ITM Web Conf.
Volume 7, 20163rd Annual International Conference on Information Technology and Applications (ITA 2016)
|Number of page(s)||5|
|Section||Session 4: Information System and its Applications|
|Published online||21 November 2016|
Modeling of Learners’ Interest in Blended Learning: Insights from Emotional Cognition
1 Institute of science and technology, Shanghai Open University, Shanghai 200433, China
2 School of Management, Fudan University, Shanghai 200433, China
3 Management School, Shanghai University of International Business and Economics, Shanghai 201620, China
4 School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai 200433, China
a Corresponding author: Yong-Hui DAI, Email: firstname.lastname@example.org
In blended learning, how to explore and evaluate the learner’s interest is very important. In this paper, we study on modeling of learners’ interest from the perspective of cognitive neuroscience. Emotional cognitive theory and brain cognitive process for situational learning interest were introduced. In addition, in order to solve the problem of quantitative assessment of interest, learner’s online operation behaviour was summarized through data mining methods, and the learners' interest regression model was built. Experimental results show that the accuracy of the model is more than 91% and it has good applicability in blended learning.
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.