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A Motivational Thermostat Framework for Enhanced E-Learning Systems

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4 Author(s)
Jaejeung Kim ; Inst. for Inf. Technol. Convergence, KAIST, Daejeon, South Korea ; Youngtae Seok ; Dongwon Lee ; Howon Lee

Motivation has never been so important since the learning environment is evolving into a self-centered, distant learning. In this paper, we introduce a motivational thermostat framework, developed based on theoretically grounded pedagogy and motivation tactics from multiple dimensions. Its mechanism maintains learner's motivational state in between "lose-of-motivation" and "over-motivated", leading to persistent, lowered attrition rate and more efficient learning. Adaptive Learning Motivational System (ALMOST) is implemented based on the framework. Its effectiveness is evaluated by web-based experiments. The results show that proposed system showed decreased attrition rate and increased learner performance.

Published in:

System Science (HICSS), 2012 45th Hawaii International Conference on

Date of Conference:

4-7 Jan. 2012