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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 on 9/16/2025 has been entered. Claims 1-3,5-12 and 14-20 are pending; claims 4 and 13 have been cancelled.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1 – 3, 5 – 12 and 14 – 20 are rejected under 35 U.S.C. 103 as being unpatentable over Gal et al. (US 2014/0335497 A1) in view of Oros et al. (US 2017/0293663 A1) and Taylor (US 8,500,450 B1).
Re claims 1, 16, 20:
1. Gal teaches [A] teaching and learning automation system (Gal, Abstract, “computerized method”; [0098], “portions of the content of educational learning objects may be automatically modified, removed or added”) comprising:
an autonomous teaching and learning system having an automation opportunity module is configured to automate identification of teaching and learning processes, a task definitions module, a version control module for maintaining different versions of different said teaching and learning processes, a repository including a relational database, an analyze module, and a design module (Gal, figs. 1 - 5);
wherein said repository is maintained remotely and centrally (Gal, fig. 3);
wherein said analyze module analyzes the state of said teaching and learning processes, identifies areas for improvement, and generates recommendations for automation (Gal, [0261]; [0282], “the system may recommend assignment or division or allocation of the students into groups (and dynamic real-time re-allocation or re-grouping, based on dynamically-monitored accomplishments of individual students)”; [0103], “system 100 modifies or re-constructs content presented to a student ( or a group of students) based on identified weaknesses of that student or group”);
wherein said automation opportunity module using said task definitions module for automating identification of said teaching and learning processes (Gal, fig. 2, “lessons”, “learning activities”, “learning objects”; [0045] – [0046]);
wherein said design module designs new automations based on the recommendations from said analyze module (Gal, Abstract, “adaptive teaching and learning”; fig. 4, “Dynamic Adaptation”; [0011]; [0109], “the new version of the learning object”);
wherein said design module is also coupled with a continuous assessment module (Gal, fig. 2, 403 – “Integrated evaluation and Assessment”; [0028], “an assessment module to assess”; [0047], “a method of evaluating performance of a member of an education system”; [0251], “the ongoing assessment results further affect and modify the teaching and learning processes”);
wherein designs developed by said design module are continuously assessed by said continuous assessment module (Gal, fig. 2, 403 – “Integrated evaluation and Assessment”; [0028], “an assessment module to assess”; [0047], “a method of evaluating performance of a member of an education system”; [0251], “the ongoing assessment results further affect and modify the teaching and learning processes”);
wherein based on the continuous assessment, a development module develops said new automations using a plurality of reusable components and technology stored in a corresponding technology component (Gal, [0011], “a modified version of at least a portion of the first digital learning object”; [0109], “both the original un-modified version and the new modified version of the learning object are stored”; [0112], “an edited scenario or layout, or a teacher generated scenario or layout, are stored in the teacher's personal "cabinet" or "private folder" (e.g., as described herein) and can by recalled for re-use or for modification”; [0283], “e) Content reuse (e.g., maintain one instance of content and re-use it with modifications)”); and
wherein said reusable components are selected from the group consisting of a lesson, a chapter, and a subject (Gal, [0011]; [0109]; [0112]; [0283]; [0041], “lesson plan”; [0112], “educational content repository (e.g., sorted or filtered by subject, difficulty level, time length, or other properties)"; [0235], “present sub-units of the lesson”); and
wherein the autonomous teaching and learning system further comprises an orchestration build console coupled with said analyze module (Gal, [0261]; [0282], “the system may recommend assignment or division or allocation of the students”; [0103], “identified weaknesses of that student”), said design module (Gal, Abstract, “adaptive teaching and learning”; fig. 4, “Dynamic Adaptation”; [0011]; [0109], “the new version of the learning object”; [0112], “an edited scenario or layout”), said development module (Gal, [0011], “a modified version of at least a portion of the first digital learning object”; [0109], “both the original un-modified version and the new modified version of the learning object are stored”; [0112], “an edited scenario or layout; [0283]”), and an integrate module for administering said teaching and learning processes (Gal, [0308], “interactive elements Educational Interactions and Applets, are then combined into lessons and courses … Multiple "atomic" digital LOs may be combined or assembled, in advance and/or dynamically in real time, into a "molecular" digital LO”).
16. Gal teaches [A] teaching and learning automation system (Gal, Abstract, “computerized method”; [0098], “portions of the content of educational learning objects may be automatically modified, removed or added”) comprising:
an autonomous teaching and learning system having an automation opportunity module is configured to automate identification of teaching and learning processes, a task definitions module, a version control module for maintaining different versions of different said teaching and learning processes, a repository including a relational database, an analyze module, and a design module (Gal, figs. 1 - 5);
wherein said repository is maintained remotely and centrally (Gal, fig. 3);
wherein said analyze module analyzes the state of said teaching and learning processes, identifies areas for improvement, and generates recommendations for automation (Gal, [0261]; [0282], “the system may recommend assignment or division or allocation of the students into groups (and dynamic real-time re-allocation or re-grouping, based on dynamically-monitored accomplishments of individual students)”; [0103], “system 100 modifies or re-constructs content presented to a student ( or a group of students) based on identified weaknesses of that student or group”);
wherein said automation opportunity module using said task definitions module for automating identification of said teaching and learning processes (Gal, fig. 2, “lessons”, “learning activities”, “learning objects”; [0045] – [0046]);
wherein said design module designs new automations based on the recommendations from said analyze module (Gal, Abstract, “adaptive teaching and learning”; fig. 4, “Dynamic Adaptation”; [0011]; [0109], “the new version of the learning object”);
wherein said design module is also coupled with a continuous assessment module (Gal, fig. 2, 403 – “Integrated evaluation and Assessment”; [0028], “an assessment module to assess”; [0047], “a method of evaluating performance of a member of an education system”; [0251], “the ongoing assessment results further affect and modify the teaching and learning processes”);
wherein designs developed by said design module are continuously assessed by said continuous assessment module (Gal, fig. 2, 403 – “Integrated evaluation and Assessment”; [0028], “an assessment module to assess”; [0047], “a method of evaluating performance of a member of an education system”; [0251], “the ongoing assessment results further affect and modify the teaching and learning processes”);
wherein based on the continuous assessment, a development module develops said new automations using a plurality of reusable components and technology stored in a corresponding technology component (Gal, [0011], “a modified version of at least a portion of the first digital learning object”; [0109], “both the original un-modified version and the new modified version of the learning object are stored”; [0112], “an edited scenario or layout, or a teacher generated scenario or layout, are stored in the teacher's personal "cabinet" or "private folder" (e.g., as described herein) and can by recalled for re-use or for modification”; [0283], “e) Content reuse (e.g., maintain one instance of content and re-use it with modifications)”);
wherein said reusable components are selected from the group consisting of a lesson, a chapter, and a subject (Gal, [0011]; [0109]; [0112]; [0283]; [0041], “lesson plan”; [0112], “educational content repository (e.g., sorted or filtered by subject, difficulty level, time length, or other properties)"; [0235], “present sub-units of the lesson”);
an operation administrator module configured to monitor an overall operation and administration of said autonomous teaching and learning system (Gal, [0009], “the real-time class management module is to automatically allocate”; [0098], “portions of the content of educational learning objects may be automatically modified, removed or added, based on characteristics of the student utilizing the learning object, thereby providing to each student a learning object accommodating the student's characteristic and record of progress”; [0112], “the script may indicate to the teaching/learning system to automatically perform one or more of these operations”; [0154], “the adaptive offering may be provided directly to students automatically”);
wherein said operation administrator module automatically operates a course delivery team and automatically delivers and activates a course or learning process (Gal, [0163], “selective activation and/or projection of a learning object”; [0184], “the teaching/learning system or a learning object may be programmed to activate”; [0263], “sequence of the learning objects to be presented or activated”);
wherein said database stores historical data, statistical data, and metadata of learners and courses received from an autonomous reporting engine (Gal, [0311], “the progress of each student in completing tasks using his/her student station; and further allows the teacher to view cumulative data, historic data, data related to performance of a group of students, or the like”; [0078], “allocates and assigns various digital learning objects to students based on their individual skills, needs and past performance”; [0167], “digital content matching one or more criteria (e.g., subject matter, topic, type of activity, or the like), optionally by searching through meta-data or tags or keywords associated with educational content items”; [0256], “a set of pre-defined rubrics or requirements of the curriculum or the lesson plan”); and
wherein the autonomous teaching and learning system further comprises an orchestration build console coupled with said analyze module (Gal, [0261]; [0282], “the system may recommend assignment or division or allocation of the students”; [0103], “identified weaknesses of that student”), said design module (Gal, Abstract, “adaptive teaching and learning”; fig. 4, “Dynamic Adaptation”; [0011]; [0109], “the new version of the learning object”; [0112], “an edited scenario or layout”), said development module (Gal, [0011], “a modified version of at least a portion of the first digital learning object”; [0109], “both the original un-modified version and the new modified version of the learning object are stored”; [0112], “an edited scenario or layout; [0283]”), and an integrate module for administering said teaching and learning processes (Gal, [0308], “interactive elements Educational Interactions and Applets, are then combined into lessons and courses … Multiple "atomic" digital LOs may be combined or assembled, in advance and/or dynamically in real time, into a "molecular" digital LO”); and
wherein the autonomous teaching and learning system further comprises a deployment console accessible by the course delivery team to monitor deployment of the delivered course or learning process (Gal, Abstract, “monitor progress of interacting with digital educational learning objects … allowing a content publisher to receive aggregated feedback based on monitored progress”; [0098], “taking into account the specific needs or skills of the student, his prior performance and answers, his specific strengths and weaknesses, his progress and decisions, or the like”; [0150], “monitoring, logging and dynamically reporting the performance of individual students through their learning”; monitoring and logging and reporting of the progress and performance of students are activities monitored by a deployment of the delivered course/learning process).
20. A teaching and learning automation system (Gal, Abstract, “computerized method”; [0098], “portions of the content of educational learning objects may be automatically modified, removed or added”) comprising:
an autonomous teaching and learning system having an automation opportunity module is configured to automate identification of teaching and learning processes, a task definitions module, a version control module for maintaining different versions of different said teaching and learning processes, a repository including a relational database, an analyze module, a design module, and a deployment executor for providing a plurality of orchestrated tasks (Gal, figs. 1 - 5);
wherein said repository is maintained remotely and centrally (Gal, fig. 3);
wherein said analyze module analyzes the state of said teaching and learning processes, identifies areas for improvement, and generates recommendations for automation (Gal, [0261]; [0282], “the system may recommend assignment or division or allocation of the students into groups (and dynamic real-time re-allocation or re-grouping, based on dynamically-monitored accomplishments of individual students)”; [0103], “system 100 modifies or re-constructs content presented to a student ( or a group of students) based on identified weaknesses of that student or group”);
wherein said automation opportunity module using said task definitions module for automating identification of said teaching and learning processes (Gal, fig. 2, “lessons”, “learning activities”, “learning objects”; [0045] – [0046]);
wherein said design module designs new automations based on the recommendations from said analyze module (Gal, Abstract, “adaptive teaching and learning”; fig. 4, “Dynamic Adaptation”; [0011]; [0109], “the new version of the learning object”);
wherein said design module is also coupled with a continuous assessment module (Gal, fig. 2, 403 – “Integrated evaluation and Assessment”; [0028], “an assessment module to assess”; [0047], “a method of evaluating performance of a member of an education system”; [0251], “the ongoing assessment results further affect and modify the teaching and learning processes”);
wherein designs developed by said design module are continuously assessed by said continuous assessment module (Gal, fig. 2, 403 – “Integrated evaluation and Assessment”; [0028], “an assessment module to assess”; [0047], “a method of evaluating performance of a member of an education system”; [0251], “the ongoing assessment results further affect and modify the teaching and learning processes”);
wherein based on the continuous assessment, a development module develops said new automations using a plurality of reusable components and technology stored in a corresponding technology component (Gal, [0011], “a modified version of at least a portion of the first digital learning object”; [0109], “both the original un-modified version and the new modified version of the learning object are stored”; [0112], “an edited scenario or layout, or a teacher generated scenario or layout, are stored in the teacher's personal "cabinet" or "private folder" (e.g., as described herein) and can by recalled for re-use or for modification”; [0283], “e) Content reuse (e.g., maintain one instance of content and re-use it with modifications)”);
wherein said reusable components are selected from the group consisting of a lesson, a chapter, and a subject (Gal, [0011]; [0109]; [0112]; [0283]; [0041], “lesson plan”; [0112], “educational content repository (e.g., sorted or filtered by subject, difficulty level, time length, or other properties)"; [0235], “present sub-units of the lesson”);
an integrate module configured to integrate said new automations into the existing said autonomous teaching and learning system for improving and personalizing said teaching and learning processes for a plurality of learners (Gal, [0308], “interactive elements Educational Interactions and Applets, are then combined into lessons and courses … Multiple "atomic" digital LOs may be combined or assembled, in advance and/or dynamically in real time, into a "molecular" digital LO”; [0109], “both the original un-modified version and the new modified version of the learning object are stored”; [0258]; [0327]);
wherein said database stores historical data, statistical data, and metadata of learners and courses received from an autonomous reporting engine (Gal, [0311], “the progress of each student in completing tasks using his/her student station; and further allows the teacher to view cumulative data, historic data, data related to performance of a group of students, or the like”; [0078], “allocates and assigns various digital learning objects to students based on their individual skills, needs and past performance”; [0167], “digital content matching one or more criteria (e.g., subject matter, topic, type of activity, or the like), optionally by searching through meta-data or tags or keywords associated with educational content items”; [0256], “a set of pre-defined rubrics or requirements of the curriculum or the lesson plan”) and
wherein the autonomous teaching and learning system further comprises an orchestration build console coupled with said analyze module (Gal, [0261]; [0282], “the system may recommend assignment or division or allocation of the students”; [0103], “identified weaknesses of that student”), said design module (Gal, Abstract, “adaptive teaching and learning”; fig. 4, “Dynamic Adaptation”; [0011]; [0109], “the new version of the learning object”; [0112], “an edited scenario or layout”), said development module (Gal, [0011], “a modified version of at least a portion of the first digital learning object”; [0109], “both the original un-modified version and the new modified version of the learning object are stored”; [0112], “an edited scenario or layout; [0283]”), and an integrate module for administering said teaching and learning processes (Gal, [0308], “interactive elements Educational Interactions and Applets, are then combined into lessons and courses … Multiple "atomic" digital LOs may be combined or assembled, in advance and/or dynamically in real time, into a "molecular" digital LO”); and
wherein the autonomous teaching and learning system further comprises a deployment console accessible by the course delivery team to monitor deployment of the delivered course or learning process, and a monitoring dashboard coupled to the autonomous reporting engine (Gal, Abstract, “monitor progress of interacting with digital educational learning objects … allowing a content publisher to receive aggregated feedback based on monitored progress”; [0098], “taking into account the specific needs or skills of the student, his prior performance and answers, his specific strengths and weaknesses, his progress and decisions, or the like”; [0150], “monitoring, logging and dynamically reporting the performance of individual students through their learning”; monitoring and logging and reporting of the progress and performance of students are activities monitored by a deployment of the delivered course/learning process).
Gal does not explicitly disclose a wherein the autonomous teaching and learning system further comprises a course delivery console for accessing a delivered course or learning process by a virtual learner.
Oros et al. (US 2017/0293663 A1) teaches a system for automatically presenting personalized
aggregated content (Oros, Abstract). Oros further teaches wherein the autonomous teaching and learning system further comprises a course delivery console for accessing a delivered course or learning process by a virtual learner (Oros, [0006], “The system for automatically presenting personalized aggregated content where the spaced delivery algorithm determines a schedule for presenting according to factors including: one or more of: the progress report; an ability of the user of the user device; a first time interval since a last aggregated content interaction; a level of difficulty of the aggregated content; a second time interval until a challenge; and a number of incomplete clauses in the one or more incomplete clauses. The system for automatically presenting personalized aggregated content further including transmitting, by the server and to the user device, a prompt to request aggregated content”; [0008] – [0010]). Therefore, in view of Oros, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the system described in Gal, by providing the automated delivery as taught by Oros, since Oros states a spaced delivery algorithm determines a schedule for presenting according to factors including: one or more of: the progress report; an ability of the user of the user device; a first time interval since a last aggregated content interaction; a level of difficulty of the aggregated content; a second time interval until a challenge; and a number of incomplete clauses in the one or more incomplete clauses (Oros, [0006]).
Gal teaches a pre validation validation (Gal, fig. 6, 615, 610). Gal does not explicitly disclose wherein the autonomous teaching and learning system is further configured to perform a pre-validation execution, an execution validation, and a post-execution validation for a plurality of orchestrated tasks; and
wherein the autonomous teaching and learning system determines if a learner is ready for any of the plurality of orchestrated tasks based on the pre-validation execution, and if the learner is determined to be ready, the respective orchestrated task is executed, and after execution the post-execution validation determines if the learner has adequately performed the respective orchestrated task, and if not, the autonomous teaching and learning system requires the learner to re-execute the respective orchestrated task and provides additional assistance to properly execute the respective orchestrated task.
Taylor teaches a method and software for presenting reading fluency training to a user via a computer (Taylor, Abstract). Taylor teaches
wherein the autonomous teaching and learning system is further configured to perform a pre-validation execution, an execution validation, and a post-execution validation for a plurality of orchestrated tasks (Taylor, fig. 1, 105 – “Placement Assessment” – pre-validation execution; 115 - “Current Level Reading Lesson(s)”; 120 - ‘Performance Assessment” – Post execution validation); and
wherein the autonomous teaching and learning system determines if a learner is ready for any of the plurality of orchestrated tasks based on the pre-validation execution (Taylor, fig. 1, 105 – “Placement Assessment” – pre-validation execution; col. 4, lines 8 – 28, “reading placement assessment can use a set of reading selections to automatedly assign the user to an appropriate content level with respect to vocabulary, content readability, comprehension, and reading rate”; Placement assessment determines if a learner is ready for a content level ), and if the learner is determined to be ready, the respective orchestrated task is executed (Taylor, fig. 1, 115 - “Current Level Reading Lesson(s)”; col. 4, lines 29 – 47, “At step 115, one or more current-level lessons are presented to the user. Each reading lesson presented at step 115, as well as each reading lesson presented at steps 105, 110”; one or more current-level lessons are orchestrated tasks), and after execution the post-execution validation determines if the learner has adequately performed the respective orchestrated task (Taylor, fig. 1, 125, “Yes”; col. 5, lines 50 – 67, “At step 125, it is determined whether or not the user's performance meets the established criteria for avoiding intervention … “), and if not, the autonomous teaching and learning system requires the learner to re-execute the respective orchestrated task and provides additional assistance to properly execute the respective orchestrated task (Taylor, fig. 1, 125, “NO”, col. 5, lines 50 – 67, “if the users performance at the current assessment does not meet the established criteria”; fig. 1, 130 - “Perform Intervention”; col. 6, lines 16 – 33, “Intervention reading lessons can include lessons repeated from the reading lessons presented during one or more prior sessions from step 110”).
Therefore, in view of Taylor, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the method/system described in Gal, by providing individualize learning as taught by Taylor, in order to provide approaches in the manner in which program content, rates of presentation and formats of training are automatically and continually adjusted according to student performance and needs to ensure adequate development. These variations in training modalities are employed to individualize student learning and to ensure maximum proficiency development (Taylor, col. 3, lines 35 – 53).
Re claim 2:
2. The teaching and learning automation system of claim 1, wherein said development module develops said new automations using a plurality of new components (Gal, [0112], “a script manager 283 may be used to create, modify and/or store scripts which define the components of the learning activity”; [0116], “sons 250 are generated and managed by a teaching/learning management system 291, which may create and/or store lessons 250”; [0129], “Content development tools 323 are used, locally or remotely, to generate original or new education content”; [0252]).
Re claims 3, 5:
3. The teaching and learning automation system of claim 2 further comprising an integrate module configured to integrate said new automations into the existing said autonomous teaching and learning system for improving and personalizing the learning processes for a plurality of learners (Gal, [0308], “interactive elements Educational Interactions and Applets, are then combined into lessons and courses … Multiple "atomic" digital LOs may be combined or assembled, in advance and/or dynamically in real time, into a "molecular" digital LO”; [0109], “both the original un-modified version and the new modified version of the learning object are stored”; [0258]; [0327]).
5. The teaching and learning automation system of claim 3, wherein said database stores historical data, statistical data, and metadata of learners and courses received from an autonomous reporting engine (Gal, [0311], “the progress of each student in completing tasks using his/her student station; and further allows the teacher to view cumulative data, historic data, data related to performance of a group of students, or the like”; [0078], “allocates and assigns various digital learning objects to students based on their individual skills, needs and past performance”; [0167], “digital content matching one or more criteria (e.g., subject matter, topic, type of activity, or the like), optionally by searching through meta-data or tags or keywords associated with educational content items”; [0256], “a set of pre-defined rubrics or requirements of the curriculum or the lesson plan”).
Re claim 6:
6. The teaching and learning automation system of claim 5, wherein said database stores secure access information of the users for accessing said autonomous teaching and learning system (Gal, fig. 8, 831, “security”; [0202], “security module”; [0212], “a log-in interface allowing the user to enter a user-name and a password”).
Re claim 7:
7. The teaching and learning automation system of claim 6, wherein said autonomous reporting engine generates reports on said autonomous teaching and learning system using the data from said historical data, said statistical data, and said metadata of the learners and courses (Gal, fig. 5, “Assessment and Reporting”; [0134], “System 300 generates reports”; [0311], “the progress of each student in completing tasks using his/her student station; and further allows the teacher to view cumulative data, historic data, data related to performance of a group of students, or the like”; [0078], “allocates and assigns various digital learning objects to students based on their individual skills, needs and past performance”).
Re claim 8:
8. The teaching and learning autonomous system of claim 7, wherein said autonomous teaching and learning system having synchronous and asynchronous modes (Gal, [0306], “the student is currently working individually and/or a-synchronously on another task via his student station … "Follow the Teacher" mode of synchronous teaching/learning”).
Re claims 9 - 10:
9. The teaching and learning autonomous system of claim 8, wherein said autonomous reporting engine configured to provide a virtual campus in a form of a learner community social network and includes a plurality of virtual learners. 10. The teaching and learning autonomous system of claim 9, wherein said plurality of virtual learners interact and collaborate with each other (Gal, [0210], “Collaborative services 840 may be able to provide one or more collaboration tools, for example, a forum service 841, an electronic mail service 842, a chat service”; [0239]; fig. 8, 840).
Re claims 11 – 12:
11. The teaching and learning autonomous system of claim 10 further comprising an operation administrator module configured to monitor an overall operation and administration of said autonomous teaching and learning system (Gal, [0009], “the real-time class management module is to automatically allocate”; [0098], “portions of the content of educational learning objects may be automatically modified, removed or added, based on characteristics of the student utilizing the learning object, thereby providing to each student a learning object accommodating the student's characteristic and record of progress”; [0112], “the script may indicate to the teaching/learning system to automatically perform one or more of these operations”; [0154], “the adaptive offering may be provided directly to students automatically”).
12. The teaching and learning autonomous system of claim 11, wherein said operation administrator module automatically operates a course delivery and automatically delivers and activates a course and learning processes (Gal, [0163], “selective activation and/or projection of a learning object”; [0184], “the teaching/learning system or a learning object may be programmed to activate”; [0263], “sequence of the learning objects to be presented or activated”).
Re claims 14, 15:
14. The teaching and learning autonomous system of claim 12, wherein said operation administrator module including said course delivery (Gal, [0163], “The real time class management module 522 further allows activation or unlocking of a learning object or a learning activity, thereby sending it to one or more students or making it available to them”), a course monitoring (Gal, [0133], “System 300 monitors, logs and reports the performance of student based on their operation of student stations 301-303”), and a course reporting (Gal, [0009], “the real-time class management module is to automatically allocate”; [0098], “portions of the content of educational learning objects may be automatically modified, removed or added, based on characteristics of the student utilizing the learning object, thereby providing to each student a learning object accommodating the student's characteristic and record of progress”; [0112], “the script may indicate to the teaching/learning system to automatically perform one or more of these operations”; [0154], “the adaptive offering may be provided directly to students automatically”).
15. The teaching and learning autonomous system of claim 12, wherein said course monitoring monitors said teaching and learning processes and provides feedback to said autonomous reporting engine (Gal, Abstract, “allowing a content publisher to receive aggregated feedback based on monitored progress”; [0124], “to perform real-time in-class management of the learning activities performed by students or groups of students, to selectively allocate or re-allocate learning activities or learning objects to students or groups of students, to receive automated feedback or manual feedback from student stations 301-303 (e.g., upon completion of a learning activity or a learning object”).
Re claims 17 – 19:
17. The teaching and learning autonomous system of claim 16, wherein said operation administrator module including a course delivery (Gal, [0163], “The real time class management module 522 further allows activation or unlocking of a learning object or a learning activity, thereby sending it to one or more students or making it available to them”), a course monitoring (Gal, [0133], “System 300 monitors, logs and reports the performance of student based on their operation of student stations 301-303”), and a course reporting (Gal, [0009], “the real-time class management module is to automatically allocate”; [0098], “portions of the content of educational learning objects may be automatically modified, removed or added, based on characteristics of the student utilizing the learning object, thereby providing to each student a learning object accommodating the student's characteristic and record of progress”; [0112], “the script may indicate to the teaching/learning system to automatically perform one or more of these operations”; [0154], “the adaptive offering may be provided directly to students automatically”).
18. The teaching and learning autonomous system of claim 17, wherein said course monitoring monitors said teaching and learning processes and provides feedback to said autonomous reporting engine (Gal, Abstract, “allowing a content publisher to receive aggregated feedback based on monitored progress”; [0124], “to perform real-time in-class management of the learning activities performed by students or groups of students, to selectively allocate or re-allocate learning activities or learning objects to students or groups of students, to receive automated feedback or manual feedback from student stations 301-303 (e.g., upon completion of a learning activity or a learning object”).
19. The teaching and learning autonomous system of claim 18 further comprising an access management and security module adapted to provide access information for said course delivery, said course monitoring, and said course reporting (Gal, fig. 8, 831, “security”; [0202], “security module”; [0212], “a log-in interface allowing the user to enter a user-name and a password”).
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-3,5-12 and 14-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
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/JACK YIP/Primary Examiner, Art Unit 3715