Abstract
In this paper, we present a knowledge learning diagnosis approach to supporting a computer-supported collaborative learning environment. Bayesian network technique is used here to diagnose the misconception about learning knowledge and to reason potential misconception for individual learners. After learners have made a test, the system using probabilistic reasoning will automatically create learning communities based on the learners' characteristics and test results. This work is motivated by diagnosing learning performance of learners for both instructors and learners to understand concept comprehension of learners in a computer-supported collaborative learning (CSCL) environment.
Original language | English |
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Title of host publication | Proceedings - 5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005 |
Pages | 33-34 |
Number of pages | 2 |
DOIs | |
Publication status | Published - 2005 Dec 1 |
Event | 5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005 - Kaohsiung, Taiwan Duration: 2005 Jul 5 → 2005 Jul 8 |
Publication series
Name | Proceedings - 5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005 |
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Volume | 2005 |
Other
Other | 5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005 |
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Country | Taiwan |
City | Kaohsiung |
Period | 05-07-05 → 05-07-08 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Engineering(all)
Cite this
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A learning diagnosis architecture with a Bayesian network approach. / Huang, Ho Chuan; Wang, Tsui-Ying.
Proceedings - 5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005. 2005. p. 33-34 1508599 (Proceedings - 5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005; Vol. 2005).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - A learning diagnosis architecture with a Bayesian network approach
AU - Huang, Ho Chuan
AU - Wang, Tsui-Ying
PY - 2005/12/1
Y1 - 2005/12/1
N2 - In this paper, we present a knowledge learning diagnosis approach to supporting a computer-supported collaborative learning environment. Bayesian network technique is used here to diagnose the misconception about learning knowledge and to reason potential misconception for individual learners. After learners have made a test, the system using probabilistic reasoning will automatically create learning communities based on the learners' characteristics and test results. This work is motivated by diagnosing learning performance of learners for both instructors and learners to understand concept comprehension of learners in a computer-supported collaborative learning (CSCL) environment.
AB - In this paper, we present a knowledge learning diagnosis approach to supporting a computer-supported collaborative learning environment. Bayesian network technique is used here to diagnose the misconception about learning knowledge and to reason potential misconception for individual learners. After learners have made a test, the system using probabilistic reasoning will automatically create learning communities based on the learners' characteristics and test results. This work is motivated by diagnosing learning performance of learners for both instructors and learners to understand concept comprehension of learners in a computer-supported collaborative learning (CSCL) environment.
UR - http://www.scopus.com/inward/record.url?scp=33749076893&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33749076893&partnerID=8YFLogxK
U2 - 10.1109/ICALT.2005.10
DO - 10.1109/ICALT.2005.10
M3 - Conference contribution
AN - SCOPUS:33749076893
SN - 0769523382
SN - 9780769523385
T3 - Proceedings - 5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005
SP - 33
EP - 34
BT - Proceedings - 5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005
ER -