Multiagent Architecture for Errors Management in Content Organized in Learning Objects
Abstract: The following paper describes the teaching-learning strategies which are related to different types of errors. Each type of error is managed by a determined agent. Said agents represent microworlds of expertise in certain instructional objectives. The multiagent architecture of an Intelligent Learning System (ILS) includes reactive agents which represent the expertise of each of the necessary sub-skills in learning the structured programming. The ILS is based upon artificial intelligence techniques for implementing the teaching-learning process The case study includes situations which are related to errors in order to link them to learning styles, knowledge domain and affective-motivational state. These assessments must determine: aspects to be explained, level of detail and timing, as well as when to interrupt the student and which information shall be provided during the interaction.