DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This office action is in response to claims filed on 1/29/2025 in relation to application 19/040,294.
The instant application claims benefit to provisional application #63/626,899 with a priority date of 1/30/2024.
The Pre-Grant publication # 2025/0246090 is issued on 7/31/2025.
Claims 1-20 are pending.
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 a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. The claimed invention is a computer system (1-8) and to a process (claim 9-20). Thus fall within one of the four statutory categories (Step 1: YES).
Claims 1 , 8 and 15 are directed to receiving, at a computer system, media, processing the media via at least one processor of the computer system, resulting in processed media, generating, via the at least one processor based on the processed media, at least one new exam question about the media; and combining, via the at least one processor, the processed media and the at least one new exam question, resulting in a course about the media. The actions of receiving, simple processing questions, combining, extracting, outputting all falls within the “Certain Method of Organizing Human Activity” groupings of abstract ideas subject to the 2019 Revised Patent Subject Matter Eligibility Guidance. Also reading, evaluating processed data, generating exam questions feature are “Mental Processes” by specifically instances of managing interactions among people. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, and/or a certain method of managing interactions between people but for the recitation of generic computer components, then it falls within the “Mental Processes” and “Certain Method of Organizing Human Activity” groupings of abstract ideas, respectively. Any analysis of skills and operation by trainees using processing algorithm is a use of existing mathematical relationships, Accordingly, the claims recite one or more groupings of abstract idea(s). (Step 2A; Prong 1: Yes).
The independent claims do not include additional elements that are sufficient to be significantly more than the judicial exception because the limitations of “a computer system with interface display”, “a processor’, “a memory’, "network remote storage", "databases of digital content with predetermined string of analyzed new exam question about the media content”. The independent claims do not include additional elements that are sufficient to be significantly more than the judicial exception because the limitations of are merely use of generic computer functions and computer parts to apply or use of judicial exception for a stipulated outcome. Hence not indicative of integration of a practical application (Step 2A: Prong 2 No).
The steps in the recited claims that are highlighted are a well-understood, routine, and conventional activities known in art. Fig. 3,4 of the instant specification indicates processed media generating exam question about media and combinations thereof using hardware/ software of a standard computational environment to generate a course about media. For example in case of Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93, the activities of storing and retrieving of information in a memory of consumer electronic for a field of use purposes are recognized to be computer functions well-understood, routine, and conventional, when they are claimed in a merely generic manner. Further, there found to be no additional elements here in the claim recitation that improves the functioning of a computer itself to overcome the abstract idea rejection (Step 2B: No).
Claims 2-7,9-14, 16-20 do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Additionally, taking the claimed elements individually yields no difference from taking them in combination because each element simply performs its respective function as discussed above. For example dependent claims are processing of the media using at least one of artificial intelligence (Al) text extraction and Al generated audio narration of the media. Also generating new exam questions
In other words, these claims merely apply an abstract idea to a programmable processor or computer and may use known algorithm and mathematical formulation but do not improve the performance of the process or computer itself or provide a technical solution to a problem in a technical field. They do not effect a transformation of a particular article to a different state or thing either and the underlying computing elements remain the same. Instead, the additional features merely amount to an instruction to apply the abstract idea using generic, functional, and conventional components well-known in the art. Mere instructions to apply an exception using the generic computer components cannot provide an inventive concept. Therefore, for these reasons, not patent-eligible under 35 USC 101.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) and 35 U.S.C. 102(a)(2) as being anticipated by US 20180366021 A1 to Zertuche.
Claim 1. Zertuche teaches a method comprising:
receiving, at a computer system, media (Fig.1 elements 106,136 course syllabi, external data media);
processing the media via at least one processor of the computer system, resulting in processed media (Fig.1 element 108 learning outcome data 108 generated based on an analysis and/or examination process of one or more course syllabi 106, course description(s), and/or other information describing a course e.g., a university class, training seminar, etc. as a resulting in processed media);
generating, via the at least one processor based on the processed media, at least one new exam question about the media ( Fig. 2B element 114 category data 114 may identify one or more categories that are assessed by or otherwise associated with questions in each of the assessment) ; and
combining, via the at least one processor, the processed media and the at least one new exam question, resulting in a course about the media (Fig.1 element 122 report may include analysis results in various forms to include course about the media such as about learning outcome textual descriptions of assessment(s), and so forth).
Claim 2. Zertuche teaches the method of claim 1, further comprising: storing the course in a database (Para 0088 report(s) may also be stored for future access).
Claim 3. Zertuche teaches the method of claim 2, wherein the database has additional courses stored therein (Para 0089 additional correlated courses present for a measure of effectiveness).
Claim 4. Zertuche teaches the method of claim 1, wherein: the media comprises text; and the processing of the media comprises at least one of artificial intelligence (Al) text extraction and Al generated audio narration of the media (Para 0088 textual descriptions of assessment as could be extracted using AI ).
Claim 5. Zertuche teaches the method of claim 1, wherein: the media comprises at least one of audio and video; and the processing of the media comprises at least one of: generating new closed captioning data from an audio track, translating the new closed captioning data, translating existing closed captioning data, and generating an Al translation voiceover which is combined with the media (Fig.11 an audio input device e.g., a microphone, a gestural input device, a haptic input device, an image or video capture device e.g., a camera, or other media devices. )
Claim 6. Zertuche teaches the method of claim 1, wherein the generating of the new exam questions comprises: accessing a pool of existing exam questions; and generating, via the at least one processor using at least one question from the pool of existing exam questions as a template, the at least one new exam question ( Para 0094 Assessment service 110 may provide ExamSoft™ to the analysis engine for assessment data to include pool of category data 114 and score data; The report can also include change information that indicates the previous value of the tracked data point e.g., a particular exam score compared to the current value of the tracked data point).
Claim 7. Zertuche teaches the method of claim 1, wherein the processing of the media further comprises:
transmitting at least a portion of the media from the computer system with a processing request to a remote computing system; and receiving, at the computer system from the remote computing system in response to the processing request, at least a portion of the processed media (Para 0138 remote computing system).
Claim 8. Zertuche teaches a system comprising: at least one processor; and a non-transitory computer-readable storage medium having instructions stored which, when executed by the at least one processor, cause the at least one processor to perform operations comprising: receiving media; processing the media, resulting in processed media; generating, based on the processed media, at least one new exam question about the media; and combining the processed media and the at least one new exam question, resulting in a course about the media (Fig.1 elements 106,136 course syllabi, external data media; Fig.1 element 108 learning outcome data 108 generated based on an analysis and/or examination process of one or more course syllabi 106, course description(s), and/or other information describing a course e.g., a university class, training seminar, etc. as a resulting in processed media; generating, via the at least one processor based on the processed media for report courses about the media; Fig. 2B element 114 category data 114 may identify one or more categories that are assessed by or otherwise associated with questions in each of the assessment).
Claim 9. Zertuche teaches the system of claim 8, the non-transitory computer-readable storage medium having additional instructions stored which, when executed by the at least one processor, cause the at least one processor to perform operations comprising: storing the course in a database (Para 0088 report(s) may also be stored for future access).
Claim 10. Zertuche teaches the system of claim 9, wherein the database has additional courses stored therein (Para 0089 additional correlated courses present for a measure of effectiveness).
Claim 11. Zertuche teaches the system of claim 8, wherein: the media comprises text; and the processing of the media comprises at least one of artificial intelligence (AI) text extraction and Al generated audio narration of the media (Para 0088 textual descriptions of assessment as could be extracted using AI ).
Claim 12. Zertuche teaches the system of claim 8, wherein: the media comprises at least one of audio and video; and the processing of the media comprises at least one of: generating new closed captioning data from an audio track, translating the new closed captioning data, translating existing closed captioning data, and generating an Al translation voiceover which is combined with the media (Para 0094 Assessment service 110 may provide ExamSoft™ to the analysis engine for assessment data to include pool of category data 114 and score data; The report can also include change information that indicates the previous value of the tracked data point e.g., a particular exam score compared to the current value of the tracked data point).
Claim 13. Zertuche teaches the system of claim 8, wherein the generating of the new exam questions comprises: accessing a pool of existing exam questions; and generating, using at least one question from the pool of existing exam questions as a template, the at least one new exam question ( Para 0094 Assessment service 110 may provide ExamSoft™ to the analysis engine for assessment data to include pool of category data 114 and score data; The report can also include change information that indicates the previous value of the tracked data point e.g., a particular exam score compared to the current value of the tracked data point).
Claim 14. Zertuche teaches the system of claim 8, wherein the processing of the media further comprises: transmitting at least a portion of the media with a processing request to a remote computing system; and receiving, from the remote computing system in response to the processing request, at least a portion of the processed media(Para 0138 remote computing system).
Claim 15. Zertuche teaches a non-transitory computer-readable storage medium having instructions stored which, when executed by at least one processor, cause the at least one processor to perform operations comprising:
receiving media; processing the media, resulting in processed media; generating, based on the processed media, at least one new exam question about the media; and combining the processed media and the at least one new exam question, resulting in a course about the media (Fig.1 elements 106,136 course syllabi, external data media; Fig.1 element 108 learning outcome data 108 generated based on an analysis and/or examination process of one or more course syllabi 106, course description(s), and/or other information describing a course e.g., a university class, training seminar, etc. as a resulting in processed media; generating, via the at least one processor based on the processed media for report courses about the media; Fig. 2B element 114 category data 114 may identify one or more categories that are assessed by or otherwise associated with questions in each of the assessment).
Claim 16. Zertuche teaches the non-transitory computer-readable storage medium of claim 15, having additional instructions stored which, when executed by the at least one processor, cause the at least one processor to perform operations comprising: storing the course in a database Fig.1 elements 106,136 course syllabi, external data media; Fig.1 element 108 learning outcome data 108 generated based on an analysis and/or examination process of one or more course syllabi 106, course description(s), and/or other information describing a course e.g., a university class, training seminar, etc. as a resulting in processed media; generating, via the at least one processor based on the processed media for report courses about the media; Fig. 2B element 114 category data 114 may identify one or more categories that are assessed by or otherwise associated with questions in each of the assessment).
Claim 17. Zertuche teaches the non-transitory computer-readable storage medium of claim 16, wherein the database has additional courses stored therein (Para 0088 report(s) may also be stored for future access; Para 0089 additional correlated courses present for a measure of effectiveness).
Claim 18. Zertuche teaches the non-transitory computer-readable storage medium of claim 15, wherein: the media comprises text; and the processing of the media comprises at least one of artificial intelligence (Al) text extraction and Al generated audio narration of the media (Para 0088 textual descriptions of assessment as could be extracted using AI ). .
Claim 19. Zertuche teaches the non-transitory computer-readable storage medium of claim 15, wherein: the media comprises at least one of audio and video; and the processing of the media comprises at least one of: generating new closed captioning data from an audio track, translating the new closed captioning data, translating existing closed captioning data, and generating an Al translation voiceover which is combined with the media (Para 0094 Assessment service 110 may provide ExamSoft™ to the analysis engine for assessment data to include pool of category data 114 and score data; The report can also include change information that indicates the previous value of the tracked data point e.g., a particular exam score compared to the current value of the tracked data point).
Claim 20. Zertuche teaches the non-transitory computer-readable storage medium of claim 15, wherein the generating of the new exam questions comprises: accessing a pool of existing exam questions; and generating, using at least one question from the pool of existing exam questions as a template, the at least one new exam question( Para 0094 Assessment service 110 may provide ExamSoft™ to the analysis engine for assessment data to include pool of category data 114 and score data; The report can also include change information that indicates the previous value of the tracked data point e.g., a particular exam score compared to the current value of the tracked data point). .
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SADARUZ ZAMAN whose telephone number is (571)270-3137. The examiner can normally be reached M-F 9am to 5pm CST.
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/S.Z/Examiner, Art Unit 3715 July 11, 2026
/XUAN M THAI/Supervisory Patent Examiner, Art Unit 3715
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