ZARERAVASAN, Ahad and A. ASHRAFI. Influencing factors on students' continuance intention to use Learning Management System (LMS). Online. In PROCEEDINGS OF 9TH INTERNATIONAL CONFERENCE ON INFORMATION COMMUNICATION AND MANAGEMENT (ICICM 2019). NEW YORK: ASSOC COMPUTING MACHINERY, 2019, p. 165-169. ISBN 978-1-4503-7188-9. Available from: https://dx.doi.org/10.1145/3357419.3357429.
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Basic information
Original name Influencing factors on students' continuance intention to use Learning Management System (LMS)
Authors ZARERAVASAN, Ahad (203 Czech Republic, belonging to the institution) and A. ASHRAFI (840 United States of America).
Edition NEW YORK, PROCEEDINGS OF 9TH INTERNATIONAL CONFERENCE ON INFORMATION COMMUNICATION AND MANAGEMENT (ICICM 2019), p. 165-169, 5 pp. 2019.
Publisher ASSOC COMPUTING MACHINERY
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
Publication form electronic version available online
RIV identification code RIV/00216224:14560/19:00120602
Organization unit Faculty of Economics and Administration
ISBN 978-1-4503-7188-9
Doi http://dx.doi.org/10.1145/3357419.3357429
UT WoS 000518414100033
Keywords in English Expectation-confirmation theory (ECT); Learning management system (LMS); Technology acceptance model (TAM)
Changed by Changed by: Mgr. Pavlína Kurková, učo 368752. Changed: 16/5/2022 08:19.
Abstract
In the last decades, universities and higher education institutes have widely employed learning management system (LMS) to monitor and manage online learning and teaching. Contrary to the significant role of LMS in educational settings, most research has focused on initial acceptance, and few attempts have been made to investigate factors influencing students' continuance intention to use LMS. The present study is an effort towards this research direction by proposing an integrated model of Expectation-Conformation Theory (ECT), and Technology Acceptance Model (TAM). The proposed model was tested using statistical data from 153 students from an online university. To verify the proposed theoretical model, we ran partial least squares (PLS)/structured equation modeling (SEM). The findings of this study revealed that the perceived usefulness is the strongest predictor of students' continuance intention. Surprisingly, our results also indicated that students' attitude toward LMS and their satisfaction level exert no significant influence on continuance intention.
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