Abstract: Embodiments herein relate to generating a personalized model using a machine learning process, identifying a learning engagement state of a learner based at least in part on the personalized model, and tailoring computerized provision of an educational program to the learner based on the learning engagement state. An apparatus to provide a computer-aided educational program may include one or more processors operating modules that may receive indications of interactions of a learner and indications of physical responses of the learner, generate a personalized model using a machine learning process based at least in part on the interactions of the learner and the indications of physical responses of the learner during a calibration time period, and identify a current learning state of the learner based at least in part on the personalized model during a usage time period. Other embodiments may be described and/or claimed.

Abstract: Embodiments herein relate to identifying a learning engagement state of a learner. A computing platform with one or more processors running modules may receive indications of interactions of a learner with an educational program as well as indications of physical responses of the learner collected substantially simultaneously as the learner interacts with the educational program. A current learning engagement state of the learner may be identified based at least in part on the received indications by using an artificial neural network associated that is calibrated to the learner. The artificial neural network may be trained and updated in part by human observation and learner self-reporting of the learner's current learning engagement state.

Abstract: Systems and methods are disclosed for determining an affective state of a user. A user behavior characteristic is detected in response to content provided to the user. Content metadata indicates a context of the content provided to the user and a probability of the user experiencing at least one expected emotion in response to an interaction with the content. Based on the context and the at least one expected emotion indicated in the content metadata, one or more rules are applied to map the detected user behavior characteristic to an affective state of the user.

Abstract: A method for receiving messages containing data conveyed over a network, using a network adapter coupled to a computing device having a system memory associated therewith. At least one queue of descriptors is generated in the system memory, each such descriptor indicating a disposition of the data contained in the messages to be received over the network. At least one of the descriptors is prefetched from the at least one queue in the system memory to a cache memory in the network adapter. When one of the messages is received at the network adapter, the adapter processes the at least one of the received messages so as to cause the data contained therein to be distributed in accordance with the at least one prefetched descriptor in the cache memory.

Abstract: A method for receiving messages containing data conveyed over a network, using a network adapter coupled to a computing device having a system memory associated therewith. At least one queue of descriptors is generated in the system memory, each such descriptor indicating a disposition of the data contained in the messages to be received over the network. At least one of the descriptors is prefetched from the at least one queue in the system memory to a cache memory in the network adapter. When one of the messages is received at the network adapter, the adapter processes the at least one of the received messages so as to cause the data contained therein to be distributed in accordance with the at least one prefetched descriptor in the cache memory.