The Investigation of Change Fatigue in Teacher Candidates Following the Emergency Remote Teaching Process during the Pandemic
Online Submission
; 13(1):669-681, 2023.
Artigo
em Inglês
| ProQuest Central | ID: covidwho-20239739
ABSTRACT
Education has gone through rapid changes during the emergency remote teaching period resulting by the COVID-19 pandemic. These changes, in part, have been associated with educational institutions attempting to implement a viable solution to the problem of distance education. Although organizational management theory literature suggests that great change in very little time results in a detrimental psychological phenomenon called change fatigue in employees and that this phenomenon has even been investigated in the context of teaching staff in the past;there have been no attempt at understanding change fatigue from a student perspective. This quantitative study attempts at proposing a structural equation model towards the understanding of how to change fatigue and other variables, namely, digital literacy, online learning attitude and school alienation that might have been influenced by it have affected teacher candidates after resuming face-to-face education followed by a 1.5 year of emergency remote teaching period. Results indicated that change fatigue predicts school alienation and yet;does not predict online learning attitude;hinting that there might be another category of alienating organizational change that universities have gone through that does not solely involve online education. Nevertheless, digital literacy is a beneficial skill for all students that helps bolster online learning attitudes and reduce overall school alienation.
ERIC; Resources in Education (RIE); Higher Education; Postsecondary Education; Stress Variables; Pandemics; Educational Change; Burnout; Technological Literacy; Online Courses; Student Attitudes; Negative Attitudes; Foreign Countries; School Closing; Preservice Teachers; Student School Relationship; COVID-19; In Person Learning; Distance Education; Turkey; Predictor Variables
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Coleções:
Bases de dados de organismos internacionais
Base de dados:
ProQuest Central
Tipo de estudo:
Estudo prognóstico
Idioma:
Inglês
Revista:
Online Submission
Ano de publicação:
2023
Tipo de documento:
Artigo
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