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 .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 03/19/2026 has been entered.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to judicial exception(s) without significantly more.
[STEP 1] The claim recites at least one step or structure. Thus, the claim is to a process or product, which is one of the statutory categories of invention (Step 1: YES).
[STEP2A PRONG I] The claim(s) 1, 10 and 18 recite(s):
Initiating, by an educational application, a workflow for a class of student users comprising a plurality of student users, the workflow comprising a set of prompts to which the student users are to respond with answers within a defined duration of time, the workflow beginning with a first of the ordered prompts for each of the plurality of students;
For each answer:
determining a predicted set of requirement for processing the answer;
determining, from a plurality of candidate model having different processing capabilities, to use a large language model (LLM) of the plurality of candidate models based on it satisfying the predicted set of requirements while requiring less processing power to process the answer relative to other ones of the plurality of candidate models that also satisfy the predicted set of requirements;
generating, by the educational application, a classification for the answer at least in part by prompting the LLM to classify the answer and storing the answer and the classification of the answer in a datastore;
and
generating for display to a teacher user a user interface that during the defined duration fo time, simultaneously tracks progress of each student user of the class of student users through the workflow in real time by:
retrieving progress information for the student users from the datastore, the progress information reflecting a portion of the workflow through which each student user has completed and a corresponding classification for each completed prompt within the portion;
outputting a progress bar for each student user showing a cell for each completed prompt within the portion; and
outputting an indicator within each cell showing a corresponding classification of the answer corresponding to each cell.
The non-highlighted aforementioned limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation between people but for the recitation of generic computer components. That is, other than reciting “LLM” [claim 1, 10 and 18], “datastore” [claim 1, 10 and 15], “user interface” [claim 1], “a non-transitory computer readable medium” [claim 10], “processor” [claim 10 and 18] and “computer-readable storage medium” [claims 8 and 15] and memory [claim 18], nothing in the claim element precludes the step from practically being performed between people. For example, but for the recited language, the step in the context of this claim encompasses a teacher receiving answer from the student, classifying and storing such answer, providing information about the progress of each student and providing classification information on each cell.
If a claim limitation, under its broadest reasonable interpretation, covers managing interactions between people, then it falls within the “Organization of Human Activity” grouping of abstract ideas.
Accordingly, the claim recites a judicial exception, and the analysis must therefore proceed to Step 2A Prong Two.
[STEP2A PRONG II] This judicial exception is not integrated into a practical application. In particular, the claim only recites the additional element(s) – “LLM” [claim 1, 10 and 18], “datastore” [claim 1, 10 and 15], “user interface” [claim 1], “a non-transitory computer readable medium” [claim 10], “processor” [claim 10 and 18] and “computer-readable storage medium” [claims 8 and 15] and memory [claim 18],
The “LLM” [claim 1, 10 and 18], “datastore” [claim 1, 10 and 15], user interface [claim 1], “a non-transitory computer readable medium” [claim 10], processor [claim 10 and 18] and “computer-readable storage medium” [claims 8 and 15] and memory [claim 18] in the aforementioned steps are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component.
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea and the claim is therefore directed to the judicial exception. (Step 2A: YES).
[STEP2B] The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform the aforementioned steps amounts to no more than mere instructions to apply the exception using a generic computer component, which cannot provide an inventive concept (for example, see paragraph 19-22, 53, 57).
As noted previously, the claim as a whole merely describes how to generally “apply” the aforementioned concept in a computer environment. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea.
The claim is not patent eligible. (Step 2B: NO).
Claim(s) 2-9, 11-17, and 19-20 is/are dependent on supra claim(s) and includes all the limitations of the claim(s). Therefore, the dependent claim(s) recite(s) the same abstract idea. The claim recites no additional limitations. Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea and the claim is therefore directed to the judicial exception. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea.
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.
Claims 1, 10 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Bardige US 8545232 and in view of Sait US 20250148931, in view of Banarjee et al US 20030044760 and further in view of Forrest US 20250124804
Claim 1, 8 and 18: The Bardige reference provides a teaching of
Initating, by an educational application, a workflow for a class of student users comprising a plurality of student users(col. 8:28-32 “student 1 – student N), the workflow comprising a set of prompts to which the student users are to respond with answers (see col. 11:25-35 ) the workflow beginning with a first of the first ordered prompts for each of the plurality of students (col. 11:25-50 showing ordered prompts for each of the plurality of student and see also FIG. 2D-G);
and
generating for display to a teacher user a user interface that tracks progress of each student user of the class of student users through the workflow in real time by:
retrieving progress information for the student users from the datastore, the progress information reflecting a portion of the workflow through which each student user has completed and a corresponding classification for each completed prompt within the portion; (see col. 3:15-35)
outputting a progress bar for each student user showing a cell for each completed prompt within the portion (see FIG. 2E col. 11:40-50); and
outputting an indicator within each cell showing a corresponding classification of the answer corresponding to each cell (see col. 11:25-30).
The Bardige reference is silent on the teaching of prompts for users to respond within a defined duration of time, generating, by the educational application, a classification for each answer at least in part by prompting at least one large language model (LLM) to classify the answer, storing the answer and the classification of the answer in a datastore and display for the teacher user interface during the defined duration of time.
However, the Sai reference provides teaching of generating, by the educational application, a classification for each answer at least in part by prompting at least one large language model (LLM) to classify the answer and storing the answer and the classification of the answer in a datastore (see paragraph 50).
Therefore, 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 Bardige reference with the feature of generating, by the educational application, a classification for each answer at least in part by prompting at least one large language model (LLM) to classify the answer and storing the answer and the classification of the answer in a datastore, as taught by the Sait, in order to providing personalized session that meets the student’s need (see paragraph 20).
The Banarjee reference provides a teaching of prompts for users to respond within a defined duration (see paragraph 72 time period for the user to answer in the time period associated with each question) and display for the teacher user interface during the defined duration of time (see paragraph 66 proctor/teacher monitoring during the defined period time).
Therefore, 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 with the feature of prompts for users to respond within a defined duration and display for the teacher user interface during the defined duration of time, as taught by the Banarjee et al, in order to provide an efficient test taking environment (see paragraph 8).
The Bardige reference is silent on the teaching of for each answer: determine a predicted set of requirements for processing the answer; determine, from a plurality of candidate models having different processing capabilities, to use a large language model (LLM) of the plurality of candidate models based on it satisfying the predicted set of requirements while requiring less processing power to process the answer relative to other ones of the plurality of candidate models that also satisfy the predicted set of requirements.
However, the Forrest reference provide a teaching of for each answer: determine a predicted set of requirements for processing the answer; determine, from a plurality of candidate models having different processing capabilities, to use a large language model (LLM) of the plurality of candidate models based on it satisfying the predicted set of requirements while requiring less processing power to process the answer relative to other ones of the plurality of candidate models that also satisfy the predicted set of requirements (see paragraph 25 and 30).
Therefore, 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 with the feature of for each answer: determine a predicted set of requirements for processing the answer; determine, from a plurality of candidate models having different processing capabilities, to use a large language model (LLM) of the plurality of candidate models based on it satisfying the predicted set of requirements while requiring less processing power to process the answer relative to other ones of the plurality of candidate models that also satisfy the predicted set of requirements, as taught by the Forrest reference, since it allows the system to minimize power consumption (see paragraph 25).
Response to Arguments
Applicant's arguments filed 03/19/2026 have been fully considered but they are not persuasive.
The applicant argued that the requirement of “determining, from a plurality of candidate models having different processing capabilities, to use a large language model (LLM) of the plurality of candidate models based on it satisfying the predicted set of requirements while requiring less processing power to process the answer relative to other ones of the plurality of candidate models that also satisfy the predicted set of requirements" should be interpreted as a solution to technical problem that integrates the abstract idea into a practical application. The applicant set forth ex parte Desjardins and applicant specification paragraph 31-32 as evidence of a technical solution that leads to improved functioning of a computer or to the technology. The examiner respectfully disagrees. An important consideration in determining whether a claim improves technology is the extent to which the claim covers a particular solution to a problem or a particular way to achieve a desired outcome, as opposed to merely claiming the idea of a solution or outcome. McRO, 837 F.3d at 1314-15, 120 USPQ2d at 1102-03; DDR Holdings, 773 F.3d at 1259, 113 USPQ2d at 1107. An indication that the claimed invention provides an improvement can include a discussion in the specification that identifies a technical problem and explains the details of an unconventional technical solution expressed in the claim, or identifies technical improvements realized by the claim over the prior art [see MPEP 2106.05(a)]. However, the applicant’s specification paragraph 30-32 does not provide the necessary details of an unconventional technical solution expressed in the claim. For example, paragraph 31-32 of the application only provide a discussion of the how one model (ChatGPT 3.5) can be substituted with another model (ChatGPT4) in order to maintain power efficiency. The specification is silent on the algorithm necessary to support the finding of improvement to the technology that integrates the abstract idea into a practical application. Furthermore, applicant’s specification does not discount the possibility of the model selection to be performed mentally in the mind of the user. For these reasons, the rejection on claims 1-20 under 35 U.S.C 101 will be maintained.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ROBERT J UTAMA whose telephone number is (571)272-1676. The examiner can normally be reached 9:00 - 17:30 Monday - Friday.
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/ROBERT J UTAMA/Primary Examiner, Art Unit 3715
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