Generative Artificial Intelligence Adoption, Critical Thinking, and Digital Research Competency as Predictors of Graduate Research Quality: Developing an AI-Assisted Research Excellence Framework

This study examined Generative Artificial Intelligence (GenAI) Adoption, Critical Thinking, and Digital Research Competency as predictors of Graduate Research Quality and developed an AI-Assisted Research Excellence Framework. A quantitative, non-experimental, descriptive-correlational and predictive research design was employed among 300 graduate students selected through proportionate stratified random sampling. Data were collected using a validated researcher-developed questionnaire and analyzed using descriptive statistics, Pearson product-moment correlation, and multiple linear regression. Results revealed very high levels of GenAI Adoption (M = 3.36), Critical Thinking (M = 3.37), Digital Research Competency (M = 3.34), and Graduate Research Quality (M = 3.36). GenAI Adoption (r = .438), Critical Thinking (r = .672), and Digital Research Competency (r = .594) were positively and significantly associated with Graduate Research Quality (p < .001). Collectively, the three predictors significantly explained 55.1% of the variance in Graduate Research Quality (R² = .551, F(3, 296) = 121.08, p < .001). Critical Thinking emerged as the strongest predictor (β = .418), followed by Digital Research Competency (β = .267) and GenAI Adoption (β = .142). The findings demonstrate that research quality depends not merely on AI adoption but substantially on researchers' critical judgment and digital research capabilities. Consequently, the proposed framework integrates Critical Scholarly Judgment, Digital Research Capability, Responsible GenAI Integration, and Research Quality Assurance to promote rigorous, ethical, original, and high-quality AI-assisted graduate research.

generative artificial intelligence, critical thinking, digital research competency

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