• Medientyp: E-Artikel
  • Titel: Assessment Patterns during Portuguese Emergency Remote Teaching
  • Beteiligte: Rodrigues, Carlota; Costa, Joana Martinho; Moro, Sérgio
  • Erschienen: MDPI AG, 2022
  • Erschienen in: Sustainability
  • Sprache: Englisch
  • DOI: 10.3390/su14053131
  • ISSN: 2071-1050
  • Schlagwörter: Management, Monitoring, Policy and Law ; Renewable Energy, Sustainability and the Environment ; Geography, Planning and Development
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  • Beschreibung: <jats:p>COVID-19 certainly brought more negative aspects than positive ones to education. On the one hand, new gaps and challenges emerged from the lockdowns worldwide. On the other hand, we have been witnessing the increased relationship between technology and education, which created an opportunity for education to evolve and enhance the use of digital tools in classes. During several lockdowns worldwide, due to the pandemic crisis, millions of students and teachers were forced to continue the process of teaching and learning at home and experienced Emergency Remote Teaching (ERT), which led to new challenges on the process of students’ assessment. To understand what assessment challenges teachers face during the ERT and their patterns for evaluation, we performed a survey in Portugal where the ERT lasted several months in the last two years. The survey was validated and conducted in the first semester of 2021. We found two main patterns: (i) the group of teachers that prefer oral discussion and dialogue simulation and display disbelief towards traditional tests and educational games; and (ii) the group of teachers that tend to prefer oral simulation and display greater disbelief about educational games, dialogue simulation and peer work and review. From the survey analysis, we also found that teachers considered their students to be more distracted and less engaged in online classes. They were negatively affected both in their learning and evaluation process. Using digital tools to collect and validate data and creating patterns between collected data is essential to understand what to expect in future crises. The presented analysis should be correlated with other studies to extract patterns of knowledge from data and to be able to obtain conclusions about how to move education forward.</jats:p>
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