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 .
Status of Claims
2. This Office Action is in response to the initial filing of application #18/963242 filed on 11/27/2024.
3. Claims 1-20 are currently pending and are considered below.
Information Disclosure Statement
4. The information disclosure statement (IDS) submitted on 11/27/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Interpretation
5. The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
6. The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
7. This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “a subscription verification module adapted to…”: “a data input module adapted to…”; a data processing module adapted to…” and “a report generation module adapted to…” in claim 1.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 101
8. 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.
9. Claims 1-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more. Representative claim 1, recites a system for generating individual student reports, comprising:
a subscription verification module adapted to control and authenticate user
access;
a data input module adapted to receive student data for report generation,
a data processing module adapted to utilize a plurality of data transformation
methods to transform the student data and generate an artificial intelligence (AI) prompt
string; and
a report generation module adapted to receive the AI prompt string and generate
an individualized student report.
The steps of,
a subscription verification module adapted to control and authenticate user
access;
a data input module adapted to receive student data for report generation,
a data processing module adapted to utilize a plurality of data transformation
methods to transform the student data and generate an artificial intelligence (AI) prompt
string; and
a report generation module adapted to receive the AI prompt string and generate
an individualized student report
as drafted, is a process that, under its broadest reasonable interpretation, covers a method of organizing human activity. Given the broadest reasonable interpretation, the claim recites a system for generating individual student reports. The above identified method steps recite commercial interactions such as sales activities and/or tailored personalized marketing relating to improving generating individual student reports.
If a claim limitation, under its broadest reasonable interpretation, covers commercial interaction such as commercial interaction, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of a subscription verification module, a data input module, a data processing module, a report generation module, a payment processing platform, machine learning algorithms, a privacy compliance module, a user interface module, a payment processor and an artificial intelligence engine. The subscription verification module, a data input module, a data processing module, a report generation module, a payment processing platform, machine learning algorithms, a privacy compliance module, a user interface module and an artificial intelligence engine is recited at a high level of generality (i.e., as a generic processor performing a generic computer functions of verifying a user's subscription status; receiving student data; processing and transforming the student data for artificial intelligence (AI)
processing; anonymizing and redacting the student data; generating an individualized student report; and providing the individualized student report to a user) such that they amount to no more than mere instructions to apply the exception using generic computer components. As for the limitation generate an artificial intelligence (AI) prompt string, this feature is considered math, and therefore is a part of the abstract idea. Because the artificial intelligence in this claim is used as a tool for improving the abstract idea, rather than improving any technical feature or function, it is not sufficient to integrate the judicial exception into a practical application. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
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 elements of a subscription verification module, a data input module, a data processing module, a report generation module, a payment processing platform, machine learning algorithms, a privacy compliance module, a user interface module, a payment processor and an artificial intelligence engine amount to no more than mere instructions to apply the exception using generic computer components. The additional elements are similar to the additional elements found by courts to be mere instructions to apply an exception because they do no more than merely invoke computers or machinery to perform an existing process such as: a common business method or mathematical algorithm being applied on a general purpose computer (Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 573 US 208, 223; Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334); generating a second menu from a first menu and sending the menu to the second location as performed by a generic computer components (Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1243-44). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
Thus, considered as an ordered combination, the additional elements add nothing that is already present when the steps are considered separately. That is, a subscription verification module, a data input module, a data processing module, a report generation module, a payment processing platform, machine learning algorithms, a privacy compliance module, a user interface module, a payment processor and an artificial intelligence engine, performing commercial interactions including: verifying a user's subscription status; receiving student data; processing and transforming the student data for artificial intelligence (AI) processing; anonymizing and redacting the student data; generating an individualized student report; and providing the individualized student report to a user, amount to mere instructions to apply the steps to a computer comprising of a processor.
Thus, independent claims 1 and 12 are not eligible.
As for dependent claims 2-11 and 13-20, these claims recite limitations that further define the same abstract idea in claims 1 and 12, to generate individualized student reports. Therefore, they are considered patent ineligible for the reasons given above. The additional limitations of the dependent claims, when considered individually and as an ordered combination, do not amount to significantly more than the abstract idea itself.
Claims 1-20 are therefore not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
10. Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is
directed to non-statutory subject matter. The claim does not fall within at least one of
the four categories of patent eligible subject matter because the claims are directed to
software per se. A computer program product can be eligible for patent protection if it is
tangibly embodied on a non-transitory machine-readable medium and, when executed
by a computer, performs the steps of the invention. Claims 2-11 are also rejected as
they depend on independent claim 1.
Claim Rejections - 35 USC § 103
11. 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.
12. 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.
13. 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.
14. Claims 1-2, 4-15 and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Davison (U.S. Pub. No. 2014/0172516) in view of King (U.S. Pub. No. 2025/0061530).
Claim 1: Davison discloses a system for generating individualized student reports, comprising:
a data input module adapted to receive student data for report generation, and generate an individualized student report, Davison teaches receive student information and selections of the displayed academic categories, performance indicators and related selected metrics from the interactive computer medium over a communication network and each of the received performance indicators are then combined with each of the received metrics and formed into at least one complete sentence presentable in a student report measuring an academic performance of the student for one or more academic categories (see at least paragraphs 0005-0006 and 0014).
While Davison teaches the limitations mentioned above, Davison does not explicitly teach a subscription verification module adapted to control and authenticate user access; a data processing module adapted to utilize a plurality of data transformation methods to transform the student data and generate an artificial intelligence (AI) prompt string; and a report generation module adapted to receive the AI prompt string.
However, King teaches a subscription verification module adapted to control and authenticate user access, King teaches student account register (100) and teacher/administrator account register (110) storing details of students (30) and teachers/administrators (60) who are registered to use the software applications (40) and (70), respectively (e.g. name, address, contact details, details relating to any relevant education institution associated with the student and/or teacher, and any additional data which may be relevant for the purpose of identifying each user). Where possible these details may be verified using identification verification services (see at least paragraph 0044); and
a data processing module adapted to utilize a plurality of data transformation methods to transform the student data and generate an artificial intelligence (AI) prompt string; and a report generation module adapted to receive the AI prompt string, King teaches an additional benefit of storing the various inputs by students (30) in response to questions and activities, and the results of analysis conducted by the artificial intelligence engine (170) and any additional processing techniques performed by server (20) with respect to the assessment of students and their learning difficulties and/or disorders, is that the server (20) may subsequently be used to conduct various additional analyses based on historical data, such as trend analyses and the like (see at least paragraphs 0037-0038, 0049-0050, 0063 and 0066-0069). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention for Davison to modify to include the teaching of King in order to determine individual student progress and identify trends that will result in difficulty for a student to achieve an expected educational proficiency in the future.
Claim 2:: Davison in view of King disclose the system according to claim 1, and King further teaches wherein the subscription verification module is adapted to interface with a subscription management system to ensure user authorization, King teaches student account register (100) and teacher/administrator account register (110) storing details of students (30) and teachers/administrators (60) who are registered to use the software applications (40) and (70), respectively (e.g. name, address, contact details, details relating to any relevant education institution associated with the student and/or teacher, and any additional data which may be relevant for the purpose of identifying each user). Where possible these details may be verified using identification verification services (see at least paragraph 0044). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention for Davison to modify to include the teaching of King in order to determine individual student progress and identify trends that will result in difficulty for a student to achieve an expected educational proficiency in the future.
Claim 4: Davison in view of King disclose the system according to claim 1, and King further teaches wherein the student data includes a plurality of standardized test scores and observation reports, King teaches segment 700 of FIG. 1 illustrates the review of class and student results (320) by the teacher/administrator (60) based upon completion of the test or assessments by the students and the analysis of the
answers/response provided, as detailed in FIG. 7. (see at least paragraphs 0033 and 0042). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention for Davison to modify to include the teaching of King in order to determine individual student progress and identify trends that will result in difficulty for a student to achieve an expected educational proficiency in the future.
Claim 5: Davison in view of King disclose the system according to claim 1, and King further teaches wherein the data transformation methods include machine learning algorithms and natural language processing techniques, King teaches an additional benefit of storing the various inputs by students (30) in response to questions and activities, and the results of analysis conducted by the artificial intelligence engine (170) and any additional processing techniques performed by server (20) with respect to the assessment of students and their learning difficulties and/or disorders, is that the server (20) may subsequently be used to conduct various additional analyses based on historical data, such as trend analyses and the like (see at least paragraphs 0037-0038, 0049-0050, 0063 and 0066-0069). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention for Davison to modify to include the teaching of King in order to determine individual student progress and identify trends that will result in difficulty for a student to achieve an expected educational proficiency in the future.
Claim 6: Davison in view of King disclose the system according to claim 1, and Davison further teaches wherein the data input module is further adapted to prompt a user to manually enter categorical information, Davison teaches user selected academic categories, performance indicators and metrics are received by a server from at least two remote devices over a communication network and the received performance
indicators are combined with each of the received metrics and based on the student information, into at least one complete sentence presentable in a student report measuring an academic performance of a student for one or more of the academic categories (see at least paragraph 0009).
Claim 7: Davison in view of King disclose the system according to claim 1, and Davison further teaches wherein the data input module is further adapted to be integrated with third-party platforms to automatically receive student data generated by the third-party platforms, Davison teaches compiling the student report from multiple
remote devices simultaneously over the communication network and the system may establish multiple data connection requests in a central server with the multiple remote
devices (see at least paragraphs 0005 and 0008).
Claim 8: Davison in view of King disclose the system according to claim 1, and Davison further teaches wherein data input module is further adapted to receive different file types, Davison teaches receive student information and selections of the displayed academic categories, performance indicators and related selected metrics from the interactive computer medium over a communication network and each of the received performance indicators are then combined with each of the received metrics and formed into at least one complete sentence presentable in a student report measuring an academic performance of the student for one or more academic categories (see at least paragraphs 0005-0007 and 0008).
Claim 9: Davison in view of King disclose the system according to claim 1, and Davison further teaches wherein the data processing module is further adapted to transform the student data into categorical scores or paragraph form, Davison teaches user selected academic categories, performance indicators and metrics are received by a server from at least two remote devices over a communication network and the received performance indicators are combined with each of the received metrics and based on the student information, into at least one complete sentence presentable in a student report measuring an academic performance of a student for one or more of the academic categories (see at least paragraph 0009).
Claim 10: Davison in view of King disclose the system according to claim 1, and King further teaches the system further comprising a privacy compliance module adapted to anonymize and redact confidential or private portions of the student data, King teaches student account register (100) and teacher/administrator account register (110) storing details of students (30) and teachers/administrators (60) who are registered to use the software applications (40) and (70), respectively (e.g. name, address, contact details, details relating to any relevant education institution associated with the student and/or teacher, and any additional data which may be relevant for the purpose of identifying each user). Where possible these details may be verified using identification verification services (see at least paragraph 0044). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention for Davison to modify to include the teaching of King in order to determine individual student progress and identify trends that will result in difficulty for a student to achieve an expected educational proficiency in the future.
Claim 11: Davison in view of King disclose the system according to claim 1, and Davison further teaches the system further comprising a user interface module adapted to provide a user-friendly interface for teachers and students, Davison teaches permitting the compiling of a student report from at least two remote devices simultaneously over the communication network. This step inherently allows the
central computer system to receiving data communications from at least two remote devices via a communication network. The two remote devices preferably connect via a web based software application that communicates with the central computer or server. This feature may also permit two users to simultaneously add, delete, or modify the student report through respective interactive computer mediums (see at least paragraphs 0005 and 0013).
Claim 12: Davison discloses a method of generating individualized student reports, comprising:
receiving student data via a data input module, Davison teaches receive student information and selections of the displayed academic categories, performance indicators and related selected metrics from the interactive computer medium over a communication network and each of the received performance indicators are then combined with each of the received metrics and formed into at least one complete sentence presentable in a student report measuring an academic performance of the student for one or more academic categories (see at least paragraphs 0005-0006 and 0014);
generating an individualized student report with the processed student data, Davison teaches receive student information and selections of the displayed academic categories, performance indicators and related selected metrics from the interactive computer medium over a communication network and each of the received performance indicators are then combined with each of the received metrics and formed into at least one complete sentence presentable in a student report measuring an academic performance of the student for one or more academic categories (see at least paragraphs 0005-0006 and 0014); and
providing the individualized student report to a user via a user interface module, Davison teaches the systems and methods disclosed herein provide access to a central electronic database via a communication network to facilitate simultaneous multi-user access, input and report generation (see at least paragraphs 0005 and 0052).
While Davison teaches all the limitations mentioned above, Davison does not explicitly teach verifying a user's subscription status with a subscription verification module; processing and transforming the student data for artificial intelligence (AI) processing via a data processing module; and anonymizing and redacting the student data via a privacy compliance module.
However, King teaches verifying a user's subscription status with a subscription verification module, King teaches student account register (100) and teacher/administrator account register (110) storing details of students (30) and teachers/administrators (60) who are registered to use the software applications (40) and (70), respectively (e.g. name, address, contact details, details relating to any relevant education institution associated with the student and/or teacher, and any additional data which may be relevant for the purpose of identifying each user). Where possible these details may be verified using identification verification services (see at least paragraph 0044);
processing and transforming the student data for artificial intelligence (AI) processing via a data processing module, King teaches an additional benefit of storing the various inputs by students (30) in response to questions and activities, and the results of analysis conducted by the artificial intelligence engine (170) and any additional processing techniques performed by server (20) with respect to the assessment of students and their learning difficulties and/or disorders, is that the server (20) may subsequently be used to conduct various additional analyses based on historical data, such as trend analyses and the like (see at least paragraphs 0037-0038, 0049-0050, 0063 and 0066-0069); and
anonymizing and redacting the student data via a privacy compliance module, King teaches student account register (100) and teacher/administrator account register (110) storing details of students (30) and teachers/administrators (60) who are registered to use the software applications (40) and (70), respectively (e.g. name, address, contact details, details relating to any relevant education institution associated with the student and/or teacher, and any additional data which may be relevant for the purpose of identifying each user). Where possible these details may be verified using identification verification services (see at least paragraph 0044). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention for Davison to modify to include the teaching of King in order to determine individual student progress and identify trends that will result in difficulty for a student to achieve an expected educational proficiency in the future.
Claim 13: Davison in view of King disclose the system according to claim 12, and King further teaches wherein verifying a user's subscription status includes prompting a user for authentication information and interfacing with a subscription management system, King teaches student account register (100) and teacher/administrator account register (110) storing details of students (30) and teachers/administrators (60) who are registered to use the software applications (40) and (70), respectively (e.g. name, address, contact details, details relating to any relevant education institution associated with the student and/or teacher, and any additional data which may be relevant for the purpose of identifying each user). Where possible these details may be verified using identification verification services (see at least paragraph 0044). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention for Davison to modify to include the teaching of King in order to determine individual student progress and identify trends that will result in difficulty for a student to achieve an expected educational proficiency in the future.
Claim 14: Davison in view of King disclose the system according to claim 12, and Davison further teaches wherein receiving student data includes:
prompting the user to input categorical information based on the type of student data, Davison teaches user selected academic categories, performance indicators and metrics are received by a server from at least two remote devices over a communication network and the received performance indicators are combined with each of the received metrics and based on the student information, into at least one complete sentence presentable in a student report measuring an academic performance of a student for one or more of the academic categories (see at least paragraph 0009).
King teaches prompting a user to select a type of student data, wherein the type of student data includes a plurality of standardized tests or observation reports, King teaches segment 700 of FIG. 1 illustrates the review of class and student results (320) by the teacher/administrator (60) based upon completion of the test or assessments by the students and the analysis of the answers/response provided, as detailed in FIG. 7. (see at least paragraphs 0033 and 0042). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention for Davison to modify to include the teaching of King in order to determine individual student progress and identify trends that will result in difficulty for a student to achieve an expected educational proficiency in the future.
Claim 15: Davison in view of King disclose the system according to claim 12, and Davison further teaches wherein receiving student data further comprises:
integrating the data input module with third-party platforms including online testing platforms or student information systems, Davison teaches the receiving step includes receiving data communications from at least two remote devices over the communication network. This allows multiple users to work on compiling the student report simultaneously. Furthermore, this may also allow multiple users to simultaneously add, delete, or modify the student report through respective interactive computer mediums (see at least paragraph 0007);
assigning a type of student data to each third-party platform, Davison teaches compiling the student report from multiple remote devices simultaneously over the communication network and the system may establish multiple data connection requests in a central server with the multiple remote devices (see at least paragraphs 0005 and 0008);
automatically importing files containing student data from the third-party platforms, Davison teaches the receiving step includes receiving data communications from at least two remote devices over the communication network. This allows multiple users to work on compiling the student report simultaneously. Furthermore, this may also allow multiple users to simultaneously add, delete, or modify the student report through respective interactive computer mediums (see at least paragraph 0007); and
extracting the student data from the third-party platforms, Davison teaches permitting the compiling of a student report from at least two remote devices simultaneously over the communication network. This step inherently allows the
central computer system to receiving data communications from at least two remote devices via a communication network. The two remote devices preferably connect via a web based software application that communicates with the central computer or server. This feature may also permit two users to simultaneously add, delete, or modify the student report through respective interactive computer mediums (see at least paragraphs 0007 and 0013).
Claim 17: Davison in view of King disclose the system according to claim 12, and King further teaches wherein processing and transforming the student data further comprises:
utilizing a plurality of data transformation methods to extract test scores or
observational data, King teaches an additional benefit of storing the various inputs
by students (30) in response to questions and activities, and the results of analysis conducted by the artificial intelligence engine (170) and any additional processing techniques performed by server (20) with respect to the assessment of students and their learning difficulties and/or disorders, is that the server (20) may subsequently be used to conduct various additional analyses based on historical data, such as trend analyses and the like (see at least paragraphs 0046 and 0069);
converting the test scores to categorical scores, King teaches an additional benefit of storing the various inputs by students (30) in response to questions and activities, and the results of analysis conducted by the artificial intelligence engine (170) and any additional processing techniques performed by server (20) with respect to the assessment of students and their learning difficulties and/or disorders, is that the server (20) may subsequently be used to conduct various additional analyses based on historical data, such as trend analyses and the like (see at least paragraphs 0046 and 0069);
converting the observational data into paragraph form, King teaches an additional benefit of storing the various inputs by students (30) in response to questions and activities, and the results of analysis conducted by the artificial intelligence engine (170) and any additional processing techniques performed by server (20) with respect to the assessment of students and their learning difficulties and/or disorders, is that the server (20) may subsequently be used to conduct various additional analyses based on historical data, such as trend analyses and the like (see at least paragraph 0069); and
generating an AI prompt string, King teaches an additional benefit of storing the various inputs by students (30) in response to questions and activities, and the results of analysis conducted by the artificial intelligence engine (170) and any additional processing techniques performed by server (20) with respect to the assessment of students and their learning difficulties and/or disorders, is that the server (20) may subsequently be used to conduct various additional analyses based on historical data, such as trend analyses and the like (see at least paragraph 0069). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention for Davison to modify to include the teaching of King in order to determine individual student progress and identify trends that will result in difficulty for a student to achieve an expected educational proficiency in the future.
Claim 18: Davison in view of King disclose the system according to claim 12, and King further teaches wherein the observation reports include a teacher response form, King teaches the teachers (60) may select an assessment based upon the subject and/or year level, and the test or assessment may be either scheduled for completion in
class time or the students (30) may be notified to complete the test or assessment for homework (see at least paragraph 0056). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention for Davison to modify to include the teaching of King in order to determine individual student progress and identify trends that will result in difficulty for a student to achieve an expected educational proficiency in the future.
Claim 19: Davison in view of King disclose the system according to claim 17, and King further teaches wherein generating the individualized student report includes querying an AI engine with the AI prompt string, King teaches an additional benefit of storing the various inputs by students (30) in response to questions and activities, and the results of analysis conducted by the artificial intelligence engine (170) and any additional processing techniques performed by server (20) with respect to the assessment of students and their learning difficulties and/or disorders, is that the server (20) may subsequently be used to conduct various additional analyses based on historical data, such as trend analyses and the like (see at least paragraphs 0037-0038, 0049-0050, 0063 and 0066-0069). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention for Davison to modify to include the teaching of King in order to determine individual student progress and identify trends that will result in difficulty for a student to achieve an expected educational proficiency in the future.
Claim 20: Davison in view of King disclose the system according to claim 12, and Davison further teaches wherein the user interface module is adapted to provide a user-friendly interface for students and teachers, Davison teaches permitting the compiling of a student report from at least two remote devices simultaneously over the communication network. This step inherently allows the central computer system to receiving data communications from at least two remote devices via a communication network. The two remote devices preferably connect via a web based software application that communicates with the central computer or server. This feature may also permit two users to simultaneously add, delete, or modify the student report through respective interactive computer mediums (see at least paragraphs 0005 and 0013).
15. Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Davison (U.S. Pub. No. 2014/0172516) in view of King (U.S. Pub. No. 2025/0061530), and further in view of Monk (U.S. Pub. No. 2025/0061221).
Claim 3: Davison in view of King disclose the system according to claim 2, but Davison in view of King does not explicitly teach wherein the subscription management system includes a payment processing platform. However, Monk teaches the parent account and/or an admin account may subscribe to a service and submit, using a payment module, payment for the subscription (see at least paragraphs 0032 and 0061). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention for Davison in view of king to modify to include the teaching of Monk in order to provide information for a database of students using the service.
16. Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Davison (U.S. Pub. No. 2014/0172516) in view of King (U.S. Pub. No. 2025/0061530), and further in view of Holt et al. (U.S. Pub. No. 2023/0135288) (hereinafter “Holt”) and Pedraza (U.S. Pub. 2024/0062666) and McCabe et al. (U.S. Patent No. 6,453,216) (hereinafter “McCabe”).
Claim 16: Davison in view of King disclose the system according to claim 14, but Davison in view of King does not explicitly teach wherein the type of standardized tests includes a Woodcock Johnson-IV (WCJ-IV), a California Standardized test, and a District Essential Mathematics Indicator assessment (DEMI). However, Holt teaches California Standard Testing (see at least paragraph 0095), Pedraza teaches
Woodcock-Johnson IV Tests (see at least paragraphs 0041 and 0141), and McCabe teaches San Diego Unified School District (see at least column 3 lines 40-48). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention for Davison in view of King to modify to include the teaching of Holt, Pedraza and McCabe in order to personalized education.
Conclusion
17. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
18. Cook et al. (U.S. Pub. No. 2002/0168621) discloses authenticating student-access requests and limiting file access to authorized users (see at least paragraph 0110).
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/MARILYN G MACASIANO/Primary Examiner, Art Unit 3622 03/26/2026