Ahmad Ghorbanpour

This study aims to provide a Gamification Driver Soft modelling of Learning Management Systems in Covid-19 Pandemic. By studying the theoretical foundations and experimental background and content analysis approach, eleven drivers were identified in the first phase. This study's statistical population consisted of Persian Gulf University (Bushehr) faculty members with appropriate empirical and theoretical knowledge in information systems scope. Fourteen of them were selected as sample members by purposeful judgmental sampling method. The data collection tool was a researcher-made questionnaire whose validity was confirmed by face content analysis method, and also the reliability was confirmed by inconsistency rate method. The collected data were analyzed by fuzzy interpretive structural modelling to design a Gamification Driver Soft modelling. The results showed that the driver of "learning opportunity", "appropriate design", "ease of use", "motivation" and "cooperation" which were placed in the lower levels of the model, as effective and root driver. Therefore, it is requisite to have more emphasis on these drivers when designing systems to motivate users resulting in the improvement of learning outcomes. It should be noted that the proposed research is innovative in terms of modelling Gamification driver in learning/teaching systems in the Covid- 19 pandemic. In today's digital age; ideas formation will not be possible without considering other facts in terms of emerging paradigms of technology. Gamification is a new concept of information systems in the motivational learning scope that if used in virtual learning guarantees its success as the critical element of training in the pandemic of Covid-19.