student account; searching the user content database)) and/or certain methods of organizing human activity in the form of teaching (associating a user with a student account; assigning a plurality of tasks to the account; scoring each of the completed tasks; triggering a reward based on the completion of the task; prompting the user to take out a virtual loan; comparing user data against a plurality of age milestones). If claim limitations, under their broadest reasonable interpretation, include a mental process and/or certain methods of organizing human activity, the limitations fall under the abstract ideas judicial exception and therefore recite ineligible subject matter. Accordingly, claims 1 and 11 recite abstract ideas.
This judicial exception is not integrated into a practical application because the claims do not recite additional elements that are significantly more than the judicial exception or meaningfully limit the practice of the judicial exception. The additional elements are storing data related to user completion of at least one of the plurality of educational jobs assigned to the student account in a user content database; interfacing, via an Application Programming Interface (API), with a third-party platform to receive external performance data representing a completed task on the third-party platform; a communication device [claim 11]; an educational jobs module [claim 11]; an API tool configured to interact with a third-party platform to receive external performance data [claim 11] a user content database [claim 11]; a scoring module [claim 11]; and a reward module [claim 11]; a plurality of saved user data comprising user actions, engagements, performance, and preferences tied to the student [claim 11]; at least one artificial intelligence (AI) or machine learning (ML) model configured to search the user content database [claim 11]; prompting via a graphical display on the student device; wherein at least one artificial intelligence (Al) or machine learning (ML) model continually analyzes the saved user data, said saved user data comprising the at least one educational jobs completed by the user; generating the virtual credit score based on an output of the at least one artificial intelligence (AI) or machine learning (ML) model; displaying the one or more additional educational jobs to a student device; displaying the at least one digit. The additional elements are insignificant extra-solution activity and instructions for applying the judicial exception with a generic computing device as, under their broadest reasonable interpretation, the additional step(s) is/are merely storing data (see MPEP 2106.05(d)(II)), interfacing/networking the device/system with a third-party platform and transmitting data over the network (see MPEP 2106.05(d)), defining the type of data stored (see MPEP 2106.05(g)), and displaying the results of the process. The other additional elements of via a graphical display on the device, a communication device, software modules, and a user content database are generic computer components for performing the above method, per MPEP 2106.05(f). Under their broadest reasonable interpretation, the additional elements are generic components of a computing device used to apply the abstract idea. Further, paragraphs 0084 and 0100 of the specification states the display device can be a mobile device/smartphone, a laptop, a computer, or a desktop, generic computing devices. As such, these additional elements are interpreted as merely instructions to apply the judicial exception. With regard to the recitation of at least one AI or ML model to analyze the saved user data and generate the virtual credit score, Examiner notes that the analysis of the saved user data is not defined and the analysis is not implemented or used in any way. Further, the models are not specifically defined and under their broadest reasonable interpretation amount to mere computer code/algorithm for performing the abstract idea of analyzing the saved user data and is merely generally linking the abstract ideas with the technical field of AI/ML as the specific steps for analyzing the user data and generating a virtual credit score are not defined beyond what would be readily capable of being performed in the human mind. Therefore, the recitation does not amount to a practical application or significantly more. Accordingly, the additional elements and steps do not integrate the abstract idea into a practical application because they do not impose any meaningful limitations on practicing the abstract idea. Therefore, the claims are directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as discussed above, the additional step(s) of storing data related to user completion in a database, interfacing with a third-party platform and receiving external data, and displaying the one or more additional educational jobs, the at least one digital badge, and the virtual credit score is/are insignificant extra-solution activity performed during the abstract idea. The additional elements of a communication device, software modules, a database, and at least one of an AI or ML model used to perform the process are generic computing components/instructions used to apply the judicial exception and therefore fall under the “apply it” limitation of the judicial exception and do not amount to significantly more per MPEP 2106.05(f). Further, the limitations, taken in combination, add nothing that is not already present when looking at the elements taken individually. With regard to the use of an API to interface and receive data from a third-party platform, as discussed above, using an API to interface and receive data is connecting systems over a network and transmitting and receiving data over the network which per MPEP 2106.05(d) is insignificant and well-understood, routine, and conventional. This is further supported by Ramos (US PGPub 2015012077) which states that networking computer or servers over a network for data retrieval including APIs is well-known to those having ordinary skill in the art (Ramos Paragraph 0103). As such, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, under their broadest reasonable interpretation, the additional elements do not meaningfully limit the practice of the abstract idea and do not amount to significantly more than the judicial exceptions. Therefore, claims 1 and 11 are not directed to eligible subject matter as they are abstract ideas without significantly more.
Claims 5-8, 10, 12, and 15-20 are dependent from claims 1 and 11 and include all the limitations of the independent claims. Therefore, the dependent claims recite the same abstract idea. The limitations of the dependent claims fail to amount to significantly more than the judicial exception. For example:
The limitations of claims 5, 10, 12, 15, and 20 recite further abstract ideas including polling user actions and data in real-time (observation MP), detecting further deviation (observation MP), notifying an administrator or the user (judgement MP and CMOHA), and assigning the plurality of educational jobs by an educational coach or the student themselves (judgement MP and CMOHA). As the limitations are further abstract ideas, the limitations cannot meaningfully limit or amount to significantly more than the abstract ideas of the independent claims. The additional elements of the dependent claims are further instructions for applying the abstract ideas with a generic computing device, specifically that some of the steps are performed using AI and ML which are recite at a high level of generality amounting to a computer algorithm/instructions for performing the abstract ideas and further software modules such as a user content module and analysis module. The limitations fail to provide any teaching that integrates the judicial exceptions into a practical application or amounts to significantly more than the judicial exceptions. For this reason, the analysis performed on the independent claims is also applicable on these claims.
The limitations of claims 6-8 and 16-18 recite further clarification of the types of educational jobs and rewards. Therefore, the limitations are defining the types of data used/comprising the educational jobs and rewards. The limitations, under their broadest reasonable interpretation, are merely defining/selecting a type of data to be manipulated which, per MPEP 2106.05(g), is insignificant extra-solution activity. Therefore, the limitations fail to provide any teaching that integrates the judicial exceptions into a practical application or amounts to significantly more than the judicial exceptions. For this reason, the analysis performed on the independent claims is also applicable on these claims.
The limitations of claim 19 recite that the educational jobs are designed by AI and ML. As the AI and ML are recited at a high level of generality, the limitations amount to mere instructions for applying the judicial exceptions with a generic computing device. Therefore, the limitations fail to provide any teaching that integrates the judicial exceptions into a practical application or amounts to significantly more than the judicial exceptions. For this reason, the analysis performed on the independent claims is also applicable on these claims.
Accordingly, claims 5-8, 10, 12, and 15-20 recite abstract ideas without significantly more and are not drawn to eligible subject matter.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 6, 10-11, 16, and 19-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bedor et al. (US PGPub 20200051460), hereinafter referred to as Bedor, in view of Kurani (US PGPub 20200258420), further in view of Chagpar et al. (US PGPub 20170206616), hereinafter referred to as Chagpar, further in view of Rollins (US PGPub 20240312363), further in view of Buten (US 8444418), further in view of Young et al. (US PGPub 20150194064), hereinafter referred to as Young, and further in view of Yang (US PGPub 20160335902).
With regard to claims 1 and 11, Bedor teaches a method of [claim 1] (Paragraph 0085; “method”) and a system for [claim 11] (Paragraph 0085; “system”) career development (Paragraphs 0008, 0161) comprising:
a communication device (Paragraph 0087; “user device 102”); an educational jobs module; a user content database; a scoring module; and a reward module [claim 11] (Paragraphs 0089-0096 teach the system is composed of a plurality of software modules for managing user data, assigning content/assignments, analyzing the content and user performance, and more);
associating a user with a student account, the student account including at least user information (Paragraphs 0105, 0186, 0367 teach the system includes the ability for a user to create a user account which is associated with a user profile which can include demographic information entered by the user);
assigning a plurality of educational jobs to the student account (Paragraphs 0090, 0103, 0252, 0373 teach that the system and/or a teacher can assign tasks, assignments, and curriculum to a student/student account);
storing data related to user completion of at least one of the plurality of educational jobs assigned to the student account in a user content database (Paragraphs 0087, 0091-0092, 0114 teach the system includes a storage device for storing system data and the system tracks and updates the user profile in the database/server based on user performance and completion and attempts of tasks);
scoring each of the at least one educational jobs completed by the user (Paragraphs 0092, 0103, 0217, 0390 teach the system assesses user performance and determines the user’s efficiency and mastery scores on the tasks and levels); and
triggering/sending a reward to the student account based on the completion of the at least one educational job (Paragraphs 0186, 0204, 0228, 0293, 0300 teaches the system provides rewards and achievements to the user that are stored in the user profile/account wherein the rewards and achievements can be triggered upon completion or “winning” a level);
a plurality of saved user data comprising user actions, engagements, performance, and preferences tied to the student [claim 11] (Paragraphs 0092, 0093, 0094, 0103 teach the system includes user profile data stored in the data storage device (saved user data) comprising user actions, engagement, performance and preferences);
searching the user content database for saved user data comprising user actions, engagements, performances and preferences tied to the student account (Paragraphs 0092-0094, 0103, 0165, 0229 teach the system can adapt the educational content based on the user learning profile which includes user actions, engagement, performance, and preferences which would thereby be “searched”); and
displaying one or more additional educational jobs to the student device (Paragraphs 0247-0248, 0373 teach the system can display unlocked content and assignments/assigned tasks which thereby includes “additional educational jobs” or tasks).
Bedor may not explicitly teach wherein at least one artificial intelligence (Al) or machine learning (ML) model continually analyzes the saved user data, said saved user data comprising the at least one educational jobs completed by the user. However, Kurani teaches a personalized and adaptive automated learning system and method based on a user’s personal attributes wherein the adaptive system includes a ML/AI model that continuously monitors and analyzes the learning processes of the student/user to make modifications to the learning content/process wherein when a user completes a lesson the system can adapt the content based on the user’s performance and attributes (saved user data) including completed processes/performances (Paragraphs 0023, 0048-0049, 0054, 0083).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bedor to incorporate the teachings of Kurani by incorporating the step of continuously monitoring and analyzing user data using AI/ML of Kurani to the user performance of Bedor, as both references and the claimed invention are directed to learning management systems that include presenting educational content to a user electronically using AI/ML modified content. One of ordinary skill in the art would modify Bedor by coding the system to continuously monitor and analyze user data using AI/ML including when a user completes an educational task/job. Upon such modification, the method and system of Bedor would include wherein at least one artificial intelligence (Al) or machine learning (ML) model continually analyzes the saved user data, said saved user data comprising the at least one educational jobs completed by the user. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate these teachings from Kurani with Bedor’s system and method in order to provide better educational content and continuously monitor user performance and data.
Bedor in view of Kurani may not explicitly teach the reward comprising at least one digital badge associated with a career or skill; and displaying the at least one digital badge to the student device. However, Chagpar teaches a system and method for learning management including tracking user status and completed learning actions and awarding badges related to user skills, knowledge, accomplishments, and challenges/certificates including using an intelligence machine/machine learning (Paragraphs 0059, 0094).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bedor in view of Kurani to incorporate the teachings of Chagpar by substituting the badges of Chagpar as the rewards of Bedor, as both references and the claimed invention are directed to learning management systems that include rewarding users for performance. One of ordinary skill in the art would modify Bedor in view of Kurani by substituting the badges of Chagpar for the rewards of Bedor for completion of a level or task associated with a skill and displaying the badges as part of the user profile as the badges of Chagpar are would have been obvious to one of ordinary skill in the art to improve Bedor in the same way by providing users with further reward options to better incentivize the users. Upon such modification, the method and system of Bedor in view of Kurani would include the reward comprising at least one digital badge associated with a skill; and displaying the at least one digital badge to the student device. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate these teachings from Chagpar with Bedor in view of Kurani’s system and method in order to provide users digital representations of their accomplishments and better incentivize users to complete educational content.
Bedor in view of Kurani and Chagpar may not explicitly teach generating, based on an output of the at least one artificial intelligence (Al) or machine learning (ML) model, a virtual credit score associated with the user; and displaying the virtual credit score to the student device. However, Rollins teaches an educational system for computing a simulated/academic credit score based on student/user factors including performance and completed assignments/tasks wherein the score can be displayed on the student/user device (Paragraphs 0014, 0017, 0028).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bedor in view of Kurani and Chagpar to incorporate the teachings of Rollins by including the simulated credit score of Rollins as one of the metrics of Bedor, as both references and the claimed invention are directed to learning management systems that include user profiles and academic performance. One of ordinary skill in the art would modify Bedor in view of Kurani and Chagpar by coding the AI/ML model of Bedor to include calculating a simulated/academic credit score based on user performance and other factors and displaying the credit score as part of the user profile. Upon such modification, the method and system of Bedor in view of Kurani and Chagpar would include generating, based on an output of the at least one artificial intelligence (Al) or machine learning (ML) model, a virtual credit score associated with the user; and displaying the virtual credit score to the student device. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate these teachings from Rollins with Bedor in view of Kurani and Chagpar’s system and method in order to further evaluate user performance and provide financial education and financial literacy education as part of the education provided.
Bedor in view of Kurani, Chagpar, and Rollins may not explicitly teach prompting the user, via a graphical display on a student device, to take out a virtual loan. However, Buten teaches a learning method and system for financial education including a simulated credit score and simulated loan options wherein the system can present a student with a selection of simulated loan options as part of a simulated educational experience (Abstract; Col 6, lines 52-56; Col 10, Line 60 – Col 11, line 16).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bedor in view of Kurani, Chagpar, and Rollins to incorporate the teachings of Buten by including the simulated loans and banking of Buten as one of the simulations/educational curriculum of Bedor, as both references and the claimed invention are directed to learning management systems that include simulated learning experiences. One of ordinary skill in the art would modify Bedor in view of Kurani, Chagpar, and Rollins by coding the system to use the simulated credit score metric of Bedor in view of Rollins to simulate and prompt a user to select a simulated loan option as part of a financial education simulation. Upon such modification, the method and system of Bedor in view of Kurani, Chagpar, and Rollins would include prompting the user, via a graphical display on a student device, to take out a virtual loan. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate these teachings from Buten with Bedor in view of Kurani, Chagpar, and Rollins’s system and method in order to provide further financial education and financial literacy education as part of the education curriculum provided.
Bedor further teaches the system can connect to user devices and servers through an application program interface and the user profile data is accessible through an API to enable integrated reporting to an educational system of record (Paragraphs 0087, 0103), but Bedor in view of Kurani, Chagpar, Rollins, and Buten may not explicitly teach interacting, via an Application Programming Interface (API), with a third-party platform to receive external performance data representing a completed task on the third party platform [claim 1]; and an API tool configured to interact with a third-party platform to receive external performance data [claim 11]; and triggering the reward based on the external performance data. However, Young teaches a learning management system including user certifications and badges related to completed user exercises, activities, or skills wherein the system can receive data from external sources through an API including systems such as skill assessment or performance systems or other LMSs wherein the system can determine/assess completion of exercises, activities, or tasks and assign points to the user upon completion (Paragraphs 0025, 0036, 0046, 0054-0055).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bedor in view of Kurani, Chagpar, Rollins, and Buten to incorporate the teachings of Young by including the API accessing external performance and LMS systems and retrieving user performance data of Young as part of the API of Bedor, as both references and the claimed invention are directed to learning management systems that include evaluating user performance. One of ordinary skill in the art would modify Bedor in view of Kurani, Chagpar, Rollins, and Buten by coding the system to include using the API to gather relevant data from external (third-party) sources including databases and systems such as skill assessment or performance systems or other LMSs and receiving the performance/task completion data from the exercises or tasks completed on the external systems. Upon such modification, the method and system of Bedor in view of Kurani Chagpar, Rollins, and Buten would include interacting, via an Application Programming Interface (API), with a third-party platform to receive external performance data representing a completed task on the third party platform [claim 1]; and an API tool configured to interact with a third-party platform to receive external performance data [claim 11]; and triggering the reward based on the external performance data. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate these teachings from Young with Bedor in view of Kurani, Chagpar, Rollins, and Buten’s system and method as using API to retrieve data from external/other sources is well-known in the art and in order to provide integrated and aggregated reporting to an educational system and provide easier access to a supervisor/teacher to monitor user performance (Bedor Paragraph 0103).
Bedor in view of Kurani, Chagpar, Rollins, Buten, and Young may not explicitly teach a comparison of the saved user data against a plurality of age milestones associated with/defined in a goal system. However, Yang teaches a learning diagnosis system and method including achievement milestones and sub-milestones associated with age and level references such that a learner/user’s performance may be assessed (compared) using the milestones to gauge user performance and provide an assessment of user performance (Paragraphs 0053, 0056, 0058, 0106).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bedor in view of Kurani, Chagpar, Rollins, Buten, and Young to incorporate the teachings of Yang by applying the technique of comparing user performance on an activity/task to an age based milestone of Yang to the game and task performance of Bedor to calculate the simulated/academic credit score of Bedor in view of Rollins, as the references and the claimed invention are directed to learning management systems that include evaluating user performance. One of ordinary skill in the art would modify Bedor in view of Kurani, Chagpar, Rollins, Buten, and Young by coding the system to include age based milestones and sub-milestones and comparing the performance data from the tasks and games against the milestones and sub-milestones and including the comparison and analysis in calculating the simulated/academic credit score. Upon such modification, the method and system of Bedor in view of Kurani Chagpar, Rollins, Buten, and Young would include comparison of the saved user data against a plurality of age milestones associated with/defined in a goal system. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate these teachings from Yang with Bedor in view of Kurani, Chagpar, Rollins, Buten, and Young’s system and method as age based milestone evaluation in learning management is well-known in the art and in order to evaluate learner performance and determine if a learner is lagging or underperforming compared to other learners (Yang paragraph 0053).
With regard to claims 6 and 16, Bedor further teaches wherein the educational jobs include at least one of a quiz (Paragraphs 0101, 0299), a curriculum (Paragraphs 0096-0097; “curriculum”), a course (Paragraphs 0118, 0140; “courses”), a live online class (Paragraphs 0118, 0132, 0134; “classroom presentations”), an educational game (Abstract; Paragraphs 0085-0086; “educational game”), and a career exploration task (Paragraph 0161; “out of game searches”).
With regard to claim 19, Bedor further teaches wherein the educational jobs are designed by AI and ML (Abstract; Paragraphs 0112, 0165, 0239 teaches the system can dynamically generate the game and content including using machine learning and artificial intelligence).
With regard to claims 10 and 20, Bedor further teaches wherein assigning the plurality of educational jobs to the student account includes at least one of automatically assigning the plurality of educational jobs by an assignment module (Paragraphs 0090, 0103 teaches the system can assign assignments with the assignment module), assigning the plurality of educational jobs by an educational coach or administrator (Paragraph 0252 teaches a teacher/administrator can issue assignments or challenges to users), or the student assigning themselves the educational jobs by selecting a subset from all available educational jobs (Paragraphs 0107-0109, 0162 teach the user can make their own selections including learning materials and accessing levels/tasks).
Claim(s) 5 and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bedor in view of Kurani, Chagpar, Rollins, Buten, Young, and Yang as applied to claims 4 and 14 above, and further in view of Alkan et al. (US PGPub 20200143498), hereinafter referred to as Alkan.
With regard to claims 5 and 15, Bedor further teaches further comprising: continuously polling at least user actions, engagements, performances, and preferences in real-time (Paragraphs 0086, 0092-0094, 0432 teach the system includes real-time tracking of user’s activity and actions and that functions of the system can be performed in real-time; see also, paragraph 0251 which teaches user’s performance can be compared to determine change over time), but Bedor in view of Kurani, Chagpar, Rollins, Buten, Young, and Yang may not explicitly teach detecting further deviation from the determined career path alignment and position and the planned career path; and notifying an administrator or the user of the further deviation. However, Alkan teaches a system and method for career planning including career paths wherein the system determines a career path and can infer missing steps and failure paths/alternative paths and alert a user or alternative users (i.e., a manager, supervisor, etc.) wherein the career path/model and failures are continuously updated over time thereby detecting “further deviations” from a desired career path (Paragraphs 0059, 0071-0073, 0075-0076).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bedor in view of Kurani, Chagpar, Rollins, Buten, Young, and Yang to incorporate the teachings of Alkan by continuously monitoring the user’s performance and career path in real time as taught by Bedor and determining if a user further deviates from a career goal/path and alerting the user and/or another user as taught by Alkan, as the references and the claimed invention are directed to career planning systems user profiles and comparing user career paths to other users/career paths. One of ordinary skill in the art would modify Bedor in view of Kurani, Chagpar, Rollins, Buten, Young, and Yang by coding the system to continuously monitor a user’s performance and career path and notify the user or another user if the user/account deviates from the career goal and/or path. Upon such modification, the method and system of Bedor in view of Kurani, Chagpar, Rollins, Buten, Young, and Yang would include detecting further deviation from the determined career path alignment and position and the planned career path; and notifying an administrator or the user of the further deviation. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate these teachings from Alkan with Bedor in view of Kurani, Chagpar, Rollins, Buten, Young, and Yang’s system and method in order to ensure a user is on the correct career path and improve user interaction/awareness by alerting the user.
Claim(s) 7 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bedor in view of Kurani, Chagpar, Rollins, Buten, Young, and Yang, as applied to claims 1 and 11 above, and further in view of Asfaw et al. (US PGPub 20190347954), hereinafter referred to as Asfaw.
With regard to claims 7 and 17, Bedor in view of Kurani, Chagpar, Rollins, Buten, Young, and Yang may not explicitly teach wherein the educational jobs include at least one of an augmented reality task, a virtual reality task, a metaverse task, and a holographic task. However, Asfaw further teaches the user electronic device includes virtual reality and augmented reality technology such that a class or task can be in VR or AR (Paragraphs 0036, 0047).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bedor in view of Kurani, Chagpar, Rollins, Buten, Young, and Yang to incorporate the teachings of Asfaw by incorporating the AR/VR system of Asfaw as the user device of Bedor and providing users AR/VR classes and content as the content of Bedor, as the references and the claimed invention are directed to learning management systems that include career profiles and presenting educational content to a user electronically. One of ordinary skill in the art would modify Bedor in view of Kurani, Chagpar, Rollins, Buten, Young, and Yang by substituting the AR/VR system for the user device and coding the system to present classes and other educational content and tasks in AR/VR. Upon such modification, the method and system of Bedor in view of Kurani, Chagpar, Rollins, Buten, Young, and Yang would include wherein the educational jobs include at least one of an augmented reality task and a virtual reality task. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate these teachings from Asfaw with Bedor in view of Kurani, Chagpar, Rollins, Buten, Young, and Yang’s system and method in order to improve user engagement and provide better educational content and resources to match a user’s goals.
Claim(s) 8 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bedor in view of Kurani, Chagpar, Rollins, Buten, Young, and Yang, as applied to claims 1 and 11 above, and further in view of Grimes et al. (US PGPub 20140272847), hereinafter referred to as Grimes.
With regard to claims 8 and 18, while Bedor in view of Kurani and Chagpar teach the reward comprises at least one digital badge (see prior art rejection of claims 1 and 11 above), Bedor in view of Kurani, Chagpar, Rollins, Buten, Young, and Yang may not explicitly teach wherein the reward is at least one of cash, cash credits, certificates, e-gifts, e-vouchers, open-loop tokenization, or closed-loop tokenization. However, Grimes teaches a system and method for reward-based learning sessions wherein reward is triggered upon a user achieving an academic milestone and/or completing a task wherein the reward can be cash, credit, intangible items, bitcoins (open-loop tokenization), gift certificate (certificate/e-gift/e-voucher) (Abstract; Paragraphs 0053, 0086, 0190).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bedor in view of Kurani, Chagpar, Rollins, Buten, Young, and Yang to incorporate the teachings of Grimes by substituting the rewards of Grimes as the rewards of Bedor, as both references and the claimed invention are directed to learning management systems that include rewarding users for performance. One of ordinary skill in the art would modify Bedor in view of Kurani, Chagpar, Rollins, Buten, Young, and Yang by substituting the rewards of Grimes including cash, bitcoin, credit, intangible items, and gift certificates for the rewards of Bedor triggered upon completion of a level or task as the enumerated rewards of Grimes are well-known and would have been obvious to one of ordinary skill in the art to improve Bedor in the same way by providing users with reward options to better incentivize the users. Upon such modification, the method and system of Bedor in view of Kurani, Chagpar, Rollins, Buten, Young, and Yang would include wherein the reward is at least one of cash, cash credits, certificates, e-gifts, e-vouchers, or open-loop tokenization. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate these teachings from Grimes with Bedor in view of Kurani, Chagpar, Rollins, Buten, Young, and Yang’s system and method in order to provide users reward options and better incentivize users to complete educational content.
Response to Arguments
Applicant's arguments, see Remarks pages 8-9, filed May 15, 2026, with respect to the rejection(s) of claim(s) 1, 5-8, 10-12, and 15-20 under 35 U.S.C. 101 have been fully considered but they are not persuasive. Applicant’s arguments is the claimed limitations, when viewed as a whole, are directed toward significantly more by being directed to a specific technical architecture for cross-platform vocational data synchronization and chronological behavioral diagnostics by interfacing via an API to perform cross-verification of external performance data. Applicant’s arguments are not substantiative and merely conclusory statements without support in the claim language or specification as the argument is not commensurate with the claim language. Specifically, it is unclear what applicant is referring to with regard to “cross-verification of external performance data” as the claimed limitations are merely interfacing with an external system/server (third-party platform) and receiving data which is used to trigger the reward. First, the triggering of the reward based on the external performance data is not even specifically defined, i.e., is the reward triggered on completion, as the claims have been interpreted above, or a certain threshold score being reached or such, and second, as discussed above, networking devices and applications and receiving data over a network is well-understood, routine, and conventional per MPEP 2106.05(d) and further supported by Ramos (US PGPub 2015012077) which states that networking computer or servers over a network for data retrieval including APIs is well-known to those having ordinary skill in the art (Ramos Paragraph 0103). Further, the use of a generic AI or ML model is merely a generic computer algorithm when recited at a high level of generality as in the instant claims as seen in Recentive Analytics, Inc. v. Fox Corp., Fox Broadcasting Company, LLC, Fox Sports Productions, LLC, Case No. 23-2437, (Fed. Cir. 2025) and the added step of comparing the data to a plurality of age milestones is a mental process and CMOHA as discussed above and not a technical improvement or specialized AI/ML engine as the step is a mental process implemented on by a generic computing algorithm as discussed above. As such, Applicant’s arguments are not persuasive and the claims are not directed to eligible subject matter as they are abstract ideas without significantly more. Therefore, the claims stand rejected under 35 U.S.C. 101.
Applicant’s arguments, see Remarks, filed May 15, 2026, with respect to the rejection(s) of claim(s) 1, 5-8, 10-12, and 15-20 under 35 U.S.C. 103 have been fully considered and are persuasive by virtue of applicant’s amendments to the claims. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of 35 U.S.C. 103 in view of the newly cited combination of prior art discussed above.
Addressing some of Applicant’s arguments that are not persuasive with regard to the rejection(s) under 35 U.S.C. 103: Applicant’s assertion of Bedor being directed to a “localized pedagogical environment and lacking the claimed API-driven architecture” is only partially persuasive as discussed above, but it is noted that Bedor’s “localization” is referring to a country or society context rather than a purely “localized” device as Bedor does teach API integration as discussed above. Further, Applicant attempts to differentiate between Bedor’s performance data and scoring and the claimed rewards and scoring by insinuating that Bedor is only directed to “gameplay mastery”. However, Bedor explicitly teaches the performance evaluation is also with regard to academic/educational performance and learning objectives such as a user’s mastery of an educational curriculum and skills such as reading, writing, critical thinking, and collaboration. In response to applicant's argument that the examiner's conclusion of obviousness is based upon improper hindsight reasoning, it must be recognized that any judgment on obviousness is in a sense necessarily a reconstruction based upon hindsight reasoning. But so long as it takes into account only knowledge which was within the level of ordinary skill at the time the claimed invention was made, and does not include knowledge gleaned only from the applicant's disclosure, such a reconstruction is proper. See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971). Further, Applicant’s arguments are not commensurate with the claim language as the instant claims do not limit the educational jobs and evaluation to “vocational skills” as the rewards and scores can be associated with a “skill” which is a broader term. Regardless, Bedor is teaching skill development and would still be applicable to the instant claims.
Conclusion
Accordingly, claims 1, 5-8, 10-12, and 15-20 are rejected.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CORRELL T FRENCH whose telephone number is (571)272-8162. The examiner can normally be reached M-Th 7:30am-5pm; Alt Fri 7:30am-4pm EST.
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/CORRELL T FRENCH/Examiner, Art Unit 3715
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