A Multidimensional Evaluation of Technology-Enabled Assessment Methods during Online Education in Developing Countries

Ambreen Sultana Khattak, Muhammad Khurram Ali () and Mohammed Al Awadh
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Ambreen Sultana Khattak: Industrial Engineering Department, University of Engineering and Technology, Taxila 47050, Pakistan
Muhammad Khurram Ali: Industrial Engineering Department, University of Engineering and Technology, Taxila 47050, Pakistan
Mohammed Al Awadh: Department of Industrial Engineering, College of Engineering, King Khalid University, Abha 62529, Saudi Arabia

Sustainability, 2022, vol. 14, issue 16, 1-20

Abstract: Humanity has faced unprecedented chaos in the education sector due to the inevitable sudden adoption of online mode of learning during the pandemic. The complexities associated with technology-enabled learning and assessment have different connotations in developing countries due to a lack of infrastructure and awareness. Such countries can switch over to an online mode of education more frequently in the future due to highly volatile local political and cultural situations on top of the pandemic. This study evaluates the complexities associated with technology-enabled online assessment methods in Pakistan. Technology readiness and performance for the learning assessment of students are appraised through approaching approximately one thousand students from more than one hundred public and private sector engineering universities. A screened list of assessment alternatives and their influencing factors are then prioritized using the multi-actor multi-criteria analysis (MAMCA) by considering the perceptions of national policymakers, faculty members and students. The aggregate results reveal that, among the influencing factors, ‘mental health’ received the highest weightage, and stakeholders are indifferent to associated costs despite financial challenges. Automated MCQs secured the top position in the ranking list. Sensitivity analysis incorporates some disagreements among the stakeholders, which makes this study highly beneficial for policy modeling.

Keywords: online learning and assessment; multi-actor multi-criteria analysis (MAMCA); technology readiness; automated assessment methods (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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