IEICE TRANSACTIONS on Information
Investigation on e-Learning Status Estimation for New Learners — Classifier Selection on Representative Sample Selection
Summary :
This article introduces our investigation on learning state estimation in e-learning on the condition that visual observation and recording of a learner's behaviors is possible. In this research, we examined methods of adaptation for a new learner for whom a small number of ground truth data can be obtained.
- Publication
- IEICE TRANSACTIONS on Information Vol.E103-D No.4 pp.905-909
- Publication Date
- 2020/04/01
- Publicized
- 2020/01/20
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2019EDL8043
- Type of Manuscript
- LETTER
- Category
- Educational Technology
Authors
Siyang YU
Kyoto University
Kazuaki KONDO
Kyoto University
Yuichi NAKAMURA
Kyoto University
Takayuki NAKAJIMA
Kyoto University
Masatake DANTSUJI
Kyoto University
Keyword
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Siyang YU, Kazuaki KONDO, Yuichi NAKAMURA, Takayuki NAKAJIMA, Masatake DANTSUJI, "Investigation on e-Learning Status Estimation for New Learners — Classifier Selection on Representative Sample Selection" in IEICE TRANSACTIONS on Information,
vol. E103-D, no. 4, pp. 905-909, April 2020, doi: 10.1587/transinf.2019EDL8043.
Abstract: This article introduces our investigation on learning state estimation in e-learning on the condition that visual observation and recording of a learner's behaviors is possible. In this research, we examined methods of adaptation for a new learner for whom a small number of ground truth data can be obtained.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2019EDL8043/_p
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@ARTICLE{e103-d_4_905,
author={Siyang YU, Kazuaki KONDO, Yuichi NAKAMURA, Takayuki NAKAJIMA, Masatake DANTSUJI, },
journal={IEICE TRANSACTIONS on Information},
title={Investigation on e-Learning Status Estimation for New Learners — Classifier Selection on Representative Sample Selection},
year={2020},
volume={E103-D},
number={4},
pages={905-909},
abstract={This article introduces our investigation on learning state estimation in e-learning on the condition that visual observation and recording of a learner's behaviors is possible. In this research, we examined methods of adaptation for a new learner for whom a small number of ground truth data can be obtained.},
keywords={},
doi={10.1587/transinf.2019EDL8043},
ISSN={1745-1361},
month={April},}
Copy
TY - JOUR
TI - Investigation on e-Learning Status Estimation for New Learners — Classifier Selection on Representative Sample Selection
T2 - IEICE TRANSACTIONS on Information
SP - 905
EP - 909
AU - Siyang YU
AU - Kazuaki KONDO
AU - Yuichi NAKAMURA
AU - Takayuki NAKAJIMA
AU - Masatake DANTSUJI
PY - 2020
DO - 10.1587/transinf.2019EDL8043
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E103-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2020
AB - This article introduces our investigation on learning state estimation in e-learning on the condition that visual observation and recording of a learner's behaviors is possible. In this research, we examined methods of adaptation for a new learner for whom a small number of ground truth data can be obtained.
ER -
English
