An educational system may include a contextualizer that accesses and processes content items and build a knowledge base including educational content and relationships between content items. The system may include a user assessor unit that determines user assessment variables based on user responses to previous educational content items and generate a user model based on the user assessment variables. The system may include a recommender that navigates the knowledge base and generates recommendations of new educational content based on the user model. The recommendation can assess the user's proficiency on a given concept based on the user model and maximize the user's probability of success around the concept of which the user shows proficiency, or improve the user's proficiency around the concept the user shows weakness. In some examples, the system may acquire an expert's knowledge about certain concepts to refine the user model, increasing the accuracy of the recommender.

An educational system may include a contextualizer that accesses and processes content items and build a knowledge base including educational content and relationships between content items. The system may include a user assessor unit that determines user assessment variables based on user responses to previous educational content items and generate a user model based on the user assessment variables. The system may include a recommender that navigates the knowledge base and generates recommendations of new educational content based on the user model. The recommendation can assess the user's proficiency on a given concept based on the user model and maximize the user's probability of success around the concept of which the user shows proficiency, or improve the user's proficiency around the concept the user shows weakness. In some examples, the system may acquire an expert's knowledge about certain concepts to refine the user model, increasing the accuracy of the recommender.

A method for improving learning comprehension regarding a lesson includes issuing a first learning illustrative model to a set of learner computing entities. The method further includes obtaining a first comprehension evaluation associated with a first learner computing entity for the first learning illustrative model. The method further includes obtaining a second comprehension evaluation associated with a second learner computing entity for the first learning illustrative model. The method further includes modifying the fundamental illustrative model to illustrate a second set of learning assets of a second learning object based on at least one of the first and second comprehension evaluations to produce a second learning illustrative model. The method further includes sending the second learning illustrative model to the set of learner computing entities.

A method for generating a virtual reality environment includes detecting an illustrative asset that is common to a first set of assets and a second sets of assets. The method further includes rendering a three-dimensional (3-D) model of the illustrative asset and a 3-D model of the first set of assets using an illustration approach to produce 3-D frames of a first descriptive asset. The method further includes obtaining an evaluation of the first descriptive asset based on a first assessment response associated with a portrayal of the first descriptive asset. The method further includes modifying the illustration approach based on the evaluation to produce an updated illustration approach. The method further includes rendering the 3-D model of the illustrative asset and a 3-D model of the second set of assets using the updated illustration approach to produce 3-D frames of a second descriptive asset.

An adaptive feedback timing system and method includes receiving, by a performance observation system, monitoring data associated with electronically monitoring a lesson by a variable feedback teaching device. Adaptive feedback timing also includes receiving, by the performance observation system, error detection data associated with the variable feedback teaching device automatically detecting an error made by a student during the lesson. After receiving the error detection data, a feedback pattern is automatically selected based on a performance history criterion. Feedback data is then communicated to the variable feedback teaching device for presentation to the student according to the automatically selected feedback pattern.

A context-aware adaptive data processing application is described. One or more computing servers establish connections with multiple user terminals to provide an application to the user terminals. The provided application is executable at the user terminals via web browser or a dedication application installed at a user terminal, for example. The provided application is context-aware to dynamically adapt to a user's changing circumstances.

A context-aware adaptive data processing application is described. One or more computing servers establish connections with multiple user terminals to provide an application to the user terminals. The provided application is executable at the user terminals via web browser or a dedication application installed at a user terminal, for example. The provided application is context-aware to dynamically adapt to a user's changing circumstances.

Methods and systems provide an adaptive method of language learning using automatic speech recognition that allows a user to learn a new language using only their voice—and without using their hands or eyes. The system may be implemented in an application for a smartphone. Each lesson comprises a series of questions that adapt to the user's knowledge. The questions ask for the translation of a word or phrase by playing an audio prompt in the origin language, recording the user speaking the translation in the target language, indicating whether the utterance was correct or incorrect, and providing feedback related to the user's utterance. Each user response is evaluated in real time, and the application provides individualized feedback to the user based on their response. Subsequent questions in the lesson and future lessons are dynamically ordered to adapt to the user's knowledge.

Methods and systems provide an adaptive method of language learning using automatic speech recognition that allows a user to learn a new language using only their voice—and without using their hands or eyes. The system may be implemented in an application for a smartphone. Each lesson comprises a series of questions that adapt to the user's knowledge. The questions ask for the translation of a word or phrase by playing an audio prompt in the origin language, recording the user speaking the translation in the target language, indicating whether the utterance was correct or incorrect, and providing feedback related to the user's utterance. Each user response is evaluated in real time, and the application provides individualized feedback to the user based on their response. Subsequent questions in the lesson and future lessons are dynamically ordered to adapt to the user's knowledge.

An interactive and automated training system, including a training portal having a training database, a training material creating module including a recorder and a dialogue identifier, a training and practicing module for training and practicing interactively with a trainee user, and a testing module for providing test case scenarios and grading a performance level of the trainee user. The recorder records real time interaction between an employee and a customer. The dialogue identifier differentiates the real time interaction into an employee dialogue and a customer dialogue, and provides indexing of subparts of the real time interaction. The training material creating module stores the real time interaction into the training database along with indexing data of the subparts of the real time interaction. The training material creating module categorizes a plurality of real time interactions stored in the training database into a plurality of training scenarios.