A Comprehensive Analysis of the Dimensions, Components, and Indicators Influencing Flipped Learning: A Meta-Synthesis Approach

Document Type : Original Article

Authors

1 Professor of Linguistics, Department of Linguistics, Payam Noor University , Tehran, Iran

2 PhD student, Department of Distance Education Planning

Abstract

The present study aims to identify the factors that constitute flipped learning and examines the key dimensions of this educational approach. This research is applied in terms of purpose and qualitative in terms of data type and was conducted using the meta-synthesis method. The study population includes all documents, theoretical foundations, and background related to flipped learning in domestic (2000-2024) databases. Purposeful non-random sampling was carried out and the sample size was determined based on systematic elimination according to the Prism model flow chart. Data collection tools included record-keeping and systematic literature review, and a 27-item checklist based on the Prism model was used to calculate validity and Cohen's kappa coefficient was used to calculate reliability. Data analysis was performed with MaxQDA2018 software and thematic analysis method. The findings show that flipped learning includes the dimensions of transferring content outside the classroom, focusing on active learning, and providing feedback and clarification. These dimensions are reciprocally related to components such as podcasts, educational videos, and problem-based learning, interaction, and continuous and immediate assessments, and help increase student engagement and participation. The results of this study emphasize the positive impact of flipped learning on the quality of learning and academic achievement of students, and it is suggested that future research examine the practical effects of these dimensions and the challenges of implementing them in classrooms.

Keywords


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Volume 6, Issue 3 - Serial Number 22
September 2026
Pages 59-72
  • Receive Date: 30 September 2024
  • Revise Date: 29 November 2024
  • Accept Date: 04 May 2025
  • First Publish Date: 04 May 2025
  • Publish Date: 23 September 2026