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Download full textPaquette, Luc; Rowe, Jonathan; Baker, Ryan; Mott, Bradford; Lester, James; DeFalco, Jeanine; Brawner, Keith; Sottilare, Robert; Georgoulas, Vasiliki – International Educational Data Mining Society, 2016
Computational models that automatically detect learners' affective states are powerful tools for investigating the interplay of affect and learning. Over the past decade, affect detectors--which recognize learners' affective states at run-time using behavior logs and sensor data--have advanced substantially across a range of K-12 and postsecondary…
Descriptors: Models, Affective Behavior, Intelligent Tutoring Systems, Games
