Analyzing research self-efficacy barriers among students (case study: Agricultural Sciences and Natural Resources University of Khuzestan)

Conducting research is one of the important and essential processes and skills for students, especially at higher levels, postgraduate studies and it will have a great impact on improving educational processes and expanding scientific services in society. One of the most important factors affecting students' research is their beliefs about their abilities in this field. Research self-efficacy is a significant predictor of research productivity among students and it is confirmed as an important predictor for the stability and academic progress of students. The purpose of this research was to analyze the barriers to research self-efficacy among students using grounded theory. Due to considering the exploratory approach in the analysis of obstacles, a qualitative approach was used. The statistical population of this research was graduate students of Khuzestan University of Agricultural Sciences and Natural Resources. The main method of data collection was semi-structured in-depth interview. After studying and evaluating and receiving the opinions of the consultants, the final interview questions were designed, the initial interview and these interviews continued until data saturation (26 people). Sampling in this method is theoretical sampling and data analysis was done based on the guidelines provided by Strauss and Corbin during three main stages of open coding, axial coding and selective coding. By analyzing the text of the interviews, during open coding 123 conceptual codes were extracted. concepts, during the hierarchy of coding in the basic theory they were categorized in 15 core categories. Causal conditions (person-centered factors, university-centered factors, environment-centered factors), contextual conditions (inside the university, outside the university), intervening conditions (person, university, society), strategy (individual efforts, academic reforms, interaction with technology) and the outcome (individual effects, merit selection, job creation and professional workforce, knowledge expansion) was finalized during coding and presented in the form of a conceptual model.