Abstract: Methods, systems and computer program products for automated learning are provided herein. A computer-implemented method includes authenticating a plurality of users for an automated learning session, wherein the plurality of users correspond to at least one device, and providing the automated learning session for the plurality of users. Providing the automated learning session comprises analyzing a plurality of learning models corresponding to one or more of the plurality of users, determining, based on the analysis, one or more activities to be performed by the plurality of users during the automated learning session, and executing the one or more activities on at least one device.

Abstract: A computer-implemented method for a socially connectable agent. A non-limiting example of the computer-implemented method includes receiving, by a processor, input events. The method includes evaluating and enacting rules, by the processor, based on the received input events, where the rule include stochastic elements and temporal operators. The method pushes, by the processor, action events that result from the evaluation and enactment of the rules, and initiates, by the processor, action events.

Abstract: An embodiment of the invention may include a method, computer program product and computer system for non-linear video navigation. The method, computer program product and computer system may include a computing device that collects source content and source content metadata from a content device. The computing device may extract the metadata from the source content and store the source content and the metadata on a server. The computing device may receive user profile data from a user device. The computing device may map the semantic data of the source content, the metadata, and the user profile data to a knowledge graph. The computing device may create navigational panels for navigating the source content based on the knowledge graph, the navigational panels enabling non-linear navigation of the source content by a user. The computing device may provide the navigational panels to the user device.

Abstract: Methods, systems, and computer program products for content marshaling using biometric data are provided herein. A computer-implemented method includes estimating a cognitive state of a user based at least in part on analyzing one or more sets of biometric data pertaining to the user; dynamically compiling multi-modal content for the user based at least in part on (i) the estimated cognitive state of the user, (ii) one or more user parameters, and (iii) content availability information; and outputting the compiled content to the user via one or more devices.

Abstract: Providing targeted, evidence-based recommendations to improve digital content quality, in one aspect, may include partitioning digital content into a sequence of logical content modules. Quality scores for the logical content modules along a plurality of quality dimensions may be determined. User interactions with the digital content on a user interface are monitored. Raw events generated from user interaction in accessing the digital content are captured. Raw event patterns for the logical content modules are detected. The raw event patterns of user interaction are transformed into a set of dynamic states representing potential user experience and performance. The set of dynamic states are associated with a respective logical content module. The quality dimensions of the logical content modules and associated quality scores are correlated with the dynamic states.

Abstract: Methods, systems, and computer program products for cognitive content mapping and collating are provided herein. A computer-implemented method includes identifying resources relevant to an existing course; partitioning, based on pre-determined partitioning parameters, (i) the existing course into multiple portions and (ii) the resources into multiple portions; detecting content coverage gaps in the existing course by semantically comparing (i) the multiple portions of the existing course with (ii) the multiple portions of the resources; retrieving, based on the detected content coverage gaps, at least one of the multiple portions of the resources; and generating an updated version of the existing course by incorporating the at least one retrieved portion of the resources into the existing course.

Abstract: One embodiment provides a method, including: receiving a plurality of transcripts, each transcript corresponding to an interaction between a student and a tutoring agent; identifying conversational patterns within the plurality of transcripts, the identified conversational patterns indicating a level of understanding regarding the interaction between the tutoring agent and the student, wherein the identifying comprises (i) identifying an exchange between the tutoring agent and the student, the exchange comprising a conversational turn by each of the tutoring agent and the student and (ii) classifying each of the conversational turns into a response type; determining, based upon the identified conversational patterns, a possible improvement to the tutoring agent, wherein the possible improvement is determined based upon the classified response types of each of (i) the tutoring agent and (ii) the student; and notifying a developer of the tutoring agent of the identified possible improvement.

Abstract: Methods and arrangements for determining at least one employment trait of an individual from online activity. Collecting a plurality of employment task data points from a plurality of online sources, wherein each employment task comprises a data set indicative of a path taken by at least one individual from a starting point to an ending point, wherein the starting point and ending point are defined on the basis of common parameters. The collected plurality of employment task data points are assessed, to determine an employment trend of the individual and creating at least one profile of the individual based on the determined employment trend. At least one profile is stored at a data storage location. Other variants and embodiments are broadly contemplated herein.

Abstract: Methods, systems and computer program products for automated learning are provided herein. A computer-implemented method includes authenticating a plurality of users for an automated learning session, wherein the plurality of users correspond to at least one device, and providing the automated learning session for the plurality of users. Providing the automated learning session comprises analyzing a plurality of learning models corresponding to one or more of the plurality of users, determining, based on the analysis, one or more activities to be performed by the plurality of users during the automated learning session, and executing the one or more activities on at least one device.

Abstract: Intelligent management of user interface and device sensed events is provided. Discrete events generated through interactions between a user and a machine are monitored, the interaction performed via a user interface associated with an application running on the machine, the discrete events stored by sessions in a storage device local to the machine as event logs. Network connection pattern of the machine with a server device is determined. Storage constraints of the storage device are determined based on the monitoring and the network connection pattern. The event logs are compacted by progressively summarizing the discrete events on dynamically adjusted segments of the sessions. The compacted event logs are transmitted to the server device responsive to determining that a network connection between the machine and the server device is available.

Abstract: Methods, systems, and computer program products for content marshaling using biometric data are provided herein. A computer-implemented method includes estimating a cognitive state of a user based at least in part on analyzing one or more sets of biometric data pertaining to the user; dynamically compiling multi-modal content for the user based at least in part on (i) the estimated cognitive state of the user, (ii) one or more user parameters, and (iii) content availability information; and outputting the compiled content to the user via one or more devices.

Abstract: Providing targeted, evidence-based recommendations to improve digital content quality, in one aspect, may include partitioning digital content into a sequence of logical content modules. Quality scores for the logical content modules along a plurality of quality dimensions may be determined. User interactions with the digital content on a user interface are monitored. Raw events generated from user interaction in accessing the digital content are captured. Raw event patterns for the logical content modules are detected. The raw event patterns of user interaction are transformed into a set of dynamic states representing potential user experience and performance. The set of dynamic states are associated with a respective logical content module. The quality dimensions of the logical content modules and associated quality scores are correlated with the dynamic states.

Abstract: A computer-implemented method for a socially connectable agent. A non-limiting example of the computer-implemented method includes receiving, by a processor, input events. The method includes evaluating and enacting rules, by the processor, based on the received input events, where the rule include stochastic elements and temporal operators. The method pushes, by the processor, action events that result from the evaluation and enactment of the rules, and initiates, by the processor, action events.

Abstract: Providing targeted, evidence-based recommendations to improve digital content quality, in one aspect, may include partitioning digital content into a sequence of logical content modules. Quality scores for the logical content modules along a plurality of quality dimensions may be determined. User interactions with the digital content on a user interface are monitored. Raw events generated from user interaction in accessing the digital content are captured. Raw event patterns for the logical content modules are detected. The raw event patterns of user interaction are transformed into a set of dynamic states representing potential user experience and performance. The set of dynamic states are associated with a respective logical content module. The quality dimensions of the logical content modules and associated quality scores are correlated with the dynamic states.

Abstract: Methods, systems, and computer program products for recommending a set of learning activities are provided herein.

Abstract: One embodiment provides a method, including: receiving a plurality of transcripts, each transcript corresponding to an interaction between a student and a tutoring agent; identifying conversational patterns within the plurality of transcripts, the identified conversational patterns indicating a level of understanding regarding the interaction between the tutoring agent and the student, wherein the identifying comprises (i) identifying an exchange between the tutoring agent and the student, the exchange comprising a conversational turn by each of the tutoring agent and the student and (ii) classifying each of the conversational turns into a response type; determining, based upon the identified conversational patterns, a possible improvement to the tutoring agent, wherein the possible improvement is determined based upon the classified response types of each of (i) the tutoring agent and (ii) the student; and notifying a developer of the tutoring agent of the identified possible improvement.

Abstract: Methods, systems, and computer program products for cognitive content mapping and collating are provided herein. A computer-implemented method includes identifying resources relevant to an existing course; partitioning, based on pre-determined partitioning parameters, (i) the existing course into multiple portions and (ii) the resources into multiple portions; detecting content coverage gaps in the existing course by semantically comparing (i) the multiple portions of the existing course with (ii) the multiple portions of the resources; retrieving, based on the detected content coverage gaps, at least one of the multiple portions of the resources; and generating an updated version of the existing course by incorporating the at least one retrieved portion of the resources into the existing course.

Abstract: An embodiment of the invention may include a method, computer program product and computer system for non-linear video navigation. The method, computer program product and computer system may include a computing device that collects source content and source content metadata from a content device. The computing device may extract the metadata from the source content and store the source content and the metadata on a server. The computing device may receive user profile data from a user device. The computing device may map the semantic data of the source content, the metadata, and the user profile data to a knowledge graph. The computing device may create navigational panels for navigating the source content based on the knowledge graph, the navigational panels enabling non-linear navigation of the source content by a user. The computing device may provide the navigational panels to the user device.

Abstract: Systems and methods are provided for monitoring and improving teacher effectiveness. The systems and methods scrutinize various aspects of teacher performance, formulate appropriate recommendations for improving such performance, and provide digital interlinkages among teachers in order to effectively distribute content and improve teacher efficiency.

Abstract: A method to provide automatic curriculum design includes building a model of benefit of each of a plurality of curriculum models under uncertainty as a function of an expected benefit of each of the curriculum models, building a model of risk of each of the curriculum models under uncertainty as a function of the expected benefit of each of the curriculum models, calculating risk of each of the plurality of curriculum models with the models of risk, calculating benefit of each of the plurality of curriculum models with the models of benefit; and finding a curriculum model among the plurality of curriculum models using the benefit and the risk.