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Student Evaluation of Distance Learning during the COVID-19 Pandemic: A Cross-Sectional Survey on Medical, Dental, and Healthcare Students at Sapienza University of Rome

Author

Listed:
  • Marco Lollobrigida

    (Department of Oral and Maxillofacial Sciences, Sapienza University of Rome, 00161 Rome, Italy)

  • Livia Ottolenghi

    (Department of Oral and Maxillofacial Sciences, Sapienza University of Rome, 00161 Rome, Italy)

  • Denise Corridore

    (Department of Oral and Maxillofacial Sciences, Sapienza University of Rome, 00161 Rome, Italy)

  • Gianluca Pingitore

    (Department of Oral and Maxillofacial Sciences, Sapienza University of Rome, 00161 Rome, Italy)

  • Cecilia Damiano

    (Department of Cardiovascular, Endocrine-Metabolic Diseases and Aging, Istituto Superiore di Sanità, 00161 Rome, Italy)

  • Giorgio Serafini

    (Department of Oral and Maxillofacial Sciences, Sapienza University of Rome, 00161 Rome, Italy)

  • Alberto De Biase

    (Department of Oral and Maxillofacial Sciences, Sapienza University of Rome, 00161 Rome, Italy)

Abstract

The COVID-19 pandemic has had a deep impact on university education, necessitating an abrupt shift from face-to-face learning to distance learning (DL). This has created new challenges, especially for those courses in which practical activities and internships are integral parts of the education program. The aim of this study was to assess the impact of DL on the study progress of a population of pregraduate students of medicine, dentistry, and healthcare professions. The survey was administered through an anonymous questionnaire by sharing a Google Forms link. Demographic data and educational background information were collected to obtain a profile of the participants. Different aspects of DL were investigated, including availability of digital devices, quality of connection, and environmental conditions; other questions focused on the effects of DL on students’ progress and professional maturation. Measures of association were also calculated using the chi-squared test, Cramer V, and Somers D. Among the 372 who participated, the results showed that students had a positive attitude toward online classroom and that DL did not substantially affect their progress. Most of the associations were statistically significant, also highlighting the effect of the degree course on the responses. Some critical issues clearly emerged, however, including the lack of adequate devices and environmental conditions due to economic disparity, poor relationships, suspension of internship programs, and clinical training. The results suggest that DL cannot be considered as a substitute for classroom-based medical education outside an emergency context.

Suggested Citation

  • Marco Lollobrigida & Livia Ottolenghi & Denise Corridore & Gianluca Pingitore & Cecilia Damiano & Giorgio Serafini & Alberto De Biase, 2022. "Student Evaluation of Distance Learning during the COVID-19 Pandemic: A Cross-Sectional Survey on Medical, Dental, and Healthcare Students at Sapienza University of Rome," IJERPH, MDPI, vol. 19(16), pages 1-10, August.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:16:p:10351-:d:892818
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    References listed on IDEAS

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    1. Roger Newson, 2006. "Confidence intervals for rank statistics: Somers' D and extensions," Stata Journal, StataCorp LP, vol. 6(3), pages 309-334, September.
    2. Francesca Carta & Marta De Philippis, 2021. "The impact of the COVID-19 shock on labour income inequality: evidence from Italy," Questioni di Economia e Finanza (Occasional Papers) 606, Bank of Italy, Economic Research and International Relations Area.
    3. Roger Newson, 2006. "Confidence intervals for rank statistics: Percentile slopes, differences, and ratios," Stata Journal, StataCorp LP, vol. 6(4), pages 497-520, December.
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