Effectiveness of E-Assessment in Quantitative Modules, COVID-19 Consequences: A Case Study by the British University in Egypt
The Covid-19 pandemic has globally influenced higher education, prompting the closure of thousands of universities as a key strategy for social distancing. Therefore, universities faced a new set of challenges; on top of them was the unprecedented request for e-assessments, instead of on-CAMPUS assessments. This paper presents the findings of a case study conducted at the Faculty of Business Administration, Economics and Political Science (BAEPS) at the British University in Egypt (BUE) over the second semester of the academic year 2019–2020. The case-study aimed to assess the fast BAEPS response to the challenges of the new assessment mechanism, which has been conducted using various interactive educational platforms. Additionally, this paper aims to examine the degree to which the results of the e-assessment conducted during the pandemic are consistent with the traditional paper assessment. The first conclusion was the existence of a significant difference between e-assessment and paper assessment, which may very well be due to the open-book nature of e-assessments. However, the paper concluded that the value of uniqueness and time factors in the design of e-assessment shrink the results gap between both types. The evidence showed the ability of e-assessment to overcome the main threat, which is external support to students, through the proper assessment design. Moreover, the paper concluded the efficiency of e-assessments to significantly reflect actual students’ capabilities and achievements in quantitative modules. Finally, the authors emphasized that e-assessment has noticeably become mandatory for the future of education in the fourth industrial revolution.
Salah W., Ramadan M., Ahmed H. (2021) Effectiveness of E-Assessment in Quantitative Modules, COVID-19 Consequences: A Case Study by the British University in Egypt. In: Auer M.E., Centea D. (eds) Visions and Concepts for Education 4.0. ICBL 2020. Advances in Intelligent Systems and Computing, vol 1314. Springer, Cham. https://doi.org/10.1007/978-3-030-67209-6_50