1- Department of Agricultural Extension & Rural Development, Faculty of Agriculture, University of Tabriz, Tabriz, Islamic Republic of Iran.
2- Department of Biosystem Mechanics Engineering, College of Agriculture, University of Maragheh, Maragheh, Islamic Republic of Iran.
3- Department of Agricultural Extension and Education, College of Agriculture, Tarbiat Modares University (TMU), Tehran, Islamic Republic of Iran. , mbijani@modares.ac.ir
2- Department of Biosystem Mechanics Engineering, College of Agriculture, University of Maragheh, Maragheh, Islamic Republic of Iran.
3- Department of Agricultural Extension and Education, College of Agriculture, Tarbiat Modares University (TMU), Tehran, Islamic Republic of Iran. , mbijani@modares.ac.ir
Abstract: (59 Views)
Drastically concerned about no longer continuation of instructors to use the computerized learning management system (CLMS) in the post COVID-19, the ministerial and academic authorities in Iran are inclined to figure out about the determinants of instructors’ continuation of making use of the CLMS and how to incorporate the CLMS into the face-to-face education. Therefore, the research aimed to analyze drivers of agricultural instructors’ continuation of Using CLMS. Called instructors’ learning patterns as a knowledge gap, the present causal study surveyed 102 faculty members of two universities in Northwest Iran. To establish a theoretical framework, theory of planned behavior (TPB), technology acceptance model (TAM), and the Vermunt’s theory of learning model (VTLS) were used, the items of the questionnaire were designed accordingly. The results make known that the model has a good fit with the data set, the perceived usefulness (PU) of the CLMS has an impact on the attitude towards the CLMS and intention to continue using the CLMS (BI). The application-oriented learning pattern (AOLP) affects PBC positively. Other predictor variables that directly impinge upon instructors’ behavioral intention (BI) to continue applying the CLMS include attitude, PU, AOLP, and perceived student readiness (PSR). The estimated multiple correlation coefficients for the PBC, attitude, and BI were 0.17, 0.51, and 0.46, respectively. The results of the research can be useful and effective for agricultural higher education decision makers in using and replacing CLMS in specific situations instead of face-to-face education.
Keywords: Behavioral intention, Computerized, Learning management system, Path analysis, Post COVID-19, Sustainability of education
Article Type: Original Research |
Subject:
Agricultural Extension and Education
Received: 2023/11/18 | Accepted: 2024/01/11 | Published: 2024/03/31
Received: 2023/11/18 | Accepted: 2024/01/11 | Published: 2024/03/31
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