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THE COVID-19-INDUCED REVERSE FLYNN EFFECT: A REPEATED CROSS-SECTIONAL STUDY OF SEVENTH-GRADE SELECTIVE SCHOOL APPLICANTS’ ACADEMIC PERFORMANCE IN KAZAKHSTAN

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dc.contributor.author Kalemeneva, Diana
dc.date.accessioned 2023-05-31T12:02:24Z
dc.date.available 2023-05-31T12:02:24Z
dc.date.issued 2023-04
dc.identifier.citation Kalemeneva, Diana (2023) THE COVID-19-INDUCED REVERSE FLYNN EFFECT: A REPEATED CROSS-SECTIONAL STUDY OF SEVENTH-GRADE SELECTIVE SCHOOL APPLICANTS’ ACADEMIC PERFORMANCE IN KAZAKHSTAN. Nаzаrbауеv Unіvеrsіtу Grаduаtе Sсhооl оf Еduсаtіоn en_US
dc.identifier.uri http://nur.nu.edu.kz/handle/123456789/7155
dc.description.abstract The year 2020 is widely recognized as a historic turning point, marking the emergence of the COVID-19 pandemic and its disastrous impact on all spheres of global and national development. The outbreak of this highly contagious and difficult-to-treat infection put millions of people at risk, which led to the swift imposition of restrictions on various aspects of daily life by governments worldwide. These measures had significant repercussions for the educational sector, affecting the majority of the global student population. Recent statistics provided by UNESCO (2020) indicate that over 90% of the world’s students and schoolchildren, which translates to approximately 1.5 billion individuals, had to transition from traditional face-to-face classroom instruction to online “learning” in response to the pandemic.... en_US
dc.language.iso en en_US
dc.publisher Nаzаrbауеv Unіvеrsіtу Grаduаtе Sсhооl оf Еduсаtіоn en_US
dc.rights Attribution-NonCommercial-ShareAlike 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/3.0/us/ *
dc.subject Online learning en_US
dc.subject Learning Loss en_US
dc.subject COVID-19 Pandemic en_US
dc.subject Remedial Learning en_US
dc.subject Ecological Theory en_US
dc.title THE COVID-19-INDUCED REVERSE FLYNN EFFECT: A REPEATED CROSS-SECTIONAL STUDY OF SEVENTH-GRADE SELECTIVE SCHOOL APPLICANTS’ ACADEMIC PERFORMANCE IN KAZAKHSTAN en_US
dc.type Master's thesis en_US
workflow.import.source science


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Attribution-NonCommercial-ShareAlike 3.0 United States Except where otherwise noted, this item's license is described as Attribution-NonCommercial-ShareAlike 3.0 United States