TY - JOUR
T1 - Theoretical model of investigating determinants for a successful Electronic Assessment System (EAS) in higher education
AU - Mo, Daniel Y.
AU - Tang, Yuk Ming
AU - Wu, Edmund Y.
AU - Tang, Valerie
N1 - Funding Information:
This work was supported in part by Research Grants Council of Hong Kong under the Research Matching Grant Scheme (RMGS, project code: 700004)
Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2022/11
Y1 - 2022/11
N2 - 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.
AB - 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.
KW - Electronic Assessment System
KW - Electronic Assessment System Acceptance model
KW - Higher education
KW - Information and Communication Technology
KW - Theoretical model
UR - http://www.scopus.com/inward/record.url?scp=85131310959&partnerID=8YFLogxK
U2 - 10.1007/s10639-022-11098-1
DO - 10.1007/s10639-022-11098-1
M3 - Journal article
AN - SCOPUS:85131310959
SN - 1360-2357
VL - 27
SP - 12543
EP - 12566
JO - Education and Information Technologies
JF - Education and Information Technologies
IS - 9
ER -