KFU. Card publication. Development of prototype of natural language answer processor for e-learning

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

DEVELOPMENT OF PROTOTYPE OF NATURAL LANGUAGE ANSWER PROCESSOR FOR E-LEARNING

Form of presentation

Articles in international journals and collections

Year of publication

2020

Язык

английский

Authors, employees of KFU

Prokopev Nikolay Arkadevich, author

Suleymanov Dzhavdet Shevketovich, author

Bibliographic description in the original language

Suleymanov D, Prokopyev N., Development of prototype of natural language answer processor for e-learning//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 2020. - Vol.12412 LNAI, Is.. - P.448-459.

Annotation

Automated knowledge control is an important component of e-Learning systems. Moreover, as an analysis of the most recent publications shows, the possibility of automated free natural language answers assessment is almost not represented in modern e-learning systems. Existing educational technologies either support only test approach to knowledge control, or when processing a natural-language answer, its semantic structure is not taken into account sufficiently for accurate assessment. This paper presents a software prototype that implements an algorithm for semantic processing of natural language answers. The basis of the algorithm is a theoretical pragmatically-oriented model proposed by D. Suleymanov, where main methodological principles are the principle of context determinism and the principle of meaning expectation. The implemented prototype was evaluated in order to verify its compliance with theoretical model and obtain the data necessary for further development of model and algorithm.

Keywords

Automatic answer assessment, Natural language processing, e-Learning, e-Assessment

The name of the journal

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

URL

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092147869&doi=10.1007%2f978-3-030-59535-7_33&partnerID=40&md5=7958ac662568cf78f5b96ce2662d0393

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=241701&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Prokopev Nikolay Arkadevich	ru_RU
dc.contributor.author	Suleymanov Dzhavdet Shevketovich	ru_RU
dc.date.accessioned	2020-01-01T00:00:00Z	ru_RU
dc.date.available	2020-01-01T00:00:00Z	ru_RU
dc.date.issued	2020	ru_RU
dc.identifier.citation	Suleymanov D, Prokopyev N., Development of prototype of natural language answer processor for e-learning//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 2020. - Vol.12412 LNAI, Is.. - P.448-459.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=241701&p_lang=2	ru_RU
dc.description.abstract	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	ru_RU
dc.description.abstract	Automated knowledge control is an important component of e-Learning systems. Moreover, as an analysis of the most recent publications shows, the possibility of automated free natural language answers assessment is almost not represented in modern e-learning systems. Existing educational technologies either support only test approach to knowledge control, or when processing a natural-language answer, its semantic structure is not taken into account sufficiently for accurate assessment. This paper presents a software prototype that implements an algorithm for semantic processing of natural language answers. The basis of the algorithm is a theoretical pragmatically-oriented model proposed by D. Suleymanov, where main methodological principles are the principle of context determinism and the principle of meaning expectation. The implemented prototype was evaluated in order to verify its compliance with theoretical model and obtain the data necessary for further development of model and algorithm.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	Automatic answer assessment	ru_RU
dc.subject	Natural language processing	ru_RU
dc.subject	e-Learning	ru_RU
dc.subject	e-Assessment	ru_RU
dc.title	Development of prototype of natural language answer processor for e-learning	ru_RU
dc.type	Articles in international journals and collections	ru_RU