The paper presents the UMLOntology structure used to automatically generate test questions. It also considers the algorithm for automatic generation of questions in the Test Generation Environment and discusses supplementary annotation elements added to the ontology. Moreover, the research presents examples of generated meaningful test questions by the Test Generation Environment using the implemented UMLOntology.
Topics
Educational assessment
REFERENCES
1.
E.
Doychev
, (2013
) “An Environment for Electronic Educational Services”, PhD thesis in Plovdiv University “Paisii Hilendarski”
2.
A.
Toskova
, “Model of Recommended System in Intelligent Game-Based Learning Platform”, Proceedings of International Conference Аutomatics and Informatics'2019 (ICAI'19
), ISSN , pp. 143
–146
, Sofia, 2019
3.
Toskova
, A.
, B.
Toskov
, L.
Doukovska
, B.
Daskalov
и I.
Radeva
, "Neural Networks in the Intelligent Educational Space", Advances in Neural Networks and Applications 2018 (ANNA '18), St. Konstantin and Elena Resort, Bulgaria
, 2018
, pp. 107
–112
, IEEE Xplore Digital Library, VDE
, Print ISBN: 978-3-8007-4756-64.
Garov
Kosta
, Tabakova-Komsalova
Veneta
“Learning Content of Educational Tasks in Computer Programming Training for 10-11 Year Old Children
. TEM Journal.
Volume 6
, Issue 4
, Pages 847
–854
, ISSN , DOI: , November 2017
5.
K.
Gramatova
, S.
Stoyanov
, E.
Doychev
, V.
Valkanov
, “Integration of eTesting in an IoT eLearning ecosystem - Virtual eLearning Space”, BCI '15, September 02-04, 2015, Craiova, Romania
, 2015
ACM, ISBN 978-1-4503-3335-1/15/09, DOI: 6.
Stancheva
N.
, Stoyanova-Doycheva
A.
, Stoyanov
S.
, Popchev
I.
, Ivanova
V.
, (2017
) An Environment for Automatic Test Generation, Cybernetics and Information Technologies
, Volume 17
, ISSN (Online) , DOI: 7.
OMG Unified Modeling LanguageTM (OMG UML
), Infrastructure Version 2.4.1 OMG Document Number: formal/2011-08-05 Standard document URL: http://www.omg.org/spec/UML/2.4.1/Infrastructure8.
Ali
, H.
, Chali
, Y.
, Hasan
, S.A.
“Automation of Question Generation From Sentences
”, Proceedings of the Third Workshop on Question Generation
, 2011
9.
Yao
, X.
, Bouma
G.
, Zhang
Y.
, “Semantics-based Question Generation and Implementation
”, Dialogue & Discourse
, Vol 3
, (2
), 2012
10.
Kunichika
H.
, Katayama
T.
, Hirashima
T.
,Takeuchi
A.
, “Automated question generation methods for intelligent English learning systems and its evaluation
”, In: Proceedings of ICCE
, pp. 2
–5
(2003
)11.
Olney
A.
, Graesser
A.
, Person
N.
, “Question Generation from Concept Maps”, Dialogue & Discourse
, Vol. 3
(2
), 2012
.12.
A.
Papasalouros
, K.
Kanaris
, and K.
Kotis
. (2008
) “Automatic generation of multiple choice questions from domain ontologies
”. in Proceedings of the IADIS e-Learning Conference
, pp. 427–434
, Amsterdam, The Netherlands, July 2008
.13.
Alsubait
, T.
, Parsia
B.
, Sattler
U.
, “Ontology-Based Multiple Choice Question Generation”, Scientific journal KI - Künstliche Intelligenz 30
, pp. 183-188
, 2016
14.
Al-yahya
M
, “OntoQue: A Question Generation Engine for Educational Assessment Based on Domain Ontologies” Proceedings of the 2011 11th IEEE International Conference on Advanced Learning Technologies
, ICALT
2011
, pp. 393
–395
, 201115.
Al-yahya
, M.
, “Ontology-Based Multiple Choice Question Generation”, The Scientific World Journal
. 2014
16.
Vinu
, E. V.
, K. P.
Sreenivasa
, “A Novel Approach to Generate MCQs from Domain Ontology: Considering DL Semantics and Open-World Assumption
”, Journal of Web Semantics: Science, Services and Agents on the World Wide Web
, Vol. 34
, pp. 40
–54
, 2015
17.
Protégé-OWL. http://protege.stanford.edu/
18.
Stancheva
, N.S.
, Popchev
, I.
, Stoyanova-Doycheva
, A.
, Stoyanov
, S.
, (2016
) Automatic generation of test questions by software agents using ontologies
, 2016 IEEE 8th International Conference on Intelligent Systems
, IS 2016 - Proceedings (2016) 741
–746
, DOI:
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