Searching for student intermediate mental steps
Year: 2007
Type: conference-paper
Abstract: This paper presents a general method for identifying student intermediate mental steps from sequences of actions stored by problem solving-based learning environments, in order to provide feedback to teachers on knowledge that statistically seems to be used by a particular student. When many intermediate mental steps are possible, ambiguity is removed using what is already known about the student. The system uses a student model to search within a huge space of possible actions, and updates this student model consequently. The user model distinguishes between two different cognitive processes: (1) planning the action by focusing on a particular part of the environment and considering an action type and (2) performing the action.
Source: HAL
Institution: Translational Innovation in Medicine and Complexity
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W2733776888