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Stimulating the Post-COVID-19 Economic Recovery Scenarios to Evaluate Students' Understanding

Author

Listed:
  • Orkida Ilollari

    (Mediterranean University of Albania, Albania)

  • Petraq Papajorgji

    (Proinfinit Consulting, Tirana, Albania)

  • Ardian Civici

    (Mediterranean University of Albania, Albania)

Abstract
This study presents a simulation of economic scenarios using Mind Genomics to evaluate the maturity and ability of students involved in the master's and bachelor's programs to make sound decisions. A third group of specialists in economics is added to the study to evaluate differences among these groups. A comprehensive investigation of the current literature is undertaken to comprehend how different studies have dealt with the issue of the post-COVID-19 recovery process. Literature findings are used to design the Mind Genomics experiment and enable comparisons of student responses with literature findings. The study shows that, in general, master students converge with specialists in economics. The study shows some discrepancies in the scenario-evaluation process between master's and bachelor's students. Finally, recommendations for program examination and potential improvements are suggested to further align the teaching process to market scenarios.

Suggested Citation

  • Orkida Ilollari & Petraq Papajorgji & Ardian Civici, 2024. "Stimulating the Post-COVID-19 Economic Recovery Scenarios to Evaluate Students' Understanding," International Journal of Sociotechnology and Knowledge Development (IJSKD), IGI Global, vol. 16(1), pages 1-14, January.
    • Handle: RePEc:igg:jskd00:v:16:y:2024:i:1:p:1-14
    as

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    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJSKD.343633
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    References listed on IDEAS

    as
    1. Fairlie, Robert W, 2020. "The Impact of Covid-19 on Small Business Owners: Evidence of Early-Stage Losses from the April 2020 Current Population Survey," Santa Cruz Department of Economics, Working Paper Series qt89w827c9, Department of Economics, UC Santa Cruz.
    2. Antonio Mucherino & Petraq J. Papajorgji & Panos M. Pardalos, 2009. "Data Mining in Agriculture," Springer Optimization and Its Applications, Springer, number 978-0-387-88615-2, June.
    3. Crane, Leland D. & Decker, Ryan A. & Flaaen, Aaron & Hamins-Puertolas, Adrian & Kurz, Christopher, 2022. "Business exit during the COVID-19 pandemic: Non-traditional measures in historical context," Journal of Macroeconomics, Elsevier, vol. 72(C).
    4. Youssef Ahmed & Walaa Mohamed Medhat & Tarek El-Shishtawy, 2021. "An Approach for Modelling Big Data and Creation of New Values," International Journal of Sociotechnology and Knowledge Development (IJSKD), IGI Global, vol. 13(4), pages 66-81, October.
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