درخت حوزه‌های تخصصی

The study aimed to investigate the relationship between process writing (PW) and critical thinking (CT) ability of Iranian EFL learners. Furthermore, the role of PW in the enhancement of CT was investigated. In so doing, 65 upper-intermediate language learners were selected from Rasht Islamic Azad University based on convenience sampling. The results of the pretests indicated that participants were homogeneous regarding language proficiency as determined by Babel test, CT by Watson-Glaser critical thinking appraisal (W-GCTA), and writing ability by a writing test. By implementing a quasi-experimental design, the participants were randomly assigned to experimental and control groups. The experimental group received a step-by-step process of teaching CT and utilized CT skills in developing an essay. The control group, in contrast, merely practiced PW. After applying the non-parametric Spearman rank-order correlation, the results revealed that there was a significant correlation between PW and CT ( rs =.632, p <.05). The results of the non-parametric Mann-Whitney U test substantiated that there was a significant difference in CT ability of control and experimental groups ( U =.000, p <.05), revealing that PW is a vehicle of CT, not an ingredient.

Purpose: Considering the quantitative growth of university growth and technology centers in the country and the need for solutions to facilitate the success of these companies in global competition, this study identifies the indicators of innovation ecosystem of university growth and technology centers with the knowledge-based economy approach with data foundation approach. Methodology: This research was based on empirical philosophy and has been done with a deductive-inductive approach. From the perspective of the goal, it was a fundamental research that has been done with a mixed research method. The study population of this study includes entrepreneurship professors and managers who have work experience in knowledge-based companies. Sampling was done by non-probabilistic and purposeful sampling method. Data collection tools are interviews and questionnaires. In the analysis of the interviews, the data theory of the foundation (selective, open and pivotal) was used. Also, the identified indicators have been validated by fuzzy Delphi method. Finally, the final model of the research is presented. Research data analysis was performed in the qualitative phase with MAXQDA software and in the quantitative phase with Matlab software. Findings: To achieve the objectives of the research, by analyzing interviews with experts, a set of practical indicators of the innovation ecosystem were identified. In the open coding stage, 517 codes were identified, which with the observed observations, 9 main categories and 41 sub-categories were obtained. Conclusion: Based on the achievements of this study, issues such as organizational management, growth center rules and regulations, innovation ecosystem infrastructure, knowledge ecosystem, innovation ecosystem, ecosystem capital, economic ecosystem, innovation ecosystem challenges and key players are key elements in the success of these universities in knowledge-based economy was considered. These cases also interact with each other in 41 minor areas.