Evaluation of ERST - An External Representation Selection Tutor

This paper describes the evaluation of ERST, an adaptive system which is designed to improve its users' external representation (ER) selection accuracy on a range of database query tasks. The design of the system was informed by the results of experimental studies. Those studies examined the interactions between the participants' background knowledge-of-external representations, their preferences for selecting particular information display forms, and their performance across a range of tasks involving database queries. The paper describes how ERST's adaptation is based on predicting users' ER-to-task matching skills and performance at reasoning with ERs, via a Bayesian user model. The

• Type: Conference
• Year: 2006
• Where: DIAGRAMS
• Authors: Beate Grawemeyer
• Keywords: Artificial Intelligence, Background Knowledge-of-external Representations, Database Query Tasks, DIAGRAMS 2006, Tasks Involving Database