Titlebook: Intelligent Tutoring Systems; 12th International C Stefan Trausan-Matu,Kristy Elizabeth Boyer,Kitty P Conference proceedings 2014 Springer

伙伴

Automated Physiological-Based Detection of Mind Wandering during Learningbtained a kappa, a measurement of accuracy corrected for random guessing, of .22, signaling feasibility of detecting MW in a student-independent manner. Though modest, we consider this result to be an important step towards fully-automated unobtrusive detection of mind wandering during learning.

Soliloquy

Identifying Learning Conditions that Minimize Mind Wandering by Modeling Individual Attributesue and difficulty separately (kappas of .16 and .24; accuracy of 59% and 64% respectively). Results are discussed in terms of creating a learning system that prospectively places learners in the optimal condition to increase learning by minimizing MW.

很是迷惑

Glutinous

神圣在玷污

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/i/image/470154.jpg

Generalize

Herbivorous

abysmal

Intelligent Tutoring Systems978-3-319-07221-0Series ISSN 0302-9743 Series E-ISSN 1611-3349

Gesture

sEMG signal analysis. Eleven university students participated the experiment. the data of subjective feeling of comfort and the sEMG of the related muscle of shoulder joint (forward extension, rear protraction, adduction, abduction, flex level, stretch level), elbow joint (flexion), wrist joint (pa

征服