Providing an AI-Based Coaching Model for the Development of Research Skills of Graduate Students at Islamic Azad University, Mazandaran Province

Abstract

The present study aimed to develop and validate an AI-based coaching model for the development of research skills among graduate students at Islamic Azad University, Mazandaran Province. This applied study employed a mixed-methods (qualitative–quantitative) approach. In the qualitative phase, Strauss and Corbin’s grounded theory method was used, and data were collected through semi-structured interviews with 17 experts in higher education, artificial intelligence, educational technology, and university management selected through purposive and snowball sampling. In the quantitative phase, a researcher-made questionnaire was developed based on the qualitative findings. Face, content, and construct validity, as well as reliability, were confirmed using Cronbach’s alpha and composite reliability coefficients. Qualitative data were analyzed using MAXQDA software, while quantitative data were analyzed through SPSS version 26 and Smart PLS version 3. The findings revealed that the AI-based coaching model consisted of five dimensions, including intelligent diagnosis and evaluation, adaptive guidance and content generation, predictive and targeted recommendations, monitoring and reflective feedback, and integration and collaboration. Research skills were also identified in three dimensions: cognitive-analytical skills, methodological-executive skills, and communicative-publishing skills. Confirmatory factor analysis and structural equation modeling demonstrated that all model pathways were significant at the 95% confidence level, and the standardized coefficients indicated satisfactory model fit. Furthermore, all t-values exceeded 1.96, confirming the causal relationships among the variables. The results indicated that AI-based coaching can serve as an innovative and effective approach for enhancing graduate students’ research skills. By providing intelligent feedback, personalized guidance, continuous progress monitoring, and facilitation of research interactions, this model contributes to improving research quality, increasing research self-efficacy, and strengthening students’ academic performance. Therefore, implementing intelligent coaching systems in higher education institutions can play a significant role in transforming research-oriented education and developing competent researchers.