An Annotations Approach to Peer Tutoring

In this paper we detail a preliminary model for reasoning about annotating learning objects and intelligently showing annotations to users who will benefit from them. Student interactions with these annotations are recorded and this data is used to reason about the best combination of annotations and learning objects to show to a specific student. Motivating examples and algorithms for reasoning about annotations are presented. The proposed approach leverages the votes for and against an annotation by previous students, considering whether those students are similar or dissimilar to the current student, in order to determine the value of showing this annotation to the student.

• Type: Conference
• Year: 2010
• Where: EDM
• Authors: John Champaign, Robin Cohen
• Keywords: Annotation, Data Mining, EDM 2010, Learning Objects, Student Interactions