| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0458062 |
| utime |
20240111140917.6 |
| mtime |
20160415235959.9 |
| SCOPUS |
84964523737 |
| title
(primary) (eng) |
Bayesian Network Models for Adaptive Testing |
| specification |
| page_count |
10 s. |
| media_type |
E |
|
| serial |
| ARLID |
cav_un_epca*0458683 |
| ISSN |
1613-0073 |
| title
|
Proceedings of the Twelfth UAI Bayesian Modeling Applications Workshop (BMAW 2015) co-located with the 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015) |
| page_num |
24-33 |
| publisher |
| place |
Achen |
| name |
Sun SITE Central Europe |
| year |
2016 |
|
| editor |
|
| editor |
| name1 |
Carvalho |
| name2 |
R. N. |
|
|
| keyword |
Bayesian networks |
| keyword |
Computerized adaptive testing |
| author
(primary) |
| ARLID |
cav_un_auth*0329423 |
| full_dept (cz) |
Matematická teorie rozhodování |
| full_dept (eng) |
Department of Decision Making Theory |
| department (cz) |
MTR |
| department (eng) |
MTR |
| full_dept |
Department of Decision Making Theory |
| name1 |
Plajner |
| name2 |
Martin |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101228 |
| full_dept (cz) |
Matematická teorie rozhodování |
| full_dept |
Department of Decision Making Theory |
| department (cz) |
MTR |
| department |
MTR |
| full_dept |
Department of Decision Making Theory |
| name1 |
Vomlel |
| name2 |
Jiří |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| ARLID |
cav_un_auth*0292670 |
| project_id |
GA13-20012S |
| agency |
GA ČR |
|
| abstract
(eng) |
Computerized adaptive testing (CAT) is an interesting and promising approach to testing human abilities. In our research we use Bayesian networks to create a model of tested humans. We collected data from paper tests performed with grammar school students. In this article we first provide the summary of data used for our experiments. We propose several different Bayesian networks, which we tested and compared by cross-validation. Interesting results were obtained and are discussed in the paper. The analysis has brought a clearer view on the model selection problem. Future research is outlined in the concluding part of the paper. |
| action |
| ARLID |
cav_un_auth*0329424 |
| name |
The Twelfth UAI Bayesian Modeling Applications Workshop (BMAW 2015) |
| dates |
16.07.2015 |
| place |
Amsterdam |
| country |
NL |
|
| RIV |
JD |
| reportyear |
2017 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0258931 |
| confidential |
S |
| mrcbT16-s |
0.186 |
| mrcbT16-E |
Q3 |
| arlyear |
2016 |
| mrcbU14 |
84964523737 SCOPUS |
| mrcbU56 |
elektronický sborník |
| mrcbU63 |
cav_un_epca*0458683 Proceedings of the Twelfth UAI Bayesian Modeling Applications Workshop (BMAW 2015) co-located with the 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015) 1613-0073 24 33 Achen Sun SITE Central Europe 2016 CEUR Workshop Proceedings Vol 1565 |
| mrcbU67 |
Agosta J. M. 340 |
| mrcbU67 |
Carvalho R. N. 340 |
|