Abstract: A system and method combine programmatic control and a guided and constrained Artificial Intelligence (AI) engine to generate dialogues for historical figures is disclosed. Historical data associated with historical figures including dates, events, and achievements are collected. Profiles of historical figures involved in the dialogues including biographical information, known speeches, writings, and significant actions are gathered. A content generation module is used to identify the context of the dialogues and generate historical content to maintain historical accuracies by verifying dates, events, and historical figures' specific details. The generated historical content is analyzed with educational standard to identify modern figure for integration with historical content. A prompt is generated to guide and constrain the AI engine to generate dialogues for historical figures based on the historical content aligned to educational standards.

Abstract: A virtual character identification system for guiding an AI engine to identify a virtual character based on AI-generated dialogues and images on an online learning platform is disclosed. The virtual character identification method involves collecting input data from user profiles and data models. The collected data is analyzed to generate insights that are used for prompt creation. These prompts are then used to guide the AI engine to generate text dialogues, which include an introduction, hints, and learning content. The AI engine also converts these dialogues into speech and dynamically generates images of the virtual character, where the image is progressively revealed based on user interaction. Furthermore, interactive audio-visual feedback, including educational videos with the virtual character, is provided to enhance the learning experience, allowing real-time engagement between the user and the platform.

Abstract: The content generation system and content generation process utilizes a prompt to guide an Artificial Intelligence (AI) engine for dynamically generating educational content, for creating an educational matching game content. The method and system utilizes an educational curriculum database to receive input, including educational standards and course details. The input is used to retrieve information for a historical figure relevant to the educational standard from the curriculum database, which includes the historical figure's image and voice. Additionally, a AI engine generates facts for the educational standard associated with the educational matching game content to ensure the educational content is rich and comprehensive. The system generates video response to present the educational content using the historical figure, adding an engaging multimedia element to the learning experience.

Abstract: A system and method for guiding an artificial intelligence (AI) engine to generate an assessment of statement truthfulness receives input data from a main data model containing educational standards and course information, and a Truth or Lies (TOL) data model containing information about historical figures. Based on the user-provided course ID and standard ID, relevant data is selected and retrieved from the main data model and the TOL data model. A prompt generator creates prompts to guide an AI engine in generating educational statements, including both true and false statements. The system and method for guiding an AI engine to generate an assessment of statement truthfulness integrates image generation to produce visuals corresponding to the statements and employs video generation and voice synthesis models to create video responses featuring historical figures explaining the statements.

Abstract: A system and method combine programmatic control and a guided and constrained Artificial Intelligence (AI) engine generate background images aligned with educational content in an online learning platform is disclosed. The integrated programmatically controlled system and guided and constrained AI engine perform operations including collecting educational content such as questions, correct answers, educational standards, and curricula associated with a user's online learning session. The collected content is analyzed to integrate relevant information and construct a detailed narrative. This narrative is then used to generate and refine text prompts via natural language processing techniques, which guide the AI engine in producing realistic background images. These images are designed to be visually appealing, contextually relevant, and to enhance user engagement and learning experience.

Abstract: The system and method combine programmatic control and a guided and constrained Artificial Intelligence (AI) engine for generating profiles for AI teachers within an online learning platform is disclosed. The programmatic control retrieves information associated with historical figures from a data store and parses user interaction data on the online learning platform to identify the engagement of each user with each historical figure. A content generation module prepares content for the AI teachers and generates a prompt and transfers the prompt to an AI engine to guide and constrain the AI engine to generate AI teacher profiles corresponding to the historical figures to utilize within the online learning platform by using the generated content and user interaction data. The AI teacher profiles are utilized to create social media accounts for the AI teachers and allow the user to interact with the AI teacher profiles on social media platforms.

Abstract: The system and method for guiding an Artificial Intelligence (AI) engine to generate a set of key terms relevant to educational standards. The system and method involve receiving input data including educational standards and key term types from educational curriculum guidelines, configuring a quality bar comprising metrics such as standard relevance, category fit, curriculum alignment, and correctness, and generating a prompt to guide the AI engine for generating key terms. An algorithm is then applied involving iterative prompt refinement and selection of key terms based on the quality bar metrics. This includes generating initial key terms using the AI engine, evaluating the generated key terms against the quality bar metrics, and refining the prompts iteratively based on the evaluation to improve the relevance and accuracy of the key terms. Furthermore, the prompt is transferred to the AI engine to generate a final set of key terms aligned with the educational standards.

Abstract: A system and method for guiding and constraining an Artificial Intelligence (AI) engine to provide personalized educational support to a user on an online learning platform using a multi-assistant framework is disclosed. The system and method access curriculum database and grading rubrics. User interaction data including user responses and selected units or topics is received. A free-response questions (FRQs) are generated using algorithms. The user responses to the FRQs are graded by utilizing the grading rubrics and providing projected score using FRQ grader assistant. The FRQ grader provides feedback aligned with scoring guidelines based on grading rubrics, and delivers projected score. A prompt is generated and transferred to AI engine to generate an assessment corresponding to the user performance based on a grading result on the user responses to FRQs. The generated FRQs, graded user responses, assessment, and projected scores are provided to the user on the online learning platform.

Abstract: An animatable image generation system and method to guide the AI engine in generating a photorealistic image of the virtual character for animating the virtual character. The method starts with the selection of a virtual character based on the educational content provided to the user on the online learning platform. The data collector accesses the databases to collect information about the virtual character. Based on the selected virtual character, AI-driven prompts are generated to guide the AI engine to generate a photorealistic image of the virtual character.

Abstract: A system and method combine programmatic control and a guided and constrained Artificial Intelligence (AI) engine to generate personalized video responses for a user. Receiving user inputs to identify a historical figure and a question directed to the corresponding historical figure. Information about the historical figure, including image, voice identifier, and biographical profile, is retrieved. Under programmatic logic control, an AI engine analyzes a question and generates an excuse for any delay in responding, else generate a dialogue response. The dialogue response is integrated with relevant information to generate a response having an audio and visual component with the voice identifier and dialogue response, and the image of the selected historical figure. A prompt is generated to guide and constrain the AI engine to create a video response that integrating audio and visual components to simulate the historical figure delivering the dialogue response and providing to an online learning platform.

Abstract: A method for guiding an artificial intelligence (AI) engine to generate and deliver educational content through an AI-generated tutor on an online learning platform. The method involves collecting input data from multiple sources, including educational, historical, image, and voice databases. Based on this data, prompts are generated to direct the AI engine in producing curriculum-aligned scripts. A digital AI tutor is created using the collected data, including synthesizing a voice that mimics the tutor and generating a corresponding visual representation. The script, voice, and visual elements are integrated into an animated video of the AI tutor. The video is then delivered and displayed to users on the learning platform at a scheduled time to facilitate personalized, standards-based instruction.