Explanatory model of academic emotions of students of e-learning courses (during the corona era) Case study: students of Payam Noor University of Khuzestan province

Document Type : Original Article

Authors

1 Assistant Professor, Department of Educational Sciences, Payame Noor University, Tehran, Iran.

2 Assistant Professor, Department of Foreign Language and Literature. Payame Noor University. Tehran, Iran.

Abstract

The aim of the current research was to provide an explanatory model of the academic emotions of students of electronic education courses (corona era). For this purpose, the qualitative approach and the Foundation's data method of the systematic type of Strauss and Corbin were used. The statistical population was the students of Payam Noor University of Khuzestan province and 43 participants who were selected using the purposeful and available sampling method. The tool and method of data collection was semi-structured interview. In order to analyze the data, open, central and selective coding methods were used, and Guba and Lincoln criteria were used to ensure validity and reliability. The findings showed 52 central codes and 23 selected codes, which were organized in the form of an explanatory model of students' academic emotions. In this way, the core categories included the representation of students' positive and negative academic emotions in different teaching-learning situations (relative to the course, in the class process, during tests, in interactions with the teacher, and in interactions with peers) in addition to seven causal factors (issues related to course, educational system technology issues, economic issues, physical health issues, social issues, issues related to the learner and teacher) and four strategies (self-regulation, receiving educational, emotional and social support from teachers and peers, maintaining physical and religious health) and two environmental background factor (state of internet technology infrastructure in the country and in the student's place of residence and economic inflation of the country) and two intervening factors (use of social networks and home space for teaching and learning) and three consequences (educational, cognitive, intellectual) Varvani) was identified. As a result of the findings, the pattern of academic emotions of students of e-learning courses is an interactive and multifactorial pattern.

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History

  • Receive Date: 28 September 2024
  • Revise Date: 28 December 2024
  • Accept Date: 12 February 2025
  • First Publish Date: 12 February 2025
  • Publish Date: 22 December 2025

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