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 6/8/2016 in relation to application 15/177,240.
The instant application claims benefit to provisional application #62/172,477 with a priority date of 6/8/2015.
The Pre-Grant publication # 2017/0282014 is issued on 12/12/2024.
Claims 1-15 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 1-15 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.
Independent claim 1 recites an abstract idea of generating learning problems with reference to setting information on a reference learning problem. Determining changeable areas in the reference learning problem and determining ranges of data change in the changeable areas within the range of data change in the at least one changeable area and generating a new learning problem from the reference learning problem on the basis of the changed data. These limitations may be characterized as an abstract idea by mechanism of collecting data (e.g., inputs from reference learning problems), analyzing those inputs (determining ranges of data change in the changeable areas) and providing an output based on that analysis (e.g., generating a new learning problem from the reference learning problem on the basis of the changed data). Thereby abstract as a mental process under, e.g., Electric Power Group; and/or abstract as a method of organizing human activity in terms of a method of teaching and learning of a human being how to perform better learning problems. The analysis of skills and operation by trainees using verified algorithm is use of existing mathematical relationships, formulas. Hence are mathematical concepts. Accordingly, the claims recite one or more groupings of abstract idea(s). (Step 2A; Prong One: Yes).
The above Judicial Exceptions as indicated are not integrated into a practical application. In particular, the claim recites the additional elements of using computer, internet-connected platform, and database to perform the claimed method steps for “new problem generations” based on reference problem and “operations skills”; determining ranges of data change in the changeable areas on an internet-connected platform, computer, and data base all recited at a high-level of generality (e.g., a generic computer system for capturing, storing and analyzing data over a network such that it amounts to no more than mere instructions to apply the exception using a generic computer component under MPEP §2106.05(f)&(h). These generic, additional elements do not integrate the abstract idea into a practical application because it not impose any meaningful limits on practicing the abstract idea under MPEP §2106.05(b)(c)&(e). They appear to fail to provide an improvement to the technical field of providing training assessments under MPEP §2106.05(a) and merely recite the use of a computer as a tool to automate existing mental and human operated practices. Any improved technical features implemented in the provision of the system is devoid from the claim language. The additional limitations in the present claims are seen more as a drafting effort toward eligibility than any meaningful employed elements that confine the claims. Accordingly, the claims are directed to an abstract idea under (Step 2A: Prong Two, No).
As analyzed, the claims as drafted do not make improvements to another technology or technical field, improve the function of a computer itself, utilize a particular machine, transform a particular article to a different state, have specific limitations or unconventional steps that limit the scope of the claim to a particular useful application beyond generally linking the use of the judicial exception to a computerized environment, or recite an inventive concept of any form therein. Accordingly, the claims do not include additional elements sufficient to amount to significantly more than the judicial exception(s) to which they are directed under Step 2B: No.
All dependent claims have been analyzed and do not cure the deficiencies of the independent claims. For further exemplification of the dependent claims simply further exemplify aspects of the abstract learning problem assessment and documentation method and mental processes performed therein as well as conventional internet messaging and communication deemed conventional above. Learning problems per the specification relies upon the well-known nature of providing a supplemental problem based on context information with pre- or post-solution activities. . These further limitations do not direct the claims to a practical application or amount to significantly more than the monopolization of the aforementioned judicial exception and are thus rejected.
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 1-15 are rejected under 35 U.S.C. 102(a)(1) and 35 U.S.C. 102(a)(2) as being anticipated by US 20180090026 AHN et al.(Ahn).
Claim 1. Ahn teaches a method for generating learning problems (Para 0004 providing sequentially learning information), the method comprising the steps of:
with reference to setting information on a reference learning problem (Para 0009 a target reference learning unit), determining changeable areas in the reference learning problem (Fig.3 addition of fraction to changeable areas), and
determining ranges of data change in the changeable areas (Para 0056 a learning range based on nodes and links); changing data included in at least one of the determined changeable areas ( Para 0057 changeable areas by determining changeable weight based on areas frequency, pattern and learners etc. ) , within the range of data change in the at least one changeable area (Para 0025 range of change could be based on a subject, a grade, and a curriculum unit, for example; Again earning unit may be classified according to stages such as concept learning, drilling and in-depth learning, and the learning information corresponding to each stage may include textbooks, questions by difficulties, learning materials, and the like); and generating a new learning problem from the reference learning problem on the basis of the changed data ( Fig.5 learner may perform supplementary learning for learning units with low academic achievements over several stages, thereby eventually increasing generating a new learning problem by academic achievements for all learning units).
Claim 2. Ahn teaches the method of Claim 1, wherein the setting information is preset by an administrator or extracted from the reference learning problem (Fig.5 elements S510, S520 setting information provided in a supplementary learning, extracted from diagnostic learning unit).
Claim 3. Ahn teaches the method of Claim 1, wherein the changeable area includes at least one of a text area, a formula area, a figure area, a graph area, and an image area (Fig.4 changeable areas and weights; Para 0030 determining one supplementary learning unit or area like graph area to be provided to the learner, with reference to a first weight, second weight based on a correlation along a determined direction).
Claim 4. Ahn teaches the method of Claim 1, wherein the range of data change in the at least one changeable area is determined on the basis of context information on the reference learning problem or the new learning problem (Para 0044-0045 learning characteristics of another learner and those of the learner are similar at or above a predefined level according to knowledge map management unit).
Claim 5. Ahn teaches the method of Claim 4, wherein the context information includes at least one of a condition of the reference learning problem, a concept associated with the reference learning problem, a difficulty level of the reference learning problem, a difficulty level of the new learning problem, an academic achievement level of a learner to be provided with the new learning problem, and a concept understanding level of the learner to be provided with the new learning problem (Fig.8 concept associated with the reference learning problem for a difficulty level of the reference learning problem).
Claim 6. Ahn teaches the method of Claim 1, wherein the range of data change in a first changeable area and the range of data change in a second changeable area are interlinked with each other (Fig.5 elements 510,520 changeable areas; Para 0056 learning range; Para 0009 concept associated with the reference learning problem, a difficulty level of the reference learning problem).
Claim 7. Ahn teaches the method of Claim 1, wherein in the creating step, the new learning problem is created by adaptively changing visual elements included in the reference learning problem on the basis of the changed data (Para 0043 changes in knowledge map i.e. visually linking and adapting changing connecting nodes ; Para 0043 knowledge map management unit may change the configuration of the knowledge map i.e. the connection relationship between the nodes by the links may with visual element and based on the correlations dynamically assigned to the links in the knowledge map).
Claim 8. (Original) A non-transitory computer-readable recording medium having stored there on a computer program for executing the method of Claim 1 (Para 0075 computer-readable medium).
Claim 9. Ah teaches a system for generating learning problems (Para 0004 providing sequentially learning information), the system comprising: a range-of-change determination unit (Para 0056 a learning range based on links and weights) configured to, with reference to setting information on a reference learning problem, determine changeable areas in the reference learning problem, and determine ranges of data change in the changeable areas; a data change unit configured to change data included in at least one of the determined changeable areas, within the range of data change in the at least one changeable area; and a new learning problem creation unit configured to create a new learning problem from the reference learning problem on the basis of the changed data (generating a new learning problem from the reference learning problem on the basis of the changed data as in Fig.5 learner may perform supplementary learning for learning units with low academic achievements over several stages, thereby eventually increasing generating a new learning problem by academic achievements for all learning units).
Claim 10. Ahn teaches the system of Claim 9, wherein the setting information is preset by an administrator or extracted from the reference learning problem (Fig.5 elements S510, S520 setting information provided in a supplementary learning, extracted from diagnostic learning unit).
Claim 11. Ahn teaches the system of Claim 9, wherein the changeable area includes at least one of a text area, a formula area, a figure area, a graph area, and an image area (Fig.4 changeable areas and weights; Para 0030 determining one supplementary learning unit or area like graph area to be provided to the learner, with reference to a first weight, second weight based on a correlation along a determined direction).
Claim 12. Ahn teaches the system of Claim 9, wherein the range of data change in the at least one changeable area is determined on the basis of context information on the reference learning problem or the new learning problem (Fig.5 elements 510, 520).
Claim 13. Ahn teaches the system of Claim 12, wherein the context information includes at least one of a condition of the reference learning problem, a concept associated with the reference learning problem, a difficulty level of the reference learning problem, a difficulty level of the new learning problem, an academic achievement level of a learner to be provided with the new learning problem, and a concept understanding level of the learner to be provided with the new learning problem (Fig.5; Para 0044-0045 learning characteristics of the another learner and those of the learner are similar at or above a predefined level according to knowledge map management unit ).
Claim 14. Ahn teaches the system of Claim 9, wherein the range of data change in a first changeable area and the range of data change in a second changeable area are interlinked with each other (Fig.5 elements 510,520 changeable areas; Para 0056 learning range; Para 0009 concept associated with the reference learning problem, a difficulty level of the reference learning problem).
Claim 15. (Currently Amended) The system of Claim 9, wherein in the creating step, the new learning problem creation unit is configured to generate the new learning problem by adaptively changing visual elements included in the reference learning problem on the basis of the changed data (Para 0043 changes in knowledge map i.e. visually linking and adapting changing connecting nodes ; Para 0043 knowledge map management unit may change the configuration of the knowledge map i.e. the connection relationship between the nodes by the links may with visual element and based on the correlations dynamically assigned to the links in the knowledge map).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20200151458 A1 SON; Jeong Woo et al.
APPARATUS AND METHOD FOR VIDEO DATA AUGMENTATION
US 20210319542 A1 Cho; Nam Ik et al.
IMAGE PROCESSING APPARATUS AND METHOD THEREOF
US 11600196 B2 Gihm; Se Hoon et al.
Method and system for supporting learning, and non-transitory computer-readable recording medium.
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/S.Z/Examiner, Art Unit 3715 February 27, 2026
/XUAN M THAI/Supervisory Patent Examiner, Art Unit 3715