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ERIC Number: EJ1356684
Record Type: Journal
Publication Date: 2022-Nov
Pages: 24
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1360-2357
EISSN: EISSN-1573-7608
Available Date: N/A
Theoretical Model of Investigating Determinants for a Successful Electronic Assessment System (EAS) in Higher Education
Mo, Daniel Y.; Tang, Yuk Ming; Wu, Edmund Y.; Tang, Valerie
Education and Information Technologies, v27 n9 p12543-12566 Nov 2022
Electronic assessment (e-assessment) is an essential part of higher education, not only used to manage a large class size of students' learning performance and particularly in assessing the learning outcomes of students. The e-assessment data generated can not only be used to determine students' study weaknesses to develop strategies for teaching and learning, but also in the development of essential teaching and learning pedagogies for online teaching and learning. Despite the wider adoption of Information and Communication Technology (ICT) technologies due to the COVID-19 pandemic, universities still encountered numerous problems during the transformation to electronic teaching as most educators struggled with the effective implementation of the Electronic Assessment System (EAS). The successful launch of EAS relied heavily on students' use intention towards the new and unfamiliar electronic system, which was actually unknown to the project managers of EAS. It is therefore important to understand students' views and concerns on EAS and the proactive measures taken by universities to enhance students' acceptance and intention of usage. Although most studies investigate students' acceptance of online learning, there is still little research on the adoption of e-assessment. In this regard, we propose to develop a theoretical model based on students' perceptions of EAS. Based on the Technology Acceptance Model (TAM) and a major successor of TAM, an electronic assessment system acceptance model (EASA model) is developed with key measures including system adoption anxiety, e-assessment facilitation, risk reduction amid, etc. The data is obtained through a survey among current students at a local university, and structural equation modeling (SEM) is applied to analyze the quantitative data. This study has a significant impact on improving educators' use of e-assessment in order to develop essential online teaching and learning pedagogy in the future.
Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: N/A