Titlebook: Artificial Intelligence in Education; 18th International C Elisabeth André,Ryan Baker,Benedict du Boulay Conference proceedings 2017 Spring

mediocrity

Improving Sensor-Free Affect Detection Using Deep Learning, such as recurrent neural networks (RNNs), have been applied to a range of other domains including pattern recognition and natural language processing with success, but have only recently been attempted in educational contexts. In this work, we construct new “deep” sensor-free affect detectors and

無(wú)所不知

contrast-medium

concentrate

FADE

ethereal

Automatic Extraction of AST Patterns for Debugging Student Programsy classify over 85% of programs based only on their structural features. For approximately 73% of incorrect submissions, we are able to generate hints that were implemented by the student in some subsequent submission.

motivate

Inducing Stealth Assessors from Game Interaction Dataudent game-based learning interaction data outperform comparable models that required labor-intensive hand-engineering of input features. The findings suggest that the LSTM-based approach holds significant promise for evidence modeling in stealth assessment.

疲勞

競(jìng)選運(yùn)動(dòng)

The Federal Government and the Familycal structure on which textual complexity indices were subsequently applied. The stepwise regression model explained 30.5% of the variance in students’ scores, while a Discriminant Function Analysis predicted with substantial accuracy (75.1%) whether they are high or low performance students.

arthroplasty