Systems and methods of presenting a study environment comprise and/or perform receiving, by an electronic processor, a context, wherein the context comprises an augmented content including a problem step pre-written by a first generative artificial intelligence (AI) model; presenting, by the electronic processor via a graphical user interface (GUI) of a user device, the problem step; receiving, by the electronic processor, an input responsive to the problem step from a user of the user device; presenting, by the electronic processor, a dynamic interaction to the user using a second generative AI model, wherein presenting the dynamic interaction includes: parsing, using the second generative AI model, the input, generating, by the second generative AI model, a response to the input, and causing the user device to display the response to the user.
Systems and methods of presenting an electronic textbook perform and/or comprise generating, by an electronic processor, a graphical user interface (GUI) for presenting an electronic textbook interface to a learner; initializing, by the electronic processor, an interactive session window within the electronic textbook interface; and via the electronic textbook interface: receiving, by the electronic processor, a user input via the GUI, determining, based on the user input, at least one of a request type and a request scope, in response to determining that the request type corresponds to a request for dynamic content: generating, using a generative artificial intelligence (AI) model and based on the request scope, the dynamic content, and presenting the dynamic content to the user via the GUI, and in response to determining that the request type corresponds to a request for pre-generated content, presenting the pre-generated content to the user via the GUI.
Systems and methods of the present invention provide for: storing a plurality of content plugins; generating a graphical user interface (GUI) including components for: selecting a subset of plugins, defining a relationship between the plugins in the subset, and defining a custom pathway through the subset, including rules or conditions for navigation; receiving, from the content creator client device, selection of the subset, the relationship, and the rule or condition; generating, from the subset, relationship, and rule or condition; and transmitting to client devices for display, a learning course content for a learning application.
Systems and methods for artificial intelligence-based language skill assessment and development using avatars provide for: determining a target language and a natural language of a user; generating a first avatar corresponding to the target language and a second avatar corresponding to the natural language on a graphical user interface; generating a first interaction for the first avatar using the target language where the first avatar is associated with a first generative artificial intelligence model; receiving a user input to select the second avatar; and in response to the user input, generating a second interaction for the second avatar using the natural language where the second interaction corresponds to the first interaction, the second avatar is associated with a second generative artificial intelligence model, and the second generative artificial intelligence model communicates with the first generative artificial intelligence model to produce the second interaction.
G09B 5/08 - Electrically-operated educational appliances providing for individual presentation of information to a plurality of student stations
G09B 7/02 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student
Systems and methods for bidirectional communication in a virtual reality environment are disclosed. The systems and methods include: generating the virtual reality environment for a first user; receiving a station selection user input to select a first language learning station; in response to the station selection user input, providing, via a graphic in the virtual reality environment, a first avatar in the first language learning station; receiving a communication from the first user in a target spoken language; providing the communication to a first artificial intelligence model; receiving, from the first artificial intelligence model, a response to the communication in the target spoken language; outputting, via the first avatar, the response in the target spoken language; and providing, via the graphic in the virtual reality environment, language assistance corresponding to the response in a natural spoken language of the first user.
G09B 5/08 - Electrically-operated educational appliances providing for individual presentation of information to a plurality of student stations
G09B 7/02 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student
Systems and methods for bidirectional communication in a virtual reality environment are disclosed. The systems and methods include: generating the virtual reality environment for a first user; receiving a station selection user input to select a first language learning station; in response to the station selection user input, providing, via a graphic in the virtual reality environment, a first avatar in the first language learning station; receiving a communication from the first user in a target spoken language; providing the communication to a first artificial intelligence model; receiving, from the first artificial intelligence model, a response to the communication in the target spoken language; outputting, via the first avatar, the response in the target spoken language; and providing, via the graphic in the virtual reality environment, language assistance corresponding to the response in a natural spoken language of the first user.
Systems and methods for artificial intelligence-based language skill assessment and development using avatars provide for: determining a target language and a natural language of a user; generating a first avatar corresponding to the target language and a second avatar corresponding to the natural language on a graphical user interface; generating a first interaction for the first avatar using the target language where the first avatar is associated with a first generative artificial intelligence model; receiving a user input to select the second avatar; and in response to the user input, generating a second interaction for the second avatar using the natural language where the second interaction corresponds to the first interaction, the second avatar is associated with a second generative artificial intelligence model, and the second generative artificial intelligence model communicates with the first generative artificial intelligence model to produce the second interaction.
Systems and methods for dynamic open activity response assessment provide for: receiving an open activity response from a client device of a user; in response to the open activity response, providing the open activity response to multiple machine learning models to process multiple open response assessments in real time; receiving multiple assessment scores from the multiple machine learning models; and providing multiple assessment results to the client device of the user based on the multiple assessment scores corresponding to the multiple open response assessments associated with the open activity response.
G09B 7/02 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student
H04L 51/02 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages
9.
SYSTEM AND METHOD FOR ARTIFICIAL INTELLIGENCE-BASED LANGUAGE SKILL ASSESSMENT AND DEVELOPMENT
Systems and methods for dynamic open activity response assessment provide for: receiving an open activity response from a client device of a user; in response to the open activity response, providing the open activity response to multiple machine learning models to process multiple open response assessments in real time; receiving multiple assessment scores from the multiple machine learning models; and providing multiple assessment results to the client device of the user based on the multiple assessment scores corresponding to the multiple open response assessments associated with the open activity response.
Systems and methods of the present invention for constructing an interactive skills map on a graphical user interface include: determining a first skill of a user; displaying the first skill on the graphical user interface; displaying one or more first possible skills adjacent to the first skill, the one or more first possible skills related to the first skill, wherein the one or more first possible skills are inactivated; receiving a first user input to select a possible skill among the one or more first possible skills on the graphical user interface; activating the selected possible skill among the one or more first possible skills to be a second skill; and in response to the first user input, dynamically displaying one or more second possible skills adjacent to the second skill, the one or more second possible skills related to the second skill.
Systems and methods of the present invention provide for: storing a plurality of content plugins; generating a graphical user interface (GUI) including components for: selecting a subset of plugins, defining a relationship between the plugins in the subset, and defining a custom pathway through the subset, including rules or conditions for navigation; receiving, from the content creator client device, selection of the subset, the relationship, and the rule or condition; generating, from the subset, relationship, and rule or condition; and transmitting to client devices for display, a learning course content for a learning application.
Techniques described herein relate to receiving multiple sources of verified data associated with a digital credential receiver, and mapping the digital credential receiver to one or more data field data objects based on analyses of the verified data. In some embodiments, a digital credential platform server may analyze the various data sources associated with the digital credential receiver, in order to determine and calculate correlation scores between the digital credential receiver and various field data objects. A combination of analyses and/or comparisons may be used between the credential receiver data and the corresponding retrieved from field data objects, such as the digital credential objects earned by the credential receiver, the credential receiver’s verified evaluation records, and/or the career phase of the digital credential receiver.
Systems and methods for feature-based alert triggering are disclosed herein. The system can include memory including a model database containing a machine-learning algorithm. The system can include a user device that can receive inputs from a user; and at least one server. The at least one server can: receive electrical signals from the user device, the electrical signals corresponding to a plurality of user inputs provided to the user device; automatically generate input-based features from the received electrical signals; input the input-based features into the machine-learning algorithm; automatically and directly generate a risk prediction with the machine-learning algorithm from the input-based features; and generate and display an alert when the risk prediction exceeds a threshold value.
G06N 7/01 - Probabilistic graphical models, e.g. probabilistic networks
G06F 3/048 - Interaction techniques based on graphical user interfaces [GUI]
G06F 21/55 - Detecting local intrusion or implementing counter-measures
G06F 21/56 - Computer malware detection or handling, e.g. anti-virus arrangements
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G09B 7/02 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student
Systems and methods of the present invention provide for a database configured to store multiple portions of experiential course content that correspond to an experiential course; a set of candidate screens apportioned accordingly, and a graphical user interface (GUI) configured to elicit, from a user, a selection of a particular set of screens from a user. The systems and methods further provide for receiving, via the GUI, a set of parameters defining a set of pathways, the set of pathways configured to route a learner user through the experiential course. The experiential course content may then be transmitted to the learner user via a GUI configured to route the learner user through the experiential course.
G09B 5/12 - Electrically-operated educational appliances providing for individual presentation of information to a plurality of student stations different stations being capable of presenting different information simultaneously
G09B 9/00 - Simulators for teaching or training purposes
G06F 3/04815 - Interaction with a metaphor-based environment or interaction object displayed as three-dimensional, e.g. changing the user viewpoint with respect to the environment or object
15.
WHITELIST-AUTHENTICATED IMAGE AND INTERACTIVE SERVICE
Systems and methods of the disclosure provide for receiving, from a GUI on a client device, a request to download and install an OS image and integrated interactive service on a bootable resource; transmitting to the client device the OS image and the integrated interactive service to be installed on the bootable resource, wherein the bootable resource is configured to: on a restart of the client device, boot to the OS image and launch the interactive service; and deny access to any software, service, or resource not available on the bootable resource.
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
Systems and methods of the present invention provide for identifying the skills of a candidate, generating and delivering one or more courses for skill development to the candidate, and/or providing certification or other credentials for skills obtained by the candidate via the courses. Identifying the skills may include a server comparing a set of initial skills to a set of requisite skills to identify a set of untrained skills. Generating and delivering courses may include generating a skill path based on the set of untrained skills and delivering course content associated with the untrained skills. Providing certification may include issuing a credential to the user upon determining that the user has successfully completed a course and sending notifications to third party servers and/or a user device indicating completion of the course.
G09B 7/02 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student
17.
Display screen or portion thereof with graphical user interface
Systems and methods of the present invention provide for receiving, from a content activity agent on a first client device, a content usage data; input, into a machine learning model, at least one content activity parameter, translated from the content usage data; generating, using an output from the machine learning model, a graphical user interface (GUI), displayed on a second client device, and including a report of: the output, a recommendation for an update to a course content, and a prediction of an increase to an average assessment score associated with the course content if the updated content is used.
Systems and methods of the present invention may be used to determine metrics and health scores for content that may correspond to an educational course or textbook, which may be in a digital format. The metrics and health scores may be determined at various hierarchical content levels, and may be used to quantitatively assess how well the corresponding content is performing based on responses submitted to assessment item parts of the content by responders. The metrics may include difficulty and discrimination metrics, which may be determined using maximum likelihood estimation methods based on a modified two parameter item response model. A content analytics interface corresponding to a given content element may be generated and displayed via a user device, and may include content health scores of subcontent within that content element. The subcontent may be ordered according to content health score.
Systems and methods may involve processing of entity data by machine learning models to produce one or more entity and/ aggregate risk scores and/or aggregate anticipated risk scores, which may be compared to one or more thresholds to determine when one or more predefined actions should be taken. The entity data may be collected for various entities related to an exam registration and delivery process, which may include a candidate, an exam, a test center, an exam registration event, a proctor, and an exam delivery event. The exam registration and delivery process may include multiple states - each being associated with a different set of entities. Aggregate risk scores for a given state may be calculated using only entity data for the set of entities associated with that state. The predetermined actions taken may also be dependent on the current state.
A multi-country data pipeline keeps all of the PII received from a user that is in a first country in the first country. The data pipeline allows the non-personal data received from the user to be transmitted and analyzed in a second country. The method further allows the results of the analysis in the second country to be transmitted back to the first country where the PII is added to the results of the analysis. The data pipeline allows the results of the analysis in the second country to be used to take a desired action for the user in the first country, all while the PII of the user never leaves the first country.
Systems and methods of the present invention provide for: storing a correlation table including images and associated strings, and a secure password table; generating a GUI, displayed on a client computer and including GUI components for visual authentication; receiving a selection of a component; updating the GUI with a menu of images associated with the selected component; receiving a selection of one of the images; identifying an associated string as an authentication string; and storing the authentication string as a secure password in the password table.
G06F 21/46 - Structures or tools for the administration of authentication by designing passwords or checking the strength of passwords
G06F 21/36 - User authentication by graphic or iconic representation
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
H04L 29/06 - Communication control; Communication processing characterised by a protocol
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
A system including a computer server implementing a learning resource configured to monitor a user interaction with the learning resource, and encode, based on the user interactions, a user event. The system includes a computer server implementing an event processor. The event processor is configured to receive, from the computer server, the user event, parse the user event to determine the identifications of the user generating the user event, the assessment item, and the learning resource, and the indication of whether the user event is associated with a correct answer or an incorrect answer, and store, in an analytics storage database, a data record including the identification of the user generating the user event, the assessment item, the learning resource, and the indication of whether the user event is associated with a correct answer or an incorrect answer.
Systems and methods of the present invention provide for receiving, from a client, a request for a collaborative environment; displaying the collaborative environment; recording a plurality of attempt steps including events input by a learner to solve a problem, and solution steps input into the collaborative environment by an instructor, which identifies a timestamp within the plurality of events and generates alternative events solving the problem. The system then receives a request to reproduce the collaborative environment; and generates a reproduction of the collaborative environment.
H04L 65/4053 - Arrangements for multi-party communication, e.g. for conferences without floor control
G09B 5/10 - Electrically-operated educational appliances providing for individual presentation of information to a plurality of student stations all student stations being capable of presenting the same information simultaneously
G09B 5/12 - Electrically-operated educational appliances providing for individual presentation of information to a plurality of student stations different stations being capable of presenting different information simultaneously
G09B 7/00 - Electrically-operated teaching apparatus or devices working with questions and answers
25.
SYSTEMS AND METHODS FOR SKILL DEVELOPMENT MONITORING AND FEEDBACK
A system and method are presented. User metadata defining a set of activities undertaken by a user are received by a processor. The processor determines, based on the set of activities, a skill history for the user. The skill history identifies a first plurality of skills associated with the user. The processor determines a preferred career associated with the user, determines, for the preferred career and by accessing a career skill repository, a second plurality of skills associated with the preferred career, determines a missing skill by comparing the first plurality of skills associated with the user to the second plurality of skills associated with the preferred career to identify the missing skill that is in the second plurality of skills and not in the first plurality of skills and outputs a user interface identifying the missing skill.
Systems and methods of the present invention provide for: storing a plurality of content plugins; generating a graphical user interface (GUI) including components for: selecting a subset of plugins, defining a relationship between the plugins in the subset, and defining a custom pathway through the subset, including rules or conditions for navigation; receiving, from the content creator client device, selection of the subset, the relationship, and the rule or condition; generating, from the subset, relationship, and rule or condition; and transmitting to client devices for display, a learning course content for a learning application.
Systems and methods of the present invention provide for: storing a plurality of content plugins; generating a graphical user interface (GUI) including components for: selecting a subset of plugins, defining a relationship between the plugins in the subset, and defining a custom pathway through the subset, including rules or conditions for navigation; receiving, from the content creator client device, selection of the subset, the relationship, and the rule or condition; generating, from the subset, relationship, and rule or condition; and transmitting to client devices for display, a learning course content for a learning application.
A system including at least one processor configured to: store learning resources and learning outcome frameworks in a database, which are then selected; map sections of learning resources to associated objectives within learning outcome frameworks; generate a GUI, including access to learning resources and frameworks; receive selection of a learning framework and a learning resource; and in response, generate a framework menu, selectable learning objectives, and an associated resource content, respectively.
A system and method are configured for receiving a data transmission encoding a content of a hypertext transfer protocol request and an identification of a first service, determining a first schema definition in a memory that is associated with the first service, the first schema definition including a plurality of schema items, and parsing the content of the hypertext transfer protocol request to identify a plurality of parameters and a plurality of values, each value in the plurality of values being associated with a parameter in the plurality of parameters. The system and method are configured for, for each schema item in the plurality of schema items, identifying a parameter in the content of the hypertext transfer protocol request that matches the schema item, and encoding the value associated with the parameter into a schema information object. The method includes storing the schema information object in the memory.
H04L 41/0273 - Exchanging or transporting network management information using the InternetEmbedding network management web servers in network elementsWeb-services-based protocols using web services for network management, e.g. simple object access protocol [SOAP]
H04L 67/02 - Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
Systems and methods for secure content delivery are disclosed herein. The system can include a content driver communicatingly connected with a user device via a layered protocol model or via a User Datagram Protocol (UDP). The content driver can generate a signal directing the creation of a secured partition on a bootable media device connected to a user device, identify content for delivery, and generate pixel data for the content. The content driver can send the pixel data to the user device, wherein the user device is configured to store the pixel data in the secured partition of the bootable media device. The content driver can receive a plurality of response inputs from the user device, wherein the response inputs are generated by a software application running on the bootable media device, generate a response based on the received response inputs, and provide the generated response to an evaluation module.
Systems and methods of the present invention provide for generating and displaying a progress monitoring assistant to show the growth scale value score comparing two or more assessments and providing a preliminary interpretation of the comparison.
Systems and methods of the present invention provide for generating and displaying a progress monitoring assistant to show the growth scale value score comparing two or more assessments and providing a preliminary interpretation of the comparison.
Systems and methods of the present invention provide for generating and displaying a progress monitoring assistant to show the growth scale value score comparing two or more assessments and providing a preliminary interpretation of the comparison.
Systems and methods may involve processing of entity data by machine learning models to produce one or more aggregate risk scores, which may be compared to one or more thresholds to determine when one or more predefined actions should be taken. The entity data may be collected for various entities related to an exam registration and delivery process, which may include a candidate, an exam, a test center, an exam registration event, a proctor, and an exam delivery event. The exam registration and delivery process may include multiple states - each being associated with a different set of entities. Aggregate risk scores for a given state may be calculated using only entity data for the set of entities associated with that state. The predetermined actions taken may also be dependent on the current state.
Systems and methods may involve processing of entity data by machine learning models to produce one or more entity and/ aggregate risk scores and/or aggregate anticipated risk scores, which may be compared to one or more thresholds to determine when one or more predefined actions should be taken. The entity data may be collected for various entities related to an exam registration and delivery process, which may include a candidate, an exam, a test center, an exam registration event, a proctor, and an exam delivery event. The exam registration and delivery process may include multiple states - each being associated with a different set of entities. Aggregate risk scores for a given state may be calculated using only entity data for the set of entities associated with that state. The predetermined actions taken may also be dependent on the current state.
Systems and methods may involve processing of entity data by machine learning models to produce one or more aggregate risk scores, which may be compared to one or more thresholds to determine when one or more predefined actions should be taken. The entity data may be collected for various entities related to an exam registration and delivery process, which may include a candidate, an exam, a test center, an exam registration event, a proctor, and an exam delivery event. The exam registration and delivery process may include multiple states—each being associated with a different set of entities. Aggregate risk scores for a given state may be calculated using only entity data for the set of entities associated with that state. The predetermined actions taken may also be dependent on the current state.
G09B 7/02 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student
Systems and methods may involve processing of entity data by nested machine learning models to produce one or more aggregate risk scores, which may be compared to one or more thresholds to determine when one or more predefined actions should be taken. The entity data may be collected for various entities related to an exam registration and delivery process, which may include a candidate, an exam, a test center, an exam registration event, a proctor, and an exam delivery event. Entity data for each entity may be separately processed by entity-specific machine learning models to generate intermediate entity risk scores. The intermediate entity risk scores may be input to an aggregate machine learning model, which may output an aggregate risk score. A resource management server may cause the predefined actions to be taken after comparing the aggregate risk score to the one or more thresholds.
Systems and methods may involve processing of entity data by machine learning models to produce one or more entity and/aggregate risk scores and/or aggregate anticipated risk scores, which may be compared to one or more thresholds to determine when one or more predefined actions should be taken. The entity data may be collected for various entities related to an exam registration and delivery process, which may include a candidate, an exam, a test center, an exam registration event, a proctor, and an exam delivery event. The exam registration and delivery process may include multiple states—each being associated with a different set of entities. Aggregate risk scores for a given state may be calculated using only entity data for the set of entities associated with that state. The predetermined actions taken may also be dependent on the current state.
Systems and methods may involve processing of entity data by machine learning models to produce one or more entity and/aggregate risk scores and/or aggregate anticipated risk scores, which may be compared to one or more thresholds to determine when one or more predefined actions should be taken. The entity data may be collected for various entities related to an exam registration and delivery process, which may include a candidate, an exam, a test center, an exam registration event, a proctor, and an exam delivery event. The exam registration and delivery process may include multiple states—each being associated with a different set of entities. Aggregate risk scores for a given state may be calculated using only entity data for the set of entities associated with that state. The predetermined actions taken may also be dependent on the current state.
G06Q 10/0635 - Risk analysis of enterprise or organisation activities
G09B 7/02 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student
40.
RISK ANALYSIS AND MITIGATION WITH NESTED MACHINE LEARNING MODELS FOR EXAM REGISTRATION AND DELIVERY PROCESSES
Systems and methods may involve processing of entity data by nested machine learning models to produce one or more aggregate risk scores, which may be compared to one or more thresholds to determine when one or more predefined actions should be taken. The entity data may be collected for various entities related to an exam registration and delivery process, which may include a candidate, an exam, a test center, an exam registration event, a proctor, and an exam delivery event. Entity data for each entity may be separately processed by entity-specific machine learning models to generate intermediate entity risk scores. The intermediate entity risk scores may be input to an aggregate machine learning model, which may output an aggregate risk score. A resource management server may cause the predefined actions to be taken after comparing the aggregate risk score to the one or more thresholds.
Systems and methods of the present invention provide for storing textbook data, a glossary, and problems within a database; identifying a problem's guided solution, and a keyword within the solution matching an entry within the glossary, from which a skill tag is associated. The disclosed system then automatically generates an assessment including an assessment problem associated with the skill. If an incorrect response is received for the assessment problem, the database is updated to associate a user that input the response with the assessment problem and a skill. The system then automatically generates a customized exercise assignment associated in the database with the skill.
G09B 7/04 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student characterised by modifying the teaching programme in response to a wrong answer, e.g. repeating the question, supplying a further explanation
Systems and methods of the present invention provide for storing textbook data, a glossary, and problems within a database; identifying a problem's guided solution, and a keyword within the solution matching an entry within the glossary, from which a skill tag is associated. The disclosed system then automatically generates an assessment including an assessment problem associated with the skill. If an incorrect response is received for the assessment problem, the database is updated to associate a user that input the response with the assessment problem and a skill. The system then automatically generates a customized exercise assignment associated in the database with the skill.
G09B 7/02 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student
G09B 7/07 - Electrically-operated teaching apparatus or devices working with questions and answers of the multiple-choice answer type, i.e. where a given question is provided with a series of answers and a choice has to be made from the answers providing for individual presentation of questions to a plurality of student stations
The disclosed embodiments include a method to predict annotation spans without requiring any labeled annotation data. The approach is to consider AES as a Multiple Instance Learning (MIL) task. The disclosed embodiments show that such models can both predict content scores and localize content by leveraging their sentence-level score predictions. This capability arises despite never having access to annotation training data. Implications are discussed for improving formative feedback and explainable AES models.
Systems and methods of the present invention provide for at least one processor executing program code instructions on a server computer coupled to a network. The program code instructions cause the server computer to receive from a user client an assessment audio file. The instructions also cause the computer to extract a plurality of audio features from the assessment audio file using a voice profile module. In addition, the instructions cause the computer to store the assessment audio file and extracted features in a database. Further, the instructions cause the computer to calculate a candidate confidence score indicating the probability that the assessment audio file is from a common speaker as a previously stored audio file within the database. Lastly, the instructions cause the computer to generate a based on the candidate confidence score.
Systems and methods of the present invention provide for at least one processor executing program code instructions on a server computer coupled to a network. The program code instructions cause the server computer to receive from a user client an assessment audio file. The instructions also cause the computer to extract a plurality of audio features from the assessment audio file using a voice profile module. In addition, the instructions cause the computer to store the assessment audio file and extracted features in a database. Further, the instructions cause the computer to calculate a candidate confidence score indicating the probability that the assessment audio file is from a common speaker as a previously stored audio file within the database. Lastly, the instructions cause the computer to generate a based on the candidate confidence score.
H04L 29/06 - Communication control; Communication processing characterised by a protocol
G06F 16/635 - Filtering based on additional data, e.g. user or group profiles
G06F 16/683 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
A website may track online activities, such as assignments and/or assessment, of students taking online digital courses (courses). Courseware-level data and student-level data may be extracted from the tracked online activities and as well as student registration data. Institutional-level data may be generated from data regarding the institutions that teach the courses. Teacher-level data may be generated for the teachers teaching the courses. A teacher or student may request on a website an analysis of a course. Data for the course may be weighted in the courseware-level data. Data for the student(s), institution and/or teacher may also be weighted, depending on the desired analysis. A Bayesian multi-level model may generate a plurality of posterior distributions using the collected data. A prediction of a difficult subject matter may be determined from the plurality of posterior distributions and used to select a targeted remediation that may be performed on a website.
Systems and methods of the present invention provide for: generating a GUI comprising survey questions associated with degree factors and associated rating GUI components indicating application of the factor to a user; receiving the factor rating for each survey question; identifying a high factor rating exceeding a threshold; selecting a degree identifier sharing a common high factor rating between the first response and a response stored in the database; generating a candidate degree list including the degree identifier; generating a second GUI including the candidate degree list; and transmitting the second GUI to a client device.
Systems and methods for adaptive assessment may utilize test deliver policies derived from a multi-armed bandit approach in combination with an item response theory model. A monotonic policy may involve defining a difficulty range according to which test items are selected for delivery during an assessment, where the difficulty range is updated following delivery of each test item based on test-taker performance. A multi-stage policy may implement several stages for test item delivery, with a different initial difficulty range for test item selection being defined for each stage and the difficulty ranges being updated based on test-taker performance within each respective stage. A probability matching policy may involve defining an item difficulty probability distribution according to which test items are selected for delivery to a test taker, where the probability distribution is initialized based on test taker skill level and updated based on test taker performance.
G09B 7/00 - Electrically-operated teaching apparatus or devices working with questions and answers
G09B 7/04 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student characterised by modifying the teaching programme in response to a wrong answer, e.g. repeating the question, supplying a further explanation
Systems and methods for adaptive assessment may utilize test deliver policies derived from a multi-armed bandit approach in combination with an item response theory model. A monotonic policy may involve defining a difficulty range according to which test items are selected for delivery during an assessment, where the difficulty range is updated following delivery of each test item based on test-taker performance. A multi-stage policy may implement several stages for test item delivery, with a different initial difficulty range for test item selection being defined for each stage and the difficulty ranges being updated based on test-taker performance within each respective stage. A probability matching policy may involve defining an item difficulty probability distribution according to which test items are selected for delivery to a test taker, where the probability distribution is initialized based on test taker skill level and updated based on test taker performance.
G09B 7/00 - Electrically-operated teaching apparatus or devices working with questions and answers
G09B 7/04 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student characterised by modifying the teaching programme in response to a wrong answer, e.g. repeating the question, supplying a further explanation
Systems and methods for adaptive assessment may utilize test deliver policies derived from a multi-armed bandit approach in combination with an item response theory model. A monotonic policy may involve defining a difficulty range according to which test items are selected for delivery during an assessment, where the difficulty range is updated following delivery of each test item based on test-taker performance. A multi-stage policy may implement several stages for test item delivery, with a different initial difficulty range for test item selection being defined for each stage and the difficulty ranges being updated based on test-taker performance within each respective stage. A probability matching policy may involve defining an item difficulty probability distribution according to which test items are selected for delivery to a test taker, where the probability distribution is initialized based on test taker skill level and updated based on test taker performance.
G09B 7/04 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student characterised by modifying the teaching programme in response to a wrong answer, e.g. repeating the question, supplying a further explanation
52.
Systems and methods for automated response data sensing-based next content presentation
Systems and methods for automatic generation of a content presentation plan are disclosed herein. The method can include receiving content identification information, retrieving objective information for the one or several objectives identified for inclusion in a content presentation plan, identifying at least one prerequisite skill for completion of at least one of the one or several objectives, generating at least one remediation question configured to delineate between users having mastery of the at least one prerequisite skill and users not having mastery of the at least one prerequisite skill, pre-selecting remedial content for providing to users identified as not having mastery of the at least one prerequisite skill, selecting objective content corresponding to the at least one objectives, and creating a content presentation plan containing the at least one remediation question, the remedial content, and the objective content.
G09B 7/02 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student
G09B 5/08 - Electrically-operated educational appliances providing for individual presentation of information to a plurality of student stations
G06T 7/70 - Determining position or orientation of objects or cameras
G09B 5/12 - Electrically-operated educational appliances providing for individual presentation of information to a plurality of student stations different stations being capable of presenting different information simultaneously
G09B 7/07 - Electrically-operated teaching apparatus or devices working with questions and answers of the multiple-choice answer type, i.e. where a given question is provided with a series of answers and a choice has to be made from the answers providing for individual presentation of questions to a plurality of student stations
G09B 7/12 - Electrically-operated teaching apparatus or devices working with questions and answers of the multiple-choice answer type, i.e. where a given question is provided with a series of answers and a choice has to be made from the answers wherein a set of answers is common to a plurality of questions characterised by modifying the teaching programme in response to a wrong answer, e.g. repeating the question, supplying further information
G09B 5/06 - Electrically-operated educational appliances with both visual and audible presentation of the material to be studied
53.
TIME-BASED DEGRADATION OF DIGITAL CREDENTIALS IN A DIGITAL CREDENTIAL PLATFORM
Techniques described herein relate to generation and time-based degradation of digital credentials within digital credentialing environments. A digital credential generation system may include a digital credential issuer and a platform server configured to determine and implement time-based degradation of the digital credentials issued to credential receivers. Different digital credentials may have different associated degradation functions, based on the type of the digital credential and/or additional factors such as the additional credentials issued to the receiver and the monitoring data of the receiver. The magnitude values computed for issued digital credentials, using the degradation functions, may be used to determine credential expiration times, re-credentialing times and/or requirements, and the like.
Systems and methods for feature-based alert triggering are disclosed herein. The system can include memory including a model database containing a machine-learning algorithm. The system can include a user device that can receive inputs from a user; and at least one server. The at least one server can: receive electrical signals from the user device, the electrical signals corresponding to a plurality of user inputs provided to the user device; automatically generate input-based features from the received electrical signals; input the input-based features into the machine-learning algorithm; automatically and directly generate a risk prediction with the machine-learning algorithm from the input-based features; and generate and display an alert when the risk prediction exceeds a threshold value.
G06F 21/55 - Detecting local intrusion or implementing counter-measures
G06F 21/56 - Computer malware detection or handling, e.g. anti-virus arrangements
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G09B 7/02 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student
Systems and methods of the present invention provide for identifying the skills of a candidate, generating and delivering one or more courses for skill development to the candidate, and/or providing certification or other credentials for skills obtained by the candidate via the courses.
G09B 5/12 - Electrically-operated educational appliances providing for individual presentation of information to a plurality of student stations different stations being capable of presenting different information simultaneously
57.
SYSTEMS AND METHODS FOR OBJECTIVE-BASED SKILL TRAINING
Systems and methods of the present invention provide for determining a required skill set for meeting a goal, determining the current skill set of a user, identifying skill gaps between the required skill set and the user's current skill set, assigning skill training objectives to the user corresponding to the skill gaps, monitoring progress of the user through completion of the skill training objectives, and alerting the user upon completion of the skill training objectives. Goals and skill training objectives may be set for multiple users to close skill gaps preventing such users from qualifying for roles of a project to which the users are closely matched. The each user's respective skill training objective progress may be monitored and tracked provided via a user interface at a manager device associated with the project. The manager device may be alerted when the skill training objectives have been completed by the users.
G09B 7/04 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student characterised by modifying the teaching programme in response to a wrong answer, e.g. repeating the question, supplying a further explanation
G06F 11/34 - Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation
58.
AUTOMATED REINFORCEMENT LEARNING BASED CONTENT RECOMMENDATION
Embodiments of the present disclosure relate to systems and methods for reinforcement learning based content recommendation. The method includes receiving configuration data for creation of a reinforcement learning model, generating a plurality of correlation matrices, receiving a request for content for providing to a user, determining a user context, the user context characterizing an aggregation of attributes of the user, and selecting a next piece of content from a database of pieces of content. The method can include presenting the selected piece of content to the user, receiving user inputs in response to the presenting of the selected piece of content to the user, and updating the value characterizing the outcome of previous presentation of the selected piece of content based on the received user input.
Systems and methods for content selection with first and second recommendation engines are disclosed herein. The system can include a memory include a content library database and a model database. The system can include a user device having a first network interface and a first I/O subsystem. The system can include one or more servers that can include a packet selection system and a presentation system. These one or more servers can: receive response data from the user device; provide received response data to a first recommendation engine; alert a second recommendation engine when a selected next node is a placeholder node; retrieve at least one statistical model relevant to selection of next node content; and select next node content based on an output of the at least one statistical model.
Systems and methods are disclosed related to the identification of key features among features input to a complex predictive model. Logistic models may be created for each of a number of defined clusters of training data used to train the complex predictive model. Coefficients of each logistic model may be analyzed to identify key features that contribute to predictions made by the logistic models. Performance of the logistic models may be compared to that of the complex model to validate the logistic models. When a prediction is made for a given student by the complex predictive model, the student may be assigned to a cluster/by identifying the cluster center having the shortest Euclidean distance to the feature data associated with the student. Key features associated with the assigned cluster may be used as a basis for generating a recommendation for the reducing a risk level of the student.
Systems and methods for accelerated stabilization of data packet metadata are disclosed herein. The system can include a memory having a content database and a user profile database. The system can include a user device having a first network interface and a first I/O subsystem. The system can include one or more servers. The one or more servers can: retrieve data packet metadata for a data packet; determine that the data packet metadata is unstable; identify a set of potential recipients of the data packet; select one of the set of potential recipients as the recipient of the data packet; provide the data packet to the recipient of the data packet; receive a response from the recipient to the provided data packet; and automatically update the data packet metadata based on the response received from the recipient.
Systems and methods of the present invention provide for: receiving a digital image data; modifying the digital image data to reduce a width of a feature within the digital image data; executing a dimension reduction process on the feature; storing a feature vector comprising: at least one feature for each of the received digital image data, and a correct or incorrect label associated with each feature vector; selecting the feature vector from a data store; training a classification software engine to classify each feature vector according to the label; classifying the image data as correct or incorrect according to a classification software engine; and generating an output labeling a second digital image data as correct or incorrect.
Systems and methods for automated sequencing database generation are disclosed herein. The system can include memory that can include a content library database; a graph database; and a model database. The system can include a user device and at least one server. The at least one server can: receive a content aggregation from the content library database; identify content components of the content aggregation based on a natural language processing analysis of at least a portion of the content aggregation; identify explicit sequencing of the content components; generate an intermediate content graph based on the explicit sequencing of the content components; generate a final content graph from the intermediate content graph based on implicit sequencing of the content components; and store the final content graph within the graph database.
A learner engagement engine provides a unique way to track and measure a learner's engagement across a plurality of different learning resources. In preferred embodiments, the learning engagement engine measures learner's engagement activities at the most detailed level (such as at a paragraph level, instead of a chapter or book level). This allows the learner engagement engine to easily aggregate learner activities, even when a course structure or context are changed during the course.
Systems, device configurations, and processes for a server to receive, from a user interface (UI) on a client, a request to generate a list from a selection of: an objective, vocabulary item, and/or grammar point mapped to a range of competency scores, and an audience. The server then selects data records storing data for the objective, vocabulary item or grammar point. The server then renders, for transmission and display on the client, a user interface control including a list of data for the objective, grammar point, and/or vocabulary item.
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
The present disclosure provides systems, device configurations, and processes for displaying presentation control interfaces as overlays of content being displayed by an interactive whiteboard computing system in an interactive presentation environment, including one or more panels displaying selectable icons for performing various control tasks, including: viewing a present position and changing position within a sequence for the presentation; inputting, finding, and loading data to be stored for the presentation; interacting with the computing system or connected devices; and the like. Additional configurations include automatically showing, hiding, and/or repositioning control interface panels so that they are accessible by the presenter without substantially interfering with the presentation.
G06F 3/04817 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance using icons
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 3/0483 - Interaction with page-structured environments, e.g. book metaphor
G06F 3/0488 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures
G06F 3/04883 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures for inputting data by handwriting, e.g. gesture or text
G06F 3/04886 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures by partitioning the display area of the touch-screen or the surface of the digitising tablet into independently controllable areas, e.g. virtual keyboards or menus
G06F 3/0489 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using dedicated keyboard keys or combinations thereof
69.
Annotate a passage to graphically displays locations and types of mistakes
A passage of selectable words and/or selectable blank spaces may be displayed on a client device of an evaluator. As a test subject reads the passage, preferably from another source, the evaluator may select a selectable word or blank space. A plurality of selectable bubbles may appear near and/or around the selected word, where each selectable bubble corresponds to a type of mistake that the test subject might make in reading the passage. The evaluator may select one of the selectable bubbles depending on the type of mistake the test subject made. After selecting a bubble, the plurality of selectable bubbles are removed from the display and a tag icon, indicating which type of mistake the evaluator selected, is displayed near the selected word. In this manner, an annotated passage may be created that graphically illustrates where and what type of mistakes the test subject made in reading the passage.
G09B 7/04 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student characterised by modifying the teaching programme in response to a wrong answer, e.g. repeating the question, supplying a further explanation
G09B 7/08 - Electrically-operated teaching apparatus or devices working with questions and answers of the multiple-choice answer type, i.e. where a given question is provided with a series of answers and a choice has to be made from the answers characterised by modifying the teaching programme in response to a wrong answer, e.g. repeating the question, supplying further information
G09B 5/06 - Electrically-operated educational appliances with both visual and audible presentation of the material to be studied
G06F 40/169 - Annotation, e.g. comment data or footnotes
70.
MULTI-COUNTRY DATA PIPELINE THAT PROTECTS PERSONALLY IDENTIFYING INFORMATION
A multi-country data pipeline keeps all of the Pll received from a user that is in a first country in the first country. The data pipeline allows the non-personal data received from the user to be transmitted and analyzed in a second country. The method further allows the results of the analysis in the second country to be transmitted back to the first country where the Pll is added to the results of the analysis. The data pipeline allows the results of the analysis in the second country to be used to take a desired action for the user in the first country, all while the Pll of the user never leaves the first country.
A multi-country data pipeline keeps all of the Pll received from a user that is in a first country in the first country. The data pipeline allows the non-personal data received from the user to be transmitted and analyzed in a second country. The method further allows the results of the analysis in the second country to be transmitted back to the first country where the Pll is added to the results of the analysis. The data pipeline allows the results of the analysis in the second country to be used to take a desired action for the user in the first country, all while the Pll of the user never leaves the first country.
A multi-country data pipeline keeps all of the PII received from a user that is in a first country in the first country. The data pipeline allows the non-personal data received from the user to be transmitted and analyzed in a second country. The method further allows the results of the analysis in the second country to be transmitted back to the first country where the PII is added to the results of the analysis. The data pipeline allows the results of the analysis in the second country to be used to take a desired action for the user in the first country, all while the PII of the user never leaves the first country.
Systems and methods for remote intervention are disclosed herein. The system can include memory including: a user profile database; a content database; and a model database. The system can include a remote device including: a network interface; and an I/O subsystem. The system can include a content management server that can: receive a first electrical signal from the remote device; generate and send an electrical signal to the remote device directing the launch of the content authoring interface; receive a second electrical signal including content received by the content authoring interface from the remote device; identify a plurality of response demands in the received content; determine a level of the received content based on the identified plurality of response demands; determine the acceptability of the received content based on the identified plurality of response demands; and generate and send an alert to the remote device.
Embodiments relate to systems and methods for electronically conditioning transmission of communications based on results of a connection assessment. An electronic file is executed at an electronic device, which causes a first query and a second query to be presented. A first query response and a second query response are identified. The first query response is stored in a locked configuration that inhibits the ability to modify the first query response to the first query. The second query response is stored but is not stored in the locked configuration. Query response data is generated that includes an identifier of the second query, an identifier of the second query response and an identifier of the electronic device. A connection variable is determined by assessing one or more network connections available to the electronic device. When a transmission condition is satisfied, the query response data is transmitted to another device.
G09B 7/02 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student
Methods and systems for automatically resolving computerized electronic communication anomalies are disclosed herein. The system can include a memory including an error database containing information identifying a plurality of previous detected errors and configuration information associated with those errors. The system can include a plurality of user devices. Each of these plurality of user devices can include: a first network interface to exchange data via the communication network; and a first I/O subsystem to convert electrical signals to user interpretable outputs via a user interface. The system can include a server that can: receive an indication of the initiation of electronic communication; receive an electrical signal including attribute information; receive an error message; identify a trend in error messages; and provide an error solution if a trend is identified.
Systems and methods of the present invention provide for one or more server computers communicatively coupled to a network and configured to: receive, from a GUI on a user device, user input including a determination of whether a prior probability of dyslexia exists for a user, a selection of a dyslexia screening test administered to the user and an indication of whether the test indicated a risk of dyslexia, and if so, calculate a Bayesian positive predictive value. If not, the system calculates a Bayesian negative predictive value. The system then generates a report GUI including the Bayesian positive or negative predictive value, a probability of the user having dyslexia, and a recommendation, according to the probability of the user having dyslexia, representing an intensity of a treatment evaluation response.
Systems and methods of the present invention provide for one or more server computers communicatively coupled to a network and configured to: receive, from a GUI on a user device, user input including a determination of whether a prior probability of dyslexia exists for a user, a selection of a dyslexia screening test administered to the user and an indication of whether the test indicated a risk of dyslexia, and if so, calculate a Bayesian positive predictive value. If not, the system calculates a Bayesian negative predictive value. The system then generates a report GUI including the Bayesian positive or negative predictive value, a probability of the user having dyslexia, and a recommendation, according to the probability of the user having dyslexia, representing an intensity of a treatment evaluation response.
Systems and methods for secure content delivery are disclosed herein. The system can include a content driver communicatingly connected with a user device via a layered protocol model or via a User Datagram Protocol (UDP). The content driver can generate a signal directing the creation of a secured partition on a bootable media device connected to a user device, identify content for delivery, and generate pixel data for the content. The content driver can send the pixel data to the user device, wherein the user device is configured to store the pixel data in the secured partition of the bootable media device. The content driver can receive a plurality of response inputs from the user device, wherein the response inputs are generated by a software application running on the bootable media device, generate a response based on the received response inputs, and provide the generated response to an evaluation module.
G06F 21/53 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems during program execution, e.g. stack integrity, buffer overflow or preventing unwanted data erasure by executing in a restricted environment, e.g. sandbox or secure virtual machine
G06F 21/10 - Protecting distributed programs or content, e.g. vending or licensing of copyrighted material
Systems and methods of the present invention may be used to determine metrics and health scores for content that may correspond to an educational course or textbook, which may be in a digital format. The metrics and health scores may be determined at various hierarchical content levels, and may be used to quantitatively assess how well the corresponding content is performing based on responses submitted to assessment item parts of the content by responders. The metrics may include difficulty and discrimination metrics, which may be determined using maximum likelihood estimation methods based on a modified two parameter item response model. A content analytics interface corresponding to a given content element may be generated and displayed via a user device, and may include content health scores of subcontent within that content element. The subcontent may be ordered according to content health score.
Systems and methods of the present invention provide for: selecting a word pair and a category, concept, or sample response from a data store; performing a data extraction on a first knowledge base, including an article or content associated with a word in the word pair or a list of articles linking to the category, concept, or sample response; inserting words generated from the data extraction into a data store; defining a difficulty level for each of the words according to a crawl of difficulty data in a second knowledge base; and rendering a GUI displaying the words and the difficulty level for each of the words.
Systems and methods are provided by which information such as text may be extracted from a captured digital image, and displayed as an editable overlay over the captured digital image in a digital user interface. One or more boundaries defining a region or regions of the captured digital image from which information is extracted may be displayed over the captured digital image, and may be selectively added, edited, or deleted, resulting in corresponding information in the editable overlay being added, edited, or deleted. Additionally, information in the editable overlay may be added, edited, or deleted directly. The extracted information may correspond to responses to a homework assignment or test depicted in the captured digital image. The extracted information may be arranged in ordered steps, with the order of the steps being editable, and individual steps being removable, addable, or otherwise editable via interaction with the user interface.
G09B 7/02 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student
Methods and systems are disclosed for interactively developing an educational course and the materials for it using a backward design, or top-down, approach based on course objectives and course outcomes in one embodiment. Educators or other course creators are able to implement this design approach through an Integrated Design and Development Interface (IDDI). The IDDI guides course development by organizing course content in a relational database. The IDDI maps a plurality of course objectives to a plurality of course outcomes to create a course model. The IDDI uses the course model to generate and/or automatically user interfaces used by a course creator to input lower-level course information.
Methods, systems, and devices for dynamic response entry are disclosed herein. In some embodiments, a dynamic response entry system can include a user device that can be a proctor device or a testee device. The testee device can display a list to a testee for a predetermined time period. After the passing of the predetermined time period, the displaying of the list to the testee can be terminated. The testee can provide response to one or several questions, which responses can be input into the proctor device. The input responses can be evaluated and categorized and displayed according to the evaluation and categorization.
G09B 7/06 - Electrically-operated teaching apparatus or devices working with questions and answers of the multiple-choice answer type, i.e. where a given question is provided with a series of answers and a choice has to be made from the answers
G06F 16/25 - Integrating or interfacing systems involving database management systems
G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 3/04883 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures for inputting data by handwriting, e.g. gesture or text
84.
SYSTEMS AND METHODS FOR PREDICTIVE MODELLING OF DIGITAL ASSESSMENTS WITH MULTI-MODEL ADAPTIVE LEARNING ENGINE
Systems and methods are provided by which an adaptive learning engine may select a machine learning model service to determine a probability that a user will respond correctly to a given assessment item of a digital assessment on their first attempt. The adaptive learning engine may receive a request identifying the user, the assessment item, and request data. A model selector may generate a model reference corresponding to a model definition based on the request data. The feature data to be retrieved and/or calculated may be defined by the model definition. The feature data may be processed by a model service executing a machine learning model selected by the adaptive learning engine based on the model definition. Based on the probability output by the model, the adaptive learning engine may whether the user should be preemptively assigned credit for the assessment item.
G09B 7/02 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student
G09B 7/06 - Electrically-operated teaching apparatus or devices working with questions and answers of the multiple-choice answer type, i.e. where a given question is provided with a series of answers and a choice has to be made from the answers
G06K 9/62 - Methods or arrangements for recognition using electronic means
Systems and methods of the present invention provide for estimating latent ability of responders to a digital assessment in the form of ability scores and estimating item parameters an assessment item of the digital assessment including difficulty scores and discrimination scores. Maximum likelihood estimation may be performed based on an item response theory model to estimate the item parameters. Supervisory, extraction, and worker modules of a workflow manager module may initiate general purpose graphics processing unit instances and cause these instances to perform the maximum likelihood estimation calculations. The item response theory model may be a two parameter model that is modified to account for changes in difficulty caused by the use of hints.
Systems and methods are provided by which a machine learning model may be executed to determine the probability that a given user will respond correctly to a given assessment item of a digital assessment on their first attempt. The machine learning model may process feature data corresponding to the user and the assessment item in order to determine the probability. The feature data may be calculated periodically and/or in real time or near-real time according to a machine learning model definition based on assessment data corresponding to the user's activity and/or based on responses submitted by all users to the assessment item and/or to content related to the assessment item.
G09B 7/00 - Electrically-operated teaching apparatus or devices working with questions and answers
G09B 7/02 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student
G09B 7/06 - Electrically-operated teaching apparatus or devices working with questions and answers of the multiple-choice answer type, i.e. where a given question is provided with a series of answers and a choice has to be made from the answers
G06F 16/14 - Details of searching files based on file metadata
G06F 18/2321 - Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions
87.
Systems and methods for assessment item credit assignment based on predictive modelling
Systems and methods are provided by which an adaptive learning engine may be executed to determine the probability that a given user will respond correctly to a given assessment item of a digital assessment on their first attempt. The adaptive learning engine may apply one or more machine learning models to feature data corresponding to the user and the assessment item in order to determine the probability. The feature data may be calculated periodically and/or in real time or near-real time according to a machine learning model definition based on assessment data corresponding to the user's activity and/or based on responses submitted globally by users to the assessment item and/or to content related to the assessment item. Based on the correct first attempt probability, the adaptive learning engine may identify and recommend assessment items for which a user should be preemptively assigned credit.
G06F 16/14 - Details of searching files based on file metadata
G06K 9/62 - Methods or arrangements for recognition using electronic means
G09B 7/02 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student
G09B 7/06 - Electrically-operated teaching apparatus or devices working with questions and answers of the multiple-choice answer type, i.e. where a given question is provided with a series of answers and a choice has to be made from the answers
88.
Systems and methods for item response modelling of digital assessments
Systems and methods of the present invention provide for estimating latent ability of responders to a digital assessment in the form of ability scores and estimating item parameters an assessment item of the digital assessment including difficulty scores and discrimination scores. Maximum likelihood estimation may be performed based on an item response theory model to estimate the item parameters. Supervisory, extraction, and worker modules of a workflow manager module may initiate general purpose graphics processing unit instances and cause these instances to perform the maximum likelihood estimation calculations. The item response theory model may be a two parameter model that is modified to account for changes in difficulty caused by the use of hints.
G09B 7/04 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student characterised by modifying the teaching programme in response to a wrong answer, e.g. repeating the question, supplying a further explanation
G09B 7/077 - Electrically-operated teaching apparatus or devices working with questions and answers of the multiple-choice answer type, i.e. where a given question is provided with a series of answers and a choice has to be made from the answers providing for individual presentation of questions to a plurality of student stations different stations being capable of presenting different questions simultaneously
G06F 17/18 - Complex mathematical operations for evaluating statistical data
G06F 17/17 - Function evaluation by approximation methods, e.g. interpolation or extrapolation, smoothing or least mean square method
G06T 1/20 - Processor architecturesProcessor configuration, e.g. pipelining
Systems and methods of the present invention may be used to determine metrics and health scores for content that may correspond to an educational course or textbook, which may be in a digital format. The metrics and health scores may be determined at the assessment-item-part-level, assessment-item-level, section-level, chapter-level, and title-level, and may be used to quantitatively assess how well the corresponding content is performing based on responses submitted to assessment item parts of the content by one or more responders. The assessment-item-part-level metrics may include difficulty and discrimination values, scores, weights, and reliability values, which may be determined in whole or in part using maximum likelihood estimation methods based on a modified two parameter item response model.
An online feedback network provides feedback from contributors to a feedback recipient for a project. A request modifier may receive a default request from a data source and allow the feedback recipients to use the default request, modify the default request and/or allow the feedback recipient to create an initial request in requesting feedback for each feedback recipient's project from the contributors. The request modifier may also modify the default or initial request so that the request from the feedback recipient receives a desired volume, type, source or network of feedback. For instance the request modifier may increase the number of contributors receiving the request or simplify the type of requested feedback in order to increase the volume of feedback received by the feedback recipients based on previous requests for feedback and the volume of feedback received by the past requests. The submitted request may be stored for future use.
Systems and methods for automated data packet selection and delivery are disclosed herein. The system can include a memory containing a data packet database including data packets for delivery to a user; and a user profile database including information identifying at least one user. The system can include a user device and one or several servers. The one or several servers can: receive a request for delivery of a set of data packets to a user via the user device; identify potential data packets for delivery to the user via the user device; determine a probability of the user providing a desired response to each of the potential data packets; weight the data packets according to weighting data and the determined probability; select a set of data packets from the potential data packets; and provide the set of data packets to the user via the user device.
Systems and methods of the present invention provide for generating a first, second, and third series of interface objects comprising a first and second sequence respectively, displayed on a graphical user interface (GUI). At least one visual indicator display object is also displayed that requires a switch between the first and second series of user interface objects. A user navigates through the first and second series of interface objects, including the visual indicator display object(s), and a score for the user is calculated according to a user input matching, or failing to match, a correct response associated with a task data defining a function skill demonstrating a cognitive ability of the user.
G09B 7/04 - Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student characterised by modifying the teaching programme in response to a wrong answer, e.g. repeating the question, supplying a further explanation
G09B 19/00 - Teaching not covered by other main groups of this subclass
G09B 5/06 - Electrically-operated educational appliances with both visual and audible presentation of the material to be studied
A61B 5/00 - Measuring for diagnostic purposes Identification of persons
G06F 3/04883 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures for inputting data by handwriting, e.g. gesture or text
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
93.
Diagnostic analyzer for content receiver using wireless execution device
Techniques described herein relate to performing wireless diagnostic analyses including execution and evaluations of interactive content resources executed by execution devices on and/or for separate content receiver devices. A multi-phrase diagnostic session may proceed with an execution of an initial set of diagnostic modules on an execution device, during which interactive content is transmitted/received from a connected receiver device. The results of the diagnostic modules may be evaluated in real-time and transmitted to a diagnostic analyzer server to select additional diagnostic modules for execution during the diagnostic session. The diagnostic analyzer server may select the additional diagnostic modules based on based on response data received via the content execution device to the interactive content of the previously executed diagnostic modules, and/or data received from additional data sources related to the content receiver.
Systems and methods for automated content generation and delivery are provided herein. The system can include a memory that can include a content item library. The content library can include a hierarchical data structure having levels and a plurality of data packets, each of which data packets is linked with at least a portion of the hierarchical data structure. The system can include at least one server that can identify and deliver an item within a first content domain to a user device, evaluate a response to the delivered item, generate a scalar estimated skill level with a unidimensional evaluation engine, select and present a next item based on the estimated skill level, and upon completion of an assessment, generate a vector estimated skill level with a multidimensional evaluation engine.
Systems and methods of visually indicating on a user interface of an electronic reader the lengths, types of content, structure and current location of a user within a corpus of electronic content are presented. The corpus of electronic content may be converted into contiguous visual sections and contiguous thumbnails (of the visual sections). The user interface includes a content strip tray displaying a viewable portion of the thumbnails and a main viewing area displaying a viewable portion of the visual sections. An accent effect may be displayed over the viewable portion of the thumbnails that corresponds with the viewable portion of the visual sections currently displayed in the main viewing area to indicate a location of the user in the electronic content. Additionally, headers, location markers, assignments and notes may be displayed on the viewable portion of the thumbnails.
Systems and methods for automated content generation and delivery are provided herein. The system can include a memory that can include a content item library. The content library can include a hierarchical data structure having levels and a plurality of data packets, each of which data packets is linked with at least a portion of the hierarchical data structure. The system can include at least one server that can generate an assessment creation interface including a plurality of nested objects each representative of a portion of the hierarchical data structure, receive a selection of a first object and a second object from the plurality of nested objects of the assessment creation interface, generate a weighting value for each of the selected objects, and generate an assessment from data packets associated with the selected objects according to the weighting value.
H04L 12/24 - Arrangements for maintenance or administration
H04L 29/08 - Transmission control procedure, e.g. data link level control procedure
G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
97.
VISUALLY INDICATING ON A USER INTERFACE LENGTHS, TYPES OF CONTENT, STRUCTURE AND CURRENT USER LOCATION WITHIN A CORPUS OF ELECTRONIC CONTENT
Systems and methods of visually indicating on a user interface of an electronic reader the lengths, types of content, structure and current location of a user within a corpus of electronic content are presented. The corpus of electronic content may be converted into contiguous visual sections and contiguous thumbnails (of the visual sections). The user interface includes a content strip tray displaying a viewable portion of the thumbnails and a main viewing area displaying a viewable portion of the visual sections. An accent effect may be displayed over the viewable portion of the thumbnails that corresponds with the viewable portion of the visual sections currently displayed in the main viewing area to indicate a location of the user in the electronic content. Additionally, headers, location markers, assignments and notes may be displayed on the viewable portion of the thumbnails.
Systems and methods of visually indicating on a user interface of an electronic reader the lengths, types of content, structure and current location of a user within a corpus of electronic content are presented. The corpus of electronic content may be converted into contiguous visual sections and contiguous thumbnails (of the visual sections). The user interface includes a content strip tray displaying a viewable portion of the thumbnails and a main viewing area displaying a viewable portion of the visual sections. An accent effect may be displayed over the viewable portion of the thumbnails that corresponds with the viewable portion of the visual sections currently displayed in the main viewing area to indicate a location of the user in the electronic content. Additionally, headers, location markers, assignments and notes may be displayed on the viewable portion of the thumbnails.
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G06F 3/0483 - Interaction with page-structured environments, e.g. book metaphor
99.
Performance support integration with E-learning system
Techniques are used to improve an e-learning or on-line learning experience for individual users. In an e-learning system, users are at client computers of a distributed network. The users are instructed via a server, connected to the clients through the network. The server has study plans of course units for each user. Study plans are customized for each user. Further, each client computer has desktop support tools, such as a toolbar, which can provide convenience feature for the user or be used to monitor the user's day-to-day activities at the computer. Based on the user's use of the desktop support tools, the study plans at the server may be modified to provide further customization of the e-learning experience for the user.
Systems and methods of the present invention provide for providing access to an electronic learning activity comprising a challenge instruction and a GUI control configured to receive a first user input responding to the challenge instruction. If the first user input does not match a first correct response, the system identifies a misconception for the challenge instruction and first user input. The system then dynamically generates a group of users with the same user input, and a customized strategy for the group, including additional challenge instructions which, if responses match a second correct response, indicate the misconception is corrected.
G09B 7/08 - Electrically-operated teaching apparatus or devices working with questions and answers of the multiple-choice answer type, i.e. where a given question is provided with a series of answers and a choice has to be made from the answers characterised by modifying the teaching programme in response to a wrong answer, e.g. repeating the question, supplying further information
