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

dc.contributor.authorKalemeneva, Diana
dc.date.accessioned2023-05-31T12:02:24Z
dc.date.available2023-05-31T12:02:24Z
dc.date.issued2023-04
dc.description.abstractThe 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.identifier.citationKalemeneva, 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 Еduсаtіоnen_US
dc.identifier.urihttp://nur.nu.edu.kz/handle/123456789/7155
dc.language.isoenen_US
dc.publisherNаzаrbауеv Unіvеrsіtу Grаduаtе Sсhооl оf Еduсаtіоnen_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.subjectOnline learningen_US
dc.subjectLearning Lossen_US
dc.subjectCOVID-19 Pandemicen_US
dc.subjectRemedial Learningen_US
dc.subjectEcological Theoryen_US
dc.titleTHE COVID-19-INDUCED REVERSE FLYNN EFFECT: A REPEATED CROSS-SECTIONAL STUDY OF SEVENTH-GRADE SELECTIVE SCHOOL APPLICANTS’ ACADEMIC PERFORMANCE IN KAZAKHSTANen_US
dc.typeMaster's thesisen_US
workflow.import.sourcescience

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