Self Versus Teacher Judgments of Learner Emotions During a Tutoring Session with AutoTutor

The relationship between emotions and learning was investigated by tracking the affective states that college students experienced while interacting with AutoTutor, an intelligent tutoring system with conversational dialogue. An emotionally responsive tutor would presumably facilitate learning, but this would only occur if learner emotions can be accurately identified. After a learning session with AutoTutor, the affective states of the learner were classified by the learner and two accomplished teachers. The classification of the teachers was not very reliable and did not match the learners self reports. This result suggests that accomplished teachers may be limited in detecting the affective states of learners. This paper discusses the implications of our findings for theories of expert tutoring and for alternate methodologies for establishing convergent validity of affect measurement.