Progress towards intelligent support for human articulation of concepts from examples

Pavel, Gabriela (2010). Progress towards intelligent support for human articulation of concepts from examples. International Journal of Knowledge and Learning, 6(1) pp. 82–97.

DOI: https://doi.org/10.1504/IJKL.2010.034485

Abstract

Within this article we present a progress plan and the motivation of the research steps involved within the proposed learning framework. In a technological century, we aim to create a guided learning technology. We aim to use machine learning to support young students to articulate concepts from examples, in particular form images. Therefore, we address here the learning of natural concepts and principles of working memories that can support the learning activities. We focus also on the learning within a visual environment. We analyse then the potential of machine learning techniques to guide the human learning from examples. For this purpose, we propose a framework based on using machine learning to reason from student classifications, which we call HMCD (Human Machine Concept Dance).

Viewing alternatives

Metrics

Item Actions

Export

You can export this page using these formats Digital Object Identifier - DOI

About

• Item ORO ID
• 32326
• Item Type
• Journal Item
• ISSN
• 1741-1009
• Keywords
• technology enhanced learning; machine learning; human learning; learning framework; natural concepts; intelligent learning system
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Research Group
• Centre for Research in Computing (CRC)
• Copyright Holders
• © 2010 Inderscience Enterprises Ltd.
• Depositing User
• Gabriela Pavel