Abstract: Computer-readable storage media, computing devices, and methods associated with an adaptive learning environment associated with an adaptive learning environment are disclosed. In embodiments, a computing device may include an instruction module and an adaptation module operatively coupled with the instruction module. The instruction module may selectively provide instructional content of one of a plurality of instructional content types to a user of the computing device via one or more output devices coupled with the computing device. The adaptation module may determine, in real-time, an engagement level associated with the user of the computing device and may cooperate with the instruction module to dynamically adapt the instructional content provided to the user based at least in part on the engagement level determined. Other embodiments may be described and/or claimed.

Abstract: Methods, apparatus, systems, and articles of manufacture for real-time voice type detection in audio data are disclosed. An example non-transitory computer-readable medium disclosed herein includes instructions, which when executed, cause one or more processors to at least identify a first vocal effort of a first audio segment of first audio data and a second vocal effort of a second audio segment of the first audio data, train a neural network including training data, the training data including the first vocal effort, the first audio segment, the second audio segment, and the second vocal effort, and deploy the neural network, the neural network to distinguish between the first vocal effort and the second vocal effort.

Abstract: Various systems and methods for engagement dissemination. A face detector detects a face in video data. A context filterer determines a student is on-platform and a section type. An appearance monitor selects an emotional and a behavioral classifiers. Emotional and behavioral components are classified based on the detected face. A context-performance monitor selects an emotional and a behavioral classifiers specific to the section type, Emotional and behavioral components are classified based on the log data. A fuser combines the emotional components into an emotional state of the student based on confidence values of the emotional components. The fuser combines the behavioral components a behavioral state of the student based on confidence values of the behavioral components. The user determine an engagement level of the student based on the emotional state and the behavioral state of the student.

Abstract: Computer-readable storage media, computing devices, and methods associated with an adaptive learning environment associated with an adaptive learning environment are disclosed. In embodiments, a computing device may include an instruction module and an adaptation module operatively coupled with the instruction module. The instruction module may selectively provide instructional content of one of a plurality of instructional content types to a user of the computing device via one or more output devices coupled with the computing device. The adaptation module may determine, in real-time, an engagement level associated with the user of the computing device and may cooperate with the instruction module to dynamically adapt the instructional content provided to the user based at least in part on the engagement level determined. Other embodiments may be described and/or claimed.

Abstract: Computer-readable storage media, computing devices, and methods associated with an adaptive learning environment associated with an adaptive learning environment are disclosed. In embodiments, a computing device may include an instruction module and an adaptation module operatively coupled with the instruction module. The instruction module may selectively provide instructional content of one of a plurality of instructional content types to a user of the computing device via one or more output devices coupled with the computing device. The adaptation module may determine, in real-time, an engagement level associated with the user of the computing device and may cooperate with the instruction module to dynamically adapt the instructional content provided to the user based at least in part on the engagement level determined. Other embodiments may be described and/or claimed.

Abstract: Various systems and methods for engagement dissemination. A face detector detects a face in video data. A context filterer determines a student is on-platform and a section type. An appearance monitor selects an emotional and a behavioral classifiers. Emotional and behavioral components are classified based on the detected face. A context-performance monitor selects an emotional and a behavioral classifiers specific to the section type, Emotional and behavioral components are classified based on the log data. A fuser combines the emotional components into an emotional state of the student based on confidence values of the emotional components. The fuser combines the behavioral components a behavioral state of the student based on confidence values of the behavioral components. The user determine an engagement level of the student based on the emotional state and the behavioral state of the student.

Abstract: Apparatus, systems, and/or methods may provide a mental state determination. For example, a data collector may collect image data for a side of a face of a user from an image capture device on the user (e.g., a wearable device). The image data may include two or more perspectives of a feature on the side of the face of the user. In addition, a state determiner may determine a mental state of the user based on the image data. In one example, fields of view may be combined to determine a total region and/or a total overlap region. Changing the position that one or more image capture devices point may modulate the total region and/or the total overlap region. In addition, one or more sensors may be utilized to further improve mental data determinations.

Abstract: Computer-readable storage media, computing devices, and methods associated with an adaptive learning environment associated with an adaptive learning environment are disclosed. In embodiments, a computing device may include an instruction module and an adaptation module operatively coupled with the instruction module. The instruction module may selectively provide instructional content of one of a plurality of instructional content types to a user of the computing device via one or more output devices coupled with the computing device. The adaptation module may determine, in real-time, an engagement level associated with the user of the computing device and may cooperate with the instruction module to dynamically adapt the instructional content provided to the user based at least in part on the engagement level determined. Other embodiments may be described and/or claimed.

Abstract: Computer-readable storage media, computing devices, and methods associated with an adaptive learning environment associated with an adaptive learning environment are disclosed. In embodiments, a computing device may include an instruction module and an adaptation module operatively coupled with the instruction module. The instruction module may selectively provide instructional content of one of a plurality of instructional content types to a user of the computing device via one or more output devices coupled with the computing device. The adaptation module may determine, in real-time, an engagement level associated with the user of the computing device and may cooperate with the instruction module to dynamically adapt the instructional content provided to the user based at least in part on the engagement level determined. Other embodiments may be described and/or claimed.

Abstract: Apparatus, systems, and/or methods may provide a mental state determination. For example, a data collector may collect image data for a side of a face of a user from an image capture device on the user (e.g., a wearable device). The image data may include two or more perspectives of a feature on the side of the face of the user. In addition, a state determiner may determine a mental state of the user based on the image data. In one example, fields of view may be combined to determine a total region and/or a total overlap region. Changing the position that one or more image capture devices point may modulate the total region and/or the total overlap region. In addition, one or more sensors may be utilized to further improve mental data determinations.

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: Computer-readable storage media, computing devices, and methods associated with an adaptive learning environment associated with an adaptive learning environment are disclosed. In embodiments, a computing device may include an instruction module and an adaptation module operatively coupled with the instruction module. The instruction module may selectively provide instructional content of one of a plurality of instructional content types to a user of the computing device via one or more output devices coupled with the computing device. The adaptation module may determine, in real-time, an engagement level associated with the user of the computing device and may cooperate with the instruction module to dynamically adapt the instructional content provided to the user based at least in part on the engagement level determined. Other embodiments may be described and/or claimed.