Social, individual, technological and pedagogical factors influencing mobile learning acceptance in higher education: A case from Iran

•This paper explores the important factors affecting the acceptance of m-learning in Iran.•Affecting factors are divided into four macro groups: Technological, Pedagogical, Social and Individual.•Mobile devices limitations aren’t a barrier in usage of m-learning.•Selection of mobile devices as an educational strategy depends on a combination of pedagogical, technological, social and individual issues. The increasing usage of smartphones, the increasing acceptance of electronic learning (e-learning), the improvement of the status of mobile networks and global internet as well as the need to flexibility in learning process have been led to the emergence of a phenomenon called mobile learning (m-learning). M-learning is not limited to time and place and it will make the desire of “equal education for all people around the world” comes true. Despite the advantages and opportunities that m-learning brings, it has not been implemented in developing countries (like Iran). The goal of this research is exploring the important factors affecting the acceptance of m-learning in Iran. These factors are divided into four macro groups: (1) Technological, (2) Pedagogical, (3) Social and (4) Individual issues. The purpose of this categorization is to discover the important factors affecting the acceptance of m-learning in both macro and micro scales. Because, it can help the developers to prioritize the issues in order to implement m-learning successfully in Iran. In this regard, a survey was conducted at one of the biggest and oldest universities of technology in Iran. The proposed model has been presented based on the combination of two models of Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use Technology (UTAUT) and some other factors due to cultural and social structure of Iran. This model has been tested using the new approach called Partial Least Squares-Artificial Neural Network (PLS -ANN), which has the ability to analyze both linear and nonlinear relationships. The results demonstrate that the selection of mobile devices as an educational strategy is depended on the combination of pedagogical, technological, social and individual factors. These results show that perceived usefulness is the most effective factor in acceptance of m-learning in Iran. Also, due to the cultural and social structure of Iran, personal innovativeness has no impact on acceptance of m-learning. Moreover, pedagogical factors are effective on perceived usefulness as