{"type":"ScholarlyArticle","title":"Evaluating a Decision-Theoretic Approach to Tailored Example Selection","authors":[{"name":"Kasia Muldner","slug":"kasia-muldner","given":"Kasia","family":"Muldner","affiliation":""},{"name":"Cristina Conati","slug":"cristina-conati","given":"Cristina","family":"Conati","affiliation":""}],"abstract":"We present the formal evaluation of a framework that helps students learn from analogical problem solving, i.e., from problem-solving activities that involve worked-out examples. The framework incorporates an innovative example-selection mechanism, which tailors the choice of example to a given student so as to trigger studying behaviors that are known to foster learning. This involves a two-phase process based on 1) a probabilistic user model and 2) a decision-theoretic mechanism that selects the example with the highest overall utility for learning and problem-solving success. We describe this example-selection process and present empirical findings from its evaluation.","doi":null,"url":"https://ijcai.org/proceedings/2007/76","pdf":"https://ijcai.org/proceedings/2007/0076.pdf","markdown":"https://ijcai.org/proceedings/2007/76.md","bibtex":"https://ijcai.org/proceedings/2007/bibtex/76","volume":{"slug":"2007","title":"Proceedings of the Twentieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2007","url":"https://ijcai.org/proceedings/2007/","year":2007,"location":"Hyderabad, India","dates":"","editors":"Ramon López de Mántaras","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":76,"pages":{"first":483,"last":487},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}