A speech-based empathy training system - initial design insights

Empathy is an essential component of human communication since it increases our understanding and perception of others. However, studies show that students\u27 empathy skills have declined rapidly in the last decades. Against this background, practitioner reports predict that the importance of empathy will increase as a skill for successful agile teamwork in the future. Therefore, researchers have designed information systems to train empathy abilities of learners in different domains. Nevertheless, research on automated speech-based training is rather scarce. Hence, we aim to investigate how to design a speech-based empathy training system that helps students react emotionally adequately in communication. This research in progress paper presents five initial requirements that guide future research and development of a speech-based empathy training system intended to support students\u27 self-regulated learning. With this, we hope to provide guidance for the design and embedding of speech-based empathy training systems at scale

Human-machine communication for educational systems design

This book contains the papers presented at the NATO Advanced Study Institute (ASI) on the Basics of man-machine communication for the design of educational systems, held August 16-26, 1993, in Eindhoven, The Netherland

Aerospace Medicine and Biology. A continuing bibliography with indexes

This bibliography lists 244 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1981. Aerospace medicine and aerobiology topics are included. Listings for physiological factors, astronaut performance, control theory, artificial intelligence, and cybernetics are included

Augmentative communication device design, implementation and evaluation

The ultimate aim of this thesis was to design and implement an advanced software based Augmentative Communication Device (ACD) , or Voice Output Communication Aid NOCA), for non-vocal Learning Disabled individuals by applying current psychological models, theories, and experimental techniques. By taking account of potential user's cognitive and linguistic abilities a symbol based device (Easy Speaker) was produced which outputs naturalistic digitised human speech and sound and makes use of a photorealistic symbol set. In order to increase the size of the available symbol set a hypermedia style dynamic screen approach was employed. The relevance of the hypermedia metaphor in relation to models of knowledge representation and language processing was explored.Laboratory based studies suggested that potential user's could learn to productively operate the software, became faster and more efficient over time when performing set conversational tasks. Studies with unimpaired individuals supported the notion that digitised speech was less cognitively demanding to decode, or listen to.With highly portable, touch based, PC compatible systems beginning to appear it is hoped that the otherwise silent will be able to use the software as their primary means of communication with the speaking world. Extensive field trials over a six month period with a prototype device and in collaboration with user's caregivers strongly suggested this might be the case.Off-device improvements were also noted suggesting that Easy Speaker, or similar software has the potential to be used as a communication training tool. Such training would be likely 10 improve overall communicative effectiveness.To conclude, a model for successful ACD development was proposed

Detecting and Modelling Stress Levels in E-Learning Environment Users

A modern Intelligent Tutoring System (ITS) should be sentient of a learner's cognitive and affective states, as a learner’s performance could be affected by motivational and emotional factors. It is important to design a method that supports low-cost, task-independent and unobtrusive sensing of a learner’s cognitive and affective states, to improve a learner's experience in e-learning, as well as to enable personalized learning. Although tremendous related affective computing research were done in this area, there is a lack of empirical research that can automatically measure a learner's stress using objective methods. This research is set to examine how an objective stress measurement model can be developed, to compute a learner’s cognitive and emotional stress automatically using mouse and keystroke dynamics. To ensure the measurement is not affected even if the user switches between tasks, three preliminary research experiments were carried out based on three common tasks during e-learning − search, assessment and typing. A stress measurement model was then built using the datasets collected from the experiments. Three stress classifiers were tested, namely certainty factors, feedforward back-propagation neural network and adaptive neuro-fuzzy inference system. The best classifier was then integrated into the ITS stress inference engine, which is designed to decide necessary adaptation, and to provide analytical information of learners' performances, which include stress levels and learners’ behaviours when answering questions