Proceedings of the 5th International Symposium on Knowledge Acquisition and Modeling

Study on Information Demands in Heuristic Teaching for Learners

Authors
Luo Qi
Corresponding Author
Luo Qi
Available Online June 2015.
DOI
10.2991/kam-15.2015.49How to use a DOI?
Keywords
heuristic teaching; information demands; system dynamics method; hierarchical model of learners’ information demands.
Abstract

To make the heuristic teaching more effectively carried out, exploring the information demands of learners is an indispensable step. The results show that: the main motivation for the information demand is still to learn knowledge; there are a variety of ways to get information, but the dominant ways are the Internet and the guidance of teachers; at the same time, the efficiency of the information obtaining is remained to be improved, etc. According to the results, we put forward the hierarchical model of learners’ information demands. And based on this model, in order to improve the teaching effect, we put forward several suggestions for the knowledge and information guidance to the learners in the heuristic teaching with the help of the personalized learning support service.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the 5th International Symposium on Knowledge Acquisition and Modeling
Series
Advances in Intelligent Systems Research
Publication Date
June 2015
ISBN
978-94-62520-87-5
ISSN
1951-6851
DOI
10.2991/kam-15.2015.49How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Luo Qi
PY  - 2015/06
DA  - 2015/06
TI  - Study on Information Demands in Heuristic Teaching for Learners
BT  - Proceedings of the 5th International Symposium on Knowledge Acquisition and Modeling
PB  - Atlantis Press
SP  - 180
EP  - 183
SN  - 1951-6851
UR  - https://doi.org/10.2991/kam-15.2015.49
DO  - 10.2991/kam-15.2015.49
ID  - Qi2015/06
ER  -