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Multilevel IRT models for the analysis of satisfaction for distance learning during the Covid-19 pandemic

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  • Bacci, Silvia
  • Fabbricatore, Rosa
  • Iannario, Maria

Abstract

The Covid-19 pandemic played a relevant role in the diffusion of distance learning alternatives to “traditional” learning based on classroom activities, to allow university students to continue attending lessons during the most severe phases of the pandemic. In such a context, investigating the students' perspective on distance learning provides useful information to stakeholders to improve effective educational strategies, which could be useful also after the end of the emergency to favor the digital transformation in the higher educational setting.

Suggested Citation

  • Bacci, Silvia & Fabbricatore, Rosa & Iannario, Maria, 2023. "Multilevel IRT models for the analysis of satisfaction for distance learning during the Covid-19 pandemic," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    • Handle: RePEc:eee:soceps:v:86:y:2023:i:c:s0038012122002683
    DOI: 10.1016/j.seps.2022.101467
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    1. Kwiatkowska-Ciotucha Dorota & Załuska Urszula, 2023. "Remote Education during the Covid-19 Pandemic in the Opinion of Students," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 27(2), pages 1-20, June.

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