Work

Models and Methods for Implementing Pedagogical Interventions in Model-tracing Cognitive Tutors

Year: 2017

Type: article

Abstract: This paper presents some models and methods for generating pedagogical interventions in model-tracing cognitive tutors. They use Bayesian networks for assessment and making decisions, this feature allows managing uncertainty reasoning based on a formal foundation. This technique combines the rigorous probabilistic formalisms with a graphical representation and efficient inference mechanisms. It is explained how Bayesian networks are employed as an inference engine to assess the degree of learning of the relevant knowledge components in the learning domain and determine the proper pedagogical interventions for performing a productive learning process

Source: RADIOELECTRONIC AND COMPUTER SYSTEMS

DOI: 10.32620/reks.2017.1.04

Authors: Juan Pablo Martinez Bastida, Андрей Григорьевич Чухрай, Елена Владимировна Гавриленко

Institution: National Aerospace University – Kharkiv Aviation Institute

Language: English

Topic: Intelligent Tutoring Systems and Adaptive Learning

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $107