Skip to main content
Top

2023 | OriginalPaper | Chapter

A Novel Model to Predict the Whack of Pandemics on the International Rankings of Academia

Authors : Nidhi Agarwal, Devendra K. Tayal

Published in: Intelligent Systems and Machine Learning

Publisher: Springer Nature Switzerland

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Pandemics bring physical life to a complete standstill; people are bound to remain confined to their homes. Students suffer a lot academically due to closure of educational institutes worldwide due to pandemic fear. In such a scenario, imparting adequate education to them so that their academics is not affected, is a big challenge. During the COVID-19 pandemic time, educational institutions have really played a good role in imparting online education to students. Their career and academic tenure were not affected. It is contrary to the past pandemics throughout the world history where students’ academic years were lost. All this has been possible because of advancement in technologies related to Human Computer Interaction. The educational institutions tried to cope up a lot with the current educational mode but lacked in some or the other international ranking parameters. This brought sudden dips in their international ranks which can be regained only in long periods of time with major extra efforts. This research work provides an insight on the slipped off international ranks of higher educational institutions during global disruptive conditions like pandemics (COVID-19 and combatting with future pandemics). The novel model proposed in this work helps academicians in predicting the impact of pandemics on their overall international rankings so that recovery decisions and plans can be taken timely by academicians to combat with the situation. The work involves developing a model based on Machine Learning advanced algorithms with the inclusion of a humongous ranking dataset. Strong empirical results support the high efficiency as sensitivity = 97.98, Accuracy = 97.54, F1 value = 97.82, Kappa-score = 0.95. Using the proposed model. To the best of our knowledge, till now none of the researchers have proposed any such pioneering tool for academicians using advanced Machine Learning algorithms.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference Alhadreti, O.: Assessing academics’ perceptions of blackboard usability using SUS and CSUQ: A case study during the COVID-19 pandemic. Int. J. Hum.-Comput. Interact. 37(11), 1003–1015 (2021)CrossRef Alhadreti, O.: Assessing academics’ perceptions of blackboard usability using SUS and CSUQ: A case study during the COVID-19 pandemic. Int. J. Hum.-Comput. Interact. 37(11), 1003–1015 (2021)CrossRef
2.
go back to reference Callaghan, F.V.O’., Neumann, D.L., Jones, L., Creed, P.A.: The use of lecture recordings in higher education: A review of institutional, student, and lecturer issues. Educ. Inf. Technol. 22(1), 399–415 (2017) Callaghan, F.V.O’., Neumann, D.L., Jones, L., Creed, P.A.: The use of lecture recordings in higher education: A review of institutional, student, and lecturer issues. Educ. Inf. Technol. 22(1), 399–415 (2017)
3.
go back to reference Park, S.W., Cornforth, D.M., Dushoff, J., Weitz, J.S.: The time scale of asymptomatic transmission affects estimates of epidemic potential in the COVID-19 outbreak. Epidemics 31, 100392 (2020)CrossRef Park, S.W., Cornforth, D.M., Dushoff, J., Weitz, J.S.: The time scale of asymptomatic transmission affects estimates of epidemic potential in the COVID-19 outbreak. Epidemics 31, 100392 (2020)CrossRef
4.
go back to reference Scagnoli, N.I., Choo, J., Tian, J.: Students’ insights on the use of video lectures in online classes. Br. J. Edu. Technol. 50(1), 399–414 (2019)CrossRef Scagnoli, N.I., Choo, J., Tian, J.: Students’ insights on the use of video lectures in online classes. Br. J. Edu. Technol. 50(1), 399–414 (2019)CrossRef
5.
go back to reference Lwoga, ET., Komba, M.: Antecedents of continued usage intentions of web-based learning management system in Tanzania. Education+ training (2015) Lwoga, ET., Komba, M.: Antecedents of continued usage intentions of web-based learning management system in Tanzania. Education+ training (2015)
6.
go back to reference Agarwal, N., Tayal, D.K.: FFT based ensembled model to predict ranks of higher educational institutions. Multimedia Tools Appli. 81, 34129–34162 (2022)CrossRef Agarwal, N., Tayal, D.K.: FFT based ensembled model to predict ranks of higher educational institutions. Multimedia Tools  Appli. 81, 34129–34162 (2022)CrossRef
7.
go back to reference Nguyen, N.T., Chinn, J., Nahmias, J., Yuen, S., Kirby, K.A., Hohmann, S., Amin, A.: Outcomes and mortality among adults hospitalized with COVID-19 at US medical centers. JAMA Netw. Open. 4(3), e210417- e210417-e210417 (2021) Nguyen, N.T., Chinn, J., Nahmias, J., Yuen, S., Kirby, K.A., Hohmann, S., Amin, A.: Outcomes and mortality among adults hospitalized with COVID-19 at US medical centers. JAMA Netw. Open. 4(3), e210417- e210417-e210417 (2021)
8.
go back to reference Marín, D.V., Cabero, A.J.: Las redes sociales en educación: desde la innovación a la investigación educativa. RIED. Revista Iboeroamericana de Educación a Distancia. 22 (2), 25–33 (2019) Marín, D.V., Cabero, A.J.: Las redes sociales en educación: desde la innovación a la investigación educativa. RIED. Revista Iboeroamericana de Educación a Distancia. 22 (2), 25–33 (2019)
9.
go back to reference Belkin, D.: Is This the End of College as We Know It?, in The Wall Street Journal (2020) Belkin, D.: Is This the End of College as We Know It?, in The Wall Street Journal (2020)
10.
go back to reference Duffy C.: Humanities degrees to double in cost as government funnels students into “job-relevant” uni courses. ABC News (2020) Duffy C.: Humanities degrees to double in cost as government funnels students into “job-relevant” uni courses. ABC News (2020)
11.
go back to reference Ratten, V.: Coronavirus (Covid-19) and the entrepreneurship education community. J. Enterprising Commun. People Places Global Econ. (2020) Ratten, V.: Coronavirus (Covid-19) and the entrepreneurship education community. J. Enterprising Commun. People  Places  Global Econ. (2020)
12.
go back to reference Feuerlicht, G., Beránek, M., Kovář, V.: Impact of COVID-19 pandemic on Higher Education. In: 2021 International Conference on Computational Science and Computational Intelligence (CSCI), pp. 1095–1098. IEEE (2021) Feuerlicht, G., Beránek, M., Kovář, V.: Impact of COVID-19 pandemic on Higher Education. In: 2021 International Conference on Computational Science and Computational Intelligence (CSCI), pp. 1095–1098. IEEE (2021)
13.
go back to reference Jackson, C.: DATA SNAPSHOT: 2019, Universities Australia (2021) Jackson, C.: DATA SNAPSHOT: 2019, Universities Australia (2021)
14.
go back to reference De, W.H., Adams, T.: Global competition in higher education: A comparative study of policies, rationales, and practices in Australia and Europe, in Higher education, policy, and the global competition phenomenon, pp. 219–233. Springer (2010) De, W.H.,  Adams, T.: Global competition in higher education: A comparative study of policies, rationales, and practices in Australia and Europe, in Higher education, policy, and the global competition phenomenon, pp. 219–233. Springer (2010)
15.
go back to reference De, W.H.: Trends, issues and challenges in internationalisation of higher education. Centre for Applied Research on Economics and Management, School of Economics (2011) De, W.H.: Trends, issues and challenges in internationalisation of higher education. Centre for Applied Research on Economics and Management, School of Economics (2011)
19.
go back to reference Ross, J.: Economic ramifications of the COVID-19 pandemic for higher education: a circuit breaker in Australian universities’ business model? Higher Educ. Res. Developm., 1–6 (2020) Ross, J.: Economic ramifications of the COVID-19 pandemic for higher education: a circuit breaker in Australian universities’ business model? Higher Educ. Res. Developm., 1–6 (2020)
21.
go back to reference Ferguson, R.: Group of Eight warns of ‘brain drain’ with 7000 jobs set to go, in The Australian. 2020, News Corp Australia: Australia (2020) Ferguson, R.: Group of Eight warns of ‘brain drain’ with 7000 jobs set to go, in The Australian. 2020, News Corp Australia: Australia (2020)
22.
go back to reference Tertiary Education Quality and Standard Agency (TESQA). Key financial metrics on Australia’s higher education sector (2018) Tertiary Education Quality and Standard Agency (TESQA). Key financial metrics on Australia’s higher education sector (2018)
23.
go back to reference Ferguson, R.: Crisis leaves unis facing global crash: Craven, in The Australian (2021), @australian Ferguson, R.: Crisis leaves unis facing global crash: Craven, in The Australian (2021), @australian
26.
go back to reference Brendan, O.M.: Education exports worth almost £20 billion to the UK, in University World News (2020) Brendan, O.M.: Education exports worth almost £20 billion to the UK, in University World News (2020)
27.
go back to reference Estermann, T., Pruvot, E.B., Kupriyanova, V., Stoyanova, H.: The Impact of the Covid-19 Crisis on University Funding in Europe: Lessons Learnt from the 2008 Global Financial Crisis. European University Association, Briefing (2020) Estermann, T., Pruvot, E.B., Kupriyanova, V., Stoyanova, H.: The Impact of the Covid-19 Crisis on University Funding in Europe: Lessons Learnt from the 2008 Global Financial Crisis. European University Association, Briefing (2020)
28.
go back to reference Lederman, D.: Will shift to remote teaching be boon or bane for online learning. Inside Higher Ed. 18 (2020) Lederman, D.: Will shift to remote teaching be boon or bane for online learning. Inside Higher Ed. 18 (2020)
29.
go back to reference Agarwal, N., Srivastava, R., Srivastava, P., Sandhu, J., Singh, P.P.: Multiclass classification of different glass types using random forest classifier. In: 6th International Conference on Intelligent Computing and Control Systems (ICICCS) 2022, pp. 1682–1689. IEEE (2022) Agarwal, N., Srivastava, R., Srivastava, P., Sandhu, J., Singh, P.P.: Multiclass classification of different glass types using random forest classifier. In: 6th International Conference on Intelligent Computing and Control Systems (ICICCS) 2022, pp. 1682–1689. IEEE (2022)
30.
go back to reference Agarwal, N., Singh, V., Singh P.: Semi-supervised learning with GANs for melanoma detection. In: 6th International Conference on Intelligent Computing and Control Systems, ICICCS 2022, pp. 141–147. IEEE (2022) Agarwal, N., Singh, V., Singh P.: Semi-supervised learning with GANs for melanoma detection. In: 6th International Conference on Intelligent Computing and Control Systems, ICICCS 2022, pp. 141–147. IEEE (2022)
31.
go back to reference Agarwal, N., Jain, A., Gupta, A., Tayal, DK.: Applying xgboost machine learning model to succor astronomers detect exoplanets in distant galaxies. In: International Conference on Artificial Intelligence and Speech Technology 2021, pp. 385–404. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-95711-7_33 Agarwal, N., Jain, A., Gupta, A., Tayal, DK.: Applying xgboost machine learning model to succor astronomers detect exoplanets in distant galaxies. In: International Conference on Artificial Intelligence and Speech Technology 2021, pp. 385–404. Springer, Cham (2021). https://​doi.​org/​10.​1007/​978-3-030-95711-7_​33
Metadata
Title
A Novel Model to Predict the Whack of Pandemics on the International Rankings of Academia
Authors
Nidhi Agarwal
Devendra K. Tayal
Copyright Year
2023
DOI
https://doi.org/10.1007/978-3-031-35081-8_3

Premium Partner