In this work, we present a novel intelligent environment for learning the core concepts of Computational Thinking. This learning environment can recognize learning-centered emotions presented by the students, performing different interventions automatically, depending on the students’ affective states. Tests were conducted to compare learning gain, and additionally, an acceptance technology model was applied to validate the students’ acceptance of this learning tool. During the cognitive evaluation, a control group had an average increase in score of MD = .636 while an experimental group reported an increase of MD = .772, which indicate a greater gain in knowledge for the experimental group. During the experiment, the system inferred a total of 2,139 emotions from the students. 56.66% of these emotions were in the categories of committed and interested, 42.22% belonged to excited and concentrated, and only 1.22% of the values were in the category of bored.