TY - GEN
T1 - Extended real-time learning behavior mining
AU - Kuo, Yen Hung
AU - Huang, Yueh Min
AU - Chen, Juei Nan
AU - Jeng, Yu Lin
PY - 2005/12/1
Y1 - 2005/12/1
N2 - Based on our previous work [3], learning patterns can be discovered and recommend to the learners. This paper extends the proposed problem to handle the questionable mining results. According to the learning patterns are discovered by using learning histories. It may be happened whenever the learners have ineffective learning behaviors, and we define them as questionable mining results. These ineffective behaviors may induce the bias suggestions. Therefore, we propose a candidate sequence set generation process to take care the stumble learning behavior.
AB - Based on our previous work [3], learning patterns can be discovered and recommend to the learners. This paper extends the proposed problem to handle the questionable mining results. According to the learning patterns are discovered by using learning histories. It may be happened whenever the learners have ineffective learning behaviors, and we define them as questionable mining results. These ineffective behaviors may induce the bias suggestions. Therefore, we propose a candidate sequence set generation process to take care the stumble learning behavior.
UR - https://www.scopus.com/pages/publications/33749041272
UR - https://www.scopus.com/pages/publications/33749041272#tab=citedBy
U2 - 10.1109/ICALT.2005.149
DO - 10.1109/ICALT.2005.149
M3 - Conference contribution
AN - SCOPUS:33749041272
SN - 0769523382
SN - 9780769523385
T3 - Proceedings - 5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005
SP - 440
EP - 441
BT - Proceedings - 5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005
T2 - 5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005
Y2 - 5 July 2005 through 8 July 2005
ER -