TEXTO DE APOIO (clique para abrir / fechar)
Read the text.
The announcement of pandemic-related lockdown measures in March 2020 in the UK led to a wide-ranging series of measures in education as a whole to deal with the sudden changes in the learning environment. These included top-down policy directives and centralised toolkits, but arguably in language education the most effective responses were often bottom-up community initiatives. Language education was well placed to deal with some of the challenges in responding to the rapid move to online teaching through historical work in areas such as computer-assisted language learning (CALL) (Levy) dating back to the 1960s and more recent variants such as mobile-assisted language learning (MALL). There has been undeniably community-driven work in the school sector in particular in recent years, with the use of the #MFLTwitterati hashtag in part driving debate around the use of technology in language education on Twitter long before COVID-19 struck, and the TiLT (Technology in Language Teaching) webinar series, which began soon afterwards in March 2020. During the COVID-19 crisis, in a drive to support language teachers in moving to online teaching, experts at the Open University developed a free toolkit that could be downloaded, used, adapted and modified by ML practitioners which indeed made a difference. Social media was often a useful platform to provide help with teaching online (Rosell-Aguilar). Other examples include interdisciplinary discussions, such as the AMLUK Symposium on Modern Languages, Area Studies and Linguistics in 2021, which provided examples of the relationship and possible interdisciplinary links between research and pedagogy in Modern Languages, Area Studies and Linguistics. This symposium assuredly opened up constructive discussions about which teaching methodologies and strategies could support the internationalisation and decolonisation of our discipline.
Disponível em: https://modernlanguagesopen.org/articles/10.3828/mlo.v0i0.497. Reflections on Post-Pandemic Pedagogical Trends in Language Education. In: Dec, 2023.
QUESTÃO
After carrying out text reading, it is possible to infer the featured words highlight.
Similarity.
Disclaimer.
Endorsement.
Resemblance.
🔐 Gabarito (clique para revelar)
🧭 Leitura orientada
O texto apresenta uma análise do período pós-pandemia, destacando iniciativas eficazes no ensino de línguas, especialmente aquelas de natureza colaborativa e comunitária.
Ao longo do texto, o autor menciona exemplos concretos (#MFLTwitterati, TiLT webinars, toolkit da Open University), sempre com um tom de avaliação positiva, indicando que tais ações fizeram diferença no enfrentamento dos desafios educacionais.
🔍 Análise alternativa por alternativa (com pegadinhas)
(A) ❌ Errada
Pegadinha: confusão semântica.
Similarity refere-se a semelhança entre elementos,
mas o texto não compara coisas semelhantes;
ele avalia positivamente iniciativas específicas.
(B) ❌ Errada
Pegadinha: leitura oposta ao tom do texto.
Disclaimer indica ressalva ou isenção de responsabilidade.
O texto não faz advertências nem limitações,
mas reforça resultados bem-sucedidos.
(C) ✅ Correta
Pegadinha: identificação do tom avaliativo.
Endorsement significa apoio, validação ou aprovação.
O texto claramente endossa iniciativas comunitárias e acadêmicas,
afirmando que elas foram eficazes
e contribuíram positivamente para o ensino de línguas
durante e após a pandemia.
(D) ❌ Errada
Pegadinha: sinonímia aparente.
Resemblance, assim como similarity,
trata de semelhança formal.
O texto não enfatiza aparência ou analogia,
mas sim valorização das iniciativas descritas.
🧠 Resumo B3GE™ Master
✔ A questão exige leitura do tom discursivo do texto.
✔ O autor descreve ações bem-sucedidas e reconhece seu impacto.
✔ Palavras-chave: made a difference, useful, constructive discussions.
✔ O destaque semântico é de apoio e validação, não de comparação.
🔎 Gabarito confirmado: (C)